2013 Annual Report of the U.S. Hospital IT Market

2013Annual Report of the U.S. Hospital IT Market

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Looking Back; Looking Ahead: The Year in Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

2012 Hospital IT Budget and Expenses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

Financial Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Financial Decision Support Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

Human Resource Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

Revenue Cycle Management Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

Next Generation Revenue Cycle Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

Health Information Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

Document Management/Electronic Forms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

Nursing Department Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

Ancillary Department Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

Laboratory Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

Surgical Information System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54

Radiology PACS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

Cardiology PACS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62

Bar Code Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65

Electronic Medical Record Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66

The EMR Adoption ModelSM: Measuring Clinical IT Transformation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71

Ambulatory (Hospital Owned/Managed) IT Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74

Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78

▶ Table of Contents

mailto:nvitucci%40himss.org?subject=

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http://www.himssanalytics.org

dear Healthcare executive:Welcome to the 2013 Annual Report of the U.S. Hospital IT Market, produced jointly by the Healthcare Information and Management Systems Society (HIMSS) and HIMSS Analytics LLC, the wholly-owned, not-for-profit market research arm of HIMSS. We are very pleased to present this comprehensive view of the current state of IT adoption in U.S. hospitals, and hospital-owned, managed and/or leased ambulatory practices.

From government incentives to planning a major investment in new technologies, a healthcare professional faces numerous challenges in wading through the complicated healthcare environment.

Since the program beginning (in 2009) until November 2012, the Department of Health and Human Services (HHS) has made incentive payments of over $9 billion to American hospitals and eligible providers authorized under the The Health Information Technology for Economic and Clinical Health Act (HITECH). As part of the provisions of the 2009 American Recovery and Reinvestment Act (ARRA),1 the incentive payments more than double the amount paid out from the program at the same time in 2011. We at HIMSS Analytics believe the incentive program is having an accelerating effect on healthcare IT adoption in U.S. hospitals. In 2012, 205 hospitals achieve Stage 6 on the Electronic Medical Record Adoption ModelSM (EMRAM), up from 102 in 2011 and 80 in 2010.

Moreover, in response to questions surrounding the efficacy of the HITECH program by certain members of Congress, HIMSS mobilized to demonstrate how the ARRA incentive program was fueling an acceleration of IT adoption in U.S. hospitals. By profiling the acute care EMRAM scores over five quarters from time of the initial stimulus payments in Q2 of 2011 through Q3 of 2012, we showed that Stages 5 and 6 had in excess of an 80 percent growth while Stage 7 had grown 66 percent.

Stage 2 Meaningful Use regulations were finalized in September of 2012. In general, the bar set by Stage 1 has been raised for Stage 2, although the onset of criteria was pushed out to 2014. Meaningful Use Stage 2, ICD-10 adoption, clinical and business intelligence to support payment reform, and Meaningful Use Stages 1 and 2 quality reporting are still in effect working to maintain the “perfect storm” of regulatory compliance facing healthcare CIOs.

From HIMSS Analytics data, we see that the number of hospitals per IDN continues to increase slightly from 6.9 to 7.0, though at decreasing rate from previous years. We perceive that the economic uncertainty for hospitals with looming significant Medicare reimbursement cuts may be cooling down the acquisition frenzy. However, the reductions of Medicare may be offset by new revenue from patients with health insurance in 2014 and beyond now that the Affordable Care Act (ACA) has been substantially accepted by the Supreme Court. Clearly, these are uncertain times for hospital CFOs.

In 2012, HIMSS Analytics produced another report in our series regarding return on investment (ROI) for healthcare IT.2 Numerous examples of efficiency, quality and safety improvements were identified from Davies Award winners and Stage 7 hospitals. Clearly, the naysayers who believe that healthcare IT does not have a payoff are incorrect.

We anticipate that 2012 will be seen as a year of acceleration where the stimulus provided by ARRA began to make an increasing affect in helping U.S. hospitals reach a “tipping point” in IT investments. You can count on HIMSS Analytics and HIMSS to equip you to stay on top of these changes, and to be your most trusted and comprehensive source of information on the adoption of IT applications, and the progress toward implementing those applications in today’s U.S. healthcare provider environment.

We hope you find this ninth edition of the Annual Report of the U.S. Hospital IT Market informative, compelling and stimulating.

Best regards,

John p. Hoyt H. stephen LieberExecutive Vice President President and CEOHIMSS Analytics HIMSS

1 http://www .cms .gov/Regulations-and-Guidance/Legislation/EHRIncentivePrograms/Downloads/Nov_Medicare_Incentive_Payments .pdf2 http://www .himss .org/transformation/docs/December2012ResearchPaper .pdf

▶ A Letter from the CEO and EVP of HIMSS and HIMSS Analytics

http://www.cms.gov/Regulations-and-Guidance/Legislation/EHRIncentivePrograms/Downloads/Nov_Medicare_Incentive_Payments.pdf

http://www.himss.org/transformation/docs/December2012ResearchPaper.pdf

Years from now, historians may look back at the year 2012 and cast it as a pivotal moment in the evolution of healthcare in the U.S. With the Supreme Court’s five to four decision to uphold the Affordable Care Act (ACA) or “Obamacare” and its individual mandate requiring individuals to obtain health insurance or pay a fine, the ruling has the potential to greatly change the healthcare industry. Additional evidence regarding the significance of the Supreme Court’s decision played out later in the year with the re-election of Barack Obama. Challenged by a Republican presidential candidate, Mitt Romney, who vowed to repeal the ACA, Americans affirmed the move to change healthcare in the U.S. as we know it. So as we stand on the precipice of a new era in healthcare, 2013 will no doubt prove to be interesting, as regulations are unfurled to support the law that begins to take effect in 2014.

The past year also saw unemployment in the U.S. steadily decrease from the nine percent level it had stubbornly fixated itself to beginning in late 2011, landing at 7.7 percent by November 2012.1 Concurrent with that gradual improvement in unemployment, the bellwether “housing starts” (number of new housing constructions) statistics from the Federal government’s Housing and Urban Development (HUD) Department showed signs of a reviving economy. Housing starts for new residential construction increased by 46.6 percent when comparing November 2012 with November 2011.2 Clearly there is some gradual improvement in the U.S. economy, albeit slower than everyone would like.

The U.S. economy though, does not operate within a vacuum. Our economic affairs influence and are influenced by those in other parts of the world. The troubles within the European financial markets for example, are believed to be having a detrimental effect on the demand for U.S. goods and services, and may slow the revitalization of the U.S. economy. Despite these external downward pressures, the NASDAQ index, where many of the publicly held healthcare information technology (IT) companies are traded, showed a healthy 13.6 percent gain in 2012, while the Dow Jones Industrial Average only eked out 7.2 percent growth.

The challenges to the U.S. economy did not let up even as the year closed. The federal government struggled mightily to avoid a self-imposed “fiscal cliff” that would have severely cut select governmental services and automatically instituted tax increases for many U.S. residents. The “fiscal cliff” remedies, which were mostly resolved at the last minute on December 31, with some key issues being deferred two months, served to highlight the discord among lawmakers. The closely watched consumer confidence index took a six percent drop in December as the fiscal cliff edged closer.3 This drop could have an effect on elective medical consumption in 2013, and is a metric many within the healthcare community will want to watch.

Hospitals are typically a “lag indicator” of the economy as the effects of a recession tend to hit hospitals at the end of the recessive cycle. HIMSS AnalyticsTM data shows that in 2012 the number of hospitals and integrated delivery networks (IDNs) that reported an increase in their IT budgets was stable with 2011 levels. Clearly hospitals are investing in IT, but not necessarily at an increasing rate, according to HIMSS Analytics data through Autumn 2012.

Slow economic growth has led to greater than expected deficits through continued transfer payments and less than projected tax revenues at both the federal and state levels. These deficits have added significant pressure to state Medicaid programs, and in response, numerous federal programs are being scrutinized for effectiveness. Efforts to reach a compromise over the automatic tax increases from the repeal of the Bush-era tax cuts have generally included some effort to extend unemployment benefits. But as unemployment continues to decrease, the appetite for continued extensions may be lessened. Again, this could have a detrimental effect on elective medical consumption in 2013.

The ARRA funding continues to be effective in stimulating the adoption of healthcare IT. In November 2012, more than 176,000 health care eligible providers received payment for participating in the Medicare and Medicaid Electronic Health Record (EHR) Incentive Programs, up from 100,000 healthcare providers in June of 2012.4 All told, over 3,300 hospitals have received $6.05B in Medicare incentive payments through November 2012, since the program began issuing incentive payments in May 2011.5

ARRA funding has clearly stimulated the acute care IT industry. Evidence of this growth can be found in the increased rate of progression up the EMRAM scale. In 2012, HIMSS Analytics recognized 205 hospitals achieving Stage 6, double the number (102) that achieved Stage 6 in 2011, and 2.5 times greater than the number achieved in 2010 (80). In October 2012, in response to questions surrounding the efficacy of the HITECH program by certain members of Congress, HIMSS produced an acute care EMRAM score table detailing five quarters of data from the initial stimulus payment in Q2 of 2011 through Q3 of 2012. Astonishingly, that table showed that Stages 5 and 6 grew by more than 80 percent while Stage 7 grew by 66 percent.

Another sign of the acute care IT industry’s growth is the continued struggle healthcare providers have in recruiting and retaining clinical system skills for the implementation and support of IT systems. According to the U.S. Department of Labor Bureau of Labor Statistics (BLS), the healthcare industry is expected to grow rapidly between 2008 and 2018 in large part due to a continued growth of our elderly population. Additionally, the national effort to effectively deal with chronic diseases such as obesity is becoming more prevalent and thus will continue to stoke the demand for clinical labor. The BLS indicates that the social services and healthcare employment sector will be the fastest growing sector from 2008 through 2018 at 2.3 percent per year, with a clear majority of this growth coming from the ambulatory care settings. When providers are competing with vendors for the same clinical IT skills, the pressure will be on the providers to be able to retain the skills necessary to support the systems that have been deployed and meet the growing demand of the medical staffs, nursing staff and other clinician users.

Consolidation continues in the hospital provider market. Acquisition and mergers of acute care providers increased slightly in 2012 compared to 2011. We perceive that access to large capital may be constrained in this uncertain economy due to the anticipated

1 http://data .bls .gov/timeseries/LNS14000000 2 http://www .census .gov/construction/nrc/pdf/newresconst .pdf 3 http://money .cnn .com/2012/12/30/news/economy/payroll-tax-consumer/index .html?hpt=hp_t1 4 https://www .cms .gov/Regulations-and-Guidance/Legislation/EHRIncentivePrograms/DataAndReports .html 5 http://www .cms .gov/Regulations-and-Guidance/Legislation/EHRIncentivePrograms/Downloads/Nov_IncentiveProgramPayment_Registration_SummaryReport .pdf

▶ Looking Back; Looking Ahead: The Year in Review

2 Source: HIMSS Analytics® Database 2012 ©2013 HIMSS Analytics .

http://data.bls.gov/timeseries/LNS14000000

http://www.census.gov/construction/nrc/pdf/newresconst.pdf

http://money.cnn.com/2012/12/30/news/economy/payroll-tax-consumer/index.html?hpt=hp_t1

https://www.cms.gov/Regulations-and-Guidance/Legislation/EHRIncentivePrograms/DataAndReports.html

http://www.cms.gov/Regulations-and-Guidance/Legislation/EHRIncentivePrograms/Downloads/Nov_IncentiveProgramPayment_Registration_SummaryReport.pdf

reductions in Medicare and Medicaid reimbursements. However, the ACA will also provide a new source of revenue to hospitals as we begin our national effort to reduce the number of uninsured consumers. These two countervailing pressures make for uncertainty, and thus diminished appetite for debt as well as a diminished appetite to loan.

HIMSS Analytics data shows that the number of hospitals per IDN continued to grow, however at a much slower rate in 2012 (1.5 percent), when compared to 2011 levels (4.5 percent). HIMSS Analytics also uncovered an interesting anomaly in the data on the number of hospitals per IDN. The median number has stayed at 3.0 for several years, but the arithmetic mean average is now 7.0 compared to 6.9 in 2011. The large disparity between the median of 3.0 and the mean of 7.0 tells us that there are significant numbers of very large IDNs but that their growth rate has slowed in 2012.

We see no force to prevent this trend from continuing as hospitals choose to consolidate to weather the storm of reduced reimbursements, Accountable Care Organizations (ACOs) and bundled payments. The desire of the Federal Government, notably the White House and Health and Human Services Department (HHS), to have the ACO program succeed, may result in a confrontation with anti-trust watch dogs in the Justice Department. No doubt, more clarity here is needed in the market.

The NPRM (notice of proposed rule making) for Meaningful Use Stage 2 regulations were released in February with the final rule being published on September 4, 2012. The extensive regulations also modified rules for Meaningful Use Stage 1. In general, the bar for criteria to satisfy Meaningful Use Stage 1 was raised, with the onset of criteria pushed back to 2014, the first year of applicability and the time when a 90-day EHR reporting period is allowed. The Stage 1 hospital requirement of 14 core measures and five of ten menu measures has been replaced with 16 core measures and three of six menu measures in Stage 2 for eligible hospitals. According to the Office of the National Coordinator for Health Information Technology (ONC), the total Federal cost of the Medicare and Medicaid EHR Incentive Programs between 2014 and 2019 is estimated to be $15.4 billion (these estimates include net payments adjustments for Medicare providers who do not achieve Meaningful Use in 2015 and subsequent years in the amount of $2.1 billion)

The Medicare ACO program continued to grow in 2012. On July 9, 2012, the Center for Medicare and Medicaid Services (CMS) announced that 89 new organizations had been selected to participate in the Shared Savings Program via the ACO construct. In addition, CMS also announced 106 new organizations had been selected to participate on January 10, 2013. ACOs are driving hospitals to enter new partnerships with competitors in order to manage the health of a defined population.

We believe these pilot programs will, by necessity, develop strengths in clinical and business intelligence (C&BI) in order to analyze the quality of their care and to drive efficiencies to meet the payment and incentive goals. One clear objective of the ACO program is to find a much better way of managing chronic diseases. According to Kaiser Permanente data, five percent of their covered population consumes fifty percent of the healthcare dollars. Clearly, we need to find ways, through patient engagement and best-practice modeling, to reduce consumption and the prevalence of chronic disease. We see a continued strong growth in software, hardware and services to meet the needs for C&BI.

The industry tension between privately funded and federally funded health information exchanges (HIEs) remained the same in 2012. Federally funded HIEs remain challenged to find long-term sustainable business models and revenue services outside of state and federal funding mechanisms. However, significant inroads have been made by many of these regional and state public HIEs in the development of sustainability models as well as forming relationships working alongside private HIEs.

The Nationwide Health Information Network (NwHIN) saw many changes in 2012. The NwHIN name changed to eHealth Exchange and oversight transitioned from ONC to Healtheway, a nonprofit–public, private partnership. Healtheway is chartered to support the eHealth Exchange and focus on cross-industry collaboration to advance HIEs across the country. eHealth Exchange continues to be a set of standards and polices that enable secure HIEs over the Internet through a common trust agreement by the community of eHealth Exchange participants.

Continued market growth is anticipated with all HIE initiatives. The private market anticipates accelerated growth as private HIEs continue to develop and open up new business channels working with other private as well as public HIEs in their local and regional markets. We expect to continue seeing payers and other private organizations enter this space, as exchanges are valued as a major source of clinical consumption data that facilitates development of the next wave of efficacy research and resultant best practices and protocols. In addition, we expect to see more incorporation of financial and business information with clinical data by the HIEs.

The ARRA also provisioned the Federal Coordinating Council for Comparative Effectiveness Research. ARRA authorized $300 million for the Agency for Healthcare Research and Quality (AHRQ), $400 million for the National Institutes of Health, and $400 million for the Secretary of Health and Human Services to support comparative effectiveness research. As hospitals implement EHRs, a wealth of data is being collected in a way that we have never had before. The goal of the Comparative Effectiveness Research program is to build the tools and methodologies to utilize this data to support clinical research, develop optimized care protocols which can be incorporated into the clinical decision support capabilities of EMRs, and also eventually drive pay for performance. Hospitals and IDNs that invest in C&BI tools and resources will be in a better position to succeed, positioning themselves to meet the new quality and efficiency requirements. Included in this research will be pharmaceutical efficacy data that goes beyond Food and Drug Administration (FDA) trials.

So, looking ahead, where are we going in 2013 and beyond? It is clear that federal policy has stimulated the adoption of healthcare IT, and that the drive to develop a successful ACO, patient-centered medical home and payment reform has picked up steam. The ACA to extend healthcare access to millions was substantially upheld by the Supreme Court. The Democratic Party picked up eight seats in the House of Representatives, narrowing the Republican majority to 33 (234 to 201). The Democratic majority in the Senate was strengthened with the addition of two seats, and two Senators serving as Independents. Dealing with the deficits and the aftermath of the “fiscal cliff” will clearly drive both parties to find ways of reducing spending and the inexorable growth of healthcare’s portion of the gross domestic product (GDP), which now stands at 17.6 percent. One fact remains clear—healthcare providers will continue to be

▶ Looking Back; Looking Ahead: The Year in Review continued

Source: HIMSS Analytics® Database 2012 ©2013 HIMSS Analytics . 3

expected to improve quality care coordination across care settings, while simultaneously reducing costs and improving efficiency.

Now that a significant proportion of hospital providers have demonstrated compliance with Stage 1 Meaningful Use, they have little time to rest on their laurels. Instead, they will be faced in rapid succession with several other major IT challenges:• Complying with unfunded government mandates to convert to

ICD-10 diagnosis coding by October 1, 2014.• Meeting the EHR-related Stage 2 Meaningful Use requirements

beginning in 2014.• Addressing the organizational and process changes required to

meet the higher mandated levels of compliance with computerized provider order entry (CPOE) and clinical decision support (CDS) usage, as well as electronic reporting in order to secure continued Meaningful Use payments.

The challenges associated with a multi-year EMR implementation process can often cause organizations to lose sight of a critical guiding IT principle: technology is simply a means to the end, not an end unto itself. As we enter 2013, we see that the industry’s attention is focused on implementing EMRs, yet the experience of early adopters has clearly and repeatedly demonstrated that implementing an EMR alone will not achieve cost savings, quality improvements or revenue enhancements unless it is a component of a broader plan with clearly defined organizational and operational improvement objectives. The most successful organizations are those which have used their EMR as a foundation for implementing process change and complementary technologies—such as business analytics and clinical decision support—to achieve improved outcomes and reduced costs.

A growing body of literature in respected journals and conference proceedings supports the idea that quality improvements truly can be derived from appropriately deployed healthcare IT concomitant with process redesign. The literature base and the HIMSS Analytics Stage 7 award winner case studies, as well as the HIMSS Davies Award winner case studies, are replete with examples of medication safety improvements; cost savings when CPOE is supported by evidence-based best practice alerts; and savings to health plans through reduced healthcare consumption, just to name a few. Naysayers who believe that healthcare IT investments do not drive quality and efficiency benefits are clearly wrong. The payoff has begun. Let us continue this progression.

However, can healthcare IT be inappropriately applied? Certainly, inadequate training and poor usability design can feed an error-prone environment. Providers and software developers alike must be on guard to optimize the tremendous power of healthcare IT appropriately. EHR safety is a concern and rightly so and it has the attention of key government agencies.

This Annual Report also demonstrates areas where healthcare IT market activity is slow, most notably in the supply chain area and revenue cycle. We have been stating that we expect an increase in activity in the supply chain area due to hospital mergers and acquisitions. The data thus far does not support that prediction. CIOs tell us that their primary focus is to implement the systems necessary to earn their Meaningful Use incentive payment and such

tasks as consolidating around a common supply chain system is temporarily a low priority.

We also believe we are not too far away from an uptick in revenue cycle system replacements to meet the new demands of payment reform. Maybe that is the next “bubble” to come after 2015.

Finally, as hospitals accumulate unprecedented levels of digital data, we see two major derivatives. First, C&BI analytics will take on a central role to help direct hospitals toward the most effective care protocols and efficiency. Second, hospital data centers themselves will become increasingly taxed to support and hold all this data. Hospitals will begin to move quickly to vendor-neutral archiving in secure data centers off campus. Manageability and physical space have become key issues for providers. Outsourced data centers or entire hosting of systems in an application service provider (ASP) model will clearly grow, harking back to the beginning of our industry where shared models were the norm.

Years from now, healthcare IT history buffs will likely look back on 2012 as a year when acute care IT adoption accelerated through the momentum gathered in 2011, and spurred on by federal stimulus dollars. But the past is merely prologue, as we expect the pace of change to continue now that President Obama has been re-elected and the ARRA stimulus program is not likely to be diminished significantly. However, we could see a significant downturn in clinical systems activity once the incentive payments cease after 2016. The interesting question is, will that be replaced by a growth of revenue-cycle system implementations to support payment reform commencing by the middle of this decade? As Confucius once said, “may we live in interesting times.”

HiMss Analytics stage 7 Awards HIMSS Analytics launched the EMRAM in 2005 to track adoption of EMR applications within hospitals and health systems. The EMRAM scores hospitals in the HIMSS Analytics® Database on their progress in completing 8 Stages (0-7), with the goal of reaching Stage 7, an environment where paper charts are no longer used to document the delivery of patient care.

In 2009, HIMSS Analytics honored 38 Stage 7 hospitals, the first hospitals to reach Stage 7. By 2011, the number of hospitals swelled to 66, including two international Stage 7 hospitals.

Stage 7 hospitals are positioned to share clinical information via standard electronic transactions with all entities within HIE networks (i.e. other hospitals, ambulatory clinics, sub-acute environments, employers, payers and patients). This stage allows the healthcare organization to support the true sharing and use of health and wellness information by consumers and providers alike. Also at this stage, healthcare organizations use data warehousing and mining techniques to capture and analyze care data for performance improvement and advancing the use of clinical decision support protocols. As such, it is these organizations that are best positioned to reach Stage 1 Meaningful Use.

The following is a list of healthcare organizations that have achieved Stage 7 of EMRAM (as of December 2012). These hospitals exemplify organizations that are using IT as the supporting infrastructure for their advances.



In 2012, a record number of 40 hospitals representing 10 different North American IDNs, satisfied the criteria to be validated as an EMRAM Stage 7 facility.

name city stateBanner Baywood Medical Center Mesa AZBanner Boswell Memorial Hospital Sun City AZBanner Churchill Community Hospital Fallon NVBanner Del E . Webb Memorial Hospital Sun City West AZBanner Desert Medical Center Mesa AZBanner Estrella Medical Center Phoenix AZBanner Gateway Medical Center Gilbert AZBanner Good Samaritan Medical Center Phoenix AZBanner Heart Hospital Mesa AZBanner Ironwood Medical Center San Tan Valley AZBanner Lassen Medical Center Susanville CABanner Thunderbird Medical Center Glendale AZCommunity Hospital Torrington WYEast Morgan County Hospital Brush COEllis Fischel Cancer Center Columbia MOFlorida Hospital North Pinellas Tarpon Springs FLFort Memorial Hospital Fort Atkinson WIHennepin County Medical Center Minneapolis MNMcKee Medical Center Loveland COMissouri Orthopedic Institute Columbia MOMissouri Psychiatric Center Columbia MONorth Colorado Medical Center Greeley COOgallala Community Hospital Ogallala NEPage Hospital Page AZPlatte County Memorial Hospital Wheatland WYSterling Regional MedCenter Sterling COTexas Health Harris Methodist Alliance Fort Worth TXThe Ohio State University Comprehensive Cancer Center –

Arthur G . James Cancer Hospital and Richard J . Solove Research Institute Columbus OH

The Ohio State University Harding Hospital Columbus OHThe Ohio State University Hospital Columbus OHThe Ohio State University Hospital East Columbus OHThe Ohio State University Rehabilitation Services at Dodd Hall Columbus OHThe Ohio State University Richard M . Ross Heart Hospital Columbus OHTruman Medical Center–Hospital Hill Kansas City MOTruman Medical Center–Lakewood Kansas City MOUC Davis Medical Center Sacramento CAUniversity Hospital Columbia MOUniversity of Iowa Hospitals and Clinics Iowa City IAWashakie Medical Center Worland WYWomen’s and Children’s Hospital Columbia MO

This is the eighth edition of the Annual Report of the U.S. Hospital IT Market. It is our deepest desire that you find this report though-provoking, stimulating and informative.

the HiMss Analytics research teamJohn HoytLorren PettitJennifer HorowitzRoger ParkMaggy Tieche

Hospitals validated as Stage 7 prior to 2012.

name city stateAlfred I . DuPont Hospital for Children Wilmington DEAmerican Family Children’s Hospital Madison WIChildren’s Hospital Boston Boston MAChildren’s Hospital of Pittsburgh Pittsburgh PAChildren’s Medical Center at Legacy Plano TXChildren’s Medical Center of Dallas Dallas TXCitizens Memorial Healthcare Bolivar MODeaconess Cross Point Center Evansville INDeaconess Gateway Hospital Newburgh INDeaconess Hospital Evansville INEvanston Hospital Evanston ILFlorida Hospital–Flagler Winter Park FLGlenbrook Hospital Glenview ILHighland Park Hospital Highland Park ILKaiser Permanente–Anaheim Medical Center Anaheim CAKaiser Permanente–Antioch Medical Center Antioch CAKaiser Permanente–Baldwin Park Medical Center Baldwin Park CAKaiser Permanente–Bellflower Medical Center Bellflower CAKaiser Permanente–Fontana Medical Center Fontana CAKaiser Permanente–Fremont Medical Center Fremont CAKaiser Permanente–Fresno Medical Center Fresno CAKaiser Permanente–Hayward Medical Center Hayward CAKaiser Permanente–Los Angeles Medical Center Los Angeles CAKaiser Permanente–Manteca Medical Center Manteca CAKaiser Permanente–Moanalua Medical Center Honolulu HIKaiser Permanente–Modesto Medical Center Modesto CAKaiser Permanente–Moreno Valley Community Hospital Moreno Valley CAKaiser Permanente–Oakland Medical Center Oakland CAKaiser Permanente–Orange County/Irvine Medical Center Irvine CAKaiser Permanente–Panorama City Medical Center Panorama City CAKaiser Permanente–Redwood City Medical Center Redwood City CAKaiser Permanente–Richmond Medical Center Richmond CAKaiser Permanente–Riverside Medical Center Riverside CAKaiser Permanente–Roseville Medical Center Roseville CAKaiser Permanente–Sacramento Medical Center Sacramento CAKaiser Permanente–San Diego Medical Center San Diego CAKaiser Permanente–San Francisco Medical Center–Geary San Francisco CAKaiser Permanente–San Jose Medical Center San Jose CAKaiser Permanente–San Rafael Medical Center San Rafael CAKaiser Permanente–Santa Clara Homestead Medical Center Santa Clara CAKaiser Permanente–Santa Rosa Medical Center Santa Rosa CAKaiser Permanente–South Bay Medical Center Harbor City CAKaiser Permanente–South Sacramento Medical Center Sacramento CAKaiser Permanente–South San Francisco Medical Center San Francisco CAKaiser Permanente–Sunnyside Medical Center Clackamas ORKaiser Permanente–Vacaville Medical Center Vacaville CAKaiser Permanente–Walnut Creek Medical Center Walnut Creek CAKaiser Permanente–West Los Angeles Medical Center Los Angeles CAKaiser Permanente–Woodland Hills Medical Center Woodland Hills CARochester Methodist Hospital Rochester MNSentara Bayside Virginia Beach VASentara CarePlex Hampton VASentara Leigh Hospital Norfolk VASentara Norfolk General Hospital Norfolk VASentara Virginia Beach General Hospital Virginia Beach VASentara Williamsburg Regional Medical Center Williamsburg VASkokie Hospital Skokie ILSt . Mary’s Hospital of Rochester Rochester MNStanford Hospital and Clinics Stanford CAThe Heart Hospital Newburgh INTucson Medical Center Tucson AZUC San Diego Medical Center–Hillcrest San Diego CAUC San Diego Medical Center–Thornton Hospital La Jolla CAUniversity of Wisconsin–Hospital and Clinics Madison WISeoul National University Bundang Hospital Seoul KORUniversitätsklinikum Hamburg-Eppendorf Hamburg GERHospital de Dénia Marina Salud S .A . Denia ESP



The 2012 Hospital IT budget and expenses report highlights financial benchmarks that provide a glimpse into IT-related spending as a percentage of organizations’ overall spending. Analyses are presented from three different perspectives. First, the average and median IT operating expenses (OPEX) are shown as a percentage of total hospital operating expense. This calculation excludes capital expenses from both the numerator and the denominator. The second set of ratios shows the average and median spending ratios for the total IT budget, including both operating and capital expense (CAPEX) for this fiscal year, as a percentage of the organizations’ overall operating and capital expenses. The final set of ratios focuses on the IT department capital expenses for this fiscal year, as a percentage of the hospital’s total capital expense. Each set of ratios is examined by hospital size, hospital type and U.S. census region.

The year 2012 represents an end to the downward trend in these ratios that were first noticed in 2010. The results of this year suggest a more positive outlook in the economy. In retrospect, the financial recession began in September 2007, when unemployment rates began to rise, lasting until the early months of 2009, when the bottom of the stock market was reached in February. Since then, the healthcare industry like other industries, has been wary of making significant investments outside of the Meaningful Use and ICD-10 directives. This period coincides with the crisis that began to directly affect healthcare provider organizations (HCOs). According to data from HIMSS Analytics, the percentage of hospitals stating that their IT operating budgets were increasing continued to fall each quarter in 2010, until the 4th quarter when we saw a return to more normal spending.

According to an annual analysis by the CMS, national healthcare spending rose at a rate of 3.9 percent in 2011, identical to what was reported in 2010. The recession and its resulting decline in the number of people covered by health insurance have been slowing the rate of healthcare spending since 2007. In 2010, according to CMS projections, healthcare spending will stay at 17.6 percent of GDP, the same rate for two years. Healthcare spending slowed across all sources, including the federal government, state governments, private employers and individuals.

The impact on hospitals was largely attributable to two factors— a drop in utilization—especially elective type procedures—which are generally tracked to unemployment, and the 3.4 percent reduction in Medicare’s private health plan payments. By early 2011, lingering unemployment and the expiration of COBRA benefits continued to slow elective admissions in many hospitals.1, 2, 3, 4

In November and December of 2011, we began to see some growth in the national employment rate. The unemployment rate began to tick down below the nine percent range where it had been stuck for most of 2011 and ended at 7.7 percent in November of 2012. The number of layoffs in U.S. hospitals in 2012 was on par with the 2011 number and below the levels in 2009 and 2010 respectively

according to the BLS. In 2012, there were an estimated 124 “mass layoffs” at U.S. hospitals (affecting 50 or more employees at once, a BLS definition) compared to 120 in 2011, 137 in 2010, and 152 in 2009. Even though the overall economy is improving and employment is growing, including in the healthcare sector, the number of “mass layoffs” is similar to 2011. The most common reason cited is impending reductions in Medicare and Medicaid payments. Other data from HIMSS Analytics indicates that hospital consolidation continues to increase, though at a markedly slower pace. In 2012, the number of hospitals per IDN was 7.0 compared to 6.9 in 2011, a positive increase of only 1.45 percent, and considerably less than a growth of 4.55 percent in 2011 over 2010.

Some evidence exists to point to an increase in hospital capital spending, possibly spurred on by the assumption of a decrease in cash flow after 2014 when planned Medicare reductions take place due to the ACA. Of course, increased admissions from expanded coverage availability may offset that decrease from Medicare. That remains to be seen. The notable slowdown in in the number of hospitals per IDN show that very large capital spending may be slowing until hospitals have a better feel for the economic environment in 2014 and beyond.

The average and median ratio of IT department operating expense to total hospital operating expense increased from 2011 to 2012 (see Table HB1).

When examining the ratio of the total IT budget (includes operating and capital expenses for this year) to total hospital operating expense, the average and median ratio decreased from 2011 to 2012; these ratios remain, however, above what was reported in 2010 (see Table HB2).

Ratios related to the hospital’s capital expense to the hospital’s overall capital expense increased from 2010 to 2011 and again from 2011 to 2012. Both the average and median ration increased during this time (see Table HB3).

tAbLe Hb1% of Total IT Operating Expense/Total Hospital Operating Expense-Overall 2010 2011 2012Avg 2 .40% 2 .39% 2 .74%Median 1 .93% 2 .11% 2 .27%N 471 475 400

tAbLe Hb2% of Total IT Budget/Total Hospital Expense–Overall 2010 2011 2012Avg 2 .77% 4 .87% 3 .21%Median 2 .26% 3 .92% 2 .66%N 469 436 479

tAbLe Hb3% IS Capital Expense/Total Hospital Capital Expense–Overall 2010 2011 2012Avg 17 .32% 17 .89% 20 .22%Median 10 .27% 12 .14% 14 .10%N 211 300 244

1 By 2018, national health spending is expected to reach $4 .4 trillion and comprise just over one-fifth (20 .3 percent) of Gross Domestic Product (GDP) . http://www .cms .gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/NationalHealthExpendData/downloads/proj2008 .pdf

2 The actuaries estimate that health spending will account for 19 .6 percent of the gross domestic product (GDP) in 2021, up from 17 .9 percent in 2010 . http://www .govhealthit .com/news/cms-estimates-healthcare-will-soar-one-fifth-gdp

3 For 2011–13, U .S . health spending is projected to grow at 4 .0 percent, on average—slightly above the historically low growth rate of 3 .8 percent in 2009 . (Published June 2012) http://content .healthaffairs .org/content/early/2012/06/11/hlthaff .2012 .0404

4 In 2014, health spending growth is expected to accelerate to 7 .4 percent as the major coverage expansions from the Affordable Care Act begin . (Published June 2012) http://content .healthaffairs .org/content/early/2012/06/11/hlthaff .2012 .0404

▶ 2012 Hospital IT Budget and Expenses


http://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/NationalHealthExpendData/downloads/proj2008.pdf

http://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/NationalHealthExpendData/downloads/proj2008.pdf

http://www.govhealthit.com/news/cms-estimates-healthcare-will-soar-one-fifth-gdp

http://www.govhealthit.com/news/cms-estimates-healthcare-will-soar-one-fifth-gdp

http://content.healthaffairs.org/content/early/2012/06/11/hlthaff.2012.0404




The general increase in the capital and operating expense ratios appear to be modest. However, this may be viewed as an indicator that the economy has recovered to a point where hospitals are beginning to feel more at ease with spending and/or budgeting increases in 2012.

it opeX as a percentage of Hospital total opeXIT OPEX as a percentage of the hospital total OPEX spending generally increased from 2011 to 2012 (see Table HB4). Almost all bed segments experienced a fairly strong increase. The 501–600 bed

segment showed the largest increase at 0.67 percent followed by the 201–300 bed segment (0.50 percent increase) and 0–100 bed segment (0.42 percent increase), while the 301–400 bed segment witnessed a negligible decline (.02 points).

In our opinion, this correlates with the general patterns we have seen with respect to the acquisition and implementation of electronic medical records (EMRs)—where hospitals in the higher bed ranges, particularly academic medical centers, implemented EMRs in larger numbers earlier than those in the middle and lower bed size categories. However, these earlier deployments in larger institutions, notably academic medical centers, were often more “best of breed-like” in their deployments and many now have aging architectures. With the growth of the integrated clinical systems offerings and the need for ARRA compliance and reporting, some of these larger institutions have begun replacing legacy pieces that may be driving this increase. As these larger institutions progress further into the operational phase of their EMR deployments, the increase in expenses typically associated with the implementation phase declines as does the depreciation expense associated with these capital intensive projects, which generally have front-loaded depreciation schedules. During this same period, the most significant increases in the sales of enterprise EMR systems were among medium sized hospital, i.e., those in the 301–500 bed range. Here, we found modest increases in the expense ratios.

An evaluation of the IT OPEX by hospital type showed that every category demonstrated an increase in IT OPEX from 2011 to 2012 (see Table HB5). Rural hospitals reflected the largest growth (0.55 percent) followed by multi-hospital systems (0.49 percent), and critical access and general medical/surgical types (both at 0.43 percent growth).

On a U.S. regional level, the IT OPEX growth occurred for most regions except for the East South Central and New England regions. The Mountain region reported the highest year-over-year growth of almost a full percent (0.88 percent) followed by East North Central and West South Central regions, at 0.64 percent growth each (see Table HB6).

The median IT OPEX ratios for hospital bed size segments shows virtually all of the segments have increased from 2011 to 2012 except the 301–400 bed segment (see Table HB7). The largest growth occurred among large hospitals. Growth in both the 401–500 and 501–600 bed segments is 0.33 percent.

tAbLe Hb72010 2011 2012

Bed Seg

Median % Total IT Operating

Expense/Total Hospital

Oper ating Expense N







0–100 beds 1 .56% 183 1 .70% 171 2 .00% 146101–200 beds 1 .73% 77 1 .98% 91 2 .05% 74201–300 beds 2 .13% 78 2 .20% 74 2 .48% 58301–400 beds 2 .74% 55 2 .75% 60 2 .54% 47401–500 beds 3 .23% 41 3 .13% 37 3 .46% 29501–600 beds 2 .43% 13 3 .17% 17 3 .50% 21Over 600 beds 2 .32% 24 2 .53% 25 2 .62% 25total 1.93% 471 2.11% 475 2.27% 400

tAbLe Hb42010 2011 2012

Bed Seg

Avg % Total IT Operating

Expense/ Total Hospital

Operating Expense N



Operating Expense N



Operating Expense N


tAbLe Hb52010 2011 2012

Type



Operating Expense N



Operating Expense N



Operating Expense N

Academic 3 .20% 39 2 .89% 37 3 .14% 38Non-Academic 2 .33% 432 2 .35% 438 2 .70% 362General Med/Surg 2 .45% 304 2 .35% 321 2 .78% 266Others 2 .31% 167 2 .48% 154 2 .66% 134Critical Access 1 .76% 102 1 .79% 84 2 .22% 78Non-Critical Access 2 .57% 369 2 .52% 391 2 .86% 322Rural 1 .69% 88 1 .79% 66 2 .34% 67Urban 2 .56% 383 2 .49% 409 2 .82% 333Multi-Hospital System 2 .55% 160 2 .52% 187 3 .01% 155Single Hospital System 2 .32% 311 2 .31% 288 2 .57% 245

tAbLe Hb62010 2011 2012

Region



Operating Expense N



Operating Expense N



Operating Expense N

East North Central 2 .60% 77 2 .34% 72 2 .98% 68East South Central 2 .82% 14 3 .28% 15 3 .19% 21Middle Atlantic 2 .35% 49 2 .44% 57 2 .52% 44Mountain 2 .41% 25 2 .34% 18 3 .22% 29New England 3 .20% 46 2 .43% 49 2 .30% 36Pacific 2 .80% 53 2 .46% 67 2 .84% 50South Atlantic 2 .26% 77 2 .36% 82 2 .53% 54West North Central 2 .41% 58 2 .62% 59 2 .76% 57West South Central 1 .46% 72 1 .86% 56 2 .50% 41

state Key for regions:New England . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .MA, ME, VT, RI, CT, NH Middle Atlantic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .NY, NJ, PA South Atlantic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .MD, DE, DC, WV, VA, NC, SC, GA, FL East North Central . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MI, OH, IN, IL, WI East South Central . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . KY, TN, MS, AL West North Central . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MN, IA, MO, KS, ND, SD, NE West South Central . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TX, LA, AR, OK Mountain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ID, CO, WY, MT, NV, UT, AZ, NM Pacific . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . WA, CA, OR, AK, HI

▶ 2012 Hospital IT Budget and Expenses continued


Upon evaluating the median operating expense ratio by hospital type category, all categories indicated a growth in IT OPEX (see Table HB8). The highest growth was among the rural hospital segment (0.42 percent), critical access hospitals (0.38 percent) and multi-hospital systems (0.38 percent).

From 2011 to 2012, most of the U.S. regions indicated IT OPEX growth except Middle Atlantic (see Table HB9). The highest growth occurred in the East South Central region at one percent followed by Mountain region (0.77 percent).

it spending as a percentage of Hospital total spending including cApeXThe average total IT budget as a percent of the total hospital operating expense (the average budget ratio) across various hospital segments is shown in Tables HB10–HB12. Overall, the IT budget ratio increased from 2011 to 2012. Based on the 2012 data, it appears as if the 2010 data was an anomaly and that the 2012 and 2011 data are more comparable than 2010 data.

An evaluation of the average IT budget ratio by bed segmentation shows that the average ratio of four of the seven bed size segments indicated an increase from 2011 to 2012 (0–100, 201–300, 501–600 beds and over 600 beds), ranging from 0.06 percent to 1.39 percent (501–600 beds) (see table HB10). The remaining segments showed a decrease from 2011, ranging from 0.18 percent to 0.32 percent, with the largest decrease among hospitals with between 401 and 500 beds.

Several of the hospital types have indicated an increase in total IT spending to total hospital spending ratio (see Table HB11). These hospital types include academic, non-academic, general medical/surgical, non-critical access, urban and multi-hospital systems. The increase in ratio ranged from 0.07 percent (non-academic facilities) to 0.33 percent (multi-hospital segment). The hospital types that demonstrated a decrease in ratio are “other” non-general medical/surgical, critical access, rural and single hospital systems. The decrease in ratio ranged from 0.06 percent to 0.44 percent. The largest decrease was among critical access hospitals.

The Pacific, East North Central and Mountain regions are the only segments to indicate an increase in spending ratio from 2011 to 2012, ranging from 0.16 percent to 1.58 percent (see Table HB12). All other regions indicated a decrease in the spending ratio with the largest decrease occurring in the West South Central region at 0.80 percent.

tAbLe Hb102010 2011 2012

Bed Seg

Avg of Total IT Budget as

% of Total Hospital Expense N






tAbLe Hb112010 2011 2012

Type








tAbLe Hb122010 2011 2012

Region









tAbLe Hb82010 2011 2012

Type











tAbLe Hb92010 2011 2012

Region












Tables HB13–HB15 represent the median of total IT budget as a percent of the total hospital operating expense (median budget ratio) in the various hospital segments.

By bed segmentation, 0–100, 201–300, 301–400 and 501–600 bed segments indicated an increase in ratio from 2011 to 2012, ranging from 0.13 percent to 1.41 percent (501–600 bed segment) (see Table HB13).

The ratio across almost all of the hospital type market segments, except “other” non-general medical/surgical hospitals and single hospital systems, indicated an increase from 2011 to 2012, ranging from 0.05 percent to 0.26 percent (multi-hospital system) (see Table HB14).

As for the U.S. regions, almost all of them, excluding Middle Atlantic and West North Central, indicated an increase in spending ratio, with the Mountain region demonstrating the highest increase at 1.79 percent (see Table HB15).

tAbLe Hb132010 2011 2012

Bed Seg

Median % Total IT Budget

as % of Total Hospital Expense N






tAbLe Hb142010 2011 2012

Type








tAbLe Hb152010 2011 2012

Region








it capital expenses as a percentage of Hospital total capital expensesAn evaluation of average total IT capital expenses (last fiscal year) to total hospital capital expenses (capital ratios) is shown in tables HB16–HB18. Overall, the general ratio increased across most of the segments from 2011 to 2012 continuing an upward trend based on the increase reported from 2010 to 2011. The economic recovery may be the driving influence in capital spending.

By bed segments, only the 101–200 and over 600 bed segments indicated a decrease in the average capital expense ratio (see Table HB16). Each of these segments showed an approximate two percent decline. The remaining bed segments demonstrated a growth in capital spending ratio from 2011 to 2012, ranging from 2.01 percent to 8.65 percent (501–600 bed segment). The increase is not statistically significant due to the small population size in 2010, 2011 and 2012.

An evaluation by hospital types shows that only academic medical centers indicated a decline from 2011 to 2012 in capital expenses (0.88 percent) (see Table HB17). The remaining hospital types have indicated growth in IT capital spending ranging from 0.26 percent to 6.25 percent (multi-hospital system).

As for the U.S. region, the average IT capital expense spending ratios are mixed. Five of the nine regions (East South Central, Middle Atlantic, Mountain, South Atlantic and West North Central) indicated an increase in spending, ranging from 1.37 percent to 11.07 percent (see Table HB18). The remaining regions demonstrated a decrease in IT capital spending ratio, ranging from 0.84 percent to 3.51 percent.

tAbLe Hb162010 2011 2012

Bed Seg

Avg % Total IT Capital

Expense Last Year/Total

Hospital Capital Expense N








tAbLe Hb172010 2011 2012

Type













tAbLe Hb182010 2011 2012

Region











tAbLe Hb192010 2011 2012

Bed Seg

Median % IT Capital Expense/

Total Hospital Capital Expense N






tAbLe Hb202010 2011 2012

Type








tAbLe Hb212010 2011 2012

Region








An evaluation of median total IT capital expenses to total hospital capital expenses (capital ratios) is shown in tables HB19–HB21. As with the average ratio, the median ratio also increased across most of the segments in the past year.

An analysis of hospital bed segments indicates that the majority of the bed segments indicated an increase in median spending ratio, ranging from 0.70 percent to 11 percent (see Table HB19). The largest increase was among hospitals with 401–500 beds. The bed segments that indicated a decrease in spending were 101–200, 201–300 and over 600 bed segments. All decreases were less than one percent.

With the exception of academic medical centers, all of the hospital types indicated an increase in IT capital spending from 2011 to 2012, ranging from 1.36 percent to 5.13 percent (rural hospitals) (see Table HB20). The decrease among academic medical centers was small at .06 percent.

The regional analysis indicated that almost all of the regions have shown an increase in the ratio from 2011 to 2012 (see Table HB21). The increase in ratio ranged from 0.50 percent to 16.71 percent. The West North Central, West South Central and Pacific regions showed a decrease in this metric.

Market drivers/Future outlook Despite the declines we saw in recent years, we expect the general trend in both average and median ratios to gradually increase as the U.S. shows signs of an economic recovery, and as federal healthcare policies and subsidies combine to drive IT spending higher. There is evidence that patient volumes are rebounding too, attributable to an aging population as well a growing workforce. Also, as cited above, there is a sense that capital spending in general (for plant and equipment) is increasing for the short-term in anticipation of tougher cash flow times ahead. However, very large capital outlays, such as for acquisition of other hospitals, may be under greater constraints.

Hospitals are facing a series of major IT initiatives with significant budgetary and cash flow implications. At the top of this list is the need to continue to acquire, install, expand and/or optimize EMR applications to meet the Stage 1 and Stage 2 Meaningful Use criteria. In 2013 and 2014, hospitals must also begin to ramp up for the implementation of ICD-10 encoding upgrades in 2014—upgrades that will impact a broad range of financial, health information management and clinical systems. Also by 2014, hospitals will need to have enhanced their EMRs to meet Stage 2 Meaningful Use criteria and, by 2015, Stage 3, or they will begin to face financial penalties for non-compliance.

As IDNs ambulatory portfolio continues to grow, some consolidation around a common AEMR and a practice management system will continue to drive some replacement activity. This additional source of patient care data will also drive some infrastructure upgrades in IDN data centers, or see an increasing use of outsourced data centers.

For clinicians, the need for ubiquitous access to EMR data of varying types from inpatient and ambulatory sources—including digital images—will necessitate improved wired and wireless network capacity; higher investments in mobile point-of-care devices; improved security; and more robust remote web access. These upgrades to hospital application portfolios will drive



spending on IT infrastructure higher as well. As more mission-critical, patient clinical data is transformed into digital form, system performance and reliability will become even more important, and costly, for those hospitals that host their own data centers.

This massive growth of clinical data is not going unnoticed by hospital boards and leadership who are expecting the wealth of information to turn into a competitive advantage. C&BI is a growth area for hospitals and the early leaders appear to be the large IDNs who are positioning themselves to be ACOs. Investments in mass data storage, vendor neutral archives, and C&BI skills and tools are driving some significant data center investments, and selective outsourcing of data storage.

While virtualization of both servers and workstations will help to mitigate some of the associated cost increases, most of these costs will be inescapable. Even hospitals that remotely host their applications will see corresponding cost increases as their service

partners will also be forced to provide the necessary additional capacity and services. It is also likely that the virtualization phenomenon that we are seeing with servers and workstations will rapidly spread to storage, as well with vendor neutral archives being a hosted service.

However, some of the costs associated with these trends may not necessarily be fully reflected in our metrics. Based on our experience with past initiatives, many of these anticipated expenses will be in the form of increased consulting costs and additional non-IT labor costs, including nursing and other clinical personnel, as well as specialty personnel in billing, finance and health information management. Although attributable to IT projects, these costs are often not charged back to IT cost centers. Also, increased mass storage costs directly attributable to medical and pathology imaging may be charged to those departments. Our evidence shows that this is more likely in the larger hospital market.

HIMSS Analytics monitors four financial management (FM) applications—accounts payable, enterprise resource planning (ERP), general ledger and materials management. Of these applications, three are highly saturated markets with installation rates exceeding 97 percent (see Table FM1). Not too surprisingly, each of these three applications indicated little or no growth from 2011 to 2012. The fourth application in this category, the ERP application, has an installed base of only 27 percent. The year-over-year growth of ERP has held steady at approximately two percent per year since 2010.

ERP applications typically replace legacy, stand-alone accounts payable, general ledger and materials management, and possibly human resource solutions. That the ERP market may not be as saturated, as general ledger, materials management and accounts payable may be attributed to the fact that these solutions are not sold as an ERP suite, or hospitals may still be running on legacy systems.

We have said in past Annual Reports that we believed that ERP implementations would increase as hospitals consolidate and try to drive supply chain efficiencies. However, we are not seeing that at this time. It is obvious that CIOs are consumed with implementing clinical systems to meet Meaningful Use requirements that have a

▶ Financial Management


cash incentive attached. It appears that major consolidations around an ERP will have to wait until after 2015.

As expected, most of the planned purchases for applications in the financial management suite are from replacement buyers. The exception being ERP, where nearly two-thirds of planned purchases are attributed to first-time purchasers (see Table FM2).

An examination of the financial management application market segment by hospital type reveals the following highlights:• Accounts payable: this market is almost 100 percent saturated

across all hospital types (see Table FM3). No growth activities were reported across all segments.

• ERP: with a market penetration of 49 percent, academic medical centers have the highest adoption rate among the various U.S. hospitals segments considered in this report (see Table FM4). Rural hospitals on the other hand, are the least penetrated hospital segment (10.4 percent). Multi-hospital systems reported the largest increase in installations from 2011 to 2012 at more than three and half percent, followed closely by general medical/surgical and non-critical access hospitals.

• General ledger: more than 99 percent of U.S. hospitals have adopted general ledger technology (see Table FM5). The level of adoption has not changed from 2011 to 2012 across the different hospital segments.

• Materials management: this market has achieved almost complete market saturation (see Table FM6). Most of the hospital segments reflected a slight increase in the past year, with the critical access (1.4 percent) and rural hospital (1.2 percent) segments reporting the greatest increase.

tAbLe FM1 | Financial ManagementN=4,217 2010 2011 2012Accounts Payable 99 .79% 99 .86% 99 .86%Enterprise Resource Planning 22 .69% 24 .19% 26 .82%General Ledger 99 .79% 99 .83% 99 .83%Materials Management 96 .92% 97 .44% 97 .82%Percentages include installed, contracted or installation in process

tAbLe FM2 | 2012# of Hospitals with Installed

Software–Replacing

% of Hospitals with Installed


# of Hospitals Planning to Purchase Software

for the First Time

% of Hospitals Planning to Purchase Software

for the First TimeN = Total Number of

Hospitals PlanningAccounts Payable 58 100 .00% 0 0 .00% 58Enterprise Resource Planning 3 37 .50% 5 62 .50% 8General Ledger 59 100 .00% 0 0 .00% 59Materials Management 45 88 .24% 6 11 .76% 51Replacing = Statuses of live and operational, contracted/not yet installed and installation in processFirst time = Status of not automated


tAbLe FM3 | Accounts payable2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 178 100 .00% 178 177 99 .44% 178 177 99 .44% 178Not Academic 4,030 99 .78% 4,039 4,034 99 .88% 4,039 4,034 99 .88% 4,039Med/Surg 2,449 99 .88% 2,452 2,452 100 .00% 2,452 2,452 100 .00% 2,452Other 1,759 99 .66% 1,765 1,759 99 .66% 1,765 1,759 99 .66% 1,765Critical Access 1,145 99 .74% 1,148 1,146 99 .83% 1,148 1,146 99 .83% 1,148Non-Critical Access 3,063 99 .80% 3,069 3,065 99 .87% 3,069 3,065 99 .87% 3,069Rural 974 99 .80% 976 976 100 .00% 976 976 100 .00% 976Urban 3,234 99 .78% 3,241 3,235 99 .81% 3,241 3,235 99 .81% 3,241Multi-Hospital System 2,585 99 .69% 2,593 2,588 99 .81% 2,593 2,588 99 .81% 2,593Single Hospital System 1,623 99 .94% 1,624 1,623 99 .94% 1,624 1,623 99 .94% 1,624All 4,208 99.79% 4,217 4,211 99.86% 4,217 4,211 99.86% 4,217

tAbLe FM4 | enterprise resource planning2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 78 43 .82% 178 83 46 .63% 178 87 48 .88% 178Non-Academic 879 21 .76% 4,039 937 23 .20% 4,039 1,044 25 .85% 4,039Med/Surg 622 25 .37% 2,452 661 26 .96% 2,452 746 30 .42% 2,452Other 335 18 .98% 1,765 359 20 .34% 1,765 385 21 .81% 1,765Critical Access 114 9 .93% 1,148 121 10 .54% 1,148 137 11 .93% 1,148Non-Critical Access 843 27 .47% 3,069 899 29 .29% 3,069 994 32 .39% 3,069Rural 76 7 .79% 976 78 7 .99% 976 101 10 .35% 976Urban 881 27 .18% 3,241 942 29 .07% 3,241 1,030 31 .78% 3,241Multi-Hospital System 794 30 .62% 2,593 844 32 .55% 2,593 940 36 .25% 2,593Single Hospital System 163 10 .04% 1,624 176 10 .84% 1,624 191 11 .76% 1,624All 957 22.69% 4,217 1,020 24.19% 4,217 1,131 26.82% 4,217

tAbLe FM5 | General Ledger2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 178 100 .00% 178 177 99 .44% 178 177 99 .44% 178Non-Academic 4,030 99 .78% 4,039 4,033 99 .85% 4,039 4,033 99 .85% 4,039Med/Surg 2,450 99 .92% 2,452 2,452 100 .00% 2,452 2,452 100 .00% 2,452Other 1,758 99 .60% 1,765 1,758 99 .60% 1,765 1,758 99 .60% 1,765Critical Access 1,144 99 .65% 1,148 1,145 99 .74% 1,148 1,145 99 .74% 1,148Non-Critical Access 3,064 99 .84% 3,069 3,065 99 .87% 3,069 3,065 99 .87% 3,069Rural 974 99 .80% 976 975 99 .90% 976 975 99 .90% 976Urban 3,234 99 .78% 3,241 3,235 99 .81% 3,241 3,235 99 .81% 3,241Multi-Hospital System 2,586 99 .73% 2,593 2,588 99 .81% 2,593 2,588 99 .81% 2,593Single Hospital System 1,622 99 .88% 1,624 1,622 99 .88% 1,624 1,622 99 .88% 1,624All 4,208 99.79% 4,217 4,210 99.83% 4,217 4,210 99.83% 4,217

tAbLe FM6 | Materials Management2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal


▶ Financial Management continued


When evaluating the market by bed size segments, the following are notable changes from 2011 to 2012:• 0–100 beds: ERP and materials management are the only

financial management applications to grow during this period (see Table FM7).

• 101–200 beds: ERP demonstrated growth of just over three percent, while the other financial management applications demonstrated no change (see Table FM8).

• 201–300 beds: ERP is the only application that demonstrated growth from 2011 to 2012 at more than three and a half percent. The install base of materials management applications decreased slightly (see Table FM9).

• 301–400 beds: At close to four percent, ERP had the highest growth in this segment when compared to the other bed size groupings. The remaining three applications, which have already achieved full market saturation, reported no growth from 2011 to 2012 (see Table FM10)

• 401–500 beds: General ledger, materials management and accounts payable reached full market maturation in 2010 and have maintained complete saturation in 2012 (see Table FM11). Use of ERP solutions grew at slightly more than three percent.

• 501–600 beds: ERP is the only financial management application that demonstrated growth at more than two percent from 2011 to 2012. Materials management reached full market saturation in 2010 and continues to be saturated at this time (see Table FM12).

• Over 600 beds: Close to five percent of growth was reported for ERP in this segment while all other financial management applications maintained market saturation (see Table FM13).

A historical review of financial management application contracts reveals that approximately ten percent of all contracts were signed between 2010 and 2012. Approximately half of all financial management application contracts were signed between 2000 and 2009 (see Tables FM14–FM15).

Purchase activities in this area are being subordinated to Meaningful Use deployments even though some financial management applications are near the end of their useful lives. Some replacement activity was driven by the ICD-10 conversion, but we expect most of that to have been accomplished by this time since the original ICD-10 conversion was set for October 2013.

tAbLe FM14# for Contract

RangeTotal

Responding% of Total

RespondingAccounts payablePrior to 1990 120 2,987 4 .02%1990 to 1994 224 2,987 7 .50%1995 to 1999 919 2,987 30 .77%2000 to 2004 827 2,987 27 .69%2005 to 2009 556 2,987 18 .61%2010 to 2012 341 2,987 11 .42%total 2,987 2,987 100.00%enterprise resource planningPrior to 1990 0 586 0 .00%1990 to 1994 19 586 3 .24%1995 to 1999 206 586 35 .15%2000 to 2004 203 586 34 .64%2005 to 2009 87 586 14 .85%2010 to 2012 71 586 12 .12%total 586 586 100.00%

tAbLe FM15# for Contract

RangeTotal


RespondingGeneral LedgerPrior to 1990 91 2,984 3 .05%1990 to 1994 220 2,984 7 .37%1995 to 1999 916 2,984 30 .70%2000 to 2004 881 2,984 29 .52%2005 to 2009 539 2,984 18 .06%2010 to 2012 337 2,984 11 .29%total 2,984 2,984 100.00%Materials ManagementPrior to 1990 70 2,676 2 .62%1990 to 1994 178 2,676 6 .65%1995 to 1999 662 2,676 24 .74%2000 to 2004 876 2,676 32 .74%2005 to 2009 576 2,676 21 .52%2010 to 2012 314 2,676 11 .73%total 2,676 2,676 100.00%

tAbLe FM70–100 beds 2010 2011 2012

% of 2,165 HospitalsAccounts Payable 2,156 99 .58% 2,160 99 .77% 2,160 99 .77%Enterprise Resource Planning 308 14 .23% 335 15 .47% 376 17 .37%General Ledger 2,156 99 .58% 2,159 99 .72% 2,159 99 .72%Materials Management 2,042 94 .32% 2,060 95 .15% 2,077 95 .94%

tAbLe FM8101–200 beds 2010 2011 2012

% of 802 HospitalsAccounts Payable 802 100 .00% 802 100 .00% 802 100 .00%Enterprise Resource Planning 192 23 .94% 204 25 .44% 229 28 .55%General Ledger 802 100 .00% 802 100 .00% 802 100 .00%Materials Management 797 99 .38% 799 99 .63% 799 99 .63%

tAbLe FM9201–300 beds 2010 2011 2012


tAbLe FM10301–400 beds 2010 2011 2012


tAbLe FM11401–500 beds 2010 2011 2012


tAbLe FM12501–600 beds 2010 2011 2012


tAbLe FM13over 600 beds 2010 2011 2012




Market drivers/Future outlookThe financial management IT application market has been and will continue to be impacted through 2013 by:• Competing IT initiatives (e.g. EHRs, and ICD-10 coding

conversion projects) leaving relatively little capital funding or resources available for the upgrade or replacement of financial management applications.

• Access to capital for replacing older legacy applications and budget battles that assign financial management system replacements a lower priority than high profile, government-mandated clinical systems with incentive dollars to be earned.

• Replacement of legacy general ledger, accounts payable, and materials management application systems by ERP systems, particularly in hospitals with more than 400 beds.

• Some revenue cycle system replacements for those IDNs that qualify as ACOs.

Beyond 2013, we see potential resurgence in purchasing activity in this area, driven by:• The need to improve supply chain management processes and

lower supply costs.• The need to incorporate newer, more automated supply chain

workflows.• The need for more accurate and flexible accounting, resulting

from mergers, acquisitions and divestitures among hospital systems.

• Improved integration with financial decision support and business analytics software.

• Satisfying the accounting and financial analysis and reporting requirements associated with ACOs, patient-centered medical home, and other bundled payment programs related to healthcare reform.


▶ Financial Decision Support Environment

The financial decision support market monitored by HIMSS Analytics consists of the following seven applications: budgeting, business intelligence-financial, cost accounting, data warehousing/mining–financial, executive information systems, financial modeling and medical necessity checking content. With the increased interest in C&BI in hospitals, HIMSS Analytics will begin reporting business intelligence applications separately for financial and clinical functions. The business intelligence–financial is covered in this chapter for 2012, while the business intelligence–clinical will be reported in the electronic medical records section in future Annual Reports.

The financial decision support market presents as a maturing market. Among the seven software solutions tracked in this market, only two applications had a market penetration of less than 50 percent (business intelligence-financial and financial modeling). The most commonly installed application was a budgeting solution (84 percent) (see Table FDS1). The adoption of financial decision support IT applications has increased since 2010 and is expected to continue growing gradually with the exception of the intelligence and warehousing tools that shows above average activity for this segment.

The financial decision support market reflects a mix of hospitals planning to purchase a solution for the first time, as well as those intending to replace existing solutions. The majority of purchases for budgeting, cost accounting, executive information systems and medical necessity content checking will be replacement purchases, while more than half of the planned purchases for business intelligence-financial, data warehousing/mining-financial and financial modeling will be among hospitals procuring these solutions for the first time (see Table FDS2).

The evaluation of the financial decision support market by the various hospital segments yields the following insights: • Budgeting: critical access, rural and non-general medical/surgical

hospitals indicated a growth of more than two percentage points from 2011 to 2012 (see Table FDS3). The academic medical center segment is approaching market saturation and did not demonstrate any growth in the past year.

• Business intelligence-financial: more than five percentage point growth was reported for the rural and critical access segments from 2011 to 2012 (see Table FDS4). All other hospital segments reported a growth of approximately four percentage points, with the exception of the academic medical center segment, which grew by slightly less than three percentage points.

• Cost accounting: both the rural and critical access segments indicated a growth of approximately two percentage points (see Table FDS5). Growth in the other segments was limited and there was no change in adoption among academic medical centers.

tAbLe Fds2 | 2012# of Hospitals with Installed





for the First Time



Hospitals PlanningBudgeting 36 94 .74% 2 5 .26% 38Business Intelligence–Financial 8 44 .44% 10 55 .56% 18Cost Accounting 35 81 .40% 8 18 .60% 43Data Warehousing/Mining–Financial 7 35 .00% 13 65 .00% 20Executive Information Systems 29 80 .56% 7 19 .44% 36Financial Modeling 6 46 .15% 7 53 .85% 13Medical Necessity Checking Content 9 60 .00% 6 40 .00% 15Replacing = Statuses of live and operational, contracted/not yet installed and installation in processFirst time = Status of not automated

tAbLe Fds1 | Financial decision supportN=4,217 2010 2011 2012Budgeting 81 .86% 82 .69% 83 .87%Business Intelligence–Financial 39 .03% 43 .18% 47 .55%Cost Accounting 69 .10% 69 .81% 70 .90%Data Warehousing/Mining–Financial 43 .13% 46 .91% 51 .03%Executive Information Systems 62 .20% 64 .33% 66 .21%Financial Modeling 34 .34% 36 .42% 39 .27%Medical Necessity Checking Content 53 .50% 58 .43% 62 .08%Percentages include installed, contracted or installation in process


▶ Financial Decision Support Environment continued

• Data warehousing/mining-financial: growth was greatest in the rural hospital and critical access hospital segments, at slightly more than five percentage points. Growth in all other segments was between three to four percentage points (see Table FDS6).

• Executive information systems: critical access hospitals and rural hos-pitals demonstrated the highest growth from 2011 to 2012 at approxi-mately three percentage points, while the remaining other segments indicated a growth of one to two percentage points (see Table FDS7).

• Financial modeling: the academic medical center segment reported the largest increase from 2011 to 2012, at more than five percentage points (see Table FDS8). The other segments demonstrated a growth of one to four percentage points.

• Medical necessity checking content: the single hospital segment demonstrated the largest growth from 2011 to 2012 (more than five percentage points). All other segments reported growth ranging from three to slightly under five percentage points (see Table FDS9).

tAbLe Fds3 | budgeting2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 169 94 .94% 178 167 93 .82% 178 167 93 .82% 178Non-Academic 3,283 81 .28% 4,039 3,320 82 .20% 4,039 3,370 83 .44% 4,039Med/Surg 2,198 89 .64% 2,452 2,206 89 .97% 2,452 2,215 90 .33% 2,452Other 1,254 71 .05% 1,765 1,281 72 .58% 1,765 1,322 74 .90% 1,765Critical Access 797 69 .43% 1,148 813 70 .82% 1,148 843 73 .43% 1,148Non-Critical Access 2,655 86 .51% 3,069 2,674 87 .13% 3,069 2,694 87 .78% 3,069Rural 691 70 .80% 976 707 72 .44% 976 730 74 .80% 976Urban 2,761 85 .19% 3,241 2,780 85 .78% 3,241 2,807 86 .61% 3,241Multi-Hospital System 2,250 86 .77% 2,593 2,259 87 .12% 2,593 2,287 88 .20% 2,593Single Hospital System 1,202 74 .01% 1,624 1,228 75 .62% 1,624 1,250 76 .97% 1,624All 3,452 81.86% 4,217 3,487 82.69% 4,217 3,537 83.87% 4,217

tAbLe Fds4 | business intelligence2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 106 59 .55% 178 118 66 .29% 178 123 69 .10% 178Non-Academic 1,540 38 .13% 4,039 1,703 42 .16% 4,039 1,882 46 .60% 4,039Med/Surg 1,066 43 .47% 2,452 1,185 48 .33% 2,452 1,296 52 .85% 2,452Other 580 32 .86% 1,765 636 36 .03% 1,765 709 40 .17% 1,765Critical Access 215 18 .73% 1,148 245 21 .34% 1,148 304 26 .48% 1,148Non-Critical Access 1,431 46 .63% 3,069 1,576 51 .35% 3,069 1,701 55 .43% 3,069Rural 162 16 .60% 976 191 19 .57% 976 242 24 .80% 976Urban 1,484 45 .79% 3,241 1,630 50 .29% 3,241 1,763 54 .40% 3,241Multi-Hospital System 1,276 49 .21% 2,593 1,398 53 .91% 2,593 1,519 58 .58% 2,593Single Hospital System 370 22 .78% 1,624 423 26 .05% 1,624 486 29 .93% 1,624All 1,646 39.03% 4,217 1,821 43.18% 4,217 2,005 47.55% 4,217

tAbLe Fds5 | cost Accounting2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 164 92 .13% 178 165 92 .70% 178 165 92 .70% 178Non-Academic 2,750 68 .09% 4,039 2,779 68 .80% 4,039 2,825 69 .94% 4,039Med/Surg 1,944 79 .28% 2,452 1,955 79 .73% 2,452 1,976 80 .59% 2,452Other 970 54 .96% 1,765 989 56 .03% 1,765 1,014 57 .45% 1,765Critical Access 604 52 .61% 1,148 618 53 .83% 1,148 641 55 .84% 1,148Non-Critical Access 2,310 75 .27% 3,069 2,326 75 .79% 3,069 2,349 76 .54% 3,069Rural 510 52 .25% 976 525 53 .79% 976 546 55 .94% 976Urban 2,404 74 .17% 3,241 2,419 74 .64% 3,241 2,444 75 .41% 3,241Multi-Hospital System 1,934 74 .59% 2,593 1,952 75 .28% 2,593 1,978 76 .28% 2,593Single Hospital System 980 60 .34% 1,624 992 61 .08% 1,624 1,012 62 .32% 1,624All 2,914 69.10% 4,217 2,944 69.81% 4,217 2,990 70.90% 4,217

tAbLe Fds6 | data Warehousing/Mining–Financial2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal



tAbLe Fds7 | executive information systems2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 134 75 .28% 178 135 75 .84% 178 138 77 .53% 178Non-Academic 2,489 61 .62% 4,039 2,578 63 .83% 4,039 2,654 65 .71% 4,039Med/Surg 1,653 67 .41% 2,452 1,713 69 .86% 2,452 1,750 71 .37% 2,452Other 970 54 .96% 1,765 1,000 56 .66% 1,765 1,042 59 .04% 1,765Critical Access 513 44 .69% 1,148 535 46 .60% 1,148 570 49 .65% 1,148Non-Critical Access 2,110 68 .75% 3,069 2,178 70 .97% 3,069 2,222 72 .40% 3,069Rural 429 43 .95% 976 451 46 .21% 976 481 49 .28% 976Urban 2,194 67 .70% 3,241 2,262 69 .79% 3,241 2,311 71 .31% 3,241Multi-Hospital System 1,760 67 .88% 2,593 1,813 69 .92% 2,593 1,854 71 .50% 2,593Single Hospital System 863 53 .14% 1,624 900 55 .42% 1,624 938 57 .76% 1,624All 2,623 62.20% 4,217 2,713 64.33% 4,217 2,792 66.21% 4,217

tAbLe Fds8 | Financial Modeling2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 96 53 .93% 178 101 56 .74% 178 111 62 .36% 178Non-Academic 1,352 33 .47% 4,039 1,435 35 .53% 4,039 1,545 38 .25% 4,039Med/Surg 942 38 .42% 2,452 989 40 .33% 2,452 1,049 42 .78% 2,452Other 506 28 .67% 1,765 547 30 .99% 1,765 607 34 .39% 1,765Critical Access 236 20 .56% 1,148 254 22 .13% 1,148 298 25 .96% 1,148Non-Critical Access 1,212 39 .49% 3,069 1,282 41 .77% 3,069 1,358 44 .25% 3,069Rural 188 19 .26% 976 209 21 .41% 976 235 24 .08% 976Urban 1,260 38 .88% 3,241 1,327 40 .94% 3,241 1,421 43 .84% 3,241Multi-Hospital System 1,053 40 .61% 2,593 1,107 42 .69% 2,593 1,202 46 .36% 2,593Single Hospital System 395 24 .32% 1,624 429 26 .42% 1,624 454 27 .96% 1,624All 1,448 34.34% 4,217 1,536 36.42% 4,217 1,656 39.27% 4,217

tAbLe Fds9 | Medical necessity checking content2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal


The following reflects the highlights of the financial decision support market by bed-size segment:• 0–100 beds: data warehousing/mining-financial and business

intelligence-financial demonstrated the greatest increase, at more than four percentage points each (see Table FDS10). All other financial decision support applications indicated growth ranging from approximately two to three percentage points.

• 101–200 beds: medical necessity checking content and business intelligence-financial indicated growth of more than four percentage points each. Data warehousing/mining-financial also showed growth of nearly four percentage points. Growth for budgeting systems was negligible during this past year (see Table FDS11).

• 201–300 beds: business intelligence-financial and financial modeling indicated the largest growth (at more than four percentage points). Use of cost accounting solutions decreased slightly (see Table FDS12).

• 301–400 beds: medical necessity checking content had the highest growth for this segment at more than four percentage

points, followed by business intelligence-financial at just less than four percent. Budgeting and cost accounting each indicated a slight decrease from 2011 to 2012 (see Table FDS13).

• 401–500 beds: business intelligence-financial had the highest growth for this segment, at more than five percent and data warehousing/mining-financial showed growth of nearly five percentage points. Cost accounting and budgeting reported no growth from 2011 to 2012 (see Table FDS14).

• 501–600 beds: the adoption of medical necessity checking content increased by more than seven percentage points in this bed segment. Almost all of the other financial decision support applications demonstrated slight growth in this bed segment, except budgeting and cost accounting, which are approaching market saturation (see Table FDS15).

• Over 600 beds: with more than a five percentage point increase from 2011 to 2012, financial modeling demonstrated the largest increase within this bed segment. Business intelligence-financial, data warehousing/mining-financial and medical necessity checking content also experienced an increase (see Table FDS16).



tAbLe Fds100–100 beds 2010 2011 2012

% of 2,165 HospitalsBudgeting 1,563 72 .19% 1,597 73 .76% 1,647 76 .07%Business Intelligence–Financial 622 28 .73% 694 32 .06% 789 36 .44%Cost Accounting 1,198 55 .33% 1,228 56 .72% 1,265 58 .43%Data Warehousing/Mining–

Financial 700 32 .33% 755 34 .87% 859 39 .68%Executive Information Systems 1,183 54 .64% 1,228 56 .72% 1,280 59 .12%Financial Modeling 532 24 .57% 577 26 .65% 639 29 .52%Medical Necessity Checking

Content 983 45 .40% 1,072 49 .52% 1,143 52 .79%

tAbLe Fds11101–200 beds 2010 2011 2012

% of 802 HospitalsBudgeting 723 90 .15% 724 90 .27% 725 90 .40%Business Intelligence–Financial 371 46 .26% 408 50 .87% 443 55 .24%Cost Accounting 615 76 .68% 615 76 .68% 627 78 .18%Data Warehousing/Mining–

Financial 397 49 .50% 437 54 .49% 467 58 .23%Executive Information Systems 543 67 .71% 567 70 .70% 577 71 .95%Financial Modeling 306 38 .15% 323 40 .27% 342 42 .64%Medical Necessity Checking

Content 505 62 .97% 540 67 .33% 576 71 .82%

tAbLe Fds12201–300 beds 2010 2011 2012



Content 287 59 .42% 328 67 .91% 342 70 .81%

tAbLe Fds13301–400 beds 2010 2011 2012



Content 196 62 .82% 211 67 .63% 224 71 .79%

tAbLe Fds14401–500 beds 2010 2011 2012



Content 122 64 .89% 134 71 .28% 138 73 .40%

tAbLe Fds15501–600 beds 2010 2011 2012



Content 72 62 .07% 75 64 .66% 84 72 .41%

tAbLe Fds16over 600 beds 2010 2011 2012



Content 91 60 .26% 104 68 .87% 111 73 .51%

At least three-quarters of the contracts signed for all of the applications in the financial decision support application suite were signed in 2000 or later. The most current contract market surrounds medical necessity checking content where more than one-third of all the contracts were signed between 2010 and 2012 (see Tables FDS17–FDS19).

tAbLe Fds17# for Contract

RangeTotal


RespondingbudgetingPrior to 1990 60 2,190 2 .74%1990 to 1994 179 2,190 8 .18%1995 to 1999 393 2,190 17 .96%2000 to 2004 757 2,190 34 .60%2005 to 2009 512 2,190 23 .40%2010 to 2012 289 2,190 13 .21%total 2,190 2,190 100.00%business intelligence–FinancialPrior to 1990 4 826 0 .49%1990 to 1994 28 826 3 .46%1995 to 1999 164 826 20 .27%2000 to 2004 238 826 29 .42%2005 to 2009 245 826 30 .28%2010 to 2012 147 826 18 .17%total 826 826 100.00%cost AccountingPrior to 1990 75 1,803 4 .16%1990 to 1994 200 1,803 11 .10%1995 to 1999 399 1,803 22 .14%2000 to 2004 487 1,803 27 .03%2005 to 2009 416 1,803 23 .09%2010 to 2012 226 1,803 12 .54%total 1,803 1,803 100.00%




RangeTotal


Respondingdata Warehousing/Mining–FinancialPrior to 1990 6 897 0 .68%1990 to 1994 49 897 5 .57%1995 to 1999 109 897 12 .40%2000 to 2004 284 897 32 .31%2005 to 2009 274 897 31 .17%2010 to 2012 175 897 19 .91%total 897 897 100.00%executive information systemsPrior to 1990 42 1,595 2 .64%1990 to 1994 128 1,595 8 .04%1995 to 1999 413 1,595 25 .94%2000 to 2004 394 1,595 24 .75%2005 to 2009 381 1,595 23 .93%2010 to 2012 237 1,595 14 .89%total 1,595 1,595 100.00%Financial ModelingPrior to 1990 6 703 0 .85%1990 to 1994 102 703 14 .53%1995 to 1999 103 703 14 .67%2000 to 2004 250 703 35 .61%2005 to 2009 137 703 19 .52%2010 to 2012 105 703 14 .96%total 703 703 100.00%


RangeTotal


RespondingMedical necessity checking contentPrior to 1990 3 673 0 .45%1990 to 1994 10 673 1 .49%1995 to 1999 123 673 18 .36%2000 to 2004 75 673 11 .19%2005 to 2009 230 673 34 .33%2010 to 2012 232 673 34 .63%total 673 673 100.00%

Market drivers/Future outlookThe financial decision support IT application market has both growth areas and sluggish areas. This market has (and will continue to have) a mixed future driven through 2015 by the following forces:• The drive to provide excellent efficiency analytics counteracts

with declining Medicare and Medicaid reimbursement.• Adoption of ICD-10 coding, and the upgrades of all applications

impacted by this coding will facilitate significantly enhanced cost and quality analyses, though most of this may have been accomplished by year end 2012.

• Continued focus on quality outcomes measures as driven both by the ARRA regulations and the general trend towards transparency and availability of quality and performance metrics to the public at large.

• Higher rates of adoption of EHR applications that provide a rich source of line item consumption data for efficiency analytics.

• Increasing pay for performance reimbursement models from private insurers and the government.

• Continued movement of patient treatment services from the acute care environment to ambulatory settings.

• Increased market competition in large metropolitan areas.• Hospital acquisition/divestiture and merger activities.• The need to carefully evaluate new or enhanced hospital services

to ensure viability, and profitability, or to determine closure or divestiture strategies.

• Increased awareness of, and movement towards, new models of service delivery, such as patient-centered medical homes and ACOs, or other models that may require increased assumption of risk.

• More mature users of performance management and decision support tools replacing their earliest efforts—principally data marts—with more integrated, more functional, enterprise-wide data warehouses.


▶ Human Resource EnvironmentHuman Resources (HR) IT applications support key staff management operations and are therefore critical to a healthcare provider’s success. The value of these applications have elevated over the years as healthcare organizations have relied on these systems to effectively manage staffing shortages and recruitment processes. Hospitals, for example, can alleviate some staff shortages by using these systems to connect to Web sources of resumes and screen the resumes for key words to find candidates.

All of the HR IT applications tracked by HIMSS Analytics grew (albeit ever so slightly) between 2010 and 2012. This growth occurred despite the fact that all these applications are at very high levels of market penetration (see Table HR1). The greatest increase in HR IT application adoption between 2011 and 2012 involved the benefits administration system (.92 percentage point increase), whereas the lowest adoption rate involved the payroll solution (.21 percentage point increase).

The HR IT buyer market is largely composed of replacement purchasers. The exception being time and attendance applications, for which two-thirds of the planned purchases are from hospitals making a purchase for the first time (see Table HR2). The high level of replacement purchases is not unexpected given the high market penetration of these applications.

tAbLe Hr2 | 2012# of Hospitals with Installed





for the First Time



Hospitals PlanningBenefits Administration 21 91 .30% 2 8 .70% 23Payroll 29 96 .67% 1 3 .33% 30Personnel Management 25 86 .21% 4 13 .79% 29Time and Attendance 4 33 .33% 8 66 .67% 12Replacing = Statuses of live and operational, contracted/not yet installed and installation in processFirst time = Status of not automated

tAbLe Hr1 | Human resourcesN=4,217 2010 2011 2012Benefits Administration 88 .64% 89 .59% 90 .51%Payroll 98 .72% 98 .98% 99 .19%Personnel Management 88 .66% 89 .90% 90 .70%Time and Attendance 92 .93% 94 .07% 94 .85%Percentages include installed, contracted or installation in process


▶ Human Resource Environment continued

The following reflects some key highlights when comparing the 2012 HR IT market profile to the 2011 market profile by various hospital segments:• Benefits administration: critical access hospitals demonstrated the

highest level of first-time buyer adoption (two percentage point increase), followed by rural and non-general medical/surgical hospitals. By organizational size, single hospitals reflected a greater first-time buyer adoption rate (just over one percentage point increase) than hospitals belonging to multi-hospital systems (see Table HR3).

• Payroll: the growth for most hospital types was less than one percentage point. The academic medical center segment is the only segment to have achieved 100 percent market penetration. The academic medical segment along with general medical/surgical facilities are the only two segments to reflect no measurable growth in the past year (see Table HR4).

• Personnel management: critical access hospitals demonstrated the largest growth, registering an increase greater than two percentage points. The rural hospital and non-medical surgical hospital segments also grew, although their growth was slightly less than the critical access hospital market. Other hospital segments indicated a year-over-year growth of less than one percent, with the exception of the academic medical center which has 100 percent market penetration and remained unchanged (see Table HR5).

• Time and attendance: rural hospitals and critical access hospitals had the largest growth (approximately two percentage points) between 2011 and 2012. Growth in the single hospital and non-medical surgical segments exceeded one percent, while most of the other segments grew at less than one percent. The academic medical center segment is the only segment to remain unchanged from last year (see Table HR6).

tAbLe Hr3 | benefits Administration2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 176 98 .88% 178 175 98 .31% 178 176 98 .88% 178Non-Academic 3,562 88 .19% 4,039 3,603 89 .21% 4,039 3,641 90 .15% 4,039Med/Surg 2,326 94 .86% 2,452 2,343 95 .55% 2,452 2,354 96 .00% 2,452Other 1,412 80 .00% 1,765 1,435 81 .30% 1,765 1,463 82 .89% 1,765Critical Access 825 71 .86% 1,148 846 73 .69% 1,148 869 75 .70% 1,148Non Critical Access 2,913 94 .92% 3,069 2,932 95 .54% 3,069 2,948 96 .06% 3,069Rural 700 71 .72% 976 727 74 .49% 976 745 76 .33% 976Urban 3,038 93 .74% 3,241 3,051 94 .14% 3,241 3,072 94 .79% 3,241Multi-Hospital System 2,480 95 .64% 2,593 2,489 95 .99% 2,593 2,509 96 .76% 2,593Single Hospital System 1,258 77 .46% 1,624 1,289 79 .37% 1,624 1,308 80 .54% 1,624All 3,738 88.64% 4,217 3,778 89.59% 4,217 3,817 90.51% 4,217

tAbLe Hr4 | payroll2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal


tAbLe Hr5 | personnel Management2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 178 100 .00% 178 178 100 .00% 178 178 100 .00% 178Non Academic 3,561 88 .17% 4,039 3,613 89 .45% 4,039 3,647 90 .29% 4,039Med/Surg 2,343 95 .55% 2,452 2,367 96 .53% 2,452 2,374 96 .82% 2,452Other 1,396 79 .09% 1,765 1,424 80 .68% 1,765 1,451 82 .21% 1,765Critical Access 804 70 .03% 1,148 831 72 .39% 1,148 856 74 .56% 1,148Non-Critical Access 2,935 95 .63% 3,069 2,960 96 .45% 3,069 2,969 96 .74% 3,069Rural 686 70 .29% 976 719 73 .67% 976 736 75 .41% 976Urban 3,053 94 .20% 3,241 3,072 94 .79% 3,241 3,089 95 .31% 3,241Multi-Hospital System 2,488 95 .95% 2,593 2,497 96 .30% 2,593 2,517 97 .07% 2,593Single Hospital System 1,251 77 .03% 1,624 1,294 79 .68% 1,624 1,308 80 .54% 1,624All 3,739 88.66% 4,217 3,791 89.90% 4,217 3,825 90.70% 4,217


tAbLe Hr6 | time and Attendance2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal


When examining the HR IT market by bed size segments, the following observations are notable changes from 2011 to 2012:• 0–100 beds: benefits administration, personnel management and

time and attendance applications increased by one and a half percentage points, while use of payroll systems increased by less than half a percent (see Table HR7).

• 101–200 beds: benefits administration indicated the largest growth in this segment (0.38 percentage points) while the other HR applications remained unchanged (see Table HR8).

• 201–300 beds: personnel management is the only HR application that indicated growth in this segment (.20 percentage points), while the other HR applications remained unchanged (see Table HR9).

• 301–400 beds: payroll and personnel management reached 100 percent market saturation in 2011 and remained unchanged in 2012. Benefits administration demonstrated a slight increase; while time and attendance remained unchanged from 2011 levels (see Table HR10).

• 401–500 beds: payroll and personnel management reached 100 percent market saturation in 2011 and remained unchanged in 2012. Time and attendance experienced a decrease from last year of 0.54 percentage points (see Table HR11).

• 501–600 beds: time and attendance indicated a growth of almost two percent. Payroll and personnel management reached market saturation in 2010 and market penetration remains unchanged. There was also no market growth in the use of benefits administration solutions (see Table HR12).

• Over 600 beds: benefits administration demonstrated an increase of almost one percent while the other applications remained unchanged. Use of payroll and personnel management systems reached market saturation in 2010 (see Table HR13).

Approximately ten percent of contracts for benefits administration, payroll and personnel management were signed within the last two years (between 2010 and 2012). The activity in these areas is not too surprising, since these are often older, legacy solutions that healthcare organizations are replacing (Table HR14 and HR15). This trend can be expected to continue, as at least 40 percent of contracts for all applications in this suite were signed prior to 2000.

That said, there is a good possibility that future purchases of HR IT applications may be deferred for many hospitals because of various federal IT related initiatives, such as ICD-10, and Medicare and Medicaid-funded EHR implementations. Hospitals leaders may elect to allocate their resources in satisfying federal initiatives instead of replacing older HR applications, unless their HR IT applications do not meet minimal requirements or been sunsetted by the vendor.

tAbLe Hr70–100 beds 2010 2011 2012

% of 2,165 HospitalsBenefits Administration 1,738 80 .28% 1,769 81 .71% 1,803 83 .28%Payroll 2,117 97 .78% 2,125 98 .15% 2,134 98 .57%Personnel Management 1,717 79 .31% 1,762 81 .39% 1,795 82 .91%Time and Attendance 1,916 88 .50% 1,953 90 .21% 1,985 91 .69%

tAbLe Hr8101–200 beds 2010 2011 2012

% of 802 HospitalsBenefits Administration 775 96 .63% 779 97 .13% 782 97 .51%Payroll 779 97 .13% 800 99 .75% 800 99 .75%Personnel Management 782 97 .51% 785 97 .88% 785 97 .88%Time and Attendance 779 97 .13% 785 97 .88% 785 97 .88%

tAbLe Hr9201–300 beds 2010 2011 2012


tAbLe Hr10301–400 beds 2010 2011 2012


tAbLe Hr11401–500 beds 2010 2011 2012


tAbLe Hr12501–600 beds 2010 2011 2012


tAbLe Hr13over 600 beds 2010 2011 2012




tAbLe Hr14# for Contract

RangeTotal


Respondingbenefits AdministrationPrior to 1990 100 2,522 3 .97%1990 to 1994 197 2,522 7 .81%1995 to 1999 747 2,522 29 .62%2000 to 2004 725 2,522 28 .75%2005 to 2009 476 2,522 18 .87%2010 to 2012 277 2,522 10 .98%total 2,522 2,522 100.00%payrollPrior to 1990 98 2,779 3 .53%1990 to 1994 207 2,779 7 .45%1995 to 1999 851 2,779 30 .62%2000 to 2004 779 2,779 28 .03%2005 to 2009 529 2,779 19 .04%2010 to 2012 315 2,779 11 .34%total 2,779 2,779 100.00%

tAbLe Hr15# for Contract

RangeTotal


Respondingpersonnel ManagementPrior to 1990 106 2,545 4 .17%1990 to 1994 197 2,545 7 .74%1995 to 1999 776 2,545 30 .49%2000 to 2004 727 2,545 28 .57%2005 to 2009 469 2,545 18 .43%2010 to 2012 270 2,545 10 .61%total 2,545 2,545 100.00%time and AttendancePrior to 1990 39 2,319 1 .68%1990 to 1994 152 2,319 6 .55%1995 to 1999 776 2,319 33 .46%2000 to 2004 749 2,319 32 .30%2005 to 2009 434 2,319 18 .71%2010 to 2012 169 2,319 7 .29%total 2,319 2,319 100.00%

Market drivers/Future outlookIt is our opinion that the HR IT application market has been and will continue to be impacted through 2015 by the following forces:• A concern over future reimbursement levels and higher IT

application priorities, such as EMR and revenue cycle management (RCM) applications, should drive most hospitals to extend the useful life of these applications for as long as possible.

• Continued shortages of clinicians, especially pharmacists, nurses and IT staff are driving an increased interest in manpower planning, skills training and enhanced recruiting tools.

• The need to track security training and policies for all hospital employees.

• Outsourcing services for the HR application suite in order to reduce capital requirements.

• The increased centralization of HR operations in IDNs where employees are internally mobile and where internal consolidation is occurring when acquired hospitals has disparate HR systems.

• Acquisitions and mergers of healthcare IT vendors.• Service as a Software (SaaS)/Application solutions provider

(ASP) products that will appeal to smaller hospitals don’t have the breadth and depth of IT staff to support a large portfolio of IT applications.

• Potential government regulations (e.g., nurse staffing ratios, healthcare savings accounts, public insurance options).

• Innovative benefits packages crafted to attract and retain skilled clinicians.

• The necessity to track clinician credentials and continuing education for all hospital employees.

• The need to drive efficiencies in HR departments through the expanded use of e-HR functions such as e-recruiting, HR portals, etc.


▶ Revenue Cycle Management Environment

The business processes supported by the applications in the Revenue Cycle Management (RCM) category are critical to a hospital’s viability. There are eight different applications tracked by HIMSS Analytics in this report: ADT/registration, bed management, contract management, credit/collections, electronic data interchange (EDI), enterprise master person index (EMPI), patient billing and patient scheduling.

Of the applications monitored, four applications have reached or are approaching market saturation. These applications are ADT/registration, patient billing, patient scheduling, and credit/collections (see Table RCM1). Bed management indicated the largest year-over-year growth from 2011 to 2012, registering an increase of approximately four percentage points. Growth for the remaining applications was three percentage points or less. ADT/registration is the only application to remain unchanged from last year.

The majority of purchasing plans for all of the RCM applications in 2012 were replacement purchases (see Table RCM2). This was not

just the case for applications that have achieved market saturation, but for all applications. Due to impending federal regulation implementation dates that will require significant changes for the RCM environment with the ICD-10 coding adoption in 2014, the impact of healthcare reform legislative provisions for bundled payments and ACOs, it is expected that replacement purchasing will continue to grow significantly for RCM applications through 2015.

tAbLe rcM1 | revenue cycle ManagementN=4,217 2010 2011 2012ADT/Registration 99 .55% 99 .67% 99 .67%Bed Management 33 .96% 38 .42% 42 .47%Contract Management 66 .11% 67 .56% 70 .05%Credit/Collections 90 .89% 91 .68% 93 .03%Electronic Data Interchange (EDI)–

Clearing House Vendor 80 .39% 84 .82% 87 .55%Enterprise Master Patient Index (EMPI) 48 .66% 52 .10% 54 .97%Patient Billing 99 .29% 99 .81% 99 .86%Patient Scheduling 95 .94% 96 .82% 97 .49%Percentages include installed, contracted or installation in process


▶ Revenue Cycle Management Environment continued

An evaluation of the RCM application market by hospital market segment indicates the following highlights:• ADT/Registration: virtually all hospitals types have reached market

saturation with adoption rates exceeding 99 percent (see Table RCM3).• Bed management: the academic medical center segment reported

the highest penetration rate at more than 78 percent in 2012. Adoption in this market grew slightly less than three percentage points in the past year. In general, there is a consistent level of adoption growth of approximately four percentage points across all other market segments (see Table RCM4).

• Contract management: the rural hospital, critical access hospital and multi-hospital segments reported a year-over-year growth that exceeded three percentage points (see Table RCM5).

• Credit/Collections: the critical access hospital, rural hospital and other non-general medical/surgical hospital segments reported the highest growth (approximately two and one half percentage points). The academic medical center segment is approaching market saturation and demonstrated no growth in the past year. Growth in all other segments was less than two percentage points (see Table RCM6).

• EDI: all of the segments indicated growth from 2011 to 2012 ranging from two to three percent, with rural hospitals indicating the largest growth (see Table RCM7).

• EMPI: the rural hospital and general medical/surgical hospital segments demonstrated the highest growth from 2011 to 2012 at more than three percentage points. The other segments indicated smaller growth rates, with the academic medical center segment indicating the smallest growth at less than one percentage point (see Table RCM8).

• Patient billing: with 99 percent of U.S. hospitals indicating they have patient billing, there is little to no growth in this market segment. Those segments that did indicate some growth had grown one-tenth of one percentage point or less (see Table RCM9).

• Patient scheduling: this is a highly saturated market. The rural hospital, critical access hospital, single hospital and other non-general medical/surgical hospital segments reported growth exceeding one percentage point from 2011 to 2012. The remaining segments reported growth at less than one percentage point. The academic medical center segment, which is fully saturated, is the only segment to report no growth from last year (see Table RCM10).

tAbLe rcM2 | 2012# of Hospitals with Installed





for the First Time



Hospitals PlanningADT/Registration 63 100 .00% 0 0 .00% 63Bed Management 34 91 .89% 3 8 .11% 37Contract Management 30 83 .33% 6 16 .67% 36Credit/Collections 44 100 .00% 0 .00% 44Electronic Data Interchange (EDI)–

Clearing House Vendor 15 93 .75% 1 6 .25% 16Enterprise Master Patient Index (EMPI) 33 82 .50% 7 17 .50% 40Patient Billing 66 100 .00% 0 0 .00% 66Patient Scheduling 64 95 .52% 3 4 .48% 67Replacing = Statuses of live and operational, contracted/not yet installed and installation in processFirst time = Status of not automated

tAbLe rcM3 | Adt/registration2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal


tAbLe rcM4 | bed Management2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 120 67 .42% 178 135 75 .84% 178 140 78 .65% 178Non-Academic 1,312 32 .48% 4,039 1,485 36 .77% 4,039 1,651 40 .88% 4,039Med/Surg 1,044 42 .58% 2,452 1,146 46 .74% 2,452 1,255 51 .18% 2,452Other 388 21 .98% 1,765 474 26 .86% 1,765 536 30 .37% 1,765Critical Access 181 15 .77% 1,148 229 19 .95% 1,148 277 24 .13% 1,148Non-Critical Access 1,251 40 .76% 3,069 1,391 45 .32% 3,069 1,514 49 .33% 3,069Rural 132 13 .52% 976 169 17 .32% 976 207 21 .21% 976Urban 1,300 40 .11% 3,241 1,451 44 .77% 3,241 1,584 48 .87% 3,241Multi-Hospital System 985 37 .99% 2,593 1,115 43 .00% 2,593 1,225 47 .24% 2,593Single Hospital System 447 27 .52% 1,624 505 31 .10% 1,624 566 34 .85% 1,624All 1,432 33.96% 4,217 1,620 38.42% 4,217 1,791 42.47% 4,217



tAbLe rcM5 | contract Management2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 147 82 .58% 178 148 83 .15% 178 150 84 .27% 178Non- Academic 2,641 65 .39% 4,039 2,701 66 .87% 4,039 2,804 69 .42% 4,039Med/Surg 1,825 74 .43% 2,452 1,863 75 .98% 2,452 1,919 78 .26% 2,452Other 963 54 .56% 1,765 986 55 .86% 1,765 1,035 58 .64% 1,765Critical Access 478 41 .64% 1,148 489 42 .60% 1,148 528 45 .99% 1,148Non-Critical Access 2,310 75 .27% 3,069 2,360 76 .90% 3,069 2,426 79 .05% 3,069Rural 410 42 .01% 976 423 43 .34% 976 458 46 .93% 976Urban 2,378 73 .37% 3,241 2,426 74 .85% 3,241 2,496 77 .01% 3,241Multi-Hospital System 1,967 75 .86% 2,593 2,008 77 .44% 2,593 2,086 80 .45% 2,593Single Hospital System 821 50 .55% 1,624 841 51 .79% 1,624 868 53 .45% 1,624All 2,788 66.11% 4,217 2,849 67.56% 4,217 2,954 70.05% 4,217

tAbLe rcM6 | credit/collections2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal


tAbLe rcM7 | electronic data interchange (edi)–clearing House vendor2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal


tAbLe rcM8 | enterprise Master person index (eMpi)2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal



tAbLe rcM9 | patient billing2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal


tAbLe rcM10 | patient scheduling2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal


The evaluation by bed size reported that ADT/registration, patient billing, and patient scheduling are at, or near, saturation across all bed segments (see Tables RCM11–RCM17). ADT/registration indicated no growth across all bed segments. Some other key findings within each bed segment are as follows:• 0–100 beds: bed management, contract management and EDI

indicated the largest growth, surpassing three percentage points from 2011 to 2012 (see Table RCM11).

• 101–200 beds: bed management reported the largest increase over the past year at slightly less than six percentage points. Contract management, EDI and EMPI showed growth of between two and four percentage points, while the remaining solutions showed growth of less than one percentage point (see Table RCM12).

• 201–300 beds: the adoption of bed management grew by more than four percentage points in this segment. Growth of the other applications ranged from less than one percentage point for credit/collections and patient scheduling to nearly three percentage points for EMPI. ADT/registration has reached market saturation and did not see any additional growth (see Table RCM13).

• 301–400 beds: bed management reported a growth of more than three percentage points, while contract management and EMPI grew at approximately two percentage points. ADT/registration, patient billing and patient scheduling, which are all at or near market saturation did not grow in the past year (see Table RCM14).

• 401–500 beds: EMPI reported the highest increase at more than three percentage points, while bed management and EDI grew approximately two percentage points. Contract management and credit/collections are the only applications which decreased slightly in penetration from 2011 to 2012 (see Table RCM15).

• 501–600 beds: bed management demonstrated the largest increase over the past year at more than six percentage points, followed by contract management at four percentage points. Applications at or

near market saturation such as ADT/registration, credit/collections, patient billing and patient scheduling demonstrated no growth (see Table RCM16).

• Over 600 beds: bed management and EDI are the only RCM applications to report a growth exceeding three percentage points from 2011 to 2012. ADT/registration, patient billing and patient scheduling, which have all reached market saturation, reported no growth. The remaining applications demonstrated growth of less than three percentage points (see Table RCM17).

tAbLe rcM110–100 beds 2010 2011 2012

% of 2,165 HospitalsADT/Registration 2,147 99 .17% 2,152 99 .40% 2,152 99 .40%Bed Management 418 19 .31% 510 23 .56% 586 27 .07%Contract Management 1,152 53 .21% 1,193 55 .10% 1,258 58 .11%Credit/Collections 1,865 86 .14% 1,889 87 .25% 1,937 89 .47%Electronic Data Interchange

(EDI)–Clearing House Vendor 1,681 77 .64% 1,770 81 .76% 1,842 85 .08%Enterprise Master Patient

Index (EMPI) 830 38 .34% 900 41 .57% 956 44 .16%Patient Billing 2,136 98 .66% 2,158 99 .68% 2,159 99 .72%Patient Scheduling 2,008 92 .75% 2,043 94 .36% 2,066 95 .43%

tAbLe rcM12101–200 beds 2010 2011 2012

% of 802 HospitalsADT/Registration 801 99 .88% 801 99 .88% 801 99 .88%Bed Management 294 36 .66% 323 40 .27% 368 45 .89%Contract Management 615 76 .68% 622 77 .56% 638 79 .55%Credit/Collections 775 96 .63% 776 96 .76% 780 97 .26%Electronic Data Interchange

(EDI)–Clearing House Vendor 663 82 .67% 699 87 .16% 717 89 .40%Enterprise Master Patient

Index (EMPI) 442 55 .11% 482 60 .10% 514 64 .09%Patient Billing 801 99 .88% 802 100 .00% 802 100 .00%Patient Scheduling 793 98 .88% 794 99 .00% 797 99 .38%



tAbLe rcM13201–300 beds 2010 2011 2012




tAbLe rcM14301–400 beds 2010 2011 2012




tAbLe rcM15401–500 beds 2010 2011 2012




tAbLe rcM16501–600 beds 2010 2011 2012




tAbLe rcM17over 600 beds 2010 2011 2012




In evaluating the RCM contract signed dates, 10 to 20 percent of the contracts signed were done so between 2010 and 2012. The exceptions are bed management and credit/collections. More than 30 percent of the contracts for bed management were signed between 2010 and 2012, while only four percent of the total credit/collections contracts were signed during this time. The majority of credit/collections contracts were signed from 1990 to 2004.

Activities between 2010 and 2012, particularly for market saturated applications such as ADT/registration, patient billing and patient scheduling, are good indications that replacement purchases are being made. It is likely that these applications will continue to be replaced over the next three to five years.

tAbLe rcM18# for Contract

RangeTotal


RespondingAdt/registrationPrior to 1990 120 3,088 3 .89%1990 to 1994 320 3,088 10 .38%1995 to 1999 749 3,088 24 .29%2000 to 2004 774 3,088 25 .10%2005 to 2009 658 3,088 21 .34%2010 to 2012 467 3,088 15 .14%total 3,088 3,088 100.00%bed ManagementPrior to 1990 9 664 1 .36%1990 to 1994 16 664 2 .41%1995 to 1999 40 664 6 .03%2000 to 2004 147 664 22 .17%2005 to 2009 253 664 38 .16%2010 to 2012 199 664 30 .02%total 664 664 100.00%contract ManagementPrior to 1990 54 1,727 3 .15%1990 to 1994 101 1,727 5 .88%1995 to 1999 406 1,727 23 .65%2000 to 2004 521 1,727 30 .34%2005 to 2009 416 1,727 24 .23%2010 to 2012 229 1,727 13 .34%total 1,727 1,727 100.00%


RangeTotal


Respondingcredit/collectionsPrior to 1990 330 2,781 11 .88%1990 to 1994 716 2,781 25 .78%1995 to 1999 656 2,781 23 .62%2000 to 2004 568 2,781 20 .45%2005 to 2009 400 2,781 14 .40%2010 to 2012 111 2,781 4 .00%total 2,781 2,781 100.00%electronic data interchange (edi)–clearing House vendorPrior to 1990 15 1,316 1 .15%1990 to 1994 71 1,316 5 .44%1995 to 1999 263 1,316 20 .14%2000 to 2004 338 1,316 25 .88%2005 to 2009 398 1,316 30 .47%2010 to 2012 231 1,316 17 .69%total 1,316 1,316 100.00%enterprise Master patient index (eMpi)Prior to 1990 13 1,338 0 .97%1990 to 1994 85 1,338 6 .35%1995 to 1999 163 1,338 12 .18%2000 to 2004 450 1,338 33 .63%2005 to 2009 360 1,338 26 .91%2010 to 2012 267 1,338 19 .96%total 1,338 1,338 100.00%




RangeTotal


Respondingpatient billingPrior to 1990 147 3,048 4 .83%1990 to 1994 309 3,048 10 .15%1995 to 1999 772 3,048 25 .37%2000 to 2004 749 3,048 24 .61%2005 to 2009 619 3,048 20 .34%2010 to 2012 452 3,048 14 .85%total 3,048 3,048 100.00%patient schedulingPrior to 1990 44 2,677 1 .65%1990 to 1994 205 2,677 7 .69%1995 to 1999 532 2,677 19 .96%2000 to 2004 784 2,677 29 .42%2005 to 2009 651 2,677 24 .43%2010 to 2012 461 2,677 17 .30%total 2,677 2,677 100.00%

Market drivers/Future outlookThe RCM IT application market has been and will continue to be impacted through 2015 by:• The conversion to ICD-10 coding currently scheduled for

October 1, 2014.• The need of many organizations to update or replace their legacy

RCM environments to effectively meet ICD-10 upgrade and conversion requirements.

• The emergence of outcomes-based reimbursement models, some of which will be driven by ARRA Meaningful Use requirements, while others will be in response to pay for performance initiatives from private insurers.

• Hospitals electing to compete as an ACO in consort with other entities.

• Hospitals focusing on bundled payments as a measure to integrate the medical and surgical staff with Medicare and possible private insurance contracts.

• The focus on consumer/patient satisfaction and patient engagement (e.g., pricing transparency, consumer-friendly billing formats, online bill paying, self-scheduling, pre-registration and other web-based, self-service applications).

• The need to more effectively integrate financial and clinical data for business analysis and government reporting.

• The need to more effectively integrate financial decision support into the RCM environment.


▶ Next Generation Revenue Cycle Management

Next generation revenue cycle management (next generation RCM) IT solutions refer to applications designed to improve collection rates, business office workflows, productivity, patient satisfaction and patient convenience. The solutions contribute to the overall efficiency of the RCM process by complementing and enhancing core legacy RCM applications.

HIMSS Analytics monitors the solutions available in the following five next generation RCM categories:1. Consumer focus: provides the ability to extend B2C (Business to

Consumer) web services to patients; and facilitates online pre-registration,self-scheduling, and bill payment to enhance patient service efficiency and convenience.

2. Eligibility verification: supports real-time insurance eligibility verification transactions to ensure that patients’ insurance covers services and procedures.

3. Rules capability for billing and payment processing: provides rules engines that facilitate medical necessity checking during patient scheduling and registration functions prior to care delivery; determine self-pay patient liability prior to or at the point of registration; and compare submitted, allowed and paid claims against contractual terms to identify and facilitate claims resubmissions. They also allow business office personnel to edit bills online prior to submission, if needed, to improve billing accuracy and compliance with contractual terms and to provide the necessary updates to all billing and accounts receivable files related to those edits. next generation RCM tools can also accommodate the auto-encoding of clinical information from the EHR system, determine claims attachment requirements, and automatically create required attachments (when such supporting data exists in digital form, such as in the EHR) prior to claim

submission to avoid denied or pended claims and improve the efficiency and accuracy of the billing process.

4. Claims processing: provides the ability to submit claims directly to payers, eliminating the need to use a third-party clearinghouse intermediary; accepts direct electronic claims remittance transactions from payers; and directly posts third-party payments against patient-specific receivables from bundled remittance transactions.

5. Treasury functions: provides electronic funds transfers (EFT) from third-party payers directly to the provider organization’s bank accounts to improve cash flow and facilitate financial reconciliation processes for the organization.

The adoption of next generation RCM solutions continued to increase this past year with the exception of EMR documentation for claims, which showed a minor decrease (less than one percent). Web self-pay demonstrated the highest growth rate among next

tAbLe nGrcM1 | next Generation revenue cycle ManagementN=4,217 2010 2011 2012Biller’s Dash Board 22 .69% 25 .85% 28 .57%Claims Attachment Rules 26 .01% 28 .72% 32 .23%Claims Remittance Updates AR 15 .27% 16 .79% 17 .95%Denial Rules 26 .68% 30 .31% 34 .01%Direct Payer Claims 12 .14% 12 .90% 13 .59%EFT Transaction 24 .24% 26 .08% 28 .05%Eligibility Transaction with Payer 15 .51% 16 .93% 17 .83%EMR Documentation for Claims 3 .84% 2 .96% 2 .82%Necessity Alert @ Registration 36 .25% 38 .65% 40 .03%Necessity Alert @ Scheduling 21 .48% 23 .14% 24 .99%Web PreRegister 16 .81% 19 .26% 20 .49%Web Schedule 6 .76% 6 .92% 9 .13%Web Self-Pay 26 .89% 32 .51% 38 .04%Percentages include installed, contracted or installation in process


▶ Next Generation Revenue Cycle Management continued

generation RCM applications (more than five percentage points), followed by denial rules (approximately four percentage points), and claims attachment rules (3.5 percentage points). The remaining next generation RCM applications increased between approximately one and three percentage points (see Table NGRCM1).

The next generation RCM index is developed by HIMSS Analytics designed to allow hospitals to compare their use of next generation RCM capabilities against other hospitals in the market. A hospital’s next generation RCM adoption is influenced by several factors that include business needs, strategies and competitive environment. Hospitals must be cognizant of the impact that ICD-10 coding upgrades and Meaningful Use objectives will have on many of these applications, and are highly encouraged to be preparing their upgrade strategies now.

An evaluation of this market in 2012 by hospital type shows the following trends:

consumer Focus:• Web pre-registration: the rural hospital segment’s adoption rate

showed the highest increase at more than two percentage points, followed closely by the critical access segment at just under two percentage points (see Table NGRCM2).

• Web scheduling: all segments indicated an increase of between one and a half and four percentage points from 2011 to 2012, with academic medical centers showing the greatest increase (see Table NGRCM3). (Note: we are not making a distinction between whether the consumer can actually write an appointment to the schedule or simply request a schedule slot which is later confirmed by the provider).

• Web self-pay: all segments increased adoption of this technology. The academic medical center, medical/surgical, non-critical access hospital and multi-hospital system segments had an increase of more than six percentage points from 2011 to 2012 (see Table NGRCM4).

eligibility verification• Medical necessity alerts at the point of scheduling: growth was

consistent at one to two percentage points across all hospital segments (see Table NGRCM5).

• Medical necessity alerts at point of registration: the highest growth in adoption occurred in the single hospital system segment at approximately three percentage points. All other segments except multi-hospital system showed growth at more than one percentage point (see Table NGRCM6).

rules and billing capabilities:• Claims attachment rules: at approximately six percentage points,

the academic medical center hospital segment had the highest growth in 2012. Adoption in the remaining hospital segments increased between three and four percentage points (see Table NGRCM7).

• Denials rules: the highest growth rate was evidenced in academic medical centers at approximately six percentage points. From 2011 to 2012, all other hospital segments increased between three and four percentage points (see Table NGRCM8).

• Biller’s dashboard (a graphical user interface of key performance indicators for billing processes that also allows for the editing of claims data): the academic medical center hospital segment had the highest growth rate at approximately four percentage points, followed closely by the single hospital system segment at more than three percentage points. The remaining segments all increased over two percentage points (see Table NGRCM9).

• EMR documentation for claims: the academic medical center hospital segment grew by one percentage point, while the remaining segments either grew by less than one percentage point or experienced a slight decrease (see Table NGRCM10).

claims processing:• Direct payer claims (no clearinghouse): between 2011 and 2012,

the medical/surgical and non-critical access hospital segments experienced the highest growth rates of approximately one percentage point. Academic medical centers had no change in adoption rates, while critical access hospitals experienced a slight decrease (see Table NGRCM11).

• Claims remittance with automatic accounts receivable update: most hospital segments grew by one percentage point while the rural hospital segment increased by roughly two percentage points (see Table NGRCM12).

• Eligibility transaction with payer (no clearinghouse): the highest growth is witnessed in the academic medical center segment at approximately two percentage points. The remaining segments grew by approximately one percentage point (see Table NGRCM13).

treasury Funds • EFT transactions (direct to organization’s bank): the academic

medical center hospital segment grew approximately three percentage points between 2011 and 2012. The general medical/surgical, non-critical access, multi-hospital and urban hospital segments experienced the next highest increases (see Table NGRCM14).

tAbLe nGrcM2 | Web pre-register2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 31 17 .42% 178 29 16 .29% 178 30 16 .85% 178Non-Academic 678 16 .79% 4,039 783 19 .39% 4,039 834 20 .65% 4,039Med/Surg 548 22 .35% 2,452 645 26 .31% 2,452 671 27 .37% 2,452Other 161 9 .12% 1,765 167 9 .46% 1,765 193 10 .93% 1,765Critical Access 99 8 .62% 1,148 104 9 .06% 1,148 126 10 .98% 1,148Non-Critical Access 610 19 .88% 3,069 708 23 .07% 3,069 738 24 .05% 3,069Rural 79 8 .09% 976 101 10 .35% 976 123 12 .60% 976Urban 630 19 .44% 3,241 711 21 .94% 3,241 741 22 .86% 3,241Multi-Hospital System 606 23 .37% 2,593 697 26 .88% 2,593 721 27 .81% 2,593Single Hospital System 103 6 .34% 1,624 115 7 .08% 1,624 143 8 .81% 1,624All 709 16.81% 4,217 812 19.26% 4,217 864 20.49% 4,217



tAbLe nGrcM3 | Web schedule2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal


tAbLe nGrcM4 | Web self-pay2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 63 35 .39% 178 60 33 .71% 178 73 41 .01% 178Non-Academic 1,071 26 .52% 4,039 1,311 32 .46% 4,039 1,531 37 .91% 4,039Med/Surg 828 33 .77% 2,452 992 40 .46% 2,452 1,152 46 .98% 2,452Other 306 17 .34% 1,765 379 21 .47% 1,765 452 25 .61% 1,765Critical Access 197 17 .16% 1,148 270 23 .52% 1,148 315 27 .44% 1,148Non-Critical Access 937 30 .53% 3,069 1,101 35 .87% 3,069 1,289 42 .00% 3,069Rural 169 17 .32% 976 229 23 .46% 976 273 27 .97% 976Urban 965 29 .77% 3,241 1,142 35 .24% 3,241 1,331 41 .07% 3,241Multi-Hospital System 885 34 .13% 2,593 1,033 39 .84% 2,593 1,189 45 .85% 2,593Single Hospital System 249 15 .33% 1,624 338 20 .81% 1,624 415 25 .55% 1,624All 1,134 26.89% 4,217 1,371 32.51% 4,217 1,604 38.04% 4,217

tAbLe nGrcM5 | necessity Alert @ scheduling2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 34 19 .10% 178 40 22 .47% 178 42 23 .60% 178Non-Academic 872 21 .59% 4,039 936 23 .17% 4,039 1,012 25 .06% 4,039Med/Surg 658 26 .84% 2,452 712 29 .04% 2,452 765 31 .20% 2,452Other 248 14 .05% 1,765 264 14 .96% 1,765 289 16 .37% 1,765Critical Access 177 15 .42% 1,148 183 15 .94% 1,148 202 17 .60% 1,148Non-Critical Access 729 23 .75% 3,069 793 25 .84% 3,069 852 27 .76% 3,069Rural 135 13 .83% 976 142 14 .55% 976 162 16 .60% 976Urban 771 23 .79% 3,241 834 25 .73% 3,241 892 27 .52% 3,241Multi-Hospital System 626 24 .14% 2,593 654 25 .22% 2,593 698 26 .92% 2,593Single Hospital System 280 17 .24% 1,624 322 19 .83% 1,624 356 21 .92% 1,624All 906 21.48% 4,217 976 23.14% 4,217 1,054 24.99% 4,217

tAbLe nGrcM6 | necessity Alert @ registration2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 59 33 .15% 178 71 39 .89% 178 73 41 .01% 178Non-Academic 1,470 36 .40% 4,039 1,559 38 .60% 4,039 1,615 39 .99% 4,039Med/Surg 997 40 .66% 2,452 1,066 43 .47% 2,452 1,103 44 .98% 2,452Other 532 30 .14% 1,765 564 31 .95% 1,765 585 33 .14% 1,765Critical Access 310 27 .00% 1,148 325 28 .31% 1,148 344 29 .97% 1,148Non-Critical Access 1,219 39 .72% 3,069 1,305 42 .52% 3,069 1,344 43 .79% 3,069Rural 264 27 .05% 976 280 28 .69% 976 297 30 .43% 976Urban 1,265 39 .03% 3,241 1,350 41 .65% 3,241 1,391 42 .92% 3,241Multi-Hospital System 1,076 41 .50% 2,593 1,132 43 .66% 2,593 1,142 44 .04% 2,593Single Hospital System 452 27 .83% 1,624 498 30 .67% 1,624 546 33 .62% 1,624All 1,529 36.25% 4,217 1,630 38.65% 4,217 1,688 40.03% 4,217



tAbLe nGrcM7 | claims Attachment rules2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 52 29 .21% 178 61 34 .27% 178 71 39 .89% 178Non-Academic 1,045 25 .87% 4,039 1,150 28 .47% 4,039 1,288 31 .89% 4,039Med/Surg 702 28 .63% 2,452 766 31 .24% 2,452 860 35 .07% 2,452Other 395 22 .38% 1,765 445 25 .21% 1,765 499 28 .27% 1,765Critical Access 201 17 .51% 1,148 235 20 .47% 1,148 271 23 .61% 1,148Non-Critical Access 896 29 .20% 3,069 976 31 .80% 3,069 1,088 35 .45% 3,069Rural 172 17 .62% 976 190 19 .47% 976 227 23 .26% 976Urban 925 28 .54% 3,241 1,021 31 .50% 3,241 1,132 34 .93% 3,241Multi-Hospital System 677 26 .11% 2,593 731 28 .19% 2,593 814 31 .39% 2,593Single Hospital System 420 25 .86% 1,624 480 29 .56% 1,624 545 33 .56% 1,624All 1,097 26.01% 4,217 1,211 28.72% 4,217 1,359 32.23% 4,217

tAbLe nGrcM8 | denial rules2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 60 33 .71% 178 71 39 .89% 178 81 45 .51% 178Non-Academic 1,065 26 .37% 4,039 1,207 29 .88% 4,039 1,353 33 .50% 4,039Med/Surg 707 28 .83% 2,452 794 32 .38% 2,452 893 36 .42% 2,452Other 418 23 .68% 1,765 484 27 .42% 1,765 541 30 .65% 1,765Critical Access 210 18 .29% 1,148 252 21 .95% 1,148 290 25 .26% 1,148Non-Critical Access 915 29 .81% 3,069 1,026 33 .43% 3,069 1,144 37 .28% 3,069Rural 181 18 .55% 976 209 21 .41% 976 249 25 .51% 976Urban 944 29 .13% 3,241 1,069 32 .98% 3,241 1,185 36 .56% 3,241Multi-Hospital System 674 25 .99% 2,593 736 28 .38% 2,593 827 31 .89% 2,593Single Hospital System 451 27 .77% 1,624 542 33 .37% 1,624 607 37 .38% 1,624All 1,125 26.68% 4,217 1,278 30.31% 4,217 1,434 34.01% 4,217

tAbLe nGrcM9 | biller’s dashboard2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 49 27 .53% 178 57 32 .02% 178 64 35 .96% 178Non-Academic 908 22 .48% 4,039 1,033 25 .58% 4,039 1,141 28 .25% 4,039Med/Surg 561 22 .88% 2,452 642 26 .18% 2,452 716 29 .20% 2,452Other 396 22 .44% 1,765 448 25 .38% 1,765 489 27 .71% 1,765Critical Access 208 18 .12% 1,148 241 20 .99% 1,148 269 23 .43% 1,148Non-Critical Access 749 24 .41% 3,069 849 27 .66% 3,069 936 30 .50% 3,069Rural 188 19 .26% 976 214 21 .93% 976 243 24 .90% 976Urban 769 23 .73% 3,241 876 27 .03% 3,241 962 29 .68% 3,241Multi-Hospital System 570 21 .98% 2,593 629 24 .26% 2,593 687 26 .49% 2,593Single Hospital System 387 23 .83% 1,624 461 28 .39% 1,624 518 31 .90% 1,624All 957 22.69% 4,217 1,090 25.85% 4,217 1,205 28.57% 4,217

tAbLe nGrcM10 | eMr documentation for claims2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal




tAbLe nGrcM11 | direct payer claims2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal


tAbLe nGrcM12 | claims remittance updates Ar2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal


tAbLe nGrcM13 | eligibility transaction with payer2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal


tAbLe nGrcM14 | eFt transaction2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 53 29 .78% 178 63 35 .39% 178 69 38 .76% 178Non-Academic 969 23 .99% 4,039 1,037 25 .67% 4,039 1,114 27 .58% 4,039Med/Surg 609 24 .84% 2,452 640 26 .10% 2,452 706 28 .79% 2,452Other 413 23 .40% 1,765 460 26 .06% 1,765 477 27 .03% 1,765Critical Access 228 19 .86% 1,148 253 22 .04% 1,148 260 22 .65% 1,148Non-Critical Access 794 25 .87% 3,069 847 27 .60% 3,069 923 30 .07% 3,069Rural 195 19 .98% 976 210 21 .52% 976 219 22 .44% 976Urban 827 25 .52% 3,241 890 27 .46% 3,241 964 29 .74% 3,241Multi-Hospital System 607 23 .41% 2,593 634 24 .45% 2,593 693 26 .73% 2,593Single Hospital System 415 25 .55% 1,624 466 28 .69% 1,624 490 30 .17% 1,624All 1,022 24.24% 4,217 1,100 26.08% 4,217 1,183 28.05% 4,217



An evaluation of next generation RCM adoption by hospital bed-size reveals the following insights (see Tables NGRCM15–NGRCM21):• 0–100 beds: web self-pay demonstrated the largest increase at

more than four percentage points. Claims attachment rules and denial rules each increased in adoption by three percentage points. EMR documentation for claims showed a slight decrease in adoption.

• 101–200 beds: web self-pay and denial rules increased in adoption by approximately four percentage points. All other next generation RCM applications, except EMR documentation for claims, increased between one and three percentage points.

• 201–300 beds: the highest increase in adoption is evidenced in the web self-pay application with an approximate growth of eight percentage points. Denial rules adoption increased by approximately five percentage points while claims attachment rules increased by slightly more than four percentage points.

• 301–400 beds: the adoption of web self-pay had the highest increase at six percentage points, followed by biller’s dashboard at more than four percentage points. Besides EMR documentation for claims and web preregister, all other next generation RCM applications increased between one and four percentage points.

• 401–500 beds: web self-pay and biller’s dashboard demonstrated the largest increases in application adoption at more than four percentage points. Necessity alert at registration decreased by more than two percentage points, while EMR documentation for claims decreased by one percentage point. Web preregister, web schedule, claims attachment rules and denial rules each increased by three percentage points from 2011 to 2012.

• 501–600 beds: the highest growth in adoption for this bed segment was for web self-pay at 11 percentage points. Web schedule had the second largest growth at approximately eight percentage points. Direct payer claims and claims remittance accounts receivable updates did not change while all other next generation RCM applications grew between one and six percentage points.

• Over 600 beds: web self-pay had the largest increase in adoption at more than 11 percentage points, followed by web schedule at six percentage points. The remaining next generation RCM applications increased approximately one to five percentage points.

tAbLe nGrcM150–100 beds 2010 2011 2012

% of 2,165 HospitalsWeb PreRegister 232 10 .72% 271 12 .52% 294 13 .58%Web Schedule 63 2 .91% 68 3 .14% 108 4 .99%Web Self-Pay 426 19 .68% 542 25 .03% 641 29 .61%Necessity Alert @ Scheduling 334 15 .43% 350 16 .17% 378 17 .46%Necessity Alert @ Registration 690 31 .87% 730 33 .72% 748 34 .55%Claims Attachment Rules 494 22 .82% 538 24 .85% 606 27 .99%Denial Rules 514 23 .74% 581 26 .84% 650 30 .02%Biller’s Dashboard 475 21 .94% 535 24 .71% 583 26 .93%EMR Documentation for Claims 53 2 .45% 42 1 .94% 39 1 .80%Direct Payer Claims 230 10 .62% 247 11 .41% 252 11 .64%Claims Remittance Updates AR 318 14 .69% 329 15 .20% 349 16 .12%Eligibility Transaction with Payer 336 15 .52% 366 16 .91% 379 17 .51%EFT Transaction 503 23 .23% 542 25 .03% 565 26 .10%

tAbLe nGrcM16101–200 beds 2010 2011 2012

% of 802 HospitalsWeb PreRegister 172 21 .45% 212 26 .43% 217 27 .06%Web Schedule 70 8 .73% 70 8 .73% 83 10 .35%Web Self-Pay 280 34 .91% 338 42 .14% 373 46 .51%Necessity Alert @ Scheduling 218 27 .18% 244 30 .42% 273 34 .04%Necessity Alert @ Registration 323 40 .27% 346 43 .14% 365 45 .51%Claims Attachment Rules 213 26 .56% 239 29 .80% 268 33 .42%Denial Rules 219 27 .31% 256 31 .92% 288 35 .91%Biller’s Dashboard 157 19 .58% 188 23 .44% 206 25 .69%EMR Documentation for Claims 34 4 .24% 24 2 .99% 21 2 .62%Direct Payer Claims 85 10 .60% 90 11 .22% 100 12 .47%Claims Remittance Updates AR 103 12 .84% 122 15 .21% 132 16 .46%Eligibility Transaction with Payer 111 13 .84% 122 15 .21% 130 16 .21%EFT Transaction 180 22 .44% 198 24 .69% 221 27 .56%

tAbLe nGrcM17201–300 beds 2010 2011 2012


tAbLe nGrcM18301–400 beds 2010 2011 2012


tAbLe nGrcM19401–500 beds 2010 2011 2012




▶ Health Information Management

tAbLe nGrcM20501–600 beds 2010 2011 2012


tAbLe nGrcM21over 600 beds 2010 2011 2012


Market drivers/Future outlookThe next generation RCM market is still in its infancy, but these applications are expected to become critical solutions for all hospitals within the next few years (see Table NGRCM1). This market will continue to be impacted through 2015 by:• Capital constraints and the intense competition of IT capital

funds, which will drive many hospitals to acquire bolt-on next generation RCM applications to enhance their existing, legacy RCM environments, extending their useful life.

• Possible major upgrades or outright replacements of RCM solutions due to the ICD-10 mandate.

• Shifting profile of the vendors offering next generation RCM solutions. Many next generation RCM applications in each of the product categories are currently delivered by relatively small, specialty vendors. Over time, we expect: – Larger RCM vendors to introduce similar capabilities as an integral component of new versions. Hospitals upgrading to these new versions will displace these niche products.

– In the near term, many of the specialty vendors offering these applications will be acquired by larger RCM vendors.

• As more small- to mid-sized hospitals contract for EMRs, many of these hospitals will acquire complete application suites, including replacement of legacy RCM applications with versions that incorporate these features.

• Stage 2 Meaningful Use has a strong intent to increase “patient engagement” as a way to begin tackling the chronic disease issues in the country. We see this as another Meaningful Use driver for web capabilities adoption.

The health information management (HIM) IT environment focuses on solutions designed to assist with the maintenance and care of paper as well as EHRs. Eleven different HIM applications are tracked by HIMSS Analytics in this report; abstracting, case mix management, chart deficiency, chart tracking/locator, computer-assisted coding, data warehousing/mining-clinical, dictation, dictation with speech recognition, encoder, outcomes and quality management and in-house transcription.

The HIM environment generally presents as a well-penetrated marketplace. Five of the 11 HIM applications tracked had penetration levels of 90 percent or greater (abstracting and encoder, chart deficiency, chart tracking/locator and dictation), while eight applications exceeded 70 percent (see Table HIM1). That said, three applications in this environment have exceedingly lower penetration levels when compared to the other applications in this suite: dictation with speech recognition (45.3 percent), data warehousing/mining–clinical (43.0 percent), and computer assisted coding (12.8 percent).

Overall, the HIM environment is a growing market as nine of the eleven applications tracked in this report increased penetration levels of one to five percentage points in 2012. The two applications with lower penetration levels in 2012 were in-house transcription (decreased by approximately one percentage point) and computer assisted coding (decreased by more than four percentage points).

While the decline of the in-house transcription market penetration may be reflective of a service increasingly outsourced, the notable decline in the computer assisted coding is due in large part to a change in HIMSS Analytics’ definition of computer assisted coding. In 2012, the definition of computer assisted coding was changed to read “software solutions that utilize natural language processing (NLP) and exclusive patented algorithmic software to electronically analyze entire medical charts to pre-code with both CPT procedure and ICD diagnostic nomenclatures.” Due to the change in the definitions, it is likely that computer assisted coding data from 2010 and 2011 were over-reported.

tAbLe HiM1 | Health information ManagementN=4,217 2010 2011 2012Abstracting 95 .61% 96 .66% 97 .34%Case Mix Management 78 .68% 79 .87% 81 .20%Chart Deficiency 90 .70% 92 .39% 93 .72%Chart Tracking/Locator 89 .49% 91 .13% 91 .89%Computer Assisted Coding 14 .63% 17 .17% 12 .78%Data Warehousing/Mining–Clinical 33 .32% 38 .42% 42 .97%Dictation 88 .10% 90 .75% 92 .13%Dictation with Speech Recognition 33 .67% 40 .67% 45 .27%Encoder 95 .94% 96 .59% 97 .15%Outcomes and Quality Management 68 .65% 70 .31% 73 .18%In-House Transcription 77 .73% 76 .76% 75 .39%Percentages include installed, contracted or installation in process


▶ Health Information Management continued

The best growth potential for the HIM market is expected in two applications—dictation with speech recognition and data warehousing/mining-clinical. However, with respect to the latter, the increasing trend towards more highly integrated, enterprise-wide architectures to support business and clinical intelligence, outcomes and quality reporting, can lead to a corresponding de-emphasis of, and decline in, specialized, department-specific data marts. We believe that a significant portion of the growth reported in the adoption of the data warehousing/mining – clinical and the outcomes and quality management applications go hand-in-hand with the growth highlighted in the Financial Decision Support section of this report.

The market penetration of computer assisted coding is highest among academic medical centers at close to 25 percent in 2012. The next highest is general medical surgical hospitals and multi-hospital systems at slightly under 15 percent. As usual, academic medical centers are often closely associated as early adopters to new technology.

Encoding upgrades (due to ICD-10 upgrade requirements) and outcomes and quality management (due to ARRA Meaningful Use reporting) are expected to be growth drivers in the HIM market. Standardization of the templates for transcribed documents will improve the ability of hospitals to share standard patient information with one another using the CDA construct (see www.HealthStory.com).

The HIM market generally reflects a replacement buyer market partially driven by continued movement away form “best of breed” solutions. This is especially true for abstracting, case mix management, chart deficiency, chart tracking/locator and in-house transcription. That said, the majority of purchases for computer assisted coding will be first time purchases (see Table HIM2).

Through 2015, two government mandates are expected to significantly impact the HIM market. The first is the requirement to upgrade encoding systems to use ICD-10 codes by October 1, 2014 (which was delayed in August 2012 from the original date of October 1, 2013). The other mandate is the requirement to report on clinical outcomes as part of the ARRA Meaningful Use requirements. Health reform, and changes in reimbursement methods demanded by both public and private insurers, will increase the need for hospitals to report process and outcomes measures in order to justify reimbursement or qualify for pay for performance bonus payments. These mandates will drive increased HIM application upgrades, if not outright system replacements.

Highlights of the past year by hospital segments reveal the following:• Abstracting: the rural hospital and critical access hospital

segments have the largest year-over-year growth at approximately two percentage points. Most of the other segments reported a

growth of one percentage point or less. Having already reached market saturation, there was no reported growth among academic medical centers (see Table HIM3).

• Case mix management: rural hospitals had the highest year-over-year growth at more than three percentage points. The critical access hospital segment also saw growth of more than two percentage points (see Table HIM4).

• Chart deficiency: both the critical access hospital and the rural hospital segments saw growth of more than three percentage points (see Table HIM5). All other segments registered growth of less than three percentage points.

• Chart tracking/locator: the critical access and rural hospital segments both reported growth of more than three percentage points. A number of segments reported a slight decline in use of chart tracking/locator solutions (see Table HIM6).

• Computer assisted coding: in 2012, about one-quarter of the academic medical centers reported adopting computer assisted coding solutions. Due to a change in definition of computer assisted coding, comparison to previous years’ data is not meaningful (see Table HIM7).

• Data warehousing/mining–clinical: all of the hospital segments indicated a growth ranging from three to six percentage points, with the highest growth demonstrated by academic medical centers and the multi-hospital system segments (see Table HIM8).

• Dictation: except for the academic medical center segment, all segments grew three percentage points or less (see Table HIM9). Growth was greatest in the critical access hospital and rural hospital segments.

• Dictation with speech recognition: the growth for all hospital segments was consistent ranging between three and five percentage points (see Table HIM10). The greatest growth was in the general medical/surgical hospital and multi-hospital system segments.

• Encoder: because this solution is on the verge of complete market saturation across all market segments, there was little increase in adoption over the past year. No segment reported growth of more than two percentage points (see Table HIM11).

• Outcomes and quality management: both the rural hospital and critical access hospital segments reported growth more than four percentage points from 2011 to 2012. The other hospital segments indicated growth ranging from two to four percentage points (see Table HIM12).

• In-house transcription: all hospital segments demonstrated a decrease in the penetration of this application. The academic medical center segment indicated the sharpest decrease in adoption at more than two percentage points (see Table HIM13).

tAbLe HiM2 | 2012# of Hospitals with Installed





for the First Time



Hospitals PlanningAbstracting 50 90 .91% 5 9 .09% 55Case Mix Management 37 97 .37% 1 2 .63% 38Chart Deficiency 45 88 .24% 6 11 .76% 51Chart Tracking/Locator 43 91 .49% 4 8 .51% 47Computer Assisted Coding 2 2 .99% 65 97 .01% 67Data Warehousing/Mining–Clinical 7 50 .00% 7 50 .00% 14Dictation 6 54 .55% 5 45 .45% 11Dictation with Speech Recognition 16 48 .48% 17 51 .52% 33Encoder 9 52 .94% 8 47 .06% 17Outcomes and Quality Management 12 63 .16% 7 36 .84% 19In-House Transcription 5 83 .33% 1 16 .67% 6Replacing = Statuses of live and operational, contracted/not yet installed and installation in processFirst time = Status of not automated


http://www.HealthStory.com


tAbLe HiM3 | Abstracting2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 176 98 .88% 178 177 99 .44% 178 177 99 .44% 178Non- Academic 3,856 95 .47% 4,039 3,899 96 .53% 4,039 3,928 97 .25% 4,039Med/Surg 2,425 98 .90% 2,452 2,432 99 .18% 2,452 2,434 99 .27% 2,452Other 1,607 91 .05% 1,765 1,644 93 .14% 1,765 1,671 94 .67% 1,765Critical Access 1,011 88 .07% 1,148 1,041 90 .68% 1,148 1,066 92 .86% 1,148Non- Critical Access 3,021 98 .44% 3,069 3,035 98 .89% 3,069 3,039 99 .02% 3,069Rural 860 88 .11% 976 883 90 .47% 976 905 92 .73% 976Urban 3,172 97 .87% 3,241 3,193 98 .52% 3,241 3,200 98 .73% 3,241Multi-Hospital System 2,531 97 .61% 2,593 2,547 98 .23% 2,593 2,556 98 .57% 2,593Single Hospital System 1,501 92 .43% 1,624 1,529 94 .15% 1,624 1,549 95 .38% 1,624All 4,032 95.61% 4,217 4,076 96.66% 4,217 4,105 97.34% 4,217

tAbLe HiM4 | case Mix Management2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 166 93 .26% 178 167 93 .82% 178 170 95 .51% 178Non- Academic 3,152 78 .04% 4,039 3,201 79 .25% 4,039 3,254 80 .56% 4,039Med/Surg 2,133 86 .99% 2,452 2,162 88 .17% 2,452 2,183 89 .03% 2,452Other 1,185 67 .14% 1,765 1,206 68 .33% 1,765 1,241 70 .31% 1,765Critical Access 668 58 .19% 1,148 675 58 .80% 1,148 707 61 .59% 1,148Non- Critical Access 2,650 86 .35% 3,069 2,693 87 .75% 3,069 2,717 88 .53% 3,069Rural 578 59 .22% 976 587 60 .14% 976 619 63 .42% 976Urban 2,740 84 .54% 3,241 2,781 85 .81% 3,241 2,805 86 .55% 3,241Multi-Hospital System 2,205 85 .04% 2,593 2,241 86 .42% 2,593 2,273 87 .66% 2,593Single Hospital System 1,113 68 .53% 1,624 1,127 69 .40% 1,624 1,151 70 .87% 1,624All 3,318 78.68% 4,217 3,368 79.87% 4,217 3,424 81.20% 4,217

tAbLe HiM5 | chart deficiency2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal


tAbLe HiM6 | chart tracking/Locator2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal




tAbLe HiM7 | computer Assisted coding2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 39 21 .91% 178 46 25 .84% 178 43 24 .16% 178Non- Academic 578 14 .31% 4,039 678 16 .79% 4,039 496 12 .28% 4,039Med/Surg 420 17 .13% 2,452 479 19 .54% 2,452 365 14 .89% 2,452Other 197 11 .16% 1,765 245 13 .88% 1,765 174 9 .86% 1,765Critical Access 122 10 .63% 1,148 148 12 .89% 1,148 97 8 .45% 1,148Non- Critical Access 495 16 .13% 3,069 576 18 .77% 3,069 442 14 .40% 3,069Rural 96 9 .84% 976 110 11 .27% 976 76 7 .79% 976Urban 521 16 .08% 3,241 614 18 .94% 3,241 463 14 .29% 3,241Multi-Hospital System 391 15 .08% 2,593 467 18 .01% 2,593 387 14 .92% 2,593Single Hospital System 226 13 .92% 1,624 257 15 .83% 1,624 152 9 .36% 1,624All 617 14.63% 4,217 724 17.17% 4,217 539 12.78% 4,217

tAbLe HiM8 | data Warehousing/Mining–clinical2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 95 53 .37% 178 108 60 .67% 178 118 66 .29% 178Non- Academic 1,310 32 .43% 4,039 1,512 37 .44% 4,039 1,694 41 .94% 4,039Med/Surg 930 37 .93% 2,452 1,088 44 .37% 2,452 1,205 49 .14% 2,452Other 475 26 .91% 1,765 532 30 .14% 1,765 607 34 .39% 1,765Critical Access 208 18 .12% 1,148 229 19 .95% 1,148 290 25 .26% 1,148Non- Critical Access 1,197 39 .00% 3,069 1,391 45 .32% 3,069 1,522 49 .59% 3,069Rural 173 17 .73% 976 196 20 .08% 976 248 25 .41% 976Urban 1,232 38 .01% 3,241 1,424 43 .94% 3,241 1,564 48 .26% 3,241Multi-Hospital System 1,026 39 .57% 2,593 1,188 45 .82% 2,593 1,332 51 .37% 2,593Single Hospital System 379 23 .34% 1,624 432 26 .60% 1,624 480 29 .56% 1,624All 1,405 33.32% 4,217 1,620 38.42% 4,217 1,812 42.97% 4,217

tAbLe HiM9 | dictation2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal


tAbLe HiM10 | dictation with speech recognition2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 111 62 .36% 178 126 70 .79% 178 134 75 .28% 178Non- Academic 1,309 32 .41% 4,039 1,589 39 .34% 4,039 1,775 43 .95% 4,039Med/Surg 1,017 41 .48% 2,452 1,225 49 .96% 2,452 1,348 54 .98% 2,452Other 403 22 .83% 1,765 490 27 .76% 1,765 561 31 .78% 1,765Critical Access 192 16 .72% 1,148 269 23 .43% 1,148 326 28 .40% 1,148Non- Critical Access 1,228 40 .01% 3,069 1,446 47 .12% 3,069 1,583 51 .58% 3,069Rural 141 14 .45% 976 194 19 .88% 976 241 24 .69% 976Urban 1,279 39 .46% 3,241 1,521 46 .93% 3,241 1,668 51 .47% 3,241Multi-Hospital System 1,031 39 .76% 2,593 1,219 47 .01% 2,593 1,357 52 .33% 2,593Single Hospital System 389 23 .95% 1,624 496 30 .54% 1,624 552 33 .99% 1,624All 1,420 33.67% 4,217 1,715 40.67% 4,217 1,909 45.27% 4,217



tAbLe HiM11 | encoder2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal


tAbLe HiM12 | outcomes and Quality Management2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 151 84 .83% 178 153 85 .96% 178 160 89 .89% 178Non- Academic 2,744 67 .94% 4,039 2,812 69 .62% 4,039 2,926 72 .44% 4,039Med/Surg 1,909 77 .85% 2,452 1,944 79 .28% 2,452 2,005 81 .77% 2,452Other 986 55 .86% 1,765 1,021 57 .85% 1,765 1,081 61 .25% 1,765Critical Access 466 40 .59% 1,148 494 43 .03% 1,148 544 47 .39% 1,148Non- Critical Access 2,429 79 .15% 3,069 2,471 80 .51% 3,069 2,542 82 .83% 3,069Rural 418 42 .83% 976 441 45 .18% 976 487 49 .90% 976Urban 2,477 76 .43% 3,241 2,524 77 .88% 3,241 2,599 80 .19% 3,241Multi-Hospital System 2,066 79 .68% 2,593 2,110 81 .37% 2,593 2,172 83 .76% 2,593Single Hospital System 829 51 .05% 1,624 855 52 .65% 1,624 914 56 .28% 1,624All 2,895 68.65% 4,217 2,965 70.31% 4,217 3,086 73.18% 4,217

tAbLe HiM13 | in-House transcription2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal


The highlights by bed size segments yielded the following (see Tables HIM14–HIM20):• 0–100 beds: data warehousing-clinical indicated the largest

increase in growth from 2011 to 2012 at nearly five percentage points, followed by dictation with speech recognition at more than four percentage points (see Table HIM14). In-house transcription and computer assisted coding (redefined for 2012) both showed decreases in market penetration.

• 101–200 beds: eight of the 11 applications indicated an increase in market penetration; the largest growth was among dictation with speech recognition solutions. Decreases in market penetration were seen for chart tracking/locator, computer assisted coding and in-house transcription (see Table HIM15).

• 201–300 beds: dictation with speech recognition showed the highest growth at more than five percentage points. Growth was also strong for data warehousing/mining-clinical solutions. Decreased market penetration was seen for chart tracking/ locator, computer assisted coding and in-house transcription (see Table HIM16).

• 301–400 beds: the application with the greatest growth in this segment was dictation with speech recognition, at nearly four percentage points. Decreased market penetration was noted for chart tracking/locator, computer assisted coding and in-house transcription (see Table HIM17).

• 401–500 beds: at more than six percentage points, data warehousing/mining-clinical demonstrated the largest growth from 2011 to 2012. This was followed by dictation with speech recognition at more than four percentage points (see Table HIM18). Adoption of both computer assisted coding and in-house transcription declined. There are also many saturated markets with no growth potential.

• 501–600 beds: both the dictation with speech recognition and data warehousing/mining-clinical indicated a growth of more than six percentage points from 2011 to 2012 (see Table HIM19). Declines in market penetration were noted in abstracting, chart deficiency, chart tracking/locator, encoder and in-house transcription.

• Over 600 beds: dictation with speech recognition and data warehousing/mining-clinical are the only two applications to indicate a growth from 2011 to 2012. All other segments reported a decline or no change (see Table HIM20).



tAbLe HiM140–100 beds 2010 2011 2012

% of 2,165 HospitalsAbstracting 1,992 92 .01% 2,031 93 .81% 2,057 95 .01%Case Mix Management 1,470 67 .90% 1,500 69 .28% 1,547 71 .45%Chart Deficiency 1,790 82 .68% 1,857 85 .77% 1,908 88 .13%Chart Tracking/Locator 1,757 81 .15% 1,824 84 .25% 1,864 86 .10%Computer Assisted Coding 246 11 .36% 293 13 .53% 199 9 .19%Data Warehousing/Mining–Clinical 506 23 .37% 581 26 .84% 682 31 .50%Dictation 1,756 81 .11% 1,832 84 .62% 1,880 86 .84%Dictation with Speech Recognition 427 19 .72% 544 25 .13% 640 29 .56%Encoder 1,998 92 .29% 2,026 93 .58% 2,048 94 .60%Outcomes and Quality Management 1,202 55 .52% 1,247 57 .60% 1,330 61 .43%In-House Transcription 1,653 76 .35% 1,663 76 .81% 1,636 75 .57%

tAbLe HiM15101–200 beds 2010 2011 2012

% of 802 HospitalsAbstracting 795 99 .13% 798 99 .50% 801 99 .88%Case Mix Management 720 89 .78% 727 90 .65% 731 91 .15%Chart Deficiency 787 98 .13% 791 98 .63% 796 99 .25%Chart Tracking/Locator 784 97 .76% 789 98 .38% 787 98 .13%Computer Assisted Coding 126 15 .71% 140 17 .46% 99 12 .34%Data Warehousing/Mining–Clinical 304 37 .91% 363 45 .26% 399 49 .75%Dictation 762 95 .01% 779 97 .13% 784 97 .76%Dictation with Speech Recognition 320 39 .90% 382 47 .63% 419 52 .24%Encoder 800 99 .75% 799 99 .63% 801 99 .88%Outcomes and Quality Management 653 81 .42% 660 82 .29% 677 84 .41%In-House Transcription 619 77 .18% 600 74 .81% 592 73 .82%

tAbLe HiM16201–300 beds 2010 2011 2012


tAbLe HiM17301–400 beds 2010 2011 2012


tAbLe HiM18401–500 beds 2010 2011 2012


tAbLe HiM19501–600 beds 2010 2011 2012


tAbLe HiM20over 600 beds 2010 2011 2012


When analyzing the HIM contract information in the HIMSS Analytics database, contracts for most of the applications tracked were signed between 1995 and 2004. The notable exception surrounds computer assisted coding contracts for which approximately three-quarters of these contracts were signed between 2010 and 2012 (see Tables HIM20–HIM23).

tAbLe HiM21# for Contract

RangeTotal


RespondingAbstractingPrior to 1990 119 2,826 4 .21%1990 to 1994 213 2,826 7 .54%1995 to 1999 694 2,826 24 .56%2000 to 2004 736 2,826 26 .04%2005 to 2009 634 2,826 22 .43%2010 to 2012 430 2,826 15 .22%total 2,826 2,826 100.00%case Mix ManagementPrior to 1990 114 2,355 4 .85%1990 to 1994 233 2,355 9 .91%1995 to 1999 552 2,355 23 .48%2000 to 2004 722 2,355 30 .71%2005 to 2009 430 2,355 18 .29%2010 to 2012 304 2,355 12 .93%total 2,355 2,355 100.00%chart deficiencyPrior to 1990 63 2,696 2 .34%1990 to 1994 171 2,696 6 .35%1995 to 1999 567 2,696 21 .05%2000 to 2004 838 2,696 31 .11%2005 to 2009 647 2,696 24 .02%2010 to 2012 410 2,696 15 .22%total 2,696 2,696 100.00%




RangeTotal


Respondingchart tracking/LocatorPrior to 1990 68 2,607 2 .61%1990 to 1994 181 2,607 6 .95%1995 to 1999 564 2,607 21 .64%2000 to 2004 808 2,607 31 .01%2005 to 2009 593 2,607 22 .76%2010 to 2012 393 2,607 15 .08%total 2,607 2,607 100.00%computer Assisted codingPrior to 1990 0 95 0 .00%1990 to 1994 0 95 0 .00%1995 to 1999 5 95 5 .26%2000 to 2004 5 95 5 .26%2005 to 2009 11 95 11 .58%2010 to 2012 74 95 77 .89%total 95 95 100.00%data Warehousing/Mining–clinicalPrior to 1990 5 974 0 .52%1990 to 1994 139 974 14 .36%1995 to 1999 70 974 7 .23%2000 to 2004 262 974 27 .07%2005 to 2009 295 974 30 .48%2010 to 2012 203 974 20 .97%total 974 974 100.00%


RangeTotal


RespondingdictationPrior to 1990 31 1,581 1 .96%1990 to 1994 76 1,581 4 .81%1995 to 1999 263 1,581 16 .64%2000 to 2004 605 1,581 38 .27%2005 to 2009 435 1,581 27 .51%2010 to 2012 171 1,581 10 .82%total 1,581 1,581 100.00%dictation with speech recognitionPrior to 1990 0 590 0 .00%1990 to 1994 6 590 1 .05%1995 to 1999 7 590 1 .23%2000 to 2004 112 590 19 .61%2005 to 2009 322 590 56 .39%2010 to 2012 143 590 25 .04%total 590 590 100.00%encoderPrior to 1990 222 2,181 10 .18%1990 to 1994 280 2,181 12 .84%1995 to 1999 681 2,181 31 .22%2000 to 2004 556 2,181 25 .49%2005 to 2009 294 2,181 13 .48%2010 to 2012 153 2,181 7 .02%total 2,186 2,181 100.23%


RangeTotal


Respondingoutcomes and Quality ManagementPrior to 1990 37 1,841 2 .02%1990 to 1994 132 1,841 7 .21%1995 to 1999 440 1,841 24 .03%2000 to 2004 620 1,841 33 .86%2005 to 2009 344 1,841 18 .79%2010 to 2012 268 1,841 14 .64%total 1,841 1,841 100.00%in-House transcriptionPrior to 1990 35 1,566 2 .25%1990 to 1994 141 1,566 9 .07%1995 to 1999 318 1,566 20 .45%2000 to 2004 477 1,566 30 .68%2005 to 2009 398 1,566 25 .59%2010 to 2012 197 1,566 12 .67%total 1,566 1,566 100.00%

Market drivers/Future outlookChart deficiency and chart tracking/locator applications are approaching this threshold (90 percent to 95 percent). Ultimately, we believe that chart deficiency and chart tracking/locator applications will become obsolete as the adoption of EHR applications become more prevalent. However, until dependence on paper documentation is completely eliminated, these applications will maintain a healthy market presence.

The HIM IT applications market will be significantly impacted through 2015 by several factors:• Preparations for conversation to ICD-10. This includes mapping

several applications that rely on encoded data to the new ICD-10 formats (also significantly affecting interfaces) by October 1, 2014.

• Negotiating the contractual commitments between hospitals and vendors for federal, state and other regulatory upgrades relative to ICD-10 encoding upgrades.

• Increased demands from the government (ARRA) and payers for reporting quality and outcomes data.

• Increased conversion of the medical record from paper to a digital format; the mixed format providing some special challenges for security and operational management, as well as patient care challenges.

• Acquisitions of ambulatory practices which have completely paper based records by IDNs.

• Increase focus on quality outcomes for participating in outcomes based reimbursement models (e.g. pay for performance, ACOs).

• Increased adoption of nomenclature coding standards such as SNOMED and LOINC and RxNorm.


▶ Document Management/Electronic Forms

Healthcare IT document management and electronic form applications are important components of the EHR environment for scanning paper forms that still may be in use as hospitals move to a paperless environment. It has been HIMSS Analytics’ expectation that the market increasingly adopted these applications to prevent having the medical staff and clinical employees look both online and into a paper chart for clinical documentation, an expectation which appears to be validated.

Document management allowing hospitals to track and store electronic documents and/or images of paper documents yielding greater efficiencies in the ability to reuse information and to control the flow of the documents, from creation to archiving. Document management is often used to store documents related to registration, personnel management, and medical records. These systems commonly provide storage, versioning, metadata, security, as well as indexing and retrieval capabilities. Electronic forms automatically generates forms and can be populated with patient data by importing data from another system and/or can export data that has been entered into another system. The electronic forms typically print identifying bar codes to facilitate immediate scanning and indexing to the right location in the right patient electronic record.

During the past three years, the document management and electronic forms application market has demonstrated a very positive growth trajectory (see Table DMEF1). Electronic forms management grew by slightly more than seven percentage points from 2011 to 2012, while the implementation of document management solutions increased by approximately 3.5 percentage points.

Three-quarters of planned purchases for electronic forms management applications are expected to be among hospitals making a purchase for the first time. In comparison, just more than half of purchases for document management solutions will be for the first time (see Table DMEF2).

An evaluation of the 2012 hospital market segments reveals the following highlights:• Document management: the critical access hospital segment

indicated the highest increase in adoption, at nearly seven percentage points (see Table DMEF3), followed closely by the rural hospital and single hospital.

• Electronic forms management: all hospital segments—except academic hospitals—grew at least five percentage points. The other non-general medical/surgical hospital segment even grew more than 10 percentage points this past year (see Table DMEF4).

Review of the document management and electronic forms management market in 2012 by bed size segments provides additional insight into this application environment (see Tables DMEF5–DMEF11). In our opinion, the adoption of these technologies, particularly electronic forms management, has been heavily influenced by the increases in EMR adoption seen across all bed size ranges by the desire to have all documentation and orders available on the network, even if it was originated on paper.

Document management adoption rates exceed 80 percent in all bed size ranges over 100 beds. Conversely, electronic forms management has lower adoption rates and demonstrated larger growth increases. • 0–100 beds: this segment has the lowest adoption rates of both

the document management and electronic forms management applications (see Table DMEF5). Electronic forms management adoption increased by more than 10 percentage points while document management adoption increased by just more than four percentage points.

• 101–200 beds: from 2011 to 2012, electronic forms management grew nearly six percentage points, while document management adoption grew by nearly four percentage points (see Table DMEF6).

• 201–300 beds: both the document management and electronic forms management applications increased by two percentage points (see Table DMEF7).

• 301–400 beds: electronic forms management increased by nearly four percentage points from 2011 to 2012, while document management’s growth was just more than one percentage point (see Table DMEF8).

tAbLe dMeF2 | 2012# of Hospitals with Installed





for the First Time



Hospitals PlanningDocument Management 34 57 .63% 25 42 .37% 59Electronic Forms Management 6 24 .00% 19 76 .00% 25Replacing = Statuses of live and operational, contracted/not yet installed and installation in processFirst time = Status of not automated

tAbLe dMeF3 | document Management2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 151 84 .83% 178 158 88 .76% 178 160 89 .89% 178Non-Academic 2,697 66 .77% 4,039 2,861 70 .83% 4,039 3,008 74 .47% 4,039Med/Surg 1,806 73 .65% 2,452 1,902 77 .57% 2,452 1,980 80 .75% 2,452Other 1,042 59 .04% 1,765 1,117 63 .29% 1,765 1,187 67 .25% 1,765Critical Access 540 47 .04% 1,148 598 52 .09% 1,148 678 59 .06% 1,148Non-Critical Access 2,308 75 .20% 3,069 2,421 78 .89% 3,069 2,490 81 .13% 3,069Rural 459 47 .03% 976 508 52 .05% 976 568 58 .20% 976Urban 2,389 73 .71% 3,241 2,511 77 .48% 3,241 2,600 80 .22% 3,241Multi-Hospital System 1,918 73 .97% 2,593 2,021 77 .94% 2,593 2,078 80 .14% 2,593Single Hospital System 930 57 .27% 1,624 998 61 .45% 1,624 1,090 67 .12% 1,624All 2,848 67.54% 4,217 3,019 71.59% 4,217 3,168 75.12% 4,217

tAbLe dMeF1 | document Management/electronic FormsN=4,217 2010 2011 2012Document Management 67 .54% 71 .59% 75 .12%Electronic Forms Management 51 .22% 56 .01% 63 .36%Percentages include installed, contracted or installation in process


▶ Document Management/Electronic Forms continued

• 401–500 beds: document management adoption neared 90 percent in 2012 as the market penetration grew by less than one percentage point in the past year (see Table DMEF9). Electronic forms management demonstrated an increase of two percentage points.

• 501–600 beds: both applications increased in adoption from 2011 to 2012. Electronic forms management adoption increased by slightly more than four percentage points while document management adoption grew by five percentage points (see Table DMEF10).

• Over 600 beds: document management adoption reached more than 90 percent market penetration in 2011 and grew by approximately one percentage point in 2012. Electronic forms management’s adoption grew by three percentage points from 2011 to 2012 (see Table DMEF11).

tAbLe dMeF50–100 beds 2010 2011 2012

% of 2,165 HospitalsDocument Management 1,242 57 .37% 1,335 61 .66% 1,429 66 .00%Electronic Forms Management 913 42 .17% 1,031 47 .62% 1,259 58 .15%

tAbLe dMeF6101–200 beds 2010 2011 2012

% of 802 HospitalsDocument Management 581 72 .44% 614 76 .56% 646 80 .55%Electronic Forms Management 457 56 .98% 485 60 .47% 531 66 .21%

tAbLe dMeF7201–300 beds 2010 2011 2012


tAbLe dMeF8301–400 beds 2010 2011 2012


tAbLe dMeF9401–500 beds 2010 2011 2012


tAbLe dMeF10501–600 beds 2010 2011 2012


tAbLe dMeF11over 600 beds 2010 2011 2012


Almost two-thirds of document management contracts were signed after 2005. One in five contracts (or 20 percent of the contracts) were signed between 2010 and 2012 (see Table DMEF12). More than 90 percent of the contracts for electronic forms have been signed since 2000.

tAbLe dMeF12# for Contract

RangeTotal


Respondingdocument ManagementPrior to 1990 2 1,277 0 .16%1990 to 1994 42 1,277 3 .32%1995 to 1999 66 1,277 5 .22%2000 to 2004 313 1,277 24 .74%2005 to 2009 576 1,277 45 .53%2010 to 2012 278 1,277 21 .98%total 1,277 1,277 100.00%electronic Forms ManagementPrior to 1990 1 907 0 .11%1990 to 1994 34 907 3 .75%1995 to 1999 39 907 4 .30%2000 to 2004 264 907 29 .14%2005 to 2009 350 907 38 .63%2010 to 2012 219 907 24 .17%total 907 907 100.00%

Market drivers/Future outlookThe document management IT application market has been and will most likely continue to be impacted by the following forces:• The need to remove paper from the care delivery and operations

processes to improve hospital efficiency.• The need to eliminate or significantly reduce paper document

storage and filing processes.• The need to improve access to information that is still captured

on paper documents and prevent errors that can occur from having critical documentation stored in two distinct locations.

• The need to make medical record information more secure.• Compliance with ARRA Meaningful Use criteria, which is

expected to drive more rapid adoption of both document management and electronic forms management to reduce dependency on paper and enhance the ability to capture more discrete data.

tAbLe dMeF4 | electronic Forms Management2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 118 66 .29% 178 128 71 .91% 178 126 70 .79% 178Non-Academic 2,042 50 .56% 4,039 2,234 55 .31% 4,039 2,546 63 .04% 4,039Med/Surg 1,383 56 .40% 2,452 1,484 60 .52% 2,452 1,608 65 .58% 2,452Other 777 44 .02% 1,765 878 49 .75% 1,765 1,064 60 .28% 1,765Critical Access 443 38 .59% 1,148 517 45 .03% 1,148 609 53 .05% 1,148Non-Critical Access 1,717 55 .95% 3,069 1,845 60 .12% 3,069 2,063 67 .22% 3,069Rural 357 36 .58% 976 412 42 .21% 976 489 50 .10% 976Urban 1,803 55 .63% 3,241 1,950 60 .17% 3,241 2,183 67 .36% 3,241Multi-Hospital System 1,422 54 .84% 2,593 1,536 59 .24% 2,593 1,741 67 .14% 2,593Single Hospital System 738 45 .44% 1,624 826 50 .86% 1,624 931 57 .33% 1,624All 2,160 51.22% 4,217 2,362 56.01% 4,217 2,672 63.36% 4,217


▶ Nursing Department Environment

tAbLe nA1 | nursing department ApplicationsN=4,217 2010 2011 2012Electronic Medication Administration

Record (eMAR) 72 .33% 79 .08% 85 .32%Infection Surveillance Systems 23 .22% 29 .52% 36 .92%Medication Reconciliation 36 .80% 50 .06% 62 .94%Nurse Call Systems 36 .87% 46 .72% 53 .95%Nurse Staffing/Scheduling 64 .76% 64 .76% 64 .06%Nursing Documentation 77 .64% 82 .50% 87 .81%Patient Acuity 29 .07% 30 .71% 33 .03%Percentages include installed, contracted or installation in process

tAbLe nA2 | 2012# of Hospitals with Installed





for the First Time



Hospitals PlanningElectronic Medication Administration Record (eMAR) 58 51 .79% 54 48 .21% 112Infection Surveillance Systems 36 57 .14% 27 42 .86% 63Medication Reconciliation 48 57 .83% 35 42 .17% 83Nurse Call Systems 7 77 .78% 2 22 .22% 9Nurse Staffing/Scheduling 13 61 .90% 8 38 .10% 21Nursing Documentation 63 63 .00% 37 37 .00% 100Patient Acuity 43 84 .31% 8 15 .69% 51Replacing = Statuses of Live and Operational, Contracted/Not Yet Installed and Installation In ProcessFirst time = Status of Not Automated

tAbLe nA3 | electronic Medication Administration record (eMAr)2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal


HIMSS Analytics monitors seven IT applications in the nursing department environment used to support the care nurses deliver to patients. These nursing applications include; electronic medication administration record (eMAR), infection surveillance system, medication reconciliation, nurse call system, nurse staffing/scheduling, nursing documentation and patient acuity.

Of the IT applications tracked in the nursing department, two applications (nursing documentation and eMAR) present as fairly universal tools. Three of the applications in this environment (nurse staffing/scheduling; medication reconciliation; nurse call system) present as a maturing product market, while infection surveillance systems and patient acuity reflect a relatively young product market. From 2011 to 2012, medication reconciliation demonstrated the highest growth of the various nursing applications (approximately 13 percent), a trajectory consistent with the applications growth between 2010 and 2011. Infection surveillance systems and nurse call systems also experienced strong growth trajectories this past year, each increasing by seven percentage points. All nursing applications, except nurse staffing/scheduling, reflected an increased market penetration this past year (see Table NA1).

The purchasers of applications in the nursing IT environment are most likely to reflect replacement buyers, although this first-time/replacement buyer mix varies by the application considered (see Table NA2). For example, at least three-quarters of patient acuity and nurse call systems purchases are expected to replace existing systems, whereas slightly more than half of eMAR purchases are projected to be a replacement purchase.

An evaluation of these seven applications by various hospital type market segments shows the following trends: • eMAR: the rural hospital segment demonstrated the largest

growth at more than 13 percentage points, followed by growth in the critical access hospital and single hospital system segments (see Table NA3). Other hospital segments indicated an increase in adoption ranging from two to nine percent.

• Infection surveillance systems: for the second year in a row, academic medical centers showed the highest increase in the use of infection surveillance systems, at more than 11 percent. The other segments demonstrated growth of approximately six to eight percent (see Table NA4).

• Medication reconciliation: the other non-general medical/surgical hospital segment reflected the highest year-over-year growth at more than 17 percentage points. The critical access hospital and rural hospital segments also saw a growth increase registering just under 17 percentage points. The lowest market penetration growth, seven percentage points, was among the market segment with the highest adoption rate, academic medical centers (see Table NA5).

• Nurse call system: three segments (critical access, multi-hospital system and other non-general medical/surgical hospitals) all experienced market penetration increases of approximately eight percentage points. Growth in all other segments ranged between five and eight percent (see Table NA6).

• Nurse staffing/scheduling: this is the only nursing IT application to indicate a decrease compared to 2011. Despite the overall decline, there are areas of growth, including the rural hospital and critical access hospital segments, each reporting a growth of more than four percentage points (see Table NA7).

• Nursing documentation: rural hospitals indicated the largest year-over-year increase of close to 12 percentage points. Growth among critical access hospitals was nearly 10 percentage points. All of the other segments reported an increase ranging from two to nine percentage points (see Table NA6).

• Patient acuity: growth in the critical access hospital and rural hospital segments was greatest, at approximately five percentage points. Growth in the other segments ranged from one to four percentage points (see Table NA7).


▶ Nursing Department Environment continued

tAbLe nA4 | infection surveillance system2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 67 37 .64% 178 90 50 .56% 178 110 61 .80% 178Non- Academic 912 22 .58% 4,039 1,155 28 .60% 4,039 1,447 35 .83% 4,039Med/Surg 698 28 .47% 2,452 869 35 .44% 2,452 1,064 43 .39% 2,452Other 281 15 .92% 1,765 376 21 .30% 1,765 493 27 .93% 1,765Critical Access 139 12 .11% 1,148 192 16 .72% 1,148 277 24 .13% 1,148Non- Critical Access 840 27 .37% 3,069 1,053 34 .31% 3,069 1,280 41 .71% 3,069Rural 114 11 .68% 976 153 15 .68% 976 215 22 .03% 976Urban 865 26 .69% 3,241 1,092 33 .69% 3,241 1,342 41 .41% 3,241Multi-Hospital System 722 27 .84% 2,593 884 34 .09% 2,593 1,073 41 .38% 2,593Single Hospital System 257 15 .83% 1,624 361 22 .23% 1,624 484 29 .80% 1,624All 979 23.22% 4,217 1,245 29.52% 4,217 1,557 36.92% 4,217

tAbLe nA5 | Medication reconciliation2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 101 56 .74% 178 127 71 .35% 178 140 78 .65% 178Non- Academic 1,451 35 .92% 4,039 1,984 49 .12% 4,039 2,514 62 .24% 4,039Med/Surg 1,049 42 .78% 2,452 1,366 55 .71% 2,452 1,598 65 .17% 2,452Other 503 28 .50% 1,765 745 42 .21% 1,765 1,056 59 .83% 1,765Critical Access 311 27 .09% 1,148 475 41 .38% 1,148 667 58 .10% 1,148Non- Critical Access 1,241 40 .44% 3,069 1,636 53 .31% 3,069 1,987 64 .74% 3,069Rural 254 26 .02% 976 387 39 .65% 976 551 56 .45% 976Urban 1,298 40 .05% 3,241 1,724 53 .19% 3,241 2,103 64 .89% 3,241Multi-Hospital System 1,020 39 .34% 2,593 1,289 49 .71% 2,593 1,596 61 .55% 2,593Single Hospital System 532 32 .76% 1,624 822 50 .62% 1,624 1,058 65 .15% 1,624All 1,552 36.80% 4,217 2,111 50.06% 4,217 2,654 62.94% 4,217

tAbLe nA6 | nurse call system2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal


tAbLe nA7 | nurse staffing/scheduling2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal




tAbLe nA8 | nursing documentation2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal


tAbLe nA9 | patient Acuity2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 84 47 .19% 178 87 48 .88% 178 92 51 .69% 178Non- Academic 1,142 28 .27% 4,039 1,208 29 .91% 4,039 1,301 32 .21% 4,039Med/Surg 819 33 .40% 2,452 852 34 .75% 2,452 881 35 .93% 2,452Other 407 23 .06% 1,765 443 25 .10% 1,765 512 29 .01% 1,765Critical Access 161 14 .02% 1,148 191 16 .64% 1,148 250 21 .78% 1,148Non- Critical Access 1,065 34 .70% 3,069 1,104 35 .97% 3,069 1,143 37 .24% 3,069Rural 134 13 .73% 976 153 15 .68% 976 197 20 .18% 976Urban 1,092 33 .69% 3,241 1,142 35 .24% 3,241 1,196 36 .90% 3,241Multi-Hospital System 854 32 .93% 2,593 887 34 .21% 2,593 951 36 .68% 2,593Single Hospital System 372 22 .91% 1,624 408 25 .12% 1,624 442 27 .22% 1,624All 1,226 29.07% 4,217 1,295 30.71% 4,217 1,393 33.03% 4,217

The profile the of nursing IT environment by bed segment from 2011 to 2012 yields the following highlights (see Tables NA10–NA16):• 0–100 beds: with more than a 17 percentage point difference

between 2012 and 2011, medication reconciliation had the highest year-over-year growth in this segment. Nurse staffing/scheduling is the only application to indicate a decrease in this segment, at approximately one percentage point (see Table NA10).

• 101–200 beds: medication reconciliation had the highest growth from 2011 to 2012, at close to 12 percentage points, followed by infection surveillance systems at eight percentage points (see Table NA11).

• 201–300 beds: infection surveillance systems reported the largest growth from 2011 to 2012 at more than eight percentage points, while eMAR indicated a decrease in adoption (see Table NA12).

• 301–400 beds: infection surveillance systems, medication reconciliation and nurse call systems had the three highest year-over-year growth rates ranging from nearly seven percentage points to nine percentage points. Growth among the other applications was approximately one to two percentage points, with the exception of nurse staffing/scheduling, which showed no growth (see Table NA13).

• 401–500 beds: at more than 97 percent, eMAR is on the verge of reaching full market saturation. Medication reconciliation and infection surveillance systems reported the largest growth at approximately six percentage points. Nurse staffing/scheduling is the only application to demonstrate a decrease in adoption at little more than one percentage point (see Table NA14).

• 501–600: infection surveillance systems is the only nursing IT application within this segment to indicate a double digit increase in adoption from 2011 to 2012. Both medication reconciliation and nurse call systems grew by more than nine percentage points. The adoption of eMAR remained unchanged from last year (see Table NA15).

• Over 600 beds: infection surveillance systems had the largest growth in this bed segment at close to 11 percentage points. This is followed by medication reconciliation at more than nine percentage points. All the other nursing IT applications market penetrations also grew this year (see Table NA16).

tAbLe nA100–100 beds 2010 2011 2012

% of 2,165 HospitalsElectronic Medication

Administration Record (eMAR) 1,338 61 .80% 1,544 71 .32% 1,730 79 .91%Infection Surveillance Systems 336 15 .52% 432 19 .95% 571 26 .37%Medication Reconciliation 620 28 .64% 910 42 .03% 1,281 59 .17%Nurse Call Systems 634 29 .28% 826 38 .15% 999 46 .14%Nurse Staffing/Scheduling 982 45 .36% 993 45 .87% 970 44 .80%Nursing Documentation 1,473 68 .04% 1,622 74 .92% 1,792 82 .77%Patient Acuity 424 19 .58% 474 21 .89% 548 25 .31%

tAbLe nA11101–200 beds 2010 2011 2012

% of 802 HospitalsElectronic Medication

Administration Record (eMAR) 624 77 .81% 651 81 .17% 700 87 .28%Infection Surveillance Systems 204 25 .44% 252 31 .42% 317 39 .53%Medication Reconciliation 316 39 .40% 402 50 .12% 497 61 .97%Nurse Call Systems 345 43 .02% 426 53 .12% 478 59 .60%Nurse Staffing/Scheduling 613 76 .43% 614 76 .56% 615 76 .68%Nursing Documentation 667 83 .17% 695 86 .66% 726 90 .52%Patient Acuity 279 34 .79% 286 35 .66% 290 36 .16%

tAbLe nA12201–300 beds 2010 2011 2012





tAbLe nA13301–400 beds 2010 2011 2012



tAbLe nA14401–500 beds 2010 2011 2012



tAbLe nA15501–600 beds 2010 2011 2012



tAbLe nA16over 600 beds 2010 2011 2012



An evaluation of the contract purchasing time frames for these nursing applications reveals that approximately half of infection surveillance systems, medication reconciliation systems and nurse call systems were signed between 2010 and 2012. Approximately one-quarter of the contracts for eMAR and nursing documentation were signed also within this time frame (see Tables NA17–NA19).

tAbLe nA17# for Contract

RangeTotal


Respondingelectronic Medication Administration record (eMAr)Prior to 1990 3 2,158 0 .14%1990 to 1994 99 2,158 4 .59%1995 to 1999 80 2,158 3 .71%2000 to 2004 568 2,158 26 .32%2005 to 2009 840 2,158 38 .92%2010 to 2012 568 2,158 26 .32%total 2,158 2,158 100.00%infection surveillance systemPrior to 1990 0 438 0 .00%1990 to 1994 4 438 0 .91%1995 to 1999 10 438 2 .28%2000 to 2004 58 438 13 .24%2005 to 2009 160 438 36 .53%2010 to 2012 206 438 47 .03%total 438 438 100.00%Medication reconciliationPrior to 1990 4 1,033 0 .39%1990 to 1994 8 1,033 0 .77%1995 to 1999 39 1,033 3 .78%2000 to 2004 121 1,033 11 .71%2005 to 2009 339 1,033 32 .82%2010 to 2012 522 1,033 50 .53%total 1,033 1,033 100.00%

tAbLe nA18# for Contract

RangeTotal


Respondingnurse call systemPrior to 1990 2 248 0 .81%1990 to 1994 2 248 0 .81%1995 to 1999 13 248 5 .24%2000 to 2004 24 248 9 .68%2005 to 2009 94 248 37 .90%2010 to 2012 113 248 45 .56%total 248 248 100.00%nurse staffing/schedulingPrior to 1990 89 1,446 6 .15%1990 to 1994 87 1,446 6 .02%1995 to 1999 196 1,446 13 .55%2000 to 2004 348 1,446 24 .07%2005 to 2009 496 1,446 34 .30%2010 to 2012 230 1,446 15 .91%total 1,446 1,446 100.00%nursing documentationPrior to 1990 8 2,273 0 .35%1990 to 1994 119 2,273 5 .24%1995 to 1999 149 2,273 6 .56%2000 to 2004 694 2,273 30 .53%2005 to 2009 765 2,273 33 .66%2010 to 2012 538 2,273 23 .67%total 2,273 2,273 100.00%

tAbLe nA19

2012# for Contract

RangeTotal


Respondingpatient AcuityPrior to 1990 5 757 0 .66%1990 to 1994 21 757 2 .77%1995 to 1999 41 757 5 .42%2000 to 2004 286 757 37 .78%2005 to 2009 259 757 34 .21%2010 to 2012 145 757 19 .15%total 757 757 100.00%



▶ Ancillary Department Environment

Market drivers/Future outlookThe nursing application IT application market has been and will continue to be impacted by:• Quality outcomes and performance improvement initiatives.• Pressures to improve patient safety and eliminate medical errors.• Intense competition for limited capital for purchasing nursing

IT solutions.• In this competition, nursing documentation purchases should fare

better than most other applications, since they include functions deemed essential for hospitals to meet the ARRA Meaningful Use criteria, measurements and reporting requirements.

• These systems, especially nursing documentation and eMAR, have proven to be nurse satisfiers, thus aid in recruiting and retention.

• The need to create an effective support foundation for computerized practitioner order entry (CPOE) as most hospitals implement nursing documentation before CPOE.

• The need to effectively and efficiently determine nurse staffing levels and assignments to meet minimum staffing requirements and help reduce the impact of the nursing shortage.

• The need to couple eMAR applications with pharmacy management and dispensing solutions to facilitate the closed-loop medication administration process for improving patient safety—a requirement that will support the medication safety requirements of Stage 2 Meaningful Use.

The applications in the ancillary department support key clinical departments and services in hospitals. HIMSS Analytics monitors the following eight applications in this environment: cardiology information system, emergency department systems (ED), intensive care (ICU), laboratory information system, obstetrical system (OB), pharmacy management system, radiology information system and respiratory care information system.

The market penetration of the applications in the ancillary department varies. Laboratory, pharmacy, and radiology for example, have almost reached complete saturation, while cardiology reflected the lowest level of adoption at 47 percent (not too surprising as not all hospitals have cardiology specific or heart centers). Respiratory had the highest year-over-year level of adoption from 2011 to 2012, with more than a six percentage point increase. At nearly five percentage points, there was also a substantial growth in the ED area. All other ancillary applications have reported an increase from the previous year (see Table AD1).

The majority of the planned purchasing for this market in this next year will be replacements purchases (see Table AD2). ED is the only ancillary application to indicate that fewer than 80 percent of planned purchase will be replacements. As in previous years, the requirement for a tight data coupling with pharmacy systems and CPOE systems is driving the replacement of legacy pharmacy systems with the organization’s EMR vendor’s pharmacy system.

Integration requirements between R-PACS and radiology systems is driving replacement purchases for radiology information systems, while replacement purchases for laboratory systems is being driven by the need for laboratories to function as both hospital laboratories and as reference laboratories for their local and/or regional markets. In addition, as Meaningful Use requirements evolve, hospital laboratories will be required to integrate laboratory results associated with their own external reference labs into the EMRs of their hospital patients and those of providers for whom they act as a reference laboratory. High volumes of molecular biologic testing (e.g., genetic and proteomic testing) may also induce laboratories to evaluate replacing their current systems if current vendors do not support these testing environments. Some laboratory replacements are beginning to occur where niche laboratory vendors are being replaced by an enterprise wide clinical vendor.

An evaluation of hospital type market segments for each ancillary department system from 2011 to 2012 shows the following:• Cardiology information systems: most of the segments reported

growth of two percentage points or less. The exception being the academic medical center segment which reported no growth from 2011 to 2012 (see Table AD3).

tAbLe Ad2 | 2012# of Hospitals with Installed





for the First Time



Hospitals PlanningCardiology Information Systems 41 82 .00% 9 18 .00% 50Emergency Department Systems 57 66 .28% 29 33 .72% 86Intensive Care 32 84 .21% 6 15 .79% 38Laboratory Information Systems 94 92 .16% 8 7 .84% 102Obstetrical Systems (Labor and Delivery) 13 86 .67% 2 13 .33% 15Pharmacy Management Systems 71 89 .87% 8 10 .13% 79Radiology Information Systems 83 88 .30% 11 11 .70% 94Respiratory Care Information Systems 41 80 .39% 10 19 .61% 51Replacing = Statuses of live and operational, contracted/not yet installed and installation in processFirst time = Status of not automated

tAbLe Ad1 | Ancillary departmentsN=4,217 2010 2011 2012Cardiology Information Systems 43 .04% 45 .34% 46 .72%Emergency Department Systems 72 .66% 77 .21% 81 .91%Intensive Care 50 .46% 53 .09% 56 .56%Laboratory Information Systems 97 .51% 98 .32% 98 .86%Obstetrical Systems (Labor and Delivery) 48 .26% 50 .58% 52 .79%Pharmacy Management Systems 94 .66% 95 .97% 97 .11%Radiology Information Systems 93 .98% 94 .88% 96 .47%Respiratory Care Information Systems 43 .49% 49 .77% 55 .96%Percentages include installed, contracted or installation in process


• Emergency department information systems: the rural and critical access hospital segments demonstrated growth of more than 10 percentage points, while academic medical centers reported a decline of less than one percentage point (see Table AD4).

• Intensive care systems: from 2011 to 2012, the general medical/surgical, rural and single hospital segments all reported growth of more than four percentage points. All other segments reported growth of two to four percentage points (see Table AD5).

• Laboratory information systems: since this application is near market saturation across all market segments, there was little growth. The critical access hospital segment had the largest growth at less than two percentage points. The academic medical center segment has reached full market segmentation and there was no growth from 2011 to 2012 (see Table AD6).

• Obstetrical systems: market penetration in 2012 is 60 percent or more for the academic medical center, general medical/surgical,

▶ Ancillary Department Environment continued

non-critical access hospital and urban hospitals. All segments reported growth from 2011 to 2012 ranging from one to nearly four percentage points (see Table AD7).

• Pharmacy management systems: the academic medical center segment, which is fully saturated, demonstrated no growth in the past year. Growth in all other hospital segments ranged from less than one percentage point to more than four percentage points. Rural hospitals demonstrated the largest year-over-year growth (see Table AD8).

• Radiology information systems: the critical access hospital and rural hospital segments reported more than four percentage point growth from 2011 to 2012 (see Table AD9).

• Respiratory care information systems: growth of five to eight percentage points was reported across all segments with critical access hospitals reporting the largest increase at eight percentage points (see Table AD10).

tAbLe Ad3 | cardiology information systems2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal


tAbLe Ad4 | emergency department systems2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 171 96 .07% 178 173 97 .19% 178 172 96 .63% 178Non- Academic 2,893 71 .63% 4,039 3,083 76 .33% 4,039 3,282 81 .26% 4,039Med/Surg 2,171 88 .54% 2,452 2,246 91 .60% 2,452 2,317 94 .49% 2,452Other 893 50 .59% 1,765 1,010 57 .22% 1,765 1,137 64 .42% 1,765Critical Access 630 54 .88% 1,148 742 64 .63% 1,148 863 75 .17% 1,148Non- Critical Access 2,434 79 .31% 3,069 2,514 81 .92% 3,069 2,591 84 .42% 3,069Rural 544 55 .74% 976 646 66 .19% 976 749 76 .74% 976Urban 2,520 77 .75% 3,241 2,610 80 .53% 3,241 2,705 83 .46% 3,241Multi-Hospital System 1,993 76 .86% 2,593 2,047 78 .94% 2,593 2,104 81 .14% 2,593Single Hospital System 1,071 65 .95% 1,624 1,209 74 .45% 1,624 1,350 83 .13% 1,624All 3,064 72.66% 4,217 3,256 77.21% 4,217 3,454 81.91% 4,217

tAbLe Ad5 | intensive care2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal



tAbLe Ad6 | Laboratory information system2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal


tAbLe Ad7 | obstetrical systems (Labor and delivery)2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal


tAbLe Ad8 | pharmacy Management system2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 178 100 .00% 178 178 100 .00% 178 178 100 .00% 178Non- Academic 3,814 94 .43% 4,039 3,869 95 .79% 4,039 3,917 96 .98% 4,039Med/Surg 2,438 99 .43% 2,452 2,442 99 .59% 2,452 2,444 99 .67% 2,452Other 1,554 88 .05% 1,765 1,605 90 .93% 1,765 1,651 93 .54% 1,765Critical Access 963 83 .89% 1,148 1,001 87 .20% 1,148 1,045 91 .03% 1,148Non- Critical Access 3,029 98 .70% 3,069 3,046 99 .25% 3,069 3,050 99 .38% 3,069Rural 818 83 .81% 976 850 87 .09% 976 890 91 .19% 976Urban 3,174 97 .93% 3,241 3,197 98 .64% 3,241 3,205 98 .89% 3,241Multi-Hospital System 2,530 97 .57% 2,593 2,549 98 .30% 2,593 2,553 98 .46% 2,593Single Hospital System 1,462 90 .02% 1,624 1,498 92 .24% 1,624 1,542 94 .95% 1,624All 3,992 94.66% 4,217 4,047 95.97% 4,217 4,095 97.11% 4,217

tAbLe Ad9 | radiology information system2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 178 100 .00% 178 178 100 .00% 178 177 99 .44% 178Non- Academic 3,785 93 .71% 4,039 3,823 94 .65% 4,039 3,891 96 .34% 4,039Med/Surg 2,416 98 .53% 2,452 2,424 98 .86% 2,452 2,435 99 .31% 2,452Other 1,547 87 .65% 1,765 1,577 89 .35% 1,765 1,633 92 .52% 1,765Critical Access 969 84 .41% 1,148 1,002 87 .28% 1,148 1,049 91 .38% 1,148Non- Critical Access 2,994 97 .56% 3,069 2,999 97 .72% 3,069 3,019 98 .37% 3,069Rural 825 84 .53% 976 855 87 .60% 976 894 91 .60% 976Urban 3,138 96 .82% 3,241 3,146 97 .07% 3,241 3,174 97 .93% 3,241Multi-Hospital System 2,503 96 .53% 2,593 2,504 96 .57% 2,593 2,526 97 .42% 2,593Single Hospital System 1,460 89 .90% 1,624 1,497 92 .18% 1,624 1,542 94 .95% 1,624All 3,963 93.98% 4,217 4,001 94.88% 4,217 4,068 96.47% 4,217



tAbLe Ad10 | respiratory care information system2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal


The analysis of the ancillary market by bed size from 2010–2012 is exhibited in Tables AD11–AD17. In evaluating the bed segments, the data indicates:• 0–100 beds: ED demonstrated the highest growth within this

segment at more than seven percentage points. There was also growth of nearly seven percentage points in the respiratory care market (see Table AD11).

• 101–200 beds: the largest year-over-year growth was respiratory care at six percentage points. Almost all other ancillary applications indicated growth ranging from less than one to four percentage points (see Table AD12).

• 201–300 beds: respiratory reported the highest growth at more than five percentage points. Laboratory and pharmacy, which are fully saturated, indicated no growth. Radiology is the only application within this segment to report a decline (see Table AD13).

• 301–400 beds: four of the eight applications reported growth from 2011 to 2012; ranging from one to five percentage points. Laboratory, OB, pharmacy and radiology, which are all at or near market saturation, reported no growth from last year (see Table AD14).

• 401–500 beds: respiratory care indicated a growth of nearly six percentage points. ICU, OB and cardiology also reported positive growth. All other applications are at or approaching market segmen-tation and indicated no growth in the past year (see Table AD15).

• 501–600 beds: respiratory systems demonstrated a six percentage point increase from 2011 to 2012. Having already achieved market saturation, laboratory, pharmacy, radiology are the only ancillary applications to remain the same compared to last year (see Table AD16).

• Over 600 beds: respiratory care and ICU reported an increase of more than three percentage points from 2011 to 2012. Cardiology is the only ancillary application to indicate a decline in adoption level from 2011 (see Table AD17).

tAbLe Ad110–100 beds 2010 2011 2012

% of 2,165 HospitalsCardiology Information Systems 308 14 .23% 348 16 .07% 384 17 .74%Emergency Department Systems 1,201 55 .47% 1,355 62 .59% 1,518 70 .12%Intensive Care 712 32 .89% 746 34 .46% 816 37 .69%Laboratory Information Systems 2,061 95 .20% 2,094 96 .72% 2,117 97 .78%Obstetrical Systems

(Labor and Delivery) 572 26 .42% 627 28 .96% 677 31 .27%Pharmacy Management Systems 1,941 89 .65% 1,996 92 .19% 2,043 94 .36%Radiology Information Systems 1,922 88 .78% 1,960 90 .53% 2,024 93 .49%Respiratory Care

Information Systems 688 31 .78% 849 39 .21% 999 46 .14%

tAbLe Ad12101–200 beds 2010 2011 2012

% of 802 HospitalsCardiology Information Systems 491 61 .22% 520 64 .84% 527 65 .71%Emergency Department Systems 690 86 .03% 709 88 .40% 730 91 .02%Intensive Care 512 63 .84% 538 67 .08% 568 70 .82%Laboratory Information Systems 801 99 .88% 802 100 .00% 802 100 .00%Obstetrical Systems

(Labor and Delivery) 523 65 .21% 541 67 .46% 564 70 .32%Pharmacy Management Systems 801 99 .88% 801 99 .88% 802 100 .00%Radiology Information Systems 792 98 .75% 793 98 .88% 797 99 .38%Respiratory Care


tAbLe Ad13201–300 beds 2010 2011 2012




tAbLe Ad14301–400 beds 2010 2011 2012




tAbLe Ad15401–500 beds 2010 2011 2012






tAbLe Ad16501–600 beds 2010 2011 2012




tAbLe Ad17over 600 beds 2010 2011 2012




An evaluation of contract purchasing time frames for ancillary department applications reveals that more than 20 percent of contracts purchased for respiratory, OB and ED were made between 2010 to 2012 (see Tables AD18–AD20). For the other ancillary applications, more than 15 to 20 percent of the contracts were signed in the same time frame. This could indicate that replacement purchases are being made, particularly in the laboratory, radiology and pharmacy markets in favor of a one-vendor integrated systems approach. Ancillary department systems contracted before 1995 will have the highest probability for replacement purchases through 2015.

tAbLe Ad18# for Contract

RangeTotal


Respondingcardiology information systemsPrior to 1990 5 853 0 .60%1990 to 1994 16 853 1 .92%1995 to 1999 56 853 6 .73%2000 to 2004 274 853 32 .93%2005 to 2009 340 853 40 .87%2010 to 2012 162 853 19 .47%total 853 853 100.00%emergency department systemsPrior to 1990 9 2,045 0 .44%1990 to 1994 43 2,045 2 .11%1995 to 1999 129 2,045 6 .32%2000 to 2004 634 2,045 31 .08%2005 to 2009 672 2,045 32 .94%2010 to 2012 558 2,045 27 .35%total 2,045 2,045 100.00%intensive carePrior to 1990 6 1,498 0 .40%1990 to 1994 117 1,498 7 .84%1995 to 1999 132 1,498 8 .84%2000 to 2004 483 1,498 32 .35%2005 to 2009 478 1,498 32 .02%2010 to 2012 282 1,498 18 .89%total 1,498 1,498 100.00%


RangeTotal


RespondingLaboratory information systemPrior to 1990 121 2,521 4 .80%1990 to 1994 225 2,521 8 .93%1995 to 1999 512 2,521 20 .31%2000 to 2004 677 2,521 26 .85%2005 to 2009 617 2,521 24 .47%2010 to 2012 369 2,521 14 .64%total 2,521 2,521 100.00%obstetrical system (Labor and delivery)Prior to 1990 0 978 0 .00%1990 to 1994 29 978 2 .97%1995 to 1999 95 978 9 .71%2000 to 2004 326 978 33 .33%2005 to 2009 301 978 30 .78%2010 to 2012 227 978 23 .21%total 978 978 100.00%pharmacy Management systemPrior to 1990 28 2,737 1 .02%1990 to 1994 195 2,737 7 .12%1995 to 1999 343 2,737 12 .53%2000 to 2004 888 2,737 32 .44%2005 to 2009 771 2,737 28 .17%2010 to 2012 512 2,737 18 .71%total 2,737 2,737 100.00%


RangeTotal


Respondingradiology information systemPrior to 1990 42 2,621 1 .60%1990 to 1994 136 2,621 5 .20%1995 to 1999 297 2,621 11 .35%2000 to 2004 817 2,621 31 .22%2005 to 2009 860 2,621 32 .86%2010 to 2012 469 2,621 17 .92%total 2,621 2,621 100.00%respiratory care information systemPrior to 1990 9 1,381 0 .65%1990 to 1994 116 1,381 8 .42%1995 to 1999 108 1,381 7 .84%2000 to 2004 394 1,381 28 .61%2005 to 2009 418 1,381 30 .36%2010 to 2012 336 1,381 24 .40%total 1,381 1,381 100.00%

Market drivers/Future outlookThe ancillary department IT application market has been and will most likely continue to be impacted by the following market forces:• The need to reduce or eliminate medical and medication errors.• The continued hospital focus on patient safety.• The need to capture more clinical data electronically to support

Meaningful Use, HIE and personal health record (PHR) initiatives.

• The continued drive towards integrated clinical systems and away from “best of breed” will drive some replacement purchases of essentially stand-alone ancillary systems.

• The need to have CPOE systems tightly coupled with pharmacy systems.

• The need to have pharmacy systems tightly coupled with eMAR systems.

• The push by the government for pay for performance and the continued need of hospitals to have discrete data with which to report against ARRA Meaningful Use criteria by 2011 and beyond.



• The need to have complete clinical transaction data for C&BI analytics for quality and efficiency improvements.

• The need to create improved data sharing/integration between clinical and financial systems to support improved claims processing accuracy and for performance analysis and reporting under bundled payment contracts.

• Intense competition for limited capital funds in a period when government-mandated initiatives will determine the applications that receive the highest priority.

• The push by the government to improve the capture, management, and sharing of electronic health information in summary data formats between all healthcare stakeholders.

• The need to provide a higher level of integration of order communications and results reporting with external providers and reference laboratories.

• Complex molecular and genomics testing in laboratories to deliver “personalized medicine.”


▶ Laboratory Environment

The applications that are part of the laboratory environment include anatomical pathology, blood bank, laboratory-molecular diagnostics, laboratory-outreach services and microbiology. These solutions focus on providing automation and efficiency in laboratory operations. Although general laboratory information system solutions could also be considered to be a part of this environment, this solution has historically appeared in the ancillary section of the HIMSS Analytics Annual Report. At least for 2012, general laboratory information systems will continue to be included in the ancillary environment section of this report.

Microbiology had the highest market penetration in 2012 at 80 percent; followed by blood bank (68 percent) and anatomical pathology (62 percent). Laboratory-molecular diagnostics has the lowest rate of adoption at just under 15 percent. Between 2011 and 2012, laboratory-outreach services demonstrated the largest year-over-year growth at approximately four percentage points (see Table LAB1).

The majority of future purchases in the laboratory environment are expected to be replacement purchases. While the laboratory-molecular diagnostics application is evenly split between first time

and replacement purchase plans, this data needs to be evaluated with caution, as only two hospitals reported plans to purchase this technology (see Table LAB2).

An evaluation of this environment from 2011 to 2012 by hospital type shows the highest growth by application occurred as follows:• Anatomical pathology: the greatest growth was demonstrated

in the critical access hospital segment at more than five percentage points. The rural, non-medical/surgical and multi-hospital system segments each had growth more than three percentage points. The academic medical center segment is saturated with 99 percent market adoption (see Table LAB3).

• Blood Bank: at just over one percentage point, the multi-hospital system segment had the greatest growth. The rural and single hospital segments saw a decrease in adoption of just more than one percentage point. While displaying a slight decrease, the academic medical center segment is still saturated, with 98 percent adoption (see Table LAB4).

• Laboratory-Molecular Diagnostics: adoption of this technology grew more than two percentage points in the academic medical center segment from 2011 to 2012. Growth in the remaining market segments was less than two percentage points (see Table LAB5).

• Laboratory-Outreach Services: the academic medical center segment reported the highest increase in adoption over the past year at nearly seven percentage points. The remaining segments grew between three to five percentage points (see Table LAB6).

• Microbiology: both the rural hospital and the critical access segments showed growth at more than three percentage points. Academic medical centers have almost reached full market penetration (99 percent adoption), while general medical/surgical hospitals are approaching saturation at 94 percent adoption (see Table LAB7).

tAbLe L Ab1 | LaboratoryN=4,217 2010 2011 2012Anatomical Pathology 58 .88% 59 .24% 62 .01%Blood Bank 67 .61% 67 .44% 67 .77%Laboratory–Molecular Diagnostics 11 .43% 13 .45% 14 .75%Laboratory–Outreach Services 21 .15% 26 .08% 30 .31%Microbiology 77 .31% 79 .23% 80 .72%Percentages include installed, contracted or installation in process NOTE: installed does not necessarily indicate full usage across all patient units or by all

categories of clinician

tAbLe L Ab2 | 2012# of Hospitals with Installed





for the First Time



Hospitals PlanningAnatomical Pathology 39 95 .12% 2 4 .88% 41Blood Bank 44 77 .19% 13 22 .81% 57Laboratory–Molecular Diagnostics 1 50 .00% 1 50 .00% 2Laboratory–Outreach Services 28 90 .32% 3 9 .68% 31Microbiology 48 94 .12% 3 5 .88% 51Replacing = Statuses of live and operational, contracted/not yet installed and installation in processFirst time = Status of not automated


▶ Laboratory Environment continued

tAbLe L Ab3 | Anatomical pathology2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 177 99 .44% 178 175 98 .31% 178 176 98 .88% 178Not Academic 2,306 57 .09% 4,039 2,323 57 .51% 4,039 2,439 60 .39% 4,039Med/Surg 1,884 76 .84% 2,452 1,882 76 .75% 2,452 1,936 78 .96% 2,452Other 599 33 .94% 1,765 616 34 .90% 1,765 679 38 .47% 1,765Critical Access 271 23 .61% 1,148 294 25 .61% 1,148 353 30 .75% 1,148Not Critical Access 2,212 72 .08% 3,069 2,204 71 .81% 3,069 2,262 73 .70% 3,069Rural 229 23 .46% 976 244 25 .00% 976 281 28 .79% 976Urban 2,254 69 .55% 3,241 2,254 69 .55% 3,241 2,334 72 .01% 3,241Multi-Hospital System 1,728 66 .64% 2,593 1,713 66 .06% 2,593 1,804 69 .57% 2,593Single Hospital System 755 46 .49% 1,624 785 48 .34% 1,624 811 49 .94% 1,624All 2,483 58.88% 4,217 2,498 59.24% 4,217 2,615 62.01% 4,217

tAbLe L Ab4 | blood bank2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 176 98 .88% 178 175 98 .31% 178 174 97 .75% 178Not Academic 2,675 66 .23% 4,039 2,669 66 .08% 4,039 2,684 66 .45% 4,039Med/Surg 2,106 85 .89% 2,452 2,084 84 .99% 2,452 2,106 85 .89% 2,452Other 745 42 .21% 1,765 760 43 .06% 1,765 752 42 .61% 1,765Critical Access 401 34 .93% 1,148 423 36 .85% 1,148 417 36 .32% 1,148Not Critical Access 2,450 79 .83% 3,069 2,421 78 .89% 3,069 2,441 79 .54% 3,069Rural 341 34 .94% 976 357 36 .58% 976 344 35 .25% 976Urban 2,510 77 .45% 3,241 2,487 76 .74% 3,241 2,514 77 .57% 3,241Multi-Hospital System 1,978 76 .28% 2,593 1,956 75 .43% 2,593 1,989 76 .71% 2,593Single Hospital System 873 53 .76% 1,624 888 54 .68% 1,624 869 53 .51% 1,624All 2,851 67.61% 4,217 2,844 67.44% 4,217 2,858 67.77% 4,217

tAbLe L Ab5 | Laboratory–Molecular diagnostics2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 71 39 .89% 178 80 44 .94% 178 84 47 .19% 178Not Academic 411 10 .18% 4,039 487 12 .06% 4,039 538 13 .32% 4,039Med/Surg 347 14 .15% 2,452 399 16 .27% 2,452 439 17 .90% 2,452Other 135 7 .65% 1,765 168 9 .52% 1,765 183 10 .37% 1,765Critical Access 25 2 .18% 1,148 43 3 .75% 1,148 48 4 .18% 1,148Not Critical Access 457 14 .89% 3,069 524 17 .07% 3,069 574 18 .70% 3,069Rural 21 2 .15% 976 34 3 .48% 976 36 3 .69% 976Urban 461 14 .22% 3,241 533 16 .45% 3,241 586 18 .08% 3,241Multi-Hospital System 374 14 .42% 2,593 438 16 .89% 2,593 483 18 .63% 2,593Single Hospital System 108 6 .65% 1,624 129 7 .94% 1,624 139 8 .56% 1,624All 482 11.43% 4,217 567 13.45% 4,217 622 14.75% 4,217

tAbLe L Ab6 | Laboratory–outreach services2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 76 42 .70% 178 88 49 .44% 178 100 56 .18% 178Not Academic 816 20 .20% 4,039 1,012 25 .06% 4,039 1,178 29 .17% 4,039Med/Surg 657 26 .79% 2,452 793 32 .34% 2,452 914 37 .28% 2,452Other 235 13 .31% 1,765 307 17 .39% 1,765 364 20 .62% 1,765Critical Access 87 7 .58% 1,148 130 11 .32% 1,148 169 14 .72% 1,148Not Critical Access 805 26 .23% 3,069 970 31 .61% 3,069 1,109 36 .14% 3,069Rural 61 6 .25% 976 94 9 .63% 976 126 12 .91% 976Urban 831 25 .64% 3,241 1,006 31 .04% 3,241 1,152 35 .54% 3,241Multi-Hospital System 629 24 .26% 2,593 784 30 .24% 2,593 917 35 .36% 2,593Single Hospital System 263 16 .19% 1,624 316 19 .46% 1,624 361 22 .23% 1,624All 892 21.15% 4,217 1,100 26.08% 4,217 1,278 30.31% 4,217



tAbLe L Ab7 | Microbiology2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 174 97 .75% 178 175 98 .31% 178 176 98 .88% 178Not Academic 3,086 76 .41% 4,039 3,166 78 .39% 4,039 3,228 79 .92% 4,039Med/Surg 2,258 92 .09% 2,452 2,282 93 .07% 2,452 2,300 93 .80% 2,452Other 1,002 56 .77% 1,765 1,059 60 .00% 1,765 1,104 62 .55% 1,765Critical Access 563 49 .04% 1,148 609 53 .05% 1,148 649 56 .53% 1,148Not Critical Access 2,697 87 .88% 3,069 2,732 89 .02% 3,069 2,755 89 .77% 3,069Rural 487 49 .90% 976 530 54 .30% 976 568 58 .20% 976Urban 2,773 85 .56% 3,241 2,811 86 .73% 3,241 2,836 87 .50% 3,241Multi-Hospital System 2,152 82 .99% 2,593 2,183 84 .19% 2,593 2,210 85 .23% 2,593Single Hospital System 1,108 68 .23% 1,624 1,158 71 .31% 1,624 1,194 73 .52% 1,624All 3,260 77.31% 4,217 3,341 79.23% 4,217 3,404 80.72% 4,217

tAbLe L Ab9101–200 beds 2010 2011 2012

% of 802 HospitalsAnatomical Pathology 612 76 .31% 607 75 .69% 625 77 .93%Blood Bank 699 87 .16% 682 85 .04% 690 86 .03%Laboratory–Molecular

Diagnostics 111 13 .84% 118 14 .71% 134 16 .71%Laboratory–Outreach Services 193 24 .06% 223 27 .81% 263 32 .79%Microbiology 756 94 .26% 757 94 .39% 759 94 .64%

tAbLe L Ab10201–300 beds 2010 2011 2012



tAbLe L Ab11301–400 beds 2010 2011 2012



tAbLe L Ab12401–500 beds 2010 2011 2012



tAbLe L Ab13501–600 beds 2010 2011 2012



Microbiology is reaching market saturation (more than 94 percent) in each bed segment except the 0–100 bed segment. Additional analysis of the laboratory market by bed size in 2012 indicates the following (see Tables LAB8–LAB14):• 0–100 beds: anatomical pathology showed the highest growth at

four percentage points, followed by laboratory-outreach services at slightly more than three percentage points (see Table LAB8).

• 101–200 beds: laboratory-outreach services demonstrated the highest growth at nearly five percentage points. Anatomical pathology, laboratory-molecular diagnostics and blood bank each grew by one to two percentage points (see Table LAB9).

• 201–300 beds: the greatest growth in this segment was for laboratory-outreach services at close to five percentage points, followed by laboratory-molecular diagnostics at nearly two percentage points (see Table LAB10).

• 301–400 beds: laboratory-outreach services and anatomical pathology each grew by more than two percentage points between 2011 and 2012 (see Table LAB11).

• 401–500 beds: the greatest growth in this segment was for laboratory-outreach services, which demonstrated an eight percentage point growth. Microbiology’s market penetration was unchanged from last year and the remaining applications grew by less than one percentage point (see Table LAB12).

• 501–600 beds: anatomical pathology, blood bank and microbiology reached near complete market saturation (more than 95 percent) in 2011 and saw little to no change in 2012. Laboratory-outreach services showed a six percentage point growth since last year (see Table LAB13).

• Over 600 beds: the greatest growth was for laboratory-outreach services at six percentage points. Blood bank and laboratory-molecular diagnostics each grew by slightly more than one percentage point from 2011 to 2012 (see Table LAB14).

tAbLe L Ab80–100 beds 2010 2011 2012

% of 2,165 HospitalsAnatomical Pathology 716 33 .07% 734 33 .90% 819 37 .83%Blood Bank 946 43 .70% 963 44 .48% 963 44 .48%Laboratory–Molecular

Diagnostics 85 3 .93% 119 5 .50% 141 6 .51%Laboratory–Outreach Services 238 10 .99% 331 15 .29% 406 18 .75%Microbiology 1,280 59 .12% 1,356 62 .63% 1,416 65 .40%



tAbLe L Ab14over 600 beds 2010 2011 2012



More than half of all the contracting for anatomical pathology, blood bank and microbiology took place before 2005, while more than half of the contracting for laboratory-molecular diagnostics and laboratory-outreach services took place during 2005 to 2012 (see Tables LAB15–LAB16).

Market drivers/Future outlookThe laboratory environment market has been or will likely be impacted through 2016 by:• An increased focus on complying with ARRA Meaningful Use

process and reporting criteria in order to qualify for EMR adoption incentives and avoid Medicare reimbursement penalties.

• Increased pressures on hospitals by federal and state authorities to participate in HIE and public health reporting activities for disease indexes and syndromic reporting.

• An increased use of laboratory components from the enterprise clinical systems vendor and a general movement away from niche vendors.

• Intense competition for capital funding, and staff resources between financial (e.g. ICD-10 coding mandate and payment reform) and clinical (e.g. ARRA Meaningful Use measurements) IT projects.

• Accelerated mergers and acquisitions in the provider market which will drive some laboratory and pathology service consolidation.

• With increased mergers and the continued growth of IDNs there will be an increase in demand from the medical staff for leading edge molecular diagnostics capabilities to develop a personalized medicine program.

• Tight capital markets may continue to impact the acquisition and installation of EMR products through 2015, especially for small community and critical access hospitals, in spite of the availability of ARRA incentives.

• The increased need to acquire, manage, and analyze clinical data for business intelligence, outcomes improvement, pay for performance incentive programs and government compliance reporting.

tAbLe L Ab15# for Contract

RangeTotal


RespondingAnatomical pathologyPrior to 1990 38 1,360 2 .79%1990 to 1994 117 1,360 8 .60%1995 to 1999 234 1,360 17 .21%2000 to 2004 445 1,360 32 .72%2005 to 2009 333 1,360 24 .49%2010 to 2012 193 1,360 14 .19%total 1,360 1,360 100.00%blood bankPrior to 1990 63 1,436 4 .39%1990 to 1994 137 1,436 9 .54%1995 to 1999 211 1,436 14 .69%2000 to 2004 383 1,436 26 .67%2005 to 2009 437 1,436 30 .43%2010 to 2012 205 1,436 14 .28%total 1,436 1,436 100.00%Laboratory–Molecular diagnosticsPrior to 1990 5 110 4 .55%1990 to 1994 4 110 3 .64%1995 to 1999 22 110 20 .00%2000 to 2004 21 110 19 .09%2005 to 2009 48 110 43 .64%2010 to 2012 10 110 9 .09%total 110 110 100.00%

tAbLe L Ab16# for Contract

RangeTotal


RespondingLaboratory–outreach servicesPrior to 1990 6 433 1 .39%1990 to 1994 23 433 5 .31%1995 to 1999 57 433 13 .16%2000 to 2004 88 433 20 .32%2005 to 2009 168 433 38 .80%2010 to 2012 91 433 21 .02%total 433 433 100.00%MicrobiologyPrior to 1990 80 1,913 4 .18%1990 to 1994 167 1,913 8 .73%1995 to 1999 375 1,913 19 .60%2000 to 2004 542 1,913 28 .33%2005 to 2009 469 1,913 24 .52%2010 to 2012 280 1,913 14 .64%total 1,913 1,913 100.00%


▶ Surgical Information System

The surgical information system environment focuses on IT applications used in the operating room (OR) and surgery setting. HIMSS Analytics monitors the following applications in this environment: OR scheduling, pre-operative and post-operative systems. As of this year, HIMSS Analytics no longer tracks peri-operative systems (see Table OR1). Moreover, all three applications increased in market adoption this year with increases ranging from three to four percentage points.

Approximately three-quarters of planned purchases across all three surgical information system applications were by hospitals intending to replace their current solution (see Table OR2).

An evaluation of the surgical information system application market by the various hospital market segments in 2012 reveals the following: • Post-operative: the rural hospital segment had the highest year-

over-year growth for this segment, at nearly eight percentage points. This is followed by the critical access and single hospital system segments, which each had growths of six to seven percentage points (see Table OR3). All other segments indicated an increase of less than five percentage points.

• Pre-operative: all segments grew between 2011 and 2012, with the largest gains occurring in the critical access and rural hospital segments (see Table OR4). Academic medical centers, which have

achieved near market saturation, reflected the smallest increase in market penetration at less than one percentage point.

• OR scheduling: the rural hospital segment reported the largest year-over-year growth at approximately seven percentage points. Strong growth (six percentage points) was also observed in the critical access hospital segment. All of the other hospital segments demonstrated an increase ranging from less than one percentage point to approximately five percentage points (see Table OR5).

An evaluation of the surgical information system market by bed size in 2012 demonstrated the following (see Tables OR6–OR12): • 0–100 beds: all three OR applications showed a growth of

approximately five percentage points (see Table OR6).• 101–200 beds: OR scheduling is the only application to report a

growth of less than two percentage points. Post-operative and pre-operative adoption grew by two to three percentage points (see Table OR7).

tAbLe or1 | operating roomN=4,217 2010 2011 2012Post-Operative 60 .52% 64 .71% 68 .72%Pre-Operative 64 .64% 67 .68% 71 .16%OR Scheduling 67 .63% 70 .41% 73 .35%Percentages include installed, contracted or installation in process

tAbLe or2 | 2012# of Hospitals with Installed





for the First Time



Hospitals PlanningPost-Operative 53 75 .71% 17 24 .29% 70Pre-Operative 55 73 .33% 20 26 .67% 75OR Scheduling 59 85 .51% 10 14 .49% 69Replacing = Statuses of live and operational, contracted/not yet installed and installation in processFirst time = Status of not automated

tAbLe or3 | post-operative2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 161 90 .45% 178 166 93 .26% 178 169 94 .94% 178Non- Academic 2,391 59 .20% 4,039 2,563 63 .46% 4,039 2,729 67 .57% 4,039Med/Surg 1,876 76 .51% 2,452 1,966 80 .18% 2,452 2,053 83 .73% 2,452Other 676 38 .30% 1,765 763 43 .23% 1,765 845 47 .88% 1,765Critical Access 401 34 .93% 1,148 476 41 .46% 1,148 556 48 .43% 1,148Non- Critical Access 2,151 70 .09% 3,069 2,253 73 .41% 3,069 2,342 76 .31% 3,069Rural 320 32 .79% 976 388 39 .75% 976 463 47 .44% 976Urban 2,232 68 .87% 3,241 2,341 72 .23% 3,241 2,435 75 .13% 3,241Multi-Hospital System 1,693 65 .29% 2,593 1,774 68 .41% 2,593 1,842 71 .04% 2,593Single Hospital System 859 52 .89% 1,624 955 58 .81% 1,624 1,056 65 .02% 1,624All 2,552 60.52% 4,217 2,729 64.71% 4,217 2,898 68.72% 4,217

tAbLe or4 | pre-operative2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 170 95 .51% 178 172 96 .63% 178 173 97 .19% 178Non- Academic 2,556 63 .28% 4,039 2,682 66 .40% 4,039 2,828 70 .02% 4,039Med/Surg 1,994 81 .32% 2,452 2,057 83 .89% 2,452 2,125 86 .66% 2,452Other 732 41 .47% 1,765 797 45 .16% 1,765 876 49 .63% 1,765Critical Access 440 38 .33% 1,148 501 43 .64% 1,148 579 50 .44% 1,148Non- Critical Access 2,286 74 .49% 3,069 2,353 76 .67% 3,069 2,422 78 .92% 3,069Rural 347 35 .55% 976 408 41 .80% 976 478 48 .98% 976Urban 2,379 73 .40% 3,241 2,446 75 .47% 3,241 2,523 77 .85% 3,241Multi-Hospital System 1,796 69 .26% 2,593 1,844 71 .11% 2,593 1,901 73 .31% 2,593Single Hospital System 930 57 .27% 1,624 1,010 62 .19% 1,624 1,100 67 .73% 1,624All 2,726 64.64% 4,217 2,854 67.68% 4,217 3,001 71.16% 4,217


▶ Surgical Information System continued

• 201–300 beds: all three applications reported an increase in adoption from 2011 to 2012, ranging from one to two percentage points (see Table OR8), with post-operative reflecting the largest increase.

• 301–400 beds: post-operative and pre-operative grew between 2011 and 2012, while OR scheduling reflected a small decline during time (see Table OR9).

• 401–500 beds: post-operative applications indicated the highest year-over-year growth from 2011 to 2012, at more than two percentage points (see Table OR10). The other two OR applications also grew during this period.

• 501–600 beds: post-operative and pre-operative systems grew less than one percent from 2011 to 2012, while there was no change in the highly saturated OR scheduling market (see Table OR11).

• Over 600 beds: all three OR applications are close to approaching, or have already achieved, market saturation (95-100 percent) in this bed segment. No growth was reported for OR scheduling, while post-operative adoption increased by more than one percentage point (see Table OR12).

tAbLe or60–100 beds 2010 2011 2012

% of 2,165 HospitalsPost-Operative 863 39 .86% 987 45 .59% 1,109 51 .22%Pre-Operative 941 43 .46% 1,037 47 .90% 1,149 53 .07%OR Scheduling 993 45 .87% 1,078 49 .79% 1,185 54 .73%

tAbLe or7101–200 beds 2010 2011 2012

% of 802 HospitalsPost-Operative 606 75 .56% 633 78 .93% 656 81 .80%Pre-Operative 640 79 .80% 660 82 .29% 678 84 .54%OR Scheduling 671 83 .67% 696 86 .78% 705 87 .91%

tAbLe or8201–300 beds 2010 2011 2012


tAbLe or9301–400 beds 2010 2011 2012


tAbLe or10401–500 beds 2010 2011 2012


tAbLe or11501–600 beds 2010 2011 2012


tAbLe or12over 600 beds 2010 2011 2012


At least 20 percent of the contracts in the surgical information system market were signed in the past two years (see Table OR13), while approximately two-thirds of all contracts were signed between 2000 and 2009.

tAbLe or13# for Contract

RangeTotal


Respondingpost-operativePrior to 1990 16 1,881 0 .85%1990 to 1994 63 1,881 3 .35%1995 to 1999 200 1,881 10 .63%2000 to 2004 660 1,881 35 .09%2005 to 2009 554 1,881 29 .45%2010 to 2012 388 1,881 20 .63%total 1,881 1,881 100.00%pre-operativePrior to 1990 17 1,837 0 .93%1990 to 1994 52 1,837 2 .84%1995 to 1999 160 1,837 8 .72%2000 to 2004 610 1,837 33 .26%2005 to 2009 595 1,837 32 .44%2010 to 2012 403 1,837 21 .97%total 1,837 1,837 100.00%or schedulingPrior to 1990 17 1,837 0 .93%1990 to 1994 52 1,837 2 .84%1995 to 1999 160 1,837 8 .72%2000 to 2004 610 1,837 33 .26%2005 to 2009 595 1,837 32 .44%2010 to 2012 403 1,837 21 .97%total 1,837 1,837 100.00%

tAbLe or5 | or scheduling2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 176 98 .88% 178 177 99 .44% 178 178 100 .00% 178Non- Academic 2,676 66 .25% 4,039 2,792 69 .13% 4,039 2,915 72 .17% 4,039Med/Surg 2,074 84 .58% 2,452 2,136 87 .11% 2,452 2,188 89 .23% 2,452Other 778 44 .08% 1,765 833 47 .20% 1,765 905 51 .27% 1,765Critical Access 473 41 .20% 1,148 532 46 .34% 1,148 603 52 .53% 1,148Non- Critical Access 2,379 77 .52% 3,069 2,437 79 .41% 3,069 2,490 81 .13% 3,069Rural 366 37 .50% 976 426 43 .65% 976 496 50 .82% 976Urban 2,486 76 .70% 3,241 2,543 78 .46% 3,241 2,597 80 .13% 3,241Multi-Hospital System 1,892 72 .97% 2,593 1,925 74 .24% 2,593 1,975 76 .17% 2,593Single Hospital System 960 59 .11% 1,624 1,044 64 .29% 1,624 1,118 68 .84% 1,624All 2,852 67.63% 4,217 2,969 70.41% 4,217 3,093 73.35% 4,217


▶ Surgical Information System continued

▶ Radiology PACS

Market drivers/Future outlookThe surgical information system market for U.S. hospitals has been and will continue to be impacted through 2015 by:• Internally and externally initiated quality outcomes and

performance improvement efforts.• A continuing focus on reducing medical and medication errors at

the point-of-care and during surgical procedures, which is again likely to be tied to ARRA reporting measures.

• An increased need to capture, share, manage, analyze, and report OR data to improve processes and drive down costs, some of which will be for ARRA measurement reporting purposes, as well as to prepare the organization to price appropriately to accept more bundled pricing risk in an ACO environment.

• Intense competition for limited capital funds, which are likely to be allocated to higher priority applications, such electronic medical record (EMR) and financial projects (e.g. ICD-10 encoding conversions) which may slow this market through at least 2015.

• The increased focus of the federal government via ARRA to improve data sharing across modalities of care and among all care providers (e.g. patient summary data).

• Increasingly stringent claims coding and supporting documentation requirements mandated by federal regulations and public and private reimbursement requirements.

• An increased consumer demand to access and evaluate hospital service performance indicators related to hospital performance score cards.

Radiology picture archive and communications systems (R-PACS) are used by hospitals to capture medical images and provide convenient access to clinicians throughout the healthcare system. The R-PACS suite monitored by HIMSS Analytics is comprised of the following 10 modalities: angiography, computed radiography, computerized tomography (CT), digital fluoroscopy, digital mammography, digital radiography, magnetic resonance imaging (MRI), nuclear medicine, orthopedic surgical templating and ultrasound.

In 2012, the R-PACS environment demonstrated market penetration growth in all modalities (see Table RP1). The rate of increase from 2011 to 2012 was generally lower than those indicated from 2010 to 2011. The digital mammography modality had the highest year-over-year growth from 2011 to 2012 at just more than five percentage points.

Relatively few hospitals indicated plans to purchase an R-PACS modality in the near distant future. Of those that did, the majority

of hospitals would be classified as first time buyers of an R-PACS modality (see Table RP2). The clear exception to this general trend involved the orthopedic surgical templating modality. More than 70 percent of the planned purchases for CT, digital fluoroscopy, digital mammography, digital radiography, nuclear medicine and ultrasound were for hospitals that do not have these solutions.

The following are some of the key findings for each R-PACS modality by hospital segment:• Angiography: all hospital segments reported a slight increase in

adoption from 2011 to 2012 (see Table RP3). This modality appears to be a good market opportunity (34 percent of hospitals have yet to acquire this technology).

• Computed radiography: the critical access and rural hospital segments reported the highest increase in adoption from 2011 to 2012 at approximately five percentage points. The academic medical center segment, which is a saturated market, had growth of less than one percentage point (see Table RP4).

• Computerized tomography: critical access and rural hospital segments were the only segments to report a growth in adoption from 2011 to 2012 at more than four percentage points. All other segments, except academic medical centers, reported a growth from one to three percentage points. The academic medical center segment has reached market segmentation and registered no market penetration change (see Table RP5).

• Digital fluoroscopy: All segments indicated growth from 2011 to 2012 with the largest growth evidenced in the rural and critical access hospital segments (see Table RP6).

tAbLe rp1 | r-pAcsN=4,217 2010 2011 2012Angiography 63 .86% 65 .26% 66 .54%Computed Radiography (CR) 82 .88% 86 .01% 88 .10%Computerized Tomography (CT) 84 .63% 87 .05% 88 .78%Digital Fluoroscopy (DF) 71 .61% 74 .18% 76 .22%Digital Mammography 50 .46% 58 .41% 63 .46%Digital Radiography (DR) 74 .48% 77 .12% 78 .35%Magnetic Resonance Imaging 79 .18% 81 .53% 83 .16%Nuclear Medicine 73 .70% 75 .84% 77 .28%Orthopedic 42 .54% 47 .33% 49 .99%Ultrasound (US) 82 .90% 86 .10% 87 .72%Percentages include installed, contracted or installation in process

tAbLe rp2 | 2012# of Hospitals with Installed





for the First Time



Hospitals PlanningAngiography 4 40 .00% 6 60 .00% 10CR (Computed Radiography) 2 33 .33% 4 66 .67% 6CT (Computerized Tomography) 3 30 .00% 7 70 .00% 10DF (Digital Fluoroscopy 2 28 .57% 5 71 .43% 7Digital Mammography 2 13 .33% 13 86 .67% 15DR (Digital Radiography) 2 28 .57% 5 71 .43% 7MRI (Magnetic Resonance Imaging) 2 33 .33% 4 66 .67% 6Nuclear Medicine 2 28 .57% 5 71 .43% 7Orthopedic 3 60 .00% 2 40 .00% 5US (Ultrasound) 2 25 .00% 6 75 .00% 8Replacing = Statuses of live and operational, contracted/not yet installed and installation in processFirst time = Status of not automated


▶ Radiology PACS continued

• Digital Mammography: all segments grew by four to eight percentage points from 2011 to 2012. The rural and critical access hospital segments reported made the biggest gains this past year (see Table RP7).

• Digital radiography: rural hospitals had the largest increase at slightly more than three percentage points; the medical/surgical and urban segments reported the lowest growth at less than one percentage point each (see Table RP8).

• MRI: the rural hospital and critical access hospital segments experienced the most growth from 2011 to 2012 at more than three percentage points. The academic medical center segment, which is approaching market saturation, showed no growth. The remaining segments showed growth of less than three percentage points (see Table RP9).

• Nuclear medicine: all of the hospital segments reported a growth of under four percentage points, with the critical access segment reflecting the largest year-over-year increase (see Table RP10).

• Orthopedic: academic medical centers had the highest growth in this segment with more than a five percentage point increase. The next highest increase was in the general medical/surgical segment at three percentage points (see Table RP11).

• Ultrasound: almost all segments indicated growth from 2011 to 20112. The exception being the academic medical center segment which is fully saturated had reported no change from 2011. The highest year-over-year growth of nearly four percentage points was found in critical access and rural hospitals (see Table RP12).

tAbLe rp3 | Angiography2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal


tAbLe rp4 | computed radiography (cr)2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal


tAbLe rp5 | computerized tomography (ct)2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 177 99 .44% 178 177 99 .44% 178 177 99 .44% 178Non- Academic 3,392 83 .98% 4,039 3,494 86 .51% 4,039 3,567 88 .31% 4,039Med/Surg 2,312 94 .29% 2,452 2,359 96 .21% 2,452 2,383 97 .19% 2,452Other 1,257 71 .22% 1,765 1,312 74 .33% 1,765 1,361 77 .11% 1,765Critical Access 899 78 .31% 1,148 968 84 .32% 1,148 1,014 88 .33% 1,148Non- Critical Access 2,670 87 .00% 3,069 2,703 88 .07% 3,069 2,730 88 .95% 3,069Rural 752 77 .05% 976 816 83 .61% 976 860 88 .11% 976Urban 2,817 86 .92% 3,241 2,855 88 .09% 3,241 2,884 88 .98% 3,241Multi-Hospital System 2,158 83 .22% 2,593 2,216 85 .46% 2,593 2,253 86 .89% 2,593Single Hospital System 1,411 86 .88% 1,624 1,455 89 .59% 1,624 1,491 91 .81% 1,624All 3,569 84.63% 4,217 3,671 87.05% 4,217 3,744 88.78% 4,217



tAbLe rp6 | digital Fluoroscopy (dF)2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 170 95 .51% 178 171 96 .07% 178 175 98 .31% 178Non- Academic 2,850 70 .56% 4,039 2,957 73 .21% 4,039 3,039 75 .24% 4,039Med/Surg 2,132 86 .95% 2,452 2,187 89 .19% 2,452 2,223 90 .66% 2,452Other 888 50 .31% 1,765 941 53 .31% 1,765 991 56 .15% 1,765Critical Access 552 48 .08% 1,148 599 52 .18% 1,148 643 56 .01% 1,148Non- Critical Access 2,468 80 .42% 3,069 2,529 82 .40% 3,069 2,571 83 .77% 3,069Rural 459 47 .03% 976 503 51 .54% 976 542 55 .53% 976Urban 2,561 79 .02% 3,241 2,625 80 .99% 3,241 2,672 82 .44% 3,241Multi-Hospital System 1,972 76 .05% 2,593 2,038 78 .60% 2,593 2,084 80 .37% 2,593Single Hospital System 1,048 64 .53% 1,624 1,090 67 .12% 1,624 1,130 69 .58% 1,624All 3,020 71.61% 4,217 3,128 74.18% 4,217 3,214 76.22% 4,217

tAbLe rp7 | digital Mammography2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal


tAbLe rp8 | digital radiography (dr)2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal


tAbLe rp9 | Magnetic resonance imaging (Mri)2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal




tAbLe rp10 | nuclear Medicine2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 169 94 .94% 178 169 94 .94% 178 170 95 .51% 178Non- Academic 2,939 72 .77% 4,039 3,029 74 .99% 4,039 3,089 76 .48% 4,039Med/Surg 2,210 90 .13% 2,452 2,256 92 .01% 2,452 2,275 92 .78% 2,452Other 898 50 .88% 1,765 942 53 .37% 1,765 984 55 .75% 1,765Critical Access 586 51 .05% 1,148 645 56 .18% 1,148 685 59 .67% 1,148Non- Critical Access 2,522 82 .18% 3,069 2,553 83 .19% 3,069 2,574 83 .87% 3,069Rural 498 51 .02% 976 552 56 .56% 976 584 59 .84% 976Urban 2,610 80 .53% 3,241 2,646 81 .64% 3,241 2,675 82 .54% 3,241Multi-Hospital System 1,988 76 .67% 2,593 2,039 78 .63% 2,593 2,074 79 .98% 2,593Single Hospital System 1,120 68 .97% 1,624 1,159 71 .37% 1,624 1,185 72 .97% 1,624All 3,108 73.70% 4,217 3,198 75.84% 4,217 3,259 77.28% 4,217

tAbLe rp11 | orthopedic2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal


tAbLe rp12 | ultrasound (us)2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal


The evaluation of R-PACS market by bed size for 2012 indicates that growth was slightly higher among the smaller hospital bed segments than larger bed segments. The adoption of digital mammography demonstrated the largest increase from 2011 to 2012 across most of the bed segments. The following list represents some key modality findings within each bed segment:• 0–100 beds: digital mammography indicated the largest year-

over-year increase at more than six percentage points, while the other modalities experienced increases ranging from one to four percentage points (see Table RP13).

• 101–200 beds: digital mammography reported the highest growth at more than four percentage points, while all other segments indicated growth two percentage points or less (see Table RP14).

• 201–300 beds: digital mammography demonstrated the highest increase from 2011 to 2012 at more than four percentage points, followed by orthopedic at more than two percentage points. Digital radiography is the only R-PACS modality to indicate a decrease in adoption (see Table RP15).

• 301–400 beds: at more than five percentage points, digital mammography had the highest adoption from 2011 to 2012, followed by orthopedic at more than four percentage points. All other modalities indicated growth of approximately one percentage point (see Table RP16).

• 401–500 beds: orthopedic indicated the largest increase from 2011 to 2012 at approximately two percentage points, followed by digital mammography, MRI and nuclear medicine. All other modalities reported no change from 2011 (see Table RP17).

• 501–600 beds: digital mammography had the highest increase in adoption from 2011 to 2012 at more than five percentage points, while digital radiography reported a decline of more than two percentage points. None of the other modalities reported a change from 2011 (see Table RP18).

• Over 600 beds: digital fluoroscopy, digital mammography and digital radiography are the only modalities to indicate an increase from 2011 to 2012. All other modalities reported no change in the past year (see Table RP19).


tAbLe rp130–100 beds 2010 2011 2012

% of 2,165 HospitalsAngiography 895 41 .34% 926 42 .77% 960 44 .34%Computed Radiography (CR) 1,560 72 .06% 1,673 77 .27% 1,751 80 .88%Computerized Tomography (CT) 1,607 74 .23% 1,697 78 .38% 1,760 81 .29%Digital Fluoroscopy (DF) 1,162 53 .67% 1,240 57 .27% 1,301 60 .09%Digital Mammography 768 35 .47% 956 44 .16% 1,087 50 .21%Digital Radiography (DR) 1,267 58 .52% 1,355 62 .59% 1,404 64 .85%Magnetic Resonance Imaging (MRI) 1,415 65 .36% 1,492 68 .91% 1,549 71 .55%Nuclear Medicine 1,194 55 .15% 1,268 58 .57% 1,318 60 .88%Orthopedic 608 28 .08% 706 32 .61% 770 35 .57%Ultrasound (US) 1,548 71 .50% 1,667 77 .00% 1,726 79 .72%

tAbLe rp14101–200 beds 2010 2011 2012

% of 802 HospitalsAngiography 635 79 .18% 649 80 .92% 661 82 .42%Computed Radiography (CR) 734 91 .52% 748 93 .27% 753 93 .89%Computerized Tomography (CT) 739 92 .14% 749 93 .39% 755 94 .14%Digital Fluoroscopy (DF) 687 85 .66% 705 87 .91% 720 89 .78%Digital Mammography 482 60 .10% 558 69 .58% 592 73 .82%Digital Radiography (DR) 698 87 .03% 713 88 .90% 716 89 .28%Magnetic Resonance Imaging (MRI) 716 89 .28% 734 91 .52% 739 92 .14%Nuclear Medicine 716 89 .28% 729 90 .90% 733 91 .40%Orthopedic 416 51 .87% 463 57 .73% 482 60 .10%Ultrasound (US) 729 90 .90% 742 92 .52% 748 93 .27%

tAbLe rp15201–300 beds 2010 2011 2012


tAbLe rp16301–400 beds 2010 2011 2012


tAbLe rp17401–500 beds 2010 2011 2012

% of 188 HospitalsAngiography 182 96 .81% 182 96 .81% 182 96 .81%Computed Radiography (CR) 184 97 .87% 183 97 .34% 183 97 .34%Computerized Tomography (CT) 186 98 .94% 186 98 .94% 186 98 .94%Digital Fluoroscopy (DF) 180 95 .74% 180 95 .74% 180 95 .74%Digital Mammography 139 73 .94% 147 78 .19% 150 79 .79%Digital Radiography ( DR) 181 96 .28% 182 96 .81% 182 96 .81%Magnetic Resonance Imaging (MRI) 184 97 .87% 184 97 .87% 185 98 .40%Nuclear Medicine 182 96 .81% 183 97 .34% 184 97 .87%Orthopedic 131 69 .68% 139 73 .94% 143 76 .06%Ultrasound (US) 186 98 .94% 186 98 .94% 186 98 .94%

tAbLe rp18501–600 beds 2010 2011 2012


tAbLe rp19over 600 beds 2010 2011 2012

% of 151 HospitalsAngiography 149 98 .68% 151 100 .00% 151 100 .00%Computed Radiography (CR) 150 99 .34% 150 99 .34% 150 99 .34%Computerized Tomography(CT) 151 100 .00% 151 100 .00% 151 100 .00%Digital Fluoroscopy (DF) 145 96 .03% 147 97 .35% 151 100 .00%Digital Mammography 118 78 .15% 128 84 .77% 131 86 .75%Digital Radiography (DR) 149 98 .68% 149 98 .68% 150 99 .34%Magnetic Resonance Imaging (MRI) 149 98 .68% 150 99 .34% 150 99 .34%Nuclear Medicine 147 97 .35% 147 97 .35% 147 97 .35%Orthopedic 111 73 .51% 121 80 .13% 121 80 .13%Ultrasound (US) 151 100 .00% 151 100 .00% 151 100 .00%

Most R-PACS application contracts were signed prior to 2010 with less than 10 percent of contracts signed across almost all modalities occurring between 2010 and 2012. Digital mammography is the only modality to have more than 10 percent of the contracts signed after 2010 (see Tables RP20–RP23).

tAbLe rp20# for Contract

RangeTotal


RespondingAngiographyPrior to 1990 0 1,826 0 .00%1990 to 1994 0 1,826 0 .00%1995 to 1999 54 1,826 2 .96%2000 to 2004 799 1,826 43 .78%2005 to 2009 874 1,826 47 .89%2010 to 2012 99 1,826 5 .42%total 1,826 1,826 100.00%computed radiography (cr)Prior to 1990 0 2,334 0 .00%1990 to 1994 0 2,334 0 .00%1995 to 1999 56 2,334 2 .40%2000 to 2004 910 2,334 39 .04%2005 to 2009 1,205 2,334 51 .69%2010 to 2012 163 2,334 6 .99%total 2,334 2,334 100.00%computerized tomography (ct)Prior to 1990 0 2,349 0 .00%1990 to 1994 0 2,349 0 .00%1995 to 1999 58 2,349 2 .20%2000 to 2004 935 2,349 35 .63%2005 to 2009 1,198 2,349 47 .93%2010 to 2012 158 2,349 6 .63%total 2,349 2,349 100.00%




RangeTotal


Respondingdigital Fluoroscopy (dF)Prior to 1990 0 2,062 0 .00%1990 to 1994 0 2,062 0 .00%1995 to 1999 54 2,062 2 .62%2000 to 2004 856 2,062 41 .53%2005 to 2009 1,028 2,062 49 .88%2010 to 2012 124 2,062 6 .02%total 2,062 2,062 100.00%digital MammographyPrior to 1990 0 1,259 0 .00%1990 to 1994 0 1,259 0 .00%1995 to 1999 17 1,259 1 .35%2000 to 2004 320 1,259 25 .44%2005 to 2009 749 1,259 59 .54%2010 to 2012 173 1,259 13 .75%total 1,259 1,259 100.00%digital radiography (dr)Prior to 1990 0 2,028 0 .00%1990 to 1994 0 2,028 0 .00%1995 to 1999 48 2,028 2 .37%2000 to 2004 820 2,028 40 .45%2005 to 2009 1,030 2,028 50 .81%2010 to 2012 130 2,028 6 .41%total 2,028 2,028 100.00%


RangeTotal


RespondingMagnetic resonance imaging (Mri)Prior to 1990 0 2,204 0 .00%1990 to 1994 0 2,204 0 .00%1995 to 1999 58 2,204 2 .63%2000 to 2004 904 2,204 41 .03%2005 to 2009 1,095 2,204 49 .70%2010 to 2012 147 2,204 6 .67%total 2,204 2,204 100.00% nuclear MedicinePrior to 1990 0 2,091 0 .00%1990 to 1994 0 2,091 0 .00%1995 to 1999 55 2,091 2 .63%2000 to 2004 858 2,091 41 .05%2005 to 2009 1,050 2,091 50 .24%2010 to 2012 128 2,091 6 .12%total 2,091 2,091 100.00%orthopedicPrior to 1990 0 1,032 0 .00%1990 to 1994 0 1,032 0 .00%1995 to 1999 21 1,032 2 .03%2000 to 2004 365 1,032 35 .37%2005 to 2009 562 1,032 54 .46%2010 to 2012 84 1,032 8 .14%total 1,032 1,032 100.00%


RangeTotal


Respondingus (ultrasound)Prior to 1990 0 2,318 0 .00%1990 to 1994 0 2,318 0 .00%1995 to 1999 57 3,218 1 .77%2000 to 2004 930 2,318 40 .16%2005 to 2009 1,175 2,318 50 .73%2010 to 2012 156 2,318 6 .74%total 2,318 2,318 100.00%

Market drivers/Future outlookThe R-PACS IT application market will most likely continue to experience growth, driven by continued first-time purchases among smaller hospitals and the early stages of replacement purchases by the larger hospitals, including academic medical centers and other early adopters. This market segment has been, and will most likely continue to be, impacted through 2015 by:• Increased demand to share medical images between care

providers in HIEs, a need that will be driven by ARRA Stage 2 and Stage 3 Meaningful Use requirements.

• Increased demand for the electronic transmittal and integration of images and reports from owned, affiliated and other ambulatory practices for which the hospital provides diagnostic imaging services.

• Ongoing market consolidation where a growing IDN elects to standardize on one R-PACS vendor solution for the entire system.

• Continued acquisitions of ambulatory centers by IDNs where they elect to standardize on one PACS vendor solution.

• Ongoing demand to drive down radiology service and storage costs and eliminate film costs.

• The increasing demand for orthopedic pre-surgical templating to improve quality related to implant surgery for a growing elderly population.

• The need to attach medical images to claims for improved payer reimbursement processes.

• The increasing adoption of care delivery models that emphasize care coordination, and reward participants for producing improved clinical outcomes, reducing redundant testing, and sharing results electronically.

• Increasing consumer demands to have access to their medical information and images.



▶ Cardiology PACS

tAbLe cp3 | cardiology–cath Lab2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 140 78 .65% 178 139 78 .09% 178 144 80 .90% 178Non- Academic 1,169 28 .94% 4,039 1,223 30 .28% 4,039 1,290 31 .94% 4,039Med/Surg 1,094 44 .62% 2,452 1,148 46 .82% 2,452 1,214 49 .51% 2,452Other 215 12 .18% 1,765 214 12 .12% 1,765 220 12 .46% 1,765Critical Access 21 1 .83% 1,148 20 1 .74% 1,148 18 1 .57% 1,148Not Critical Access 1,288 41 .97% 3,069 1,342 43 .73% 3,069 1,416 46 .14% 3,069Rural 18 1 .84% 976 18 1 .84% 976 24 2 .46% 976Urban 1,291 39 .83% 3,241 1,344 41 .47% 3,241 1,410 43 .51% 3,241Multi-Hospital System 962 37 .10% 2,593 984 37 .95% 2,593 1,036 39 .95% 2,593Single Hospital System 347 21 .37% 1,624 378 23 .28% 1,624 398 24 .51% 1,624All 1,309 31.04% 4,217 1,362 32.30% 4,217 1,434 34.01% 4,217

tAbLe cp2 | 2012# of Hospitals with Installed





for the First Time



Hospitals PlanningCardiology–Cath Lab 7 50 .00% 7 50 .00% 14Cardiology–Computerized Tomography (CT) 6 75 .00% 2 25 .00% 8Cardiology–Echocardiology 7 50 .00% 7 50 .00% 14Cardiology–Intravascular Ultrasound 1 25 .00% 3 75 .00% 4Cardiology–Nuclear Cardiology 5 45 .45% 6 54 .55% 11Replacing = Statuses of live and operational, contracted/not yet installed and installation in processFirst time = Status of not automated

A cardiology picture archive and communications system (C-PACS) solution refers to electronic storage of images in a networked digital archive that stores, manages, transmits and displays cardiology images. The C-PACS market is comprised five different modalities including cath lab, computerized tomography (CT), echocardiology, intravascular ultrasound and nuclear cardiology.

More than one-third of U.S. hospitals have incorporated the echocardiology and cath lab modalities, while approximately 20 percent of hospitals have the other C-PACS modalities in place. The C-PACS environment demonstrated a growth ranging from one to three percent for all modalities (see Table CP1). The growth from 2011 to 2012 slowed in comparison to 2010 to 2011. Historically, C-PACS tend to grow at a slow but steady pace. The C-PACS growth is thought to be slower than the R-PACS growth due to a lack of significant cost reduction from the replacement of film.

When evaluating planned purchases, CT is the only C-PACS modality to indicate more plans for replacements than first time purchases. Intravascular ultrasound purchase plans reflect more first time purchasers than replacements. The remaining modalities

indicated almost the same amount of first time and replacement purchases (see Table CP2).

An evaluation of market segments in 2012 by hospital type reveals the following highlights for each C-PACS modality:• Cath lab: the academic medical center segment indicated the

highest increase from 2011 to 2012 at slightly less than three percentage points. The general medical/surgical, non-critical access, urban and multi-hospital segments all grew by more than two percentage points. The critical access hospital segment is the only segment to report a decrease from 2011 (see Table CP3).

• Computerized tomography: all of the hospital segments reported a growth from 2011 to 2012 with general medical/surgical reporting the largest year-over-year increase at about three percentage points (see Table CP4). Growth ranged from less than one to slightly under three percentage points across all segments.

• Echocardiology: growth for academic medical center, general medical/surgical and non-critical access segments all exceeded three percentage points from 2011 to 2012 (see Table CP5). All other segments demonstrated an increase of one to three percentage points.

• Intravascular ultrasound: the academic medical center segment demonstrated the largest year-over-year growth at approximately four percentage points. The critical access hospital segment demonstrated the lowest increase (see Table CP6).

• Nuclear cardiology: with more than a five percentage point increase, the academic medical center market segment reflected the highest year-over-year growth, followed by the general medical/surgical and non-critical access segments (see Table CP7).

tAbLe cp1 | c-pAcs N=4,217 2010 2011 2012Cardiology–Cath Lab 31 .04% 32 .30% 34 .01%Cardiology–Computerized Tomography (CT) 19 .99% 22 .15% 24 .02%Cardiology–Echocardiology 30 .78% 33 .55% 36 .19%Cardiology–Intravascular Ultrasound 18 .90% 21 .22% 23 .17%Cardiology–Nuclear Cardiology 18 .00% 20 .99% 23 .12%Percentages include installed, contracted or installation in process


▶ Cardiology PACS continued

tAbLe cp4 | cardiology–computerized tomography (ct)2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 90 50 .56% 178 96 53 .93% 178 100 56 .18% 178Non- Academic 753 18 .64% 4,039 838 20 .75% 4,039 913 22 .60% 4,039Med/Surg 684 27 .90% 2,452 761 31 .04% 2,452 830 33 .85% 2,452Other 159 9 .01% 1,765 173 9 .80% 1,765 183 10 .37% 1,765Critical Access 41 3 .57% 1,148 48 4 .18% 1,148 50 4 .36% 1,148Not Critical Access 802 26 .13% 3,069 886 28 .87% 3,069 963 31 .38% 3,069Rural 23 2 .36% 976 28 2 .87% 976 36 3 .69% 976Urban 820 25 .30% 3,241 906 27 .95% 3,241 977 30 .15% 3,241Multi-Hospital System 612 23 .60% 2,593 673 25 .95% 2,593 724 27 .92% 2,593Single Hospital System 231 14 .22% 1,624 261 16 .07% 1,624 289 17 .80% 1,624All 843 19.99% 4,217 934 22.15% 4,217 1,013 24.02% 4,217

tAbLe cp5 | cardiology–echocardiology2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 130 73 .03% 178 131 73 .60% 178 138 77 .53% 178Non- Academic 1,168 28 .92% 4,039 1,284 31 .79% 4,039 1,388 34 .36% 4,039Med/Surg 1,046 42 .66% 2,452 1,137 46 .37% 2,452 1,218 49 .67% 2,452Other 252 14 .28% 1,765 278 15 .75% 1,765 308 17 .45% 1,765Critical Access 69 6 .01% 1,148 89 7 .75% 1,148 106 9 .23% 1,148Not Critical Access 1,229 40 .05% 3,069 1,326 43 .21% 3,069 1,420 46 .27% 3,069Rural 45 4 .61% 976 63 6 .45% 976 83 8 .50% 976Urban 1,253 38 .66% 3,241 1,352 41 .72% 3,241 1,443 44 .52% 3,241Multi-Hospital System 910 35 .09% 2,593 973 37 .52% 2,593 1,038 40 .03% 2,593Single Hospital System 388 23 .89% 1,624 442 27 .22% 1,624 488 30 .05% 1,624All 1,298 30.78% 4,217 1,415 33.55% 4,217 1,526 36.19% 4,217

tAbLe cp6 | cardiology–intravascular ultrasound2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 94 52 .81% 178 98 55 .06% 178 105 58 .99% 178Non- Academic 703 17 .41% 4,039 797 19 .73% 4,039 872 21 .59% 4,039Med/Surg 652 26 .59% 2,452 735 29 .98% 2,452 804 32 .79% 2,452Other 145 8 .22% 1,765 160 9 .07% 1,765 173 9 .80% 1,765Critical Access 26 2 .26% 1,148 33 2 .87% 1,148 35 3 .05% 1,148Not Critical Access 771 25 .12% 3,069 862 28 .09% 3,069 942 30 .69% 3,069Rural 19 1 .95% 976 27 2 .77% 976 37 3 .79% 976Urban 778 24 .00% 3,241 868 26 .78% 3,241 940 29 .00% 3,241Multi-Hospital System 565 21 .79% 2,593 627 24 .18% 2,593 686 26 .46% 2,593Single Hospital System 232 14 .29% 1,624 268 16 .50% 1,624 291 17 .92% 1,624All 797 18.90% 4,217 895 21.22% 4,217 977 23.17% 4,217

tAbLe cp7 | cardiology–nuclear cardiology2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 88 49 .44% 178 91 51 .12% 178 101 56 .74% 178Non- Academic 671 16 .61% 4,039 794 19 .66% 4,039 874 21 .64% 4,039Med/Surg 611 24 .92% 2,452 721 29 .40% 2,452 787 32 .10% 2,452Other 148 8 .39% 1,765 164 9 .29% 1,765 188 10 .65% 1,765Critical Access 35 3 .05% 1,148 47 4 .09% 1,148 57 4 .97% 1,148Not Critical Access 724 23 .59% 3,069 838 27 .31% 3,069 918 29 .91% 3,069Rural 25 2 .56% 976 38 3 .89% 976 48 4 .92% 976Urban 734 22 .65% 3,241 847 26 .13% 3,241 927 28 .60% 3,241Multi-Hospital System 523 20 .17% 2,593 601 23 .18% 2,593 653 25 .18% 2,593Single Hospital System 236 14 .53% 1,624 284 17 .49% 1,624 322 19 .83% 1,624All 759 18.00% 4,217 885 20.99% 4,217 975 23.12% 4,217



The evaluation of the C-PACS market by bed size segments for 2012 reveals the following (see Tables CP8–CP14): • 0–100 beds: echocardiology had the highest growth at nearly two

percentage points, while the other modalities reported an increase of under two percentage points (see Table CP8).

• 101–200 beds: for the second year in a row, echocardiology indicated the highest increase at more than four percentage points, followed by nuclear cardiology at slightly more than three percentage points (see Table CP9). All other modalities indicated an increase of at least two percentage points from last year.

• 201–300 beds: nuclear cardiology grew by almost four percentage points, followed by cath lab at slightly more than three percentage points. All other modalities reported a growth of slightly under three percentage points (see Table CP10).

• 301–400 beds: the cath lab modality increased by more than five percentage points from 2011 to 2012. All other modalities grew by two to four percentage points (see Table CP11).

• 401–500 beds: echocardiology and nuclear cardiology are tied for the highest increase in adoption from 2011 to 2012, at close to four percentage points (see Table CP12).

• 501–600 beds: intravascular ultrasound reported the largest increase in adoption from 2011 to 2012 at more than four percentage points. The level of adoption for cath lab declined slightly in this segment (see Table CP13).

• Over 600 beds: at more than six percentage points, the largest year-over-year growth in this bed segment was intravascular ultrasound, followed by computerized tomography at more than five percentage points (see Table CP14).

When evaluating the historical contracting activity in the C-PACS modalities market, we discovered that more than 10 percent of contracts were signed between 2010 and 2012 (see Tables CP15–CP16), while more than half of contracts for all modalities were signed from 2005 to 2009. In addition, as EMR deployments in academic medical centers and the larger and multi-hospital market segments have matured, we are seeing an increase in EMR deployments that incorporate digital images of all types into their contents. We expect digital imaging modalities of all types to continue to proliferate over the next several years as the industry embraces various forms of HIE. Not all of these types of images will neatly fit into cardiology or R-PACS, since they will be from other sources, such as gastroenology, pthalmology, dermatology, tele-medicine, etc.

tAbLe cp80–100 beds 2010 2011 2012

% of 2,165 HospitalsCardiology–Cath Lab 125 5 .77% 128 5 .91% 143 6 .61%Cardiology–Computerized

Tomography (CT) 105 4 .85% 124 5 .73% 144 6 .65%Cardiology–Echocardiology 190 8 .78% 232 10 .72% 273 12 .61%Cardiology–Intravascular

Ultrasound 87 4 .02% 109 5 .03% 129 5 .96%Cardiology–Nuclear Cardiology 97 4 .48% 134 6 .19% 157 7 .25%

tAbLe cp9101–200 beds 2010 2011 2012

% of 802 HospitalsCardiology–Cath Lab 323 40 .27% 334 41 .65% 357 44 .51%Cardiology–Computerized



tAbLe cp10201–300 beds 2010 2011 2012




tAbLe cp11301–400 beds 2010 2011 2012




tAbLe cp12401–500 beds 2010 2011 2012




tAbLe cp13501–600 beds 2010 2011 2012




tAbLe cp14over 600 beds 2010 2011 2012






▶ Bar Code Technology

tAbLe cp15# for Contract

RangeTotal


Respondingcardiology–cath LabPrior to 1990 0 558 0 .00%1990 to 1994 1 558 0 .18%1995 to 1999 9 558 1 .63%2000 to 2004 150 558 27 .17%2005 to 2009 319 558 57 .79%2010 to 2012 79 558 14 .31%total 558 558 100.00%cardiology–computerized tomography (ct)Prior to 1990 0 336 0 .00%1990 to 1994 0 336 0 .00%1995 to 1999 5 336 1 .49%2000 to 2004 101 336 30 .06%2005 to 2009 196 336 58 .33%2010 to 2012 34 336 10 .12%total 336 336 100.00%cardiology–echocardiologyPrior to 1990 0 562 0 .00%1990 to 1994 1 562 0 .18%1995 to 1999 8 562 1 .42%2000 to 2004 133 562 23 .67%2005 to 2009 336 562 59 .79%2010 to 2012 84 562 14 .95%total 562 562 100.00%

tAbLe cp15# for Contract

RangeTotal


Respondingcardiology–intravascular ultrasoundPrior to 1990 0 353 0 .00%1990 to 1994 0 353 0 .00%1995 to 1999 5 353 1 .42%2000 to 2004 94 353 26 .70%2005 to 2009 214 353 60 .80%2010 to 2012 40 353 11 .36%total 353 353 100.00%cardiology–nuclear cardiologyPrior to 1990 0 351 0 .00%1990 to 1994 0 351 0 .00%1995 to 1999 6 351 1 .71%2000 to 2004 98 351 27 .92%2005 to 2009 206 351 58 .69%2010 to 2012 41 351 11 .68%total 351 351 100.00%

Market drivers/Future outlookDespite the near-term mixed outlook for capital budgets, which will tend to moderate demand, the prospects for long-term growth in this market segment are very positive. The C-PACS IT application market has been and will most likely continue to be impacted by:• The demand to increase medical image sharing among providers

in an EMR environment.

• The demand to share medical images within emerging healthcare information exchanges.

• The highly competitive landscape for cardiology and cardiac surgery, and the ability to recruit recent residency graduates who have been users of C-PACS.

• The demand to decrease costs for medical imaging services.• The increased acceptance and adoption of standards that will

facilitate the capture, rendering, and transmission of various types of medical images across digital imaging modalities and between vendor PACS solutions.

• Continued favorable cost trends for on-line and archival storage, including the impact of storage virtualization technologies.

This section tracks the use of bar code technology across eight different hospital departments/functions. Bar coding technology is most widely used in the laboratory as more than 85 percent of U.S. hospitals had a laboratory bar coding system in place in 2012. During this past year, the market penetration all of the bar code technologies tracked by HIMSS Analytics increased. Medication administration and pharmacy administration demonstrated the largest increases, at eight and seven percent respectively (see Table BC1). Bar code technology is least likely to be used for fixed assets/equipment tracking, as only seven percent of U.S. hospitals use bar codes in this area. The use of bar code technology for patient registration applications is expected to grow as these applications support a very key area of the hospital, point-of-care medication administration.

With respect to bar coding purchasing plans, medication administration once again tops the list (31 percent of all U.S. hospitals) (see Table BC2). The projected use of the other bar coding technologies increased from 2011 to 2012.

tAbLe bc1 | bar coding (current)N=4,217 2010 2011 2012

Count Percent Count Percent Count PercentFixed Assets/Equipment

Tracking 165 3 .91% 212 5 .03% 281 6 .66%Laboratory 3,442 81 .62% 3,519 83 .45% 3,605 85 .49%Materials Management 1,981 46 .98% 2,101 49 .82% 2,207 52 .34%Medication Administration 1,868 44 .30% 2,096 49 .70% 2,447 58 .03%Patient Registration 390 9 .25% 497 11 .79% 594 14 .09%Pharmacy Administration 2,602 61 .70% 2,825 66 .99% 3,119 73 .96%Radiology 2,098 49 .75% 2,122 50 .32% 2,153 51 .06%

tAbLe bc2 | bar coding (planned)N=4,217 2010 2011 2012

Count Percent Count Percent Count PercentFixed Assets/Equipment

Tracking 62 1 .47% 96 2 .28% 115 2 .73%Laboratory 195 4 .62% 209 4 .96% 221 5 .24%Materials Management 325 7 .71% 351 8 .32% 368 8 .73%Medication Administration 1,549 36 .73% 1,468 34 .81% 1,304 30 .92%Patient Registration 90 2 .13% 120 2 .85% 131 3 .11%Pharmacy Administration 908 21 .53% 848 20 .11% 694 16 .46%Radiology 138 3 .27% 145 3 .44% 156 3 .70%


▶ Bar Code Technology continued

▶ Electronic Medical Record Environment

Use of bar coding technologies is expected to increase for a multiplicity of reasons. For example, bar coding supports patient safety efforts by ensuring hospitals follow the “five rights” of medication administration (right patient, right dose, right drug, right time and right route). Bar coding is also associated with automated medication administration that is an “assistive technology” used in conjunction with an eMAR, which is a Stage 2 Meaningful Use requirement for any acute care hospital with an average daily census of greater than nine patients.

Market drivers/Future outlookThe bar code technology market has been and will continue to be impacted through 2015 by:• The drive for hospitals to implement the “five rights” of

medication administration and to improve patient safety through information technology.

• The drive for hospitals to implement the “five rights” of medication administration and to improve nurse satisfaction and patient experience.

• Stage 2 ARRA Meaningful Use requirements which require the use of assistive technologies in conjunction with an eMAR for medication administration processes.

• The growing use of bar code usage in blood tracking and blood administration.

• The need to effectively manage patient tracking and patient flows. • The desire to improve supply chain management functions

throughout the hospital to reduce inventory and management costs.

• Though a nascent market now, asset tracking and real time location tracking with also drive some bar code technology adoption.

• The lack of consistent standards for the technology of materials packaging and medication packaging.

• The adoption of RFID technologies in patient tracking and material management, which may begin to reduce some growth of bar code technologies in these applications over the next several years.

HIMSS Analytics monitors the following seven applications as part of the EMR application suite: clinical data repository; clinical decision support system; computerized practitioner order entry; order entry; patient portal; physician documentation; physician portal. These applications have the ability to significantly impact clinical outcomes, patient safety and efficiency for hospitals if implemented as part of a comprehensive change management process and used directly by all clinicians, including physicians. While nursing applications are also part of the EMR suite, we have broken them out for separate analysis (please refer to the Nursing IT section for additional information).

All of the applications in this suite grew in their market penetration in the past year. The highest increases were for CPOE (over ten percentage points), physician documentation (seven percentage points) and physician portal (over five percentage points). All other

applications, except general order entry, increased by at least 2.5 percentage points (see Table EMR1). General order entry is reaching market saturation (over 95 percent penetration) and may become an obsolete application as hospitals adopt CPOE applications in place of legacy systems. Clinical data repositories are also nearing market saturation, rising to 94 percent in 2012.

The majority of purchases for CPOE and physician documentation solutions will be made by hospitals that are planning to purchase this technology for the first time. The remaining applications in the EMR segment have more replacement than first time purchase plans (see Table EMR2).

An evaluation of this market from 2011 to 2012 by hospital type reveals the following highlights:• CDR: the rural and critical hospital segments had the highest

growth rates between 2011 and 2012 at around seven percentage points each, while single hospital systems showed growth of over five percentage points (see Table EMR3). Academic medical centers reached full market penetration in 2010 and have seen no changes since then.

• Clinical decision support: the highest increases from 2011 to 2012 were in the rural and critical access segments, each at nearly seven percentage points (see Table EMR4). Growth in the single hospital segment was over 5.5 percentage points.

tAbLe eMr1 | electronic Medical recordN=4,217 2010 2011 2012Clinical Data Repository 88 .24% 91 .11% 94 .00%Clinical Decision Support Systems (CDSS) 85 .72% 88 .62% 91 .25%Computerized Practitioner Order Entry (CPOE) 56 .58% 67 .77% 78 .35%Order Entry (includes Order Communication) 91 .65% 93 .64% 95 .26%Patient Portal 41 .71% 50 .34% 54 .59%Physician Documentation 53 .17% 61 .80% 68 .98%Physician Portal 42 .87% 50 .75% 56 .27%Percentages include installed, contracted or installation in process

tAbLe eMr2 | 2012# of Hospitals with Installed





for the First Time



Hospitals PlanningClinical Data Repository 71 71 .00% 29 29 .00% 100Clinical Decision Support Systems (CDSS) 68 70 .83% 28 29 .17% 96Computerized Practitioner Order Entry (CPOE) 50 30 .86% 112 69 .14% 162Order Entry (includes Order Communication) 67 72 .04% 26 27 .96% 93Patient Portal 29 51 .79% 27 48 .21% 56Physician Documentation 51 40 .48% 75 59 .52% 126Physician Portal 29 64 .44% 16 35 .56% 45Replacing = Statuses of live and operational, contracted/not yet installed and installation in processFirst time = Status of not automated


▶ Electronic Medical Record Environment continued

• CPOE: all hospital segments except academic hospitals increased CPOE implementation by at least eight percentage points (see Table EMR5). At 96 percent, implementation is nearing market saturation in the academic medical center segment. Rural hospitals showed the highest increase with an 18 percentage point gain from 2011 to 2012.

• Order entry: academic medical centers, medical surgical hospitals, non-critical access hospitals, urban hospitals and the multi-hospital system segments are highly saturated markets with market penetration of more than 95 percent (see Table EMR6). Critical access and rural hospitals indicated the highest growths with approximately 4.5 percentage point increases.

• Patient Portal: from 2011 to 2012, there was an increase in market penetration in each hospital segment (see Table EMR7). Academic hospitals demonstrated the largest increase (six percentage points), followed closely by single hospital systems and critical access hospitals, each just over five percentage points.

• Physician documentation: all hospital segments demonstrated growth from 2011 to 2012. Critical access, rural hospitals and single hospital systems indicated at least a ten percentage point increase (see Table EMR8).

• Physician portal: the academic medical center segment demonstrated the greatest growth between 2011 and 2012 at almost nine percentage points (see Table EMR9). All other hospital segments showed increases of at least five percentage points.

Academic medical centers and larger medical/surgical hospitals demonstrated the highest adoption rates in physician-focused applications (e.g. CPOE, physician documentation, physician portal). These organizations tend to have higher staffing levels of residents and hospitalists, who are generally required to use the clinical applications for patient care. Critical access and rural hospitals showed higher adoption increases as they continue to expand their EMR application capabilities and increasingly adopt the role of hospitalists.

tAbLe eMr3 | clinical data repository2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal


tAbLe eMr4 | clinical decision support system (cdss)2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal


tAbLe eMr5 | computerized practitioner order entry (cpoe)2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 160 89 .89% 178 165 92 .70% 178 170 95 .51% 178Non- Academic 2,226 55 .11% 4,039 2,693 66 .67% 4,039 3,134 77 .59% 4,039Med/Surg 1,437 58 .61% 2,452 1,710 69 .74% 2,452 1,972 80 .42% 2,452Other 949 53 .77% 1,765 1,148 65 .04% 1,765 1,332 75 .47% 1,765Critical Access 452 39 .37% 1,148 631 54 .97% 1,148 799 69 .60% 1,148Non- Critical Access 1,934 63 .02% 3,069 2,227 72 .56% 3,069 2,505 81 .62% 3,069Rural 358 36 .68% 976 500 51 .23% 976 677 69 .36% 976Urban 2,028 62 .57% 3,241 2,358 72 .76% 3,241 2,627 81 .06% 3,241Multi-Hospital System 1,639 63 .21% 2,593 1,834 70 .73% 2,593 2,046 78 .90% 2,593Single Hospital System 747 46 .00% 1,624 1,024 63 .05% 1,624 1,258 77 .46% 1,624All 2,386 56.58% 4,217 2,858 67.77% 4,217 3,304 78.35% 4,217



tAbLe eMr6 | order entry (includes order communication)2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 177 99 .44% 178 177 99 .44% 178 177 99 .44% 178Non- Academic 3,688 91 .31% 4,039 3,772 93 .39% 4,039 3,840 95 .07% 4,039Med/Surg 2,373 96 .78% 2,452 2,400 97 .88% 2,452 2,413 98 .41% 2,452Other 1,492 84 .53% 1,765 1,549 87 .76% 1,765 1,604 90 .88% 1,765Critical Access 905 78 .83% 1,148 954 83 .10% 1,148 1,006 87 .63% 1,148Non- Critical Access 2,960 96 .45% 3,069 2,995 97 .59% 3,069 3,011 98 .11% 3,069Rural 788 80 .74% 976 823 84 .32% 976 866 88 .73% 976Urban 3,077 94 .94% 3,241 3,126 96 .45% 3,241 3,151 97 .22% 3,241Multi-Hospital System 2,471 95 .30% 2,593 2,508 96 .72% 2,593 2,523 97 .30% 2,593Single Hospital System 1,394 85 .84% 1,624 1,441 88 .73% 1,624 1,494 92 .00% 1,624All 3,865 91.65% 4,217 3,949 93.64% 4,217 4,017 95.26% 4,217

tAbLe eMr7 | patient portal2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal


tAbLe eMr8 | physician documentation2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountAcademic/Teaching 145 81 .46% 178 153 85 .96% 178 161 90 .45% 178Non- Academic 2,097 51 .92% 4,039 2,453 60 .73% 4,039 2,748 68 .04% 4,039Med/Surg 1,383 56 .40% 2,452 1,618 65 .99% 2,452 1,767 72 .06% 2,452Other 859 48 .67% 1,765 988 55 .98% 1,765 1,142 64 .70% 1,765Critical Access 393 34 .23% 1,148 516 44 .95% 1,148 637 55 .49% 1,148Non- Critical Access 1,849 60 .25% 3,069 2,090 68 .10% 3,069 2,272 74 .03% 3,069Rural 316 32 .38% 976 420 43 .03% 976 538 55 .12% 976Urban 1,926 59 .43% 3,241 2,186 67 .45% 3,241 2,371 73 .16% 3,241Multi-Hospital System 1,560 60 .16% 2,593 1,745 67 .30% 2,593 1,880 72 .50% 2,593Single Hospital System 682 42 .00% 1,624 861 53 .02% 1,624 1,029 63 .36% 1,624All 2,242 53.17% 4,217 2,606 61.80% 4,217 2,909 68.98% 4,217

tAbLe eMr9 | physician portal2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal




Analysis of the EMR market by bed size in 2012 indicates that CPOE demonstrated the highest growth across almost the majority of bed segments. The exceptions being the 301–400 and over 600 bed segments. CPOE and physician documentation showed five percentage point growth in the 401–500 beds segment while CPOE, patient portal and physician documentation showed six percentage point growth in the 501–600 bed segment. The following provides an analyses of growth from 2011 to 2012 by hospital bed size (see Tables EMR10–EMR16):• 0–100 beds: CPOE had the highest growth in this segment at

almost 13 percentage points, while physician documentation grew by nearly ten percentage points. Physician portal showed the third highest growth in this segment with a six percentage point increase.

• 101–200 beds: CPOE adoption grew by nearly 11 percentage points, followed by physician documentation (4.6 percentage points).

• 201–300 beds: the highest growth in the past year was for CPOE (nearly eight percentage points) followed by physician portal (nearly six percentage points).

• 301–400 beds: physician documentation and CPOE had similar growth (nearly six percentage points) from 2011 to 2012. Physician and patient portals also grew by more than five percentage points in the past year.

• 401–500 beds: Use of CDR and clinical decision support software is nearly universal in this bed segment, and there was no growth in the past year. CPOE and patient portal each demonstrated growth of at least five percentage points in the past year.

• 501–600 beds: Use of CDR, clinical decision support and order entry software is universal in this bed segment. CPOE, physician portal and patient portal each had a growth of six percentage points in this segment.

• Over 600 beds: CDR, clinical decision support, CPOE and order entry have achieved market saturation. The highest growth in this segment was for physician portal (over eight percentage points), followed by CPOE and patient portal (each over 4.5 percentage points).

tAbLe eMr100–100 beds 2010 2011 2012

% of 2,165 HospitalsClinical Data Repository 1,714 79 .17% 1,828 84 .43% 1,934 89 .33%Clinical Decision Support

Systems (CDSS) 1,659 76 .63% 1,763 81 .43% 1,859 85 .87%Computerized Practitioner

Order Entry (CPOE) 1,021 47 .16% 1,298 59 .95% 1,578 72 .89%Order Entry (includes Order

Communication) 1,853 85 .59% 1,928 89 .05% 1,990 91 .92%Patient Portal 643 29 .70% 807 37 .27% 896 41 .39%Physician Documentation 934 43 .14% 1,124 51 .92% 1,336 61 .71%Physician Portal 626 28 .91% 819 37 .83% 951 43 .93%

tAbLe eMr11101–200 beds 2010 2011 2012

% of 802 HospitalsClinical Data Repository 765 95 .39% 771 96 .13% 784 97 .76%Clinical Decision Support

Systems (CDSS) 743 92 .64% 753 93 .89% 764 95 .26%Computerized Practitioner

Order Entry (CPOE) 451 56 .23% 536 66 .83% 623 77 .68%Order Entry (includes Order

Communication) 774 96 .51% 780 97 .26% 784 97 .76%Patient Portal 405 50 .50% 489 60 .97% 515 64 .21%Physician Documentation 452 56 .36% 529 65 .96% 566 70 .57%Physician Portal 400 49 .88% 457 56 .98% 488 60 .85%

tAbLe eMr12201–300 beds 2010 2011 2012





tAbLe eMr13301–400 beds 2010 2011 2012





tAbLe eMr14401–500 beds 2010 2011 2012





tAbLe eMr15501–600 beds 2010 2011 2012





tAbLe eMr16over 600 beds 2010 2011 2012







Over three-quarters of all applications in the EMR segment were contracted after 2000 (see Tables EMR17–EMR19). The majority of contracts for patient portal and physician portal were signed in 2010 or later. The availability of ARRA incentives are expected to drive higher adoption rates for CPOE, physician documentation, patient portal and physician portal through 2016 as hospitals strive to meet Meaningful Use criteria.

tAbLe eMr17# for Contract

RangeTotal


Respondingclinical data repositoryPrior to 1990 17 2,654 0 .64%1990 to 1994 89 2,654 3 .36%1995 to 1999 386 2,654 14 .56%2000 to 2004 838 2,654 31 .60%2005 to 2009 795 2,654 29 .98%2010 to 2012 529 2,654 19 .95%total 2,654 2,654 100.00%clinical decision support system (cdss)Prior to 1990 15 2,409 0 .63%1990 to 1994 85 2,409 3 .56%1995 to 1999 332 2,409 13 .91%2000 to 2004 694 2,409 29 .07%2005 to 2009 760 2,409 31 .84%2010 to 2012 523 2,409 21 .91%total 2,409 2,409 100.00%computerized practitioner order entry (cpoe)Prior to 1990 2 2,032 0 .10%1990 to 1994 90 2,032 4 .45%1995 to 1999 43 2,032 2 .13%2000 to 2004 449 2,032 22 .19%2005 to 2009 681 2,032 33 .66%2010 to 2012 767 2,032 37 .91%total 2,032 2,023 100.00%


RangeTotal


Respondingorder entry (includes order communication)Prior to 1990 40 2,898 1 .38%1990 to 1994 197 2,898 6 .80%1995 to 1999 445 2,898 15 .36%2000 to 2004 914 2,898 31 .54%2005 to 2009 764 2,898 26 .36%2010 to 2012 538 2,898 18 .56%total 2,898 2,898 100.00%patient portalPrior to 1990 0 181 0 .00%1990 to 1994 0 181 0 .00%1995 to 1999 1 181 0 .55%2000 to 2004 19 181 10 .50%2005 to 2009 38 181 14 .36%2010 to 2012 123 181 67 .96%total 181 181 100.00%


RangeTotal


Respondingphysician documentationPrior to 1990 3 1,840 0 .16%1990 to 1994 92 1,840 5 .00%1995 to 1999 48 1,840 2 .61%2000 to 2004 457 1,840 24 .85%2005 to 2009 563 1,840 30 .61%2010 to 2012 677 1,840 36 .81%total 1,840 1,840 100.00%physician portalPrior to 1990 0 848 0 .00%1990 to 1994 6 848 0 .71%1995 to 1999 20 848 2 .36%2000 to 2004 187 848 22 .08%2005 to 2009 277 848 32 .70%2010 to 2012 358 848 42 .27%total 848 848 100.00%

Market drivers/Future outlookThe EMR environment market has been or will most likely be impacted through 2015 by:• An increased focus on complying with ARRA Meaningful Use

Stage 1 and Stage 2 requirements and reporting criteria in order to qualify for EMR adoption incentives and avoid Medicare reimbursement penalties.

• While Stage 2 Meaningful Use has raised the bar on all the Stage 1 measures for EMR use, clearly there is a strong intent to increase “patient engagement” as a way to begin tackling the chronic disease issues in the country. We see this as another Meaningful Use driver for portal adoption.

• The increased need to acquire, manage and analyze clinical data for business intelligence, outcomes improvement, pay for performance incentive programs and government compliance reporting.

• Increased hiring of hospitalists who are expected to use CPOE and physician documentation applications as a condition of employment.

• Increased purchasing of physician practices which are expected to use CPOE and physician documentation applications as a condition of purchase and employment.

• Increased pressures on hospitals by federal and state authorities to participate in HIE and public health reporting activities, or the desire of IDNs to actively participate in private HIEs.

• Tight capital markets which may impact the acquisition and installation of EMR products through 2015, especially for small community and critical access hospitals, in spite of the availability of ARRA incentives.

• The continued resistance of attending physicians in a competitive community hospital environment to the adoption and use of CPOE and physician documentation applications.


▶ The EMR Adoption ModelSM: Measuring Clinical IT Transformation

The acute care EMR Adoption ModelSM (EMRAM) was developed by HIMSS Analytics to assess the status of clinical system/EMR implementations in care delivery organizations (CDOs), specifically hospitals. HIMSS Analytics collects data on healthcare IT deployments and uses this data to measure the degree of deployment of core technologies and processes that support an electronic medical record environment. This model, which uses an algorithm to score more than 5,300 U.S. acute care hospitals, demonstrates consistent upward movement among U.S. hospitals (see Figure EMRAM1). This same algorithm-based technique is used to measure movement towards an EMR environment in Canada, Europe, the Middle East and Asia.

eMr Adoption ModelSM: An eMr Market transformation Assessment toolThe stages of the model are as follows:

stage 0: Some clinical automation may be present, but all three of the major ancillary department systems for laboratory, pharmacy, and radiology are not implemented.

stage 1: All three of the major ancillary clinical systems (pharmacy, laboratory and radiology) are installed.

stage 2: Major ancillary clinical systems feed orders and results data to a CDR that provides physician access for retrieving and reviewing results. The CDR contains a controlled medical vocabulary (CMV), and the clinical decision support/rules engine (CDSS) for rudimentary conflict checking such as duplicate orders. Information from document imaging systems may be linked to the CDR at this stage.

stage 3: Clinical documentation (e.g., vital signs, flow sheets, nursing notes, and the eMAR) is required; care plan charting is scored with extra points, and is implemented and integrated with the CDR for at least one service or one unit in the hospital. Some level of medical image access from radiology picture archive and communication systems (R-PACS) is available to physicians via the organization’s intranet or other secure networks outside of the radiology department confines. If clinical documentation (e.g., vital signs, flow sheets, nursing notes, and eMAR) is implemented for one inpatient service area and completed the previous stages, then this stage has been achieved.

stage 4: CPOE for use by any clinician is added to the nursing and CDR environment along with the second level of clinical decision support capabilities related to evidence-based medicine protocols and order sets. An organization is given credit for having achieved this stage if one patient service area (excluding the emergency department) has implemented CPOE and completed the previous stages.

stage 5: The closed-loop medication administration environment is fully implemented in at least one patient care service area. The eMAR and bar coding or other auto identification technology, such as RFID, are implemented and integrated with CPOE and pharmacy to support the five rights of medication administration (right patient, right drug, right dose, right route and right time), thereby maximizing point-of-care patient safety processes.

stage 6: Full physician documentation/charting (using structured templates) is implemented for at least one patient care service area supported by clinical decision support. Level three of clinical decision support is implemented, which provides guidance for all clinician activities related to protocols and outcomes in the form of variance and compliance alerts. A full complement of R-PACS systems provides medical images to physicians via an intranet and displaces all film-based images.

stage 7: The hospital has a paperless EMR environment to support patient care delivery. Patient data/information is easily exchanged between the inpatient, out-patient, and emergency department domains. All radiology images are digital and easily accessed by all authorized clinicians. Clinical information can be readily analyzed and reported on for quality and patient safety initiatives, and shared via standardized electronic transactions with all entities within a HIE (i.e., other hospitals, ambulatory clinics, sub-acute environments, employers, payers and patients). This stage allows the healthcare organization to support the true sharing and use of health and wellness information by consumers and providers alike using CCD, CCR, or state required transaction formats.

scoring FormatAn EMR score is represented by the following format—S.nnnn, where “S” equals the current stage achieved for the model, and the “.nnnn” represents the weighted score representing the implementation of higher stage clinical applications that have been implemented before the higher stage has been fully achieved. In this model all applications in previous stages and the current stage must be achieved before the current stage score is achieved. For example, if a hospital has installed CPOE (Stage 4), but has not yet implemented all of the components required for clinical documentation used by nursing (Stage 3), then the hospital would be scored as a Stage 2 hospital and the four digits after the stage designation would identify the weighted points that had been achieved for implementing CPOE (2.nnnn).

A comparison of the EMRAM scores for U.S. hospitals by individual stage for the third quarter of 2012 as compared to year end 2011 final numbers is shown in Figure EMRAM1. Continuing trends from previous years, hospitals in Stages 4 through 6 increased from end of year 2011 to the Q3 of 2012, while the percentage of hospitals in Stages 0 to 3 have decreased in the same timeframe showing that hospitals are moving up the EMRAM stages. The increase in the percentage of hospitals in Stages 4 to 6 can largely be attributed directly to the ARRA incentive and meeting the Meaningful Use criteria. The number of U.S. Stage 7 hospitals increased slightly from 2011 to 2012, while the number of U.S. hospitals in Stage 3 decreased by almost three percent. Stage 3 provides the foundation for advancing to more advanced stages of clinical information system capabilities (e.g., CPOE, closed-loop medication administration, and physician documentation).


▶ The EMR Adoption ModelSM: Measuring Clinical IT Transformation continued

Stage 7 Complete EMR; CCD transactions to share data; Data 1.2% 1.8% warehousing; Data continuity with ED, ambulatory, OP

Stage 6 Physician documentation (structured templates), 5.2% 7.3% full CDSS (variance & compliance), full R-PACS

Stage 5 Closed loop medication administration 8.4% 12.0%

Stage 4 CPOE, Clinical Decision Support (clinical protocols) 13.2% 14.2%

Stage 3 Nursing/clinical documentation (flow sheets), CDSS 44.9% 41.3% (error checking), PACS available outside Radiology

Stage 2 CDR, Controlled Medical Vocabulary, CDS, may have 12.4% 11.2% Document Imaging; HIE capable

Stage 1 Ancillaries - Lab, Rad, Pharmacy - All Installed 5.7% 4.8%

Stage 0 All Three Ancillaries Not Installed 9.0% 7.4%

Data from HIMSS AnalyticsTM Database ©2012 N = 5,337 N = 5,319

Stage

Figure EMRAM1: US EMR Adoption ModelSM

2012Q3

2011FinalCumulative Capabilities

The EMRAM scores of U.S. hospitals have moved positively since 2008, as Stages 4 through 7 have increased while Stages 0 through 3 have decreased. The following is a representation of a five-year trend (see Table EMRAM1):

tAbLe eMr AM12008 (Q4) 2009 (Q4) 2010 (Q4) 2011 (Q4) 2012 (Q3)

Stage 7 0 .3% 0 .7% 1 .0% 1 .2% 1 .8%Stage 6 0 .5% 1 .6% 3 .2% 5 .2% 7 .3%Stage 5 2 .5% 3 .8% 4 .5% 8 .4% 12 .0%Stage 4 2 .5% 7 .4% 10 .5% 13 .2% 14 .2%Stage 3 35 .7% 50 .9% 49 .0% 44 .9% 41 .3%Stage 2 31 .4% 16 .9% 14 .6% 12 .4% 11 .2%Stage 1 11 .5% 7 .2% 7 .1% 5 .7% 4 .8%Stage 0 15 .6% 11 .5% 11 .5% 9 .0% 7 .4%N 5,168 5,235 5,281 5,337 5,319

A more comprehensive evaluation of the U.S. hospital EMRAM model is presented in the HIMSS Analytics’ Essentials of the U.S. Hospital IT Market quarterly reports.

It is also worth noting that in 2012, seven critical access hospitals (all with 25 and under bed size and all part of an integrated delivery system) have attained Stage 7 status. Additionally, a free standing hospital with 82 beds also achieved Stage 7. This clearly demonstrates that achieving Stage 7 of the EMRAM model is not exclusively the purview of large hospitals.

An evaluation of U.S. hospitals by type, bed size and region (see Table EMRAM2) with 2012 data shows that:• Among all hospital types, academic medical centers had the

highest mean and median EMRAM scores; this hospital segment is also the only group that has both a median and mean score of 4.000. This is followed by general medical/surgical and urban hospitals. This is unchanged from previous Annual Reports.

• A positive correlation continues between larger bed hospitals and high EMRAM average and median scores. Hospitals in both the 501 to 600 bed segment and the over 600 bed segment categories have achieved both a median and average score of at least four. Hospitals with fewer than 100 beds have the lowest mean and median scores.

• The New England region had the highest mean and median score by region, as also reported in previous years. New England is also the only region to have both a median and mean score of four. The Mountain and West South Central regions have hospitals with the lowest average and median scores. The East South Central region is the only region that does not have a hospital that has achieved Stage 7.

tAbLe eMr AM2segment Mean Min Max Median NumberHospital type segmentAcademic/Teaching 4 .5386 0 .3870 7 .0710 4 .3270 207Non-Academic 3 .4372 0 .0000 7 .0710 3 .3670 5,112General Medical/Surgical 3 .7575 0 .0000 7 .0710 3 .4300 3,177Others (Non-General Medical/Surgical) 3 .0686 0 .0000 7 .0710 3 .2225 2,142Rural 2 .8370 0 .0000 7 .0710 3 .1990 1,193Urban 3 .6660 0 .0000 7 .0710 3 .4150 4,126IDS 3 .5982 0 .0000 7 .0710 3 .3900 3,387Independent Hospital 3 .2731 0 .0000 7 .0710 3 .3640 1,932Critical Access 2 .8503 0 .0000 7 .0390 3 .2100 1,333bed segment0–100 Beds 3 .0229 0 .0000 7 .0710 3 .2220 2,779101–200 Beds 3 .6841 0 .0000 7 .0710 3 .4140 970201–300 Beds 4 .0363 0 .0000 7 .0710 3 .4620 613301–400 Beds 4 .0817 0 .0810 7 .0710 3 .4620 400401–500 Beds 4 .1525 2 .0540 7 .0710 3 .5340 222501–600 Beds 4 .4725 2 .1700 7 .0710 4 .3160 144Over 600 beds 4 .5214 2 .1020 7 .0710 4 .3000 191regions (u.s. census defined)East North Central 3 .7730 0 .0000 7 .0710 3 .4380 843East South Central 3 .1427 0 .0000 6 .0710 3 .3340 447Middle Atlantic 3 .6997 0 .0050 7 .0390 3 .4150 481Mountain 3 .0790 0 .0000 7 .0630 3 .2670 421New England 4 .3040 0 .2400 7 .0630 4 .2310 199Pacific 3 .6038 0 .0000 7 .0710 3 .3680 583South Atlantic 3 .6680 0 .0000 7 .0710 3 .4225 790West North Central 3 .4461 0 .0000 7 .0710 3 .4150 713West South Central 3 .0203 0 .0000 7 .0390 3 .2310 839All Hospitalstotal 3.4801 0.0000 7.0710 3.3830 5,319

region Key for states:New England . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .MA, ME, VT, RI, CT, NH Middle Atlantic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .NY, NJ, PA South Atlantic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .MD, DE, DC, WV, VA, NC, SC, GA, FL East North Central . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MI, OH, IN, IL, WI East South Central . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . KY, TN, MS, AL West North Central . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MN, IA, MO, KS, ND, SD, NE West South Central . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TX, LA, AR, OK Mountain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ID, CO, WY, MT, NV, UT, AZ, NM Pacific . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . WA, CA, OR, AK, HI


▶ The EMR Adoption ModelSM: Measuring Clinical IT Transformation continued

An analysis of the EMRAM scores by individual U.S. state shows that seven states (Rhode Island, Vermont, Maine, Minnesota, Connecticut, Massachusetts and Iowa) have median scores above 4.0000. Montana and District of Columbia have median EMRAM scores below 3, the lowest reported (see Table EMR3).

tAbLe eMr AM3State Mean Min Max Median NumberRhode Island 4 .7805 0 .3870 6 .0710 6 .0320 11Vermont 4 .9062 3 .4160 6 .0710 5 .1100 14Maine 4 .5703 3 .2070 6 .0710 4 .3140 37Minnesota 4 .1482 0 .0000 7 .0710 4 .2690 136Connecticut 4 .2186 1 .0790 6 .0710 4 .2300 33Massachusetts 4 .3003 0 .2400 7 .0630 4 .2160 78Iowa 3 .9563 0 .0050 7 .0710 4 .0230 121Delaware 4 .3137 2 .6370 7 .0470 3 .6200 9Virginia 4 .3354 2 .0390 7 .0710 3 .5400 83Maryland 4 .1783 0 .0810 6 .0710 3 .5180 48Illinois 3 .9257 0 .0450 7 .0710 3 .4700 197Wisconsin 3 .9177 0 .0550 7 .0710 3 .4700 137Washington 3 .7755 0 .0000 6 .0710 3 .4540 94New Jersey 3 .7200 0 .1900 6 .0710 3 .4465 84Michigan 3 .9086 0 .0050 6 .0710 3 .4395 160Indiana 3 .6542 0 .0000 7 .0550 3 .4380 143Missouri 3 .7895 0 .0250 7 .0550 3 .4310 132Alaska 3 .7316 0 .0050 6 .0710 3 .4310 17Colorado 3 .3341 0 .0150 7 .0470 3 .4300 84North Carolina 3 .5571 0 .0100 6 .0710 3 .4220 121Alabama 3 .2861 0 .0000 5 .1640 3 .4220 98Georgia 3 .4860 0 .0000 6 .0710 3 .4215 158Florida 3 .6388 0 .0640 7 .0710 3 .4175 240Pennsylvania 3 .7130 0 .0050 7 .0390 3 .4160 195Oregon 3 .7692 0 .0420 7 .0230 3 .4150 61South Carolina 3 .5681 0 .2400 6 .0710 3 .4150 71Utah 3 .0502 0 .0000 5 .1180 3 .3830 49South Dakota 3 .3348 0 .0000 6 .0710 3 .3740 53Idaho 3 .1915 0 .0000 6 .0560 3 .3580 43Tennessee 3 .2744 0 .0000 6 .0710 3 .3510 140New York 3 .6785 0 .0850 6 .0710 3 .3500 202Ohio 3 .5077 0 .0000 7 .0710 3 .3420 206Hawaii 3 .0211 0 .0050 7 .0470 3 .3420 23Kentucky 3 .2623 0 .0480 6 .0710 3 .3300 107New Hampshire 3 .5188 2 .0860 6 .0470 3 .3260 26West Virginia 3 .2907 0 .0700 6 .0630 3 .3175 50California 3 .5652 0 .0000 7 .0710 3 .3085 388Nebraska 3 .0087 0 .0100 7 .0080 3 .2900 87Arizona 3 .6851 0 .0610 7 .0630 3 .2820 82New Mexico 3 .0383 0 .0000 6 .0310 3 .2800 38Texas 3 .1401 0 .0000 7 .0390 3 .2570 486Louisiana 2 .8118 0 .0180 6 .0710 3 .2270 147Oklahoma 2 .8168 0 .0000 6 .0710 3 .2150 121Arkansas 2 .9856 0 .0350 6 .0710 3 .2060 85Nevada 2 .5724 0 .0000 7 .0160 3 .1700 42Mississippi 2 .6988 0 .0000 6 .0710 3 .1665 102Wyoming 3 .1957 0 .0200 7 .0390 3 .1620 27Kansas 2 .5744 0 .0000 6 .0480 3 .1540 139North Dakota 2 .6142 0 .0250 6 .0710 3 .0900 45District of Columbia 2 .6105 1 .0000 4 .2920 2 .6305 10Montana 2 .0988 0 .0000 6 .0310 2 .1670 56

For additional information about EMRAM, go to the link shown below:

http://www.himssanalytics.org/emram/index.aspx

The first incentive payments were issued in May 2011, for Meaningful Use Stage 1 achievement measured in late 2010. Data that compares the growth of EMR adoption over the five quarters that followed showed an admirable growth in EMRAM Stages 5 and 6 of more than 80 percent with more than 66 percent in Stage 7. Concomitantly, there was a 16 percent to 27 percent decrease in Stages 0, 1 and 2, the lower, elementary stages of the EMRAM. We believe this indicates that the incentive program is clearly working to motivate hospitals to invest in healthcare IT to improve quality and safety while earning incentive payments. However, while the rate of progress is commendable and vital to the long-term “health” of health care, much more work remains to be accomplished if the government’s goal of 70 percent of the U.S. healthcare providers is to achieve meaningful criteria by the end of 2015 (see Figure EMRAM2).

Stage 7 Complete EMR; CCD transactions to share data; Data 1.1% 1.8% warehousing; Data continuity with ED, ambulatory, OP

Stage 6 Physician documentation (structured templates), 4.0% 7.3% full CDSS (variance & compliance), full R-PACS

Stage 5 Closed loop medication administration 6.1% 12.0%

Stage 4 CPOE, Clinical Decision Support (clinical protocols) 12.3% 14.2%

Stage 3 Nursing/clinical documentation (flow sheets), CDSS 46.3% 41.3% (error checking), PACS available outside Radiology

Stage 2 CDR, Controlled Medical Vocabulary, CDS, may have 13.7% 11.2% Document Imaging; HIE capable

Stage 1 Ancillaries - Lab, Rad, Pharmacy - All Installed .6% 4.8%

Stage 0 All Three Ancillaries Not Installed 10.0% 7.4%

Data from HIMSS AnalyticsTM Database ©2012 N = 5,310 N = 5,310

Stage

Figure EMRAM2: US EMR Adoption ModelSM

2012Q3

2011Q2Cumulative Capabilities


http://www.himssanalytics.org/emram/index.aspx

▶ Ambulatory (Hospital Owned/Managed) IT Environment

In 2012, HIMSS Analytics streamlined our data collection efforts in the ambulatory market to focus on applications of greatest interest to the IT vendor community. As a result, this report no longer includes data on ambulatory laboratory, pharmacy and radiology systems, and will instead just report on the following three applications: Ambulatory EMR (A-EMR), Ambulatory PACS, and Practice Management.

Of the applications tracked in the hospital-owned/managed ambulatory IT market, the A-EMR software application market reflected the most positive market penetration gains this past year (see Table AH1). It is reasonable to assume that A-EMR growth can be traced to hospitals and clinics having a better understanding of the ARRA Meaningful Use metrics released in 2010. The ambulatory PACS market penetration decreased by less than one percent this past year, while practice management growth was negligible given this market reflecting near market saturation levels (95 percent or better) in the hospital owned/managed clinic environment.

More than three-quarters of purchasing plans for practice management applications are projected to be replacement purchases (see Table AH2), whereas A-EMR and ambulatory PACS continue to primarily reflect first time purchasers.

Since the Meaningful Use definition will be introduced in three stages through 2015, and providers can qualify for the full value of the incentive if they are fully qualified before the end of 2012, it is reasonable to assume that A-EMR first time purchases will continue to increase over the next few years as the data in the following tables demonstrates.

However, if the demand continues to sustain, we remain concerned about whether the industry has the number of implementation professionals that will be required to meet the ARRA Meaningful Use measurements for 2013 and beyond.

An evaluation of the urban vs. rural and multi- vs. single hospital system ownership/management market segments of ambulatory facilities provides the following insights:• A-EMR: ambulatory facilities owned/managed by rural

hospitals demonstrated the highest growth year-over-year at more than 11 percentage points (see Table AH3). Ambulatory facilities owned/managed by a single hospital system segment demonstrated growth of approximately ten percentage points. Growth in the urban and multi-hospital owned/managed segments was between five and seven percentage points.

• Ambulatory PACS: the rural market segment for ambulatory facilities showed the highest growth rates, at just less than one percentage point. Single hospital system owned/managed ambulatory facilities had the largest market penetration decrease of nearly three percentage points (see Table AH4).

tAbLe AH3 | Ambulatory eMr2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountRural 1,093 50 .70% 2,156 1,233 57 .19% 2,156 1,483 68 .78% 2,156Urban 10,180 58 .19% 17,493 11,088 63 .39% 17,493 12,279 70 .19% 17,493Multi-Hospital System 7,562 59 .54% 12,700 8,152 64 .19% 12,700 8,885 69 .96% 12,700Single Hospital System 3,711 53 .40% 6,949 4,169 59 .99% 6,949 4,877 70 .18% 6,949All 11,273 57.37% 19,649 12,321 62.71% 19,649 13,762 70.04% 19,649

tAbLe AH4 | Ambulatory pAcs*2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountRural 108 44 .63% 242 99 40 .91% 242 101 41 .74% 242Urban 2,049 63 .65% 3,219 1,981 61 .54% 3,219 1,956 60 .76% 3,219Multi-Hospital System 1,547 64 .40% 2,402 1,462 60 .87% 2,402 1,468 61 .12% 2,402Single Hospital System 610 57 .60% 1,059 618 58 .36% 1,059 589 55 .62% 1,059All 2,157 62.32% 3,461 2,080 60.10% 3,461 2,057 59.43% 3,461* Only includes ambulatory facilities doing imaging on site

tAbLe AH5 | practice Management2010 2011 2012

TypeSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountSegment

Count PercentTotal

CountRural 2,033 94 .29% 2,156 2,051 95 .13% 2,156 2,052 95 .18% 2,156Urban 16,951 96 .90% 17,493 17,088 97 .68% 17,493 17,093 97 .71% 17,493Multi-Hospital System 12,337 97 .14% 12,700 12,437 97 .93% 12,700 12,403 97 .66% 12,700Single Hospital System 6,647 95 .65% 6,949 6,702 96 .45% 6,949 6,742 97 .02% 6,949All 18,984 96.62% 19,649 19,139 97.40% 19,649 19,145 97.43% 19,649

tAbLe AH1 | Ambulatory N = 19,649 2010 2011 2012Ambulatory EMR 57 .37% 62 .71% 70 .04%Ambulatory PACS* 62 .32% 60 .10% 59 .43%Practice Management 96 .62% 97 .40% 97 .43%Percentages include installed, contracted or installation in process*N = 3,461 only includes ambulatory facilities that offer on-site imaging

tAbLe AH2 | 2012# of Hospitals with Installed





for the First Time



Hospitals PlanningAmbulatory EMR 85 23 .04% 284 76 .96% 369Ambulatory PACS 1 11 .11% 8 88 .89% 9Practice Management 119 78 .81% 32 21 .19% 151Replacing = Statuses of live and operational, contracted/not yet installed and installation in processFirst time = Status of not automated


▶ Ambulatory (Hospital Owned/Managed) IT Environment continued

• Practice management: market penetration for practice management is over 95 percent in all segments. Growth for all segments was less than one percentage point (see Table AH5).

More than three-quarters of the contracts for A-EMR were signed between 2005 and 2012. Nearly 80 percent of ambulatory PACS contracts were signed between 2000 and 2009 (see Table AH6). More than half of the contract activity for practice management solutions occurred in 2004 or prior. The applications contracted before 2000 may be entering a stage when the hospitals begin to evaluate them for replacement.

The impending deadline for conversion to ICD-10 diagnostic coding will require a major upgrade to these legacy practice management applications. The one year extension of the ICD-10 implementation was welcomed by the physician community as this was the market segment that needed more time to adapt to the new coding requirement. In our view, the next two years will see an increase in purchasing activity for updating practice management among these facilities.

tAbLe AH9# for Contract

RangeTotal


RespondingAmbulatory eMrPrior to 1990 0 6,939 0 .00%1990 to 1994 42 6,939 0 .61%1995 to 1999 216 6,939 3 .11%2000 to 2004 1,321 6,939 19 .04%2005 to 2009 3,477 6,939 50 .11%2010 to 2012 1,883 6,939 27 .14%total 6,939 6,939 100.00%Ambulatory pAcs*Prior to 1990 0 488 0 .00%1990 to 1994 0 488 0 .00%1995 to 1999 14 488 2 .87%2000 to 2004 163 488 33 .40%2005 to 2009 224 488 45 .90%2010 to 2012 87 488 17 .83%total 488 488 100.00%practice ManagementPrior to 1990 129 10,071 1 .28%1990 to 1994 455 10,071 4 .52%1995 to 1999 1,521 10,071 15 .10%2000 to 2004 3,253 10,071 32 .30%2005 to 2009 2,972 10,071 29 .51%2010 to 2012 1,741 10,071 17 .29%total 10,071 10,071 100.00%* Based on ambulatory facilities doing imaging on site

Market drivers/Future outlookThe hospital owned/managed ambulatory IT application market has been and will continue to be impacted through 2015 by:• The need to comply with ARRA Meaningful Use criteria to

achieve funding for A-EMR implementations or recover A-EMR investments already made.

• The need to facilitate the interoperable flow of information between the acute care and ambulatory environments, as well as with external HIE entities, which will be essential to receive Meaningful Use incentive payments beyond Stage 1.

• The need to facilitate the interoperable flow of information between the acute care and ambulatory environments for both clinical and financial applications to support a shared savings / bundled payment environment.

• The need to better track episodes of care for quality outcomes and pay for performance reimbursement models, especially for the ARRA Meaningful Use criteria, patient centered medical home and ACOs.

• Completion of practice management system upgrades in time for the ICD-10 implementation deadline.

• The likely increase use of hospital PACS systems by tethered (ambulatory facilities owned, operated and/or managed by a hospitals) ambulatory facilities and thus a decrease of free standing PACS environments.

• Growing efforts of HIE projects, and the ability to create, manage, and exchange patient summary data from all modalities of patient care.

• Access to capital by hospitals to make application purchases for their ambulatory environments (this will be easier for ambulatory facilities owned by hospitals than for stand-alone/independent clinics, which may drive further market consolidation of clinics and ambulatory services and hospitals).

• Relaxation of the Stark Laws related to hospital subsidies for ambulatory practice EMR purchases, which are set to expire in 2013.

• Ongoing activity with respect to standards adoption and government mandates to ensure interoperability will lead to frequent version upgrades of installed products.

• Usability of HIT systems that will accommodate a variety of clinical specialties in addition to primary care clinicians.

• Consumer demands for personal health information and patient safety derived from the A-EMR and the provisions of Meaningful Use Stage 2 to increase patient engagement.

• Increase in consumer demands to have emerging technologies (i.e. mobile health or mHealth) available to communicate with clinicians and manage their healthcare.

• Shortages of trained HIT professionals available to assist ambulatory clinics in meeting the implementation and reporting Meaningful Use Requirements.



the Ambulatory eMr Adoption ModelSM HIMSS Analytics launched the Ambulatory EMR Adoption ModelSM (A-EMRAM) in 2012 to monitor EMR adoption in ambulatory settings. Since there is such wide variation in ambulatory care settings, we strive to apply the A-EMRAM to the following care delivery environment: where there is a patient and care giver encounter where the care giver is licensed to asses, diagnose, document findings and impressions, generate orders and prescribe medications. This patient and care giver encounter does not necessarily have to be face to face, but it must include a care giver whose license and scope of practice includes the ability to asses, diagnose, document findings and impressions, generate orders and prescribe medications. Similar to the hospital EMRAM, this model uses an algorithm to score ambulatory facilities owned, operated and/or managed by a hospital (a.k.a. tethered facility). The A-EMRAM creates a framework for dialogue among ambulatory facilities by focusing on the systems which will provide higher levels of access, quality, efficiency and safety.

Ambulatory eMr Adoption ModelSM

The stages of the model are as follows:

stage 0: There is no EMR at all; paper charts are the only means of storing and accessing clinical information (even if there is a computerized billing system).

stage 1: Access to limited clinical information available through computers for doctors and nurses; information is from multiple data sources, no CDR functionality.

stage 2: Computers may be at point-of-care; orders and results are beginning to feed a CDR; results from outside facilities made available on-line.

stage 3: Nursing/clinical documentation charting includes vitals, nursing intake assessment, encounter procedures with clinical decision support; electronic messaging utilized; computers have replaced paper charts; Problem lists, e-prescribing utilized and all medications tracked for medication reconciliation.

stage 4: CPOE and physician documentation; discrete structured data used in EMR; electronic growth charts supported where appropriate, data shared both internally and externally.

stage 5: Online patient portal; personal health record created.

stage 6: Advanced clinical decision support is implemented which provides guidance for all clinician activities related to protocols and outcomes in the form of variance and compliance alerts; structured messaging in use for communication; proactive care management; follow-up notices sent directly to patients are initiated by flags set by provider.

stage 7: Patient data/information is easily exchanged between the inpatient, out-patient, and emergency department domains. Clinical information can be readily analyzed and reported on for quality and patient safety initiatives, and shared via standardized electronic transactions with all entities within a HIE (i.e., hospitals, other ambulatory clinics, sub-acute environments, employers, payers and patients).

scoring FormatAn Ambulatory EMR score is represented by the following format—S.nnnn, where “S” equals the current stage achieved for the model, and the “.nnnn” represents the weighted score representing the implementation of higher stage clinical applications and functions that have been implemented before the higher stage has been fully achieved. In this model all applications and functions in previous stages and the current stage must be achieved before the current stage score is achieved. For example, if an ambulatory facility uses electronic messaging for intra-office communication (Stage 3), but has not yet implemented all of the components required for an Ambulatory EMR (Stage 2), then the ambulatory facility would be scored as a Stage 2 ambulatory and the four digits after the stage designation would identify the weighted points that had been achieved for implementing intra-office electronic messaging (2.nnnn). As with the hospital EMRAM, there is a validation process for Stage 6 and Stage 7 ambulatories to confirm the facility’s capabilities.

Stage 7 HIE capable, sharing of data between the EMR and 0.00% community based EHR, business and clinical intelligence

Stage 6 Advanced clinical decision support, proactive care 0.81% management, structured messaging

Stage 5 Personal health record, online tethered patient portal 2.13%

Stage 4 CPOE, use of structured data for accessibility in EMR and 0.24% internal and external sharing of data

Stage 3 Electronic messaging, computers have replaced the paper 7.59% chart, clinical documentation and clinical decision support

Stage 2 Beginning of a CDR with orders and results, computers may 30.54% be at point-of-care, access to results from outside facilities

Stage 2 Desktop access to clinical information, unstructured data 4.29% multiple data sources, intra-o ce/informal messaging

Stage 0 Paper chart based 53.77%

Data from HIMSS AnalyticsTM Database ©2012 N = 14,872

Stage

Fig. AEMRAM1: Ambulatory EMR Adoption ModelSM

2012Q3Cumulative Capabilities

An overall profile of A-EMRAM scores by tethered U.S. ambulatory facilities for the third quarter of 2012 is shown in Figure AEMRAM1. The majority of ambulatory facilities (53.8 percent) still rely on paper based charts. Thirty (30) percent of scored ambulatories are Stage 3, showing increased use of computers for documenting care. No ambulatory site has achieved Stage 7 and less than one percent of all scored facilities have reached Stage 6. In subsequent Annual Reports, comparison between years will be made.

An evaluation of U.S. ambulatories by healthcare system type and region (see Table AEMRAM1) with 2012 data shows that:• Ambulatory facilities that are part of an IDS had the highest

mean and median A-EMRAM scores compared to facilities that are associated with single hospital organization. Nearly two-thirds of all ambulatory facilities included in this sample are part of a multi-hospital healthcare system.

• The West North Central region had the highest mean score by region. New England had the highest median score and the second highest mean score. The lowest average score is in the East South Central region. The lowest median score was seen in the East South Central and West South Central regions.



tAbLe AeMr AM1segment Mean Min Max Median NumberHospital type segmentIDS 1 .20346 0 .00000 6 .21500 0 .15500 9,427Independent Hospital 0 .98925 0 .00000 6 .17500 0 .06600 5,445regions (u.s. census defined)East North Central 1 .24456 0 .00000 6 .19500 0 .18700 3,154East South Central 0 .77785 0 .00000 5 .14000 0 .03100 713Middle Atlantic 1 .01284 0 .00000 3 .26900 0 .06400 1,947Mountain 1 .11020 0 .00000 3 .26600 1 .03200 893New England 1 .28528 0 .00000 3 .21200 1 .03500 995Pacific 1 .16493 0 .00000 6 .17500 0 .25800 1,477South Atlantic 1 .04261 0 .00000 5 .21500 0 .05400 2,344West North Central 1 .34047 0 .00000 6 .19500 1 .03200 2,183West South Central 0 .78774 0 .00000 6 .21500 0 .03100 1,166All Ambulatoriestotal 1.12503 0.00000 6.21500 0.10800 14,872

region Key for states:New England . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .MA, ME, VT, RI, CT, NH Middle Atlantic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .NY, NJ, PA South Atlantic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .MD, DE, DC, WV, VA, NC, SC, GA, FL East North Central . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MI, OH, IN, IL, WI East South Central . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . KY, TN, MS, AL West North Central . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MN, IA, MO, KS, ND, SD, NE West South Central . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TX, LA, AR, OK Mountain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ID, CO, WY, MT, NV, UT, AZ, NM Pacific . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . WA, CA, OR, AK, HI

An evaluation of the A-EMRAM scores by individual U.S. state reveals that 16 states have median scores above 2.00000. Virginia, Maine and New Hampshire have the highest median scores. The District of Columba, Minnesota and Virginia each have average scores above 2.00000, the three highest average A-EMRAM. Rhode Island has the lowest mean and median scores and is ranked 50th of all the U.S. states and District of Columbia (see Table AEMRAM2).

For additional information about A-EMRAM, go to the link shown below:

http://www.himssanalytics.org/emram/AEMRAM.aspx

The year 2011 marked the beginning of the period of payout for ARRA’s EMR adoption incentives and measures of activity during the latter half of 2010 suggest that the rate of EMR acquisition and implementation is escalating and we anticipate this trend will further accelerate in 2013. However, while the rate of progress is commendable and vital to the long-term “health” of health care, much more work remains to be accomplished if the government’s goal of 70 percent of the U.S. healthcare providers is to achieve meaningful criteria by the end of 2015.

tAbLe AeMr AM2State Mean Min Max Median NumberVirginia 2 .13581 0 .00000 5 .21500 2 .27100 432Maine 1 .68731 0 .00000 3 .11200 2 .12000 200New Hampshire 1 .61433 0 .01100 3 .21200 2 .11700 203Wisconsin 1 .58376 0 .00000 6 .19500 2 .06200 597Hawaii 1 .73169 0 .00000 3 .26600 2 .06000 29New Mexico 1 .29698 0 .00000 2 .25500 2 .05800 50Idaho 1 .49682 0 .00000 3 .17600 2 .05600 138Minnesota 2 .30576 0 .00000 6 .19500 2 .05500 502Utah 1 .94325 0 .00000 2 .07100 2 .05400 156District of Columbia 2 .60462 0 .00000 5 .14500 2 .03900 21Iowa 1 .32649 0 .00000 3 .13000 2 .03900 308Pennsylvania 1 .23048 0 .00000 3 .23600 2 .03700 932Oregon 1 .41315 0 .00000 3 .26600 2 .03200 205Ohio 1 .22700 0 .00000 5 .14000 2 .01950 617North Dakota 1 .75407 0 .00000 6 .19500 2 .01000 81Washington 1 .29264 0 .00000 4 .12700 2 .00500 370Massachusetts 1 .17901 0 .00000 3 .20600 1 .05600 383Maryland 1 .49273 0 .00000 5 .14500 1 .04900 219Nevada 1 .06246 0 .00000 2 .04900 1 .04500 59Illinois 1 .60910 0 .00000 6 .16500 1 .03500 874Connecticut 0 .81581 0 .00000 3 .14700 0 .52650 131South Dakota 1 .00295 0 .00000 3 .18600 0 .12000 223South Carolina 0 .36012 0 .00000 2 .08300 0 .08900 289Oklahoma 0 .71163 0 .00000 2 .21500 0 .08100 249California 1 .04695 0 .00000 6 .17500 0 .07600 851Indiana 0 .99505 0 .00000 2 .17400 0 .07600 438Arkansas 0 .38573 0 .00000 3 .23100 0 .07600 167Montana 0 .38526 0 .00000 2 .12300 0 .06400 82Missouri 1 .07922 0 .00000 6 .18500 0 .06300 657New York 0 .92832 0 .00000 3 .26900 0 .04800 805Wyoming 1 .05947 0 .00000 3 .13000 0 .04300 30Michigan 0 .60603 0 .00000 5 .12000 0 .04000 628Mississippi 0 .87734 0 .00000 3 .20900 0 .03900 174Vermont 0 .80876 0 .00000 3 .18400 0 .03900 68Arizona 0 .62123 0 .00000 3 .19500 0 .03900 195Colorado 0 .92707 0 .00000 3 .26600 0 .03500 183Nebraska 0 .70725 0 .00000 2 .21300 0 .03450 191Florida 0 .53492 0 .00000 3 .22000 0 .03200 342Georgia 0 .82164 0 .00000 3 .26600 0 .03100 429Kentucky 0 .79596 0 .00000 5 .14000 0 .03100 216North Carolina 0 .71442 0 .00000 3 .13000 0 .03100 493Kansas 0 .68019 0 .00000 6 .18500 0 .03100 221Tennessee 0 .88289 0 .00000 2 .23300 0 .03050 175Louisiana 1 .50221 0 .00000 6 .21500 0 .03000 157Texas 0 .74376 0 .00000 6 .19500 0 .03000 593West Virginia 0 .80465 0 .00000 2 .24600 0 .02300 80Alabama 0 .51024 0 .00000 2 .23300 0 .01800 148Alaska 0 .52082 0 .00000 2 .06000 0 .01100 22New Jersey 0 .37095 0 .00000 2 .13500 0 .01100 210Delaware 0 .14792 0 .00000 2 .13500 0 .01100 39Rhode Island 0 .02520 0 .00000 0 .05900 0 .01100 10


http://www.himssanalytics.org/emram/AEMRAM.aspx

Applications

0–100 beds 101–200 beds 201–300 beds 301–400 beds 401–500 beds 501–600 beds over 600 beds

2011 2012 2011 2012 2011 2012 2011 2012 2011 2012 2011 2012 2011 2012

% of 2,165 hospitals % of 2,165 hospitals % of 802 hospitals % of 802 hospitals % of 483 hospitals % of 483 hospitals % of 312 hospitals % of 312 hospitals % of 188 hospitals % of 188 hospitals % of 116 hospitals % of 116 hospitals % of 151 hospitals % of 151 hospitals

Abstracting 2,031 93 .81% 2,057 95 .01% 798 99 .50% 801 99 .88% 483 100 .00% 483 100 .00% 309 99 .04% 310 99 .36% 188 100 .00% 188 100 .00% 116 100 .00% 115 99 .14% 151 100 .00% 151 100 .00%

Accounts payable 2,160 99 .77% 2,160 99 .77% 802 100 .00% 802 100 .00% 483 100 .00% 483 100 .00% 312 100 .00% 312 100 .00% 188 100 .00% 188 100 .00% 115 99 .14% 115 99 .14% 151 100 .00% 151 100 .00%

Adt/registration 2,152 99 .40% 2,152 99 .40% 801 99 .88% 801 99 .88% 483 100 .00% 483 100 .00% 312 100 .00% 312 100 .00% 188 100 .00% 188 100 .00% 116 100 .00% 116 100 .00% 151 100 .00% 151 100 .00%

Anatomical pathology 734 33 .90% 819 37 .83% 607 75 .69% 625 77 .93% 437 90 .48% 441 91 .30% 286 91 .67% 294 94 .23% 173 92 .02% 174 92 .55% 113 97 .41% 114 98 .28% 148 98 .01% 148 98 .01%

bed Management 510 23 .56% 586 27 .07% 323 40 .27% 368 45 .89% 263 54 .45% 285 59 .01% 196 62 .82% 207 66 .35% 125 66 .49% 129 68 .62% 77 66 .38% 84 72 .41% 126 83 .44% 132 87 .42%

benefits Administration 1,769 81 .71% 1,803 83 .28% 779 97 .13% 782 97 .51% 475 98 .34% 475 98 .34% 308 98 .72% 309 99 .04% 186 98 .94% 186 98 .94% 114 98 .28% 114 98 .28% 147 97 .35% 148 98 .01%

blood bank 963 44 .48% 963 44 .48% 682 85 .04% 690 86 .03% 458 94 .82% 460 95 .24% 300 96 .15% 301 96 .47% 182 96 .81% 183 97 .34% 114 98 .28% 114 98 .28% 145 96 .03% 147 97 .35%

budgeting 1,597 73 .76% 1,647 76 .07% 724 90 .27% 725 90 .40% 441 91 .30% 441 91 .30% 292 93 .59% 291 93 .27% 180 95 .74% 180 95 .74% 111 95 .69% 111 95 .69% 142 94 .04% 142 94 .04%

business intelligence–Financial 694 32 .06% 789 36 .44% 408 50 .87% 443 55 .24% 255 52 .80% 278 57 .56% 183 58 .65% 195 62 .50% 110 58 .51% 120 63 .83% 75 64 .66% 77 66 .38% 96 63 .58% 103 68 .21%

cardiology–cath Lab 128 5 .91% 143 6 .61% 334 41 .65% 357 44 .51% 300 62 .11% 316 65 .42% 218 69 .87% 234 75 .00% 154 81 .91% 155 82 .45% 100 86 .21% 99 85 .34% 128 84 .77% 130 86 .09%

cardiology–ct (computerized tomography) 124 5 .73% 144 6 .65% 234 29 .18% 257 32 .04% 189 39 .13% 203 42 .03% 130 41 .67% 140 44 .87% 104 55 .32% 106 56 .38% 63 54 .31% 65 56 .03% 90 59 .60% 98 64 .90%

cardiology–echocardiology 232 10 .72% 273 12 .61% 340 42 .39% 377 47 .07% 273 56 .52% 284 58 .80% 210 67 .31% 222 71 .15% 143 76 .06% 150 79 .79% 92 79 .31% 92 79 .31% 125 82 .78% 128 84 .77%

cardiology–intravascular ultrasound 109 5 .03% 129 5 .96% 202 25 .19% 226 28 .18% 185 38 .30% 196 40 .58% 139 44 .55% 146 46 .79% 104 55 .32% 109 57 .98% 65 56 .03% 70 60 .34% 91 60 .26% 101 66 .89%

cardiology–nuclear cardiology 134 6 .19% 157 7 .25% 207 25 .81% 232 28 .93% 174 36 .02% 193 39 .96% 126 40 .38% 133 42 .63% 93 49 .47% 100 53 .19% 66 56 .90% 68 58 .62% 85 56 .29% 92 60 .93%

cardiology information system 348 16 .07% 384 17 .74% 520 64 .84% 527 65 .71% 378 78 .26% 382 79 .09% 255 81 .73% 264 84 .62% 166 88 .30% 168 89 .36% 101 87 .07% 102 87 .93% 144 95 .36% 143 94 .70%

case Mix Management 1,500 69 .28% 1,547 71 .45% 727 90 .65% 731 91 .15% 441 91 .30% 443 91 .72% 280 89 .74% 280 89 .74% 174 92 .55% 174 92 .55% 101 87 .07% 104 89 .66% 145 96 .03% 146 96 .03%

chart deficiency 1,857 85 .77% 1,908 88 .13% 791 98 .63% 796 99 .25% 481 99 .59% 482 99 .79% 312 100 .00% 312 100 .00% 188 100 .00% 188 100 .00% 116 100 .00% 115 99 .14% 151 100 .00% 151 100 .00%

chart tracking/Locator 1,824 84 .25% 1,864 86 .10% 789 98 .38% 787 98 .13% 476 98 .55% 474 98 .14% 309 99 .04% 308 98 .72% 183 97 .34% 182 96 .81% 115 99 .14% 113 97 .41% 147 97 .35% 147 97 .35%

clinical data repository 1,828 84 .43% 1,934 89 .33% 771 96 .13% 784 97 .76% 476 98 .55% 479 99 .17% 312 100 .00% 312 100 .00% 188 100 .00% 188 100 .00% 116 100 .00% 166 100 .00% 151 100 .00% 151 100 .00%

clinical decision support system (cdss) 1,763 81 .43% 1,859 85 .87% 753 93 .89% 764 95 .26% 471 97 .52% 472 97 .72% 302 96 .79% 303 97 .12% 185 98 .40% 185 98 .40% 115 99 .14% 115 99 .14% 148 98 .01% 150 99 .34%

computer Assisted coding 293 13 .53% 199 9 .19% 140 17 .46% 99 12 .34% 109 22 .57% 85 17 .60% 67 21 .47% 52 16 .67% 47 25 .00% 36 19 .15% 25 21 .55% 26 22 .41% 43 28 .48% 42 27 .81%

computerized practitioner order entry (cpoe) 1,298 59 .95% 1,578 72 .89% 536 66 .83% 623 77 .68% 376 77 .85% 414 85 .71% 253 81 .09% 270 86 .54% 157 83 .51% 167 88 .83% 99 85 .34% 106 91 .38% 139 92 .05% 146 96 .69%

contract Management 1,193 55 .10% 1,258 58 .11% 622 77 .56% 638 79 .55% 390 80 .75% 397 82 .19% 255 81 .73% 264 84 .62% 164 87 .23% 163 86 .70% 95 81 .90% 100 86 .21% 130 86 .09% 134 88 .74%

cost Accounting 1,228 56 .72% 1,265 58 .43% 615 76 .68% 627 78 .18% 408 84 .47% 407 84 .27% 273 87 .50% 272 87 .18% 170 90 .43% 170 90 .43% 109 93 .97% 109 93 .97% 141 93 .38% 140 92 .72%

credit/collections 1,889 87 .25% 1,937 89 .47% 776 96 .76% 780 97 .26% 465 96 .27% 469 97 .10% 296 94 .87% 297 95 .19% 183 97 .34% 182 96 .81% 111 95 .69% 111 95 .69% 146 96 .69% 147 97 .35%

data Warehousing/Mining–Financial 755 34 .87% 859 39 .68% 437 54 .49% 467 58 .23% 280 57 .97% 297 61 .49% 201 64 .42% 210 67 .31% 124 65 .96% 133 70 .74% 67 57 .76% 69 59 .48% 114 75 .50% 117 77 .48%

data Warehousing/Mining–clinical 581 26 .84% 682 31 .50% 363 45 .26% 399 49 .75% 249 51 .55% 271 56 .11% 170 54 .49% 179 57 .37% 99 52 .66% 111 59 .04% 58 50 .00% 65 56 .03% 112 74 .17% 120 79 .47%

dbMs 1,149 53 .07% 1,194 55 .15% 615 76 .68% 628 78 .30% 381 78 .88% 392 81 .16% 255 81 .73% 260 83 .33% 158 84 .04% 163 86 .70% 98 84 .48% 100 86 .21% 133 88 .08% 136 90 .07%

dictation 1,832 84 .62% 1,880 86 .84% 779 97 .13% 784 97 .76% 471 97 .52% 474 98 .14% 306 98 .08% 309 99 .04% 181 96 .28% 183 97 .34% 113 97 .41% 113 97 .41% 142 94 .04% 145 96 .03%

dictation with speech recognition 544 25 .13% 640 29 .56% 382 47 .63% 419 52 .24% 285 59 .01% 310 64 .18% 196 62 .82% 208 66 .67% 118 62 .77% 126 67 .02% 78 67 .24% 86 74 .14% 99 65 .56% 112 74 .17%

disaster recovery 719 33 .21% 787 36 .35% 358 44 .64% 410 51 .12% 217 44 .93% 246 50 .93% 135 43 .27% 150 48 .08% 84 44 .68% 97 51 .60% 54 46 .55% 64 55 .17% 87 57 .62% 94 62 .25%

document Management 1,335 61 .66% 1,429 66 .00% 614 76 .56% 646 80 .55% 403 83 .44% 413 85 .51% 263 84 .29% 267 85 .58% 168 89 .36% 169 89 .89% 97 83 .62% 103 88 .79% 139 92 .05% 141 93 .38%

edi-cleaninghouse vendor 1,770 81 .76% 1,842 85 .08% 699 87 .16% 717 89 .40% 422 87 .37% 432 89 .44% 281 90 .06% 285 91 .35% 162 86 .17% 166 88 .30% 104 89 .66% 106 91 .38% 139 92 .05% 144 95 .36%

electronic Forms Management 1,031 47 .62% 1,259 58 .15% 485 60 .47% 531 66 .21% 315 65 .22% 325 67 .29% 212 67 .95% 224 71 .79% 134 71 .28% 138 73 .40% 80 68 .97% 85 73 .28% 105 69 .54% 110 72 .85%

electronic Medication Administration record (eMAr) 1,544 71 .32% 1,730 79 .91% 651 81 .17% 700 87 .28% 428 88 .61% 443 91 .72% 280 89 .74% 286 91 .67% 181 96 .28% 183 97 .34% 111 95 .69% 111 95 .69% 140 92 .72% 145 96 .03%

emergency department systems 1,355 62 .59% 1,518 70 .12% 709 88 .40% 730 91 .02% 459 95 .03% 469 97 .10% 292 93 .59% 295 94 .55% 183 97 .34% 183 97 .34% 107 92 .24% 108 93 .10% 151 100 .00% 151 100 .00%

encoder 2,026 93 .58% 2,048 94 .60% 799 99 .63% 801 99 .88% 483 100 .00% 483 100 .00% 310 99 .36% 311 99 .68% 188 100 .00% 188 100 .00% 116 100 .00% 115 99 .14% 151 100 .00% 151 100 .00%

encryption 997 46 .05% 1,129 52 .15% 524 65 .34% 568 70 .82% 330 68 .32% 359 74 .33% 209 66 .99% 225 72 .12% 131 69 .68% 140 74 .47% 75 64 .66% 84 72 .41% 108 71 .52% 116 76 .82%

enterprise Master person index (eMpi) 900 41 .57% 956 44 .16% 482 60 .10% 514 64 .09% 297 61 .49% 311 64 .39% 202 64 .74% 209 66 .99% 121 64 .36% 127 67 .55% 74 63 .79% 77 66 .38% 121 80 .13% 124 82 .12%

enterprise resource planning 335 15 .47% 376 17 .37% 204 25 .44% 229 28 .55% 152 31 .47% 169 34 .99% 120 38 .46% 132 42 .31% 78 41 .49% 84 44 .68% 55 47 .41% 58 50 .00% 76 50 .33% 83 54 .97%

executive information systems 1,228 56 .72% 1,280 59 .12% 567 70 .70% 577 71 .95% 344 71 .22% 353 73 .08% 230 73 .72% 235 75 .32% 139 73 .94% 141 75 .00% 86 74 .14% 87 75 .00% 119 78 .81% 119 78 .81%

Financial Modeling 577 26 .65% 639 29 .52% 323 40 .27% 342 42 .64% 217 44 .93% 237 49 .07% 160 51 .28% 166 53 .21% 107 56 .91% 108 57 .45% 71 61 .21% 75 64 .66% 81 53 .64% 89 58 .94%

Firewall 1,346 62 .17% 1,455 67 .21% 609 75 .94% 635 79 .18% 382 79 .09% 397 82 .19% 237 75 .96% 244 78 .21% 152 80 .85% 157 83 .51% 84 72 .41% 90 77 .59% 122 80 .79% 126 83 .44%

General Ledger 2,159 99 .72% 2,159 99 .72% 802 100 .00% 802 100 .00% 483 100 .00% 483 100 .00% 312 100 .00% 312 100 .00% 188 100 .00% 188 100 .00% 115 99 .14% 115 99 .14% 151 100 .00% 151 100 .00%

infection surveillance system 432 19 .95% 571 26 .37% 252 31 .42% 317 39 .53% 200 41 .41% 241 49 .90% 128 41 .03% 156 50 .00% 91 48 .40% 102 54 .26% 53 45 .69% 65 56 .03% 89 58 .94% 105 69 .54%

in-House transcription 1,663 76 .81% 1,636 75 .57% 600 74 .81% 592 73 .82% 381 78 .88% 372 77 .02% 235 75 .32% 233 74 .68% 141 75 .00% 137 72 .87% 95 81 .90% 92 79 .31% 122 80 .79% 117 77 .48%

intensive care 746 34 .46% 816 37 .69% 538 67 .08% 568 70 .82% 360 74 .53% 385 79 .71% 220 70 .51% 227 72 .76% 143 76 .06% 150 79 .79% 99 85 .34% 101 87 .07% 133 88 .08% 138 91 .39%

interface engines 967 44 .67% 1,053 48 .64% 551 68 .70% 580 72 .32% 363 75 .16% 374 77 .43% 248 79 .49% 248 79 .49% 162 86 .17% 163 86 .70% 102 87 .93% 104 89 .66% 136 90 .07% 142 94 .04%

Laboratory–Molecular diagnostics 119 5 .50% 141 6 .51% 118 14 .71% 134 16 .71% 83 17 .18% 91 18 .84% 81 25 .96% 86 27 .56% 52 27 .66% 53 28 .19% 34 29 .31% 35 30 .17% 80 52 .98% 82 54 .30%

Laboratory–outreach services 331 15 .29% 406 18 .75% 223 27 .81% 263 32 .79% 179 37 .06% 202 41 .82% 139 44 .55% 148 47 .44% 83 44 .15% 98 52 .13% 54 46 .55% 61 52 .59% 91 60 .26% 100 66 .23%

Laboratory information system 2,094 96 .72% 2,117 97 .78% 802 100 .00% 802 100 .00% 483 100 .00% 483 100 .00% 312 100 .00% 312 100 .00% 188 100 .00% 188 100 .00% 116 100 .00% 116 100 .00% 151 100 .00% 151 100 .00%

Materials Management 2,060 95 .15% 2,077 95 .94% 799 99 .63% 799 99 .63% 483 100 .00% 482 99 .79% 312 100 .00% 312 100 .00% 188 100 .00% 188 100 .00% 116 100 .00% 116 100 .00% 151 100 .00% 151 100 .00%

Medical necessity checking content 1,072 49 .52% 1,143 52 .79% 540 67 .33% 576 71 .82% 328 67 .91% 342 70 .81% 211 67 .63% 224 71 .79% 134 71 .28% 138 73 .40% 75 64 .66% 84 72 .41% 104 68 .87% 111 73 .51%

Medication reconciliation 910 42 .03% 1,281 59 .17% 402 50 .12% 497 61 .97% 294 60 .87% 317 65 .63% 186 59 .62% 208 66 .67% 135 71 .81% 142 75 .53% 77 66 .38% 88 75 .86% 107 70 .86% 121 80 .13%

Microbiology 1,356 62 .63% 1,416 65 .40% 757 94 .39% 759 94 .64% 472 97 .72% 473 97 .93% 307 98 .40% 306 98 .08% 187 99 .47% 187 99 .47% 113 97 .41% 113 97 .41% 149 98 .68% 150 99 .34%

nurse call system 826 38 .15% 999 46 .14% 426 53 .12% 478 59 .60% 285 59 .01% 310 64 .18% 168 53 .85% 189 60 .58% 105 55 .85% 116 61 .70% 66 56 .90% 77 66 .38% 94 62 .25% 106 70 .20%

nurse staffing/scheduling 993 45 .87% 970 44 .80% 614 76 .56% 615 76 .68% 417 86 .34% 414 85 .71% 288 92 .31% 288 92 .31% 169 89 .89% 166 88 .30% 108 93 .10% 110 94 .83% 142 94 .04% 144 95 .36%

nursing documentation 1,622 74 .92% 1,792 82 .77% 695 86 .66% 726 90 .52% 441 91 .30% 452 93 .58% 287 91 .99% 291 93 .27% 177 94 .15% 180 95 .74% 112 96 .55% 113 97 .41% 145 96 .03% 149 98 .68%

obstetrical systems (Labor and delivery) 627 28 .96% 677 31 .27% 541 67 .46% 564 70 .32% 348 72 .05% 362 74 .95% 241 77 .24% 241 77 .24% 150 79 .79% 150 79 .79% 96 82 .76% 98 84 .48% 130 86 .09% 131 86 .75%

▶ Appendix


Applications


2011 2012 2011 2012 2011 2012 2011 2012 2011 2012 2011 2012 2011 2012


Abstracting 2,031 93 .81% 2,057 95 .01% 798 99 .50% 801 99 .88% 483 100 .00% 483 100 .00% 309 99 .04% 310 99 .36% 188 100 .00% 188 100 .00% 116 100 .00% 115 99 .14% 151 100 .00% 151 100 .00%

Accounts payable 2,160 99 .77% 2,160 99 .77% 802 100 .00% 802 100 .00% 483 100 .00% 483 100 .00% 312 100 .00% 312 100 .00% 188 100 .00% 188 100 .00% 115 99 .14% 115 99 .14% 151 100 .00% 151 100 .00%

Adt/registration 2,152 99 .40% 2,152 99 .40% 801 99 .88% 801 99 .88% 483 100 .00% 483 100 .00% 312 100 .00% 312 100 .00% 188 100 .00% 188 100 .00% 116 100 .00% 116 100 .00% 151 100 .00% 151 100 .00%

Anatomical pathology 734 33 .90% 819 37 .83% 607 75 .69% 625 77 .93% 437 90 .48% 441 91 .30% 286 91 .67% 294 94 .23% 173 92 .02% 174 92 .55% 113 97 .41% 114 98 .28% 148 98 .01% 148 98 .01%

bed Management 510 23 .56% 586 27 .07% 323 40 .27% 368 45 .89% 263 54 .45% 285 59 .01% 196 62 .82% 207 66 .35% 125 66 .49% 129 68 .62% 77 66 .38% 84 72 .41% 126 83 .44% 132 87 .42%

benefits Administration 1,769 81 .71% 1,803 83 .28% 779 97 .13% 782 97 .51% 475 98 .34% 475 98 .34% 308 98 .72% 309 99 .04% 186 98 .94% 186 98 .94% 114 98 .28% 114 98 .28% 147 97 .35% 148 98 .01%

blood bank 963 44 .48% 963 44 .48% 682 85 .04% 690 86 .03% 458 94 .82% 460 95 .24% 300 96 .15% 301 96 .47% 182 96 .81% 183 97 .34% 114 98 .28% 114 98 .28% 145 96 .03% 147 97 .35%

budgeting 1,597 73 .76% 1,647 76 .07% 724 90 .27% 725 90 .40% 441 91 .30% 441 91 .30% 292 93 .59% 291 93 .27% 180 95 .74% 180 95 .74% 111 95 .69% 111 95 .69% 142 94 .04% 142 94 .04%

business intelligence–Financial 694 32 .06% 789 36 .44% 408 50 .87% 443 55 .24% 255 52 .80% 278 57 .56% 183 58 .65% 195 62 .50% 110 58 .51% 120 63 .83% 75 64 .66% 77 66 .38% 96 63 .58% 103 68 .21%

cardiology–cath Lab 128 5 .91% 143 6 .61% 334 41 .65% 357 44 .51% 300 62 .11% 316 65 .42% 218 69 .87% 234 75 .00% 154 81 .91% 155 82 .45% 100 86 .21% 99 85 .34% 128 84 .77% 130 86 .09%

cardiology–ct (computerized tomography) 124 5 .73% 144 6 .65% 234 29 .18% 257 32 .04% 189 39 .13% 203 42 .03% 130 41 .67% 140 44 .87% 104 55 .32% 106 56 .38% 63 54 .31% 65 56 .03% 90 59 .60% 98 64 .90%

cardiology–echocardiology 232 10 .72% 273 12 .61% 340 42 .39% 377 47 .07% 273 56 .52% 284 58 .80% 210 67 .31% 222 71 .15% 143 76 .06% 150 79 .79% 92 79 .31% 92 79 .31% 125 82 .78% 128 84 .77%

cardiology–intravascular ultrasound 109 5 .03% 129 5 .96% 202 25 .19% 226 28 .18% 185 38 .30% 196 40 .58% 139 44 .55% 146 46 .79% 104 55 .32% 109 57 .98% 65 56 .03% 70 60 .34% 91 60 .26% 101 66 .89%

cardiology–nuclear cardiology 134 6 .19% 157 7 .25% 207 25 .81% 232 28 .93% 174 36 .02% 193 39 .96% 126 40 .38% 133 42 .63% 93 49 .47% 100 53 .19% 66 56 .90% 68 58 .62% 85 56 .29% 92 60 .93%

cardiology information system 348 16 .07% 384 17 .74% 520 64 .84% 527 65 .71% 378 78 .26% 382 79 .09% 255 81 .73% 264 84 .62% 166 88 .30% 168 89 .36% 101 87 .07% 102 87 .93% 144 95 .36% 143 94 .70%

case Mix Management 1,500 69 .28% 1,547 71 .45% 727 90 .65% 731 91 .15% 441 91 .30% 443 91 .72% 280 89 .74% 280 89 .74% 174 92 .55% 174 92 .55% 101 87 .07% 104 89 .66% 145 96 .03% 146 96 .03%

chart deficiency 1,857 85 .77% 1,908 88 .13% 791 98 .63% 796 99 .25% 481 99 .59% 482 99 .79% 312 100 .00% 312 100 .00% 188 100 .00% 188 100 .00% 116 100 .00% 115 99 .14% 151 100 .00% 151 100 .00%

chart tracking/Locator 1,824 84 .25% 1,864 86 .10% 789 98 .38% 787 98 .13% 476 98 .55% 474 98 .14% 309 99 .04% 308 98 .72% 183 97 .34% 182 96 .81% 115 99 .14% 113 97 .41% 147 97 .35% 147 97 .35%

clinical data repository 1,828 84 .43% 1,934 89 .33% 771 96 .13% 784 97 .76% 476 98 .55% 479 99 .17% 312 100 .00% 312 100 .00% 188 100 .00% 188 100 .00% 116 100 .00% 166 100 .00% 151 100 .00% 151 100 .00%

clinical decision support system (cdss) 1,763 81 .43% 1,859 85 .87% 753 93 .89% 764 95 .26% 471 97 .52% 472 97 .72% 302 96 .79% 303 97 .12% 185 98 .40% 185 98 .40% 115 99 .14% 115 99 .14% 148 98 .01% 150 99 .34%

computer Assisted coding 293 13 .53% 199 9 .19% 140 17 .46% 99 12 .34% 109 22 .57% 85 17 .60% 67 21 .47% 52 16 .67% 47 25 .00% 36 19 .15% 25 21 .55% 26 22 .41% 43 28 .48% 42 27 .81%

computerized practitioner order entry (cpoe) 1,298 59 .95% 1,578 72 .89% 536 66 .83% 623 77 .68% 376 77 .85% 414 85 .71% 253 81 .09% 270 86 .54% 157 83 .51% 167 88 .83% 99 85 .34% 106 91 .38% 139 92 .05% 146 96 .69%

contract Management 1,193 55 .10% 1,258 58 .11% 622 77 .56% 638 79 .55% 390 80 .75% 397 82 .19% 255 81 .73% 264 84 .62% 164 87 .23% 163 86 .70% 95 81 .90% 100 86 .21% 130 86 .09% 134 88 .74%

cost Accounting 1,228 56 .72% 1,265 58 .43% 615 76 .68% 627 78 .18% 408 84 .47% 407 84 .27% 273 87 .50% 272 87 .18% 170 90 .43% 170 90 .43% 109 93 .97% 109 93 .97% 141 93 .38% 140 92 .72%

credit/collections 1,889 87 .25% 1,937 89 .47% 776 96 .76% 780 97 .26% 465 96 .27% 469 97 .10% 296 94 .87% 297 95 .19% 183 97 .34% 182 96 .81% 111 95 .69% 111 95 .69% 146 96 .69% 147 97 .35%

data Warehousing/Mining–Financial 755 34 .87% 859 39 .68% 437 54 .49% 467 58 .23% 280 57 .97% 297 61 .49% 201 64 .42% 210 67 .31% 124 65 .96% 133 70 .74% 67 57 .76% 69 59 .48% 114 75 .50% 117 77 .48%

data Warehousing/Mining–clinical 581 26 .84% 682 31 .50% 363 45 .26% 399 49 .75% 249 51 .55% 271 56 .11% 170 54 .49% 179 57 .37% 99 52 .66% 111 59 .04% 58 50 .00% 65 56 .03% 112 74 .17% 120 79 .47%

dbMs 1,149 53 .07% 1,194 55 .15% 615 76 .68% 628 78 .30% 381 78 .88% 392 81 .16% 255 81 .73% 260 83 .33% 158 84 .04% 163 86 .70% 98 84 .48% 100 86 .21% 133 88 .08% 136 90 .07%

dictation 1,832 84 .62% 1,880 86 .84% 779 97 .13% 784 97 .76% 471 97 .52% 474 98 .14% 306 98 .08% 309 99 .04% 181 96 .28% 183 97 .34% 113 97 .41% 113 97 .41% 142 94 .04% 145 96 .03%

dictation with speech recognition 544 25 .13% 640 29 .56% 382 47 .63% 419 52 .24% 285 59 .01% 310 64 .18% 196 62 .82% 208 66 .67% 118 62 .77% 126 67 .02% 78 67 .24% 86 74 .14% 99 65 .56% 112 74 .17%

disaster recovery 719 33 .21% 787 36 .35% 358 44 .64% 410 51 .12% 217 44 .93% 246 50 .93% 135 43 .27% 150 48 .08% 84 44 .68% 97 51 .60% 54 46 .55% 64 55 .17% 87 57 .62% 94 62 .25%

document Management 1,335 61 .66% 1,429 66 .00% 614 76 .56% 646 80 .55% 403 83 .44% 413 85 .51% 263 84 .29% 267 85 .58% 168 89 .36% 169 89 .89% 97 83 .62% 103 88 .79% 139 92 .05% 141 93 .38%

edi-cleaninghouse vendor 1,770 81 .76% 1,842 85 .08% 699 87 .16% 717 89 .40% 422 87 .37% 432 89 .44% 281 90 .06% 285 91 .35% 162 86 .17% 166 88 .30% 104 89 .66% 106 91 .38% 139 92 .05% 144 95 .36%

electronic Forms Management 1,031 47 .62% 1,259 58 .15% 485 60 .47% 531 66 .21% 315 65 .22% 325 67 .29% 212 67 .95% 224 71 .79% 134 71 .28% 138 73 .40% 80 68 .97% 85 73 .28% 105 69 .54% 110 72 .85%

electronic Medication Administration record (eMAr) 1,544 71 .32% 1,730 79 .91% 651 81 .17% 700 87 .28% 428 88 .61% 443 91 .72% 280 89 .74% 286 91 .67% 181 96 .28% 183 97 .34% 111 95 .69% 111 95 .69% 140 92 .72% 145 96 .03%

emergency department systems 1,355 62 .59% 1,518 70 .12% 709 88 .40% 730 91 .02% 459 95 .03% 469 97 .10% 292 93 .59% 295 94 .55% 183 97 .34% 183 97 .34% 107 92 .24% 108 93 .10% 151 100 .00% 151 100 .00%

encoder 2,026 93 .58% 2,048 94 .60% 799 99 .63% 801 99 .88% 483 100 .00% 483 100 .00% 310 99 .36% 311 99 .68% 188 100 .00% 188 100 .00% 116 100 .00% 115 99 .14% 151 100 .00% 151 100 .00%

encryption 997 46 .05% 1,129 52 .15% 524 65 .34% 568 70 .82% 330 68 .32% 359 74 .33% 209 66 .99% 225 72 .12% 131 69 .68% 140 74 .47% 75 64 .66% 84 72 .41% 108 71 .52% 116 76 .82%

enterprise Master person index (eMpi) 900 41 .57% 956 44 .16% 482 60 .10% 514 64 .09% 297 61 .49% 311 64 .39% 202 64 .74% 209 66 .99% 121 64 .36% 127 67 .55% 74 63 .79% 77 66 .38% 121 80 .13% 124 82 .12%

enterprise resource planning 335 15 .47% 376 17 .37% 204 25 .44% 229 28 .55% 152 31 .47% 169 34 .99% 120 38 .46% 132 42 .31% 78 41 .49% 84 44 .68% 55 47 .41% 58 50 .00% 76 50 .33% 83 54 .97%

executive information systems 1,228 56 .72% 1,280 59 .12% 567 70 .70% 577 71 .95% 344 71 .22% 353 73 .08% 230 73 .72% 235 75 .32% 139 73 .94% 141 75 .00% 86 74 .14% 87 75 .00% 119 78 .81% 119 78 .81%

Financial Modeling 577 26 .65% 639 29 .52% 323 40 .27% 342 42 .64% 217 44 .93% 237 49 .07% 160 51 .28% 166 53 .21% 107 56 .91% 108 57 .45% 71 61 .21% 75 64 .66% 81 53 .64% 89 58 .94%

Firewall 1,346 62 .17% 1,455 67 .21% 609 75 .94% 635 79 .18% 382 79 .09% 397 82 .19% 237 75 .96% 244 78 .21% 152 80 .85% 157 83 .51% 84 72 .41% 90 77 .59% 122 80 .79% 126 83 .44%

General Ledger 2,159 99 .72% 2,159 99 .72% 802 100 .00% 802 100 .00% 483 100 .00% 483 100 .00% 312 100 .00% 312 100 .00% 188 100 .00% 188 100 .00% 115 99 .14% 115 99 .14% 151 100 .00% 151 100 .00%

infection surveillance system 432 19 .95% 571 26 .37% 252 31 .42% 317 39 .53% 200 41 .41% 241 49 .90% 128 41 .03% 156 50 .00% 91 48 .40% 102 54 .26% 53 45 .69% 65 56 .03% 89 58 .94% 105 69 .54%

in-House transcription 1,663 76 .81% 1,636 75 .57% 600 74 .81% 592 73 .82% 381 78 .88% 372 77 .02% 235 75 .32% 233 74 .68% 141 75 .00% 137 72 .87% 95 81 .90% 92 79 .31% 122 80 .79% 117 77 .48%

intensive care 746 34 .46% 816 37 .69% 538 67 .08% 568 70 .82% 360 74 .53% 385 79 .71% 220 70 .51% 227 72 .76% 143 76 .06% 150 79 .79% 99 85 .34% 101 87 .07% 133 88 .08% 138 91 .39%

interface engines 967 44 .67% 1,053 48 .64% 551 68 .70% 580 72 .32% 363 75 .16% 374 77 .43% 248 79 .49% 248 79 .49% 162 86 .17% 163 86 .70% 102 87 .93% 104 89 .66% 136 90 .07% 142 94 .04%

Laboratory–Molecular diagnostics 119 5 .50% 141 6 .51% 118 14 .71% 134 16 .71% 83 17 .18% 91 18 .84% 81 25 .96% 86 27 .56% 52 27 .66% 53 28 .19% 34 29 .31% 35 30 .17% 80 52 .98% 82 54 .30%

Laboratory–outreach services 331 15 .29% 406 18 .75% 223 27 .81% 263 32 .79% 179 37 .06% 202 41 .82% 139 44 .55% 148 47 .44% 83 44 .15% 98 52 .13% 54 46 .55% 61 52 .59% 91 60 .26% 100 66 .23%

Laboratory information system 2,094 96 .72% 2,117 97 .78% 802 100 .00% 802 100 .00% 483 100 .00% 483 100 .00% 312 100 .00% 312 100 .00% 188 100 .00% 188 100 .00% 116 100 .00% 116 100 .00% 151 100 .00% 151 100 .00%

Materials Management 2,060 95 .15% 2,077 95 .94% 799 99 .63% 799 99 .63% 483 100 .00% 482 99 .79% 312 100 .00% 312 100 .00% 188 100 .00% 188 100 .00% 116 100 .00% 116 100 .00% 151 100 .00% 151 100 .00%

Medical necessity checking content 1,072 49 .52% 1,143 52 .79% 540 67 .33% 576 71 .82% 328 67 .91% 342 70 .81% 211 67 .63% 224 71 .79% 134 71 .28% 138 73 .40% 75 64 .66% 84 72 .41% 104 68 .87% 111 73 .51%

Medication reconciliation 910 42 .03% 1,281 59 .17% 402 50 .12% 497 61 .97% 294 60 .87% 317 65 .63% 186 59 .62% 208 66 .67% 135 71 .81% 142 75 .53% 77 66 .38% 88 75 .86% 107 70 .86% 121 80 .13%

Microbiology 1,356 62 .63% 1,416 65 .40% 757 94 .39% 759 94 .64% 472 97 .72% 473 97 .93% 307 98 .40% 306 98 .08% 187 99 .47% 187 99 .47% 113 97 .41% 113 97 .41% 149 98 .68% 150 99 .34%

nurse call system 826 38 .15% 999 46 .14% 426 53 .12% 478 59 .60% 285 59 .01% 310 64 .18% 168 53 .85% 189 60 .58% 105 55 .85% 116 61 .70% 66 56 .90% 77 66 .38% 94 62 .25% 106 70 .20%

nurse staffing/scheduling 993 45 .87% 970 44 .80% 614 76 .56% 615 76 .68% 417 86 .34% 414 85 .71% 288 92 .31% 288 92 .31% 169 89 .89% 166 88 .30% 108 93 .10% 110 94 .83% 142 94 .04% 144 95 .36%

nursing documentation 1,622 74 .92% 1,792 82 .77% 695 86 .66% 726 90 .52% 441 91 .30% 452 93 .58% 287 91 .99% 291 93 .27% 177 94 .15% 180 95 .74% 112 96 .55% 113 97 .41% 145 96 .03% 149 98 .68%

obstetrical systems (Labor and delivery) 627 28 .96% 677 31 .27% 541 67 .46% 564 70 .32% 348 72 .05% 362 74 .95% 241 77 .24% 241 77 .24% 150 79 .79% 150 79 .79% 96 82 .76% 98 84 .48% 130 86 .09% 131 86 .75%


Applications


2011 2012 2011 2012 2011 2012 2011 2012 2011 2012 2011 2012 2011 2012


operating room (surgery)–post-operative 987 45 .59% 1,109 51 .22% 633 78 .93% 656 81 .80% 409 84 .68% 420 86 .96% 277 88 .78% 282 90 .38% 170 90 .43% 175 93 .09% 107 92 .24% 108 93 .10% 146 96 .69% 148 98 .01%

operating room (surgery)–pre-operative 1,037 47 .90% 1,149 53 .07% 660 82 .29% 678 84 .54% 434 89 .86% 443 91 .72% 287 91 .99% 290 92 .95% 178 94 .68% 181 96 .28% 110 94 .83% 111 95 .69% 148 98 .01% 149 98 .68%

or scheduling 1,078 49 .79% 1,185 54 .73% 696 86 .78% 705 87 .91% 452 93 .58% 458 94 .82% 295 94 .55% 294 29 .23% 183 97 .34% 186 98 .94% 114 98 .28% 114 98 .28% 151 100 .00% 151 100 .00%

order entry (includes order communications) 1,928 89 .05% 1,990 91 .92% 780 97 .26% 784 97 .76% 588 98 .76% 480 99 .38% 310 99 .36% 309 99 .04% 187 99 .47% 187 99 .47% 116 100 .00% 116 100 .00% 151 100 .00% 151 100 .00%

outcomes and Quality Management 1,247 57 .60% 1,330 61 .43% 660 82 .29% 677 84 .41% 407 84 .27% 417 86 .34% 259 83 .01% 264 84 .62% 160 85 .11% 163 86 .70% 95 81 .90% 98 84 .48% 137 90 .73% 137 90 .73%

patient Acuity (formerly nurse Acuity) 474 21 .89% 548 25 .31% 286 35 .66% 290 36 .16% 196 40 .58% 203 42 .03% 124 39 .74% 130 41 .67% 91 48 .40% 92 48 .94% 51 43 .97% 53 45 .69% 73 48 .34% 77 50 .99%

patient billing 2,158 99 .68% 2,159 99 .72% 802 100 .00% 802 100 .00% 482 99 .79% 483 100 .00% 312 100 .00% 312 100 .00% 188 100 .00% 188 100 .00% 116 100 .00% 116 100 .00% 151 100 .00% 151 100 .00%

patient portal 807 37 .27% 896 41 .39% 489 60 .97% 515 64 .21% 310 64 .18% 334 69 .15% 202 64 .74% 218 69 .87% 125 66 .49% 135 71 .81% 80 68 .97% 87 75 .00% 110 72 .85% 117 77 .48%

patient scheduling 2,043 94 .36% 2,066 95 .43% 794 99 .00% 797 99 .38% 480 99 .38% 482 99 .79% 311 99 .68% 311 99 .68% 188 100 .00% 188 100 .00% 116 100 .00% 116 100 .00% 151 100 .00% 151 100 .00%

payroll 2,125 98 .15% 2,134 98 .57% 800 99 .75% 800 99 .75% 482 99 .79% 482 99 .79% 312 100 .00% 312 100 .00% 188 100 .00% 188 100 .00% 116 100 .00% 116 100 .00% 151 100 .00% 151 100 .00%

personnel Management 1,762 81 .39% 1,795 82 .91% 785 97 .88% 785 97 .88% 477 98 .76% 478 98 .96% 312 100 .00% 312 100 .00% 188 100 .00% 188 100 .00% 116 100 .00% 116 100 .00% 151 100 .00% 151 100 .00%

pharmacy Management system 1,996 92 .19% 2,043 94 .36% 801 99 .88% 802 100 .00% 483 100 .00% 483 100 .00% 312 100 .00% 312 100 .00% 188 100 .00% 188 100 .00% 116 100 .00% 116 100 .00% 151 100 .00% 151 100 .00%

physician documentation 1,124 51 .92% 1,336 61 .71% 529 65 .96% 566 70 .57% 366 75 .78% 384 79 .50% 220 70 .51% 238 76 .28% 136 72 .34% 256 77 .13% 96 82 .76% 100 86 .21% 135 89 .40% 140 92 .72%

physician portal 819 37 .83% 951 43 .93% 457 56 .98% 488 60 .85% 312 64 .60% 340 70 .39% 213 68 .27% 227 72 .76% 143 76 .06% 151 80 .32% 83 71 .55% 90 77 .59% 113 74 .83% 126 83 .44%

radiology–Angiography 926 42 .77% 960 44 .34% 649 80 .92% 661 82 .42% 442 91 .51% 447 92 .55% 289 92 .63% 292 93 .59% 182 96 .81% 182 96 .81% 113 97 .41% 113 97 .41% 151 100 .00% 151 100 .00%

radiology–computed radiography (cr) 1,673 77 .27% 1,751 80 .88% 748 93 .27% 753 93 .89% 457 94 .62% 460 95 .24% 301 69 .47% 303 97 .17% 182 97 .34% 183 97 .34% 115 99 .14% 115 99 .14% 150 99 .34% 150 99 .34%

radiology–computerized tomography (ct) 1,697 78 .38% 1,760 81 .29% 749 93 .39% 755 94 .14% 469 97 .10% 472 97 .72% 304 97 .44% 305 97 .76% 186 98 .94% 186 98 .94% 115 99 .14% 115 99 .14% 151 100 .00% 151 100 .00%

radiology–digital Fluoroscopy (dF) 1,240 57 .27% 1,301 60 .09% 705 87 .91% 720 89 .78% 447 92 .55% 450 93 .17% 295 94 .55% 298 95 .51% 180 95 .74% 180 95 .74% 114 98 .28% 114 92 .28% 147 97 .35% 151 100 .00%

radiology–digital Mammography 956 44 .16% 1,087 50 .21% 558 69 .58% 592 73 .82% 343 71 .01% 396 75 .16% 236 75 .64% 252 80 .77% 147 78 .19% 150 79 .79% 95 81 .90% 101 87 .07% 128 84 .77% 131 86 .75%

radiology–digital radiography (dr) 1,355 62 .59% 1,404 64 .85% 713 88 .90% 716 89 .28% 444 91 .93% 442 91 .51% 295 94 .55% 299 95 .83% 182 96 .81% 182 96 .81% 114 98 .28% 111 95 .69% 149 98 .68% 150 99 .34%

radiology–Magnetic resonance imaging (Mri) 1,492 68 .91% 1,549 71 .55% 734 91 .52% 739 92 .14% 461 95 .45% 465 96 .27% 302 96 .79% 304 97 .44% 184 97 .87% 185 98 .40% 115 99 .14% 115 99 .14% 150 99 .34% 150 99 .34%

radiology–nuclear Medicine 1,268 58 .57% 1,318 60 .88% 729 90 .90% 733 91 .40% 459 95 .03% 462 95 .65% 299 95 .83% 302 96 .79% 183 97 .34% 184 97 .87% 113 97 .41% 113 97 .41% 147 97 .35% 147 97 .35%

radiology–orthopedic 706 32 .61% 770 35 .57% 463 57 .73% 482 60 .10% 295 61 .08% 306 63 .35% 193 61 .86% 207 66 .35% 139 73 .94% 143 76 .06% 79 68 .10% 79 68 .10% 121 80 .13% 121 80 .13%

radiology–ultrasound (us) 1,667 77 .00% 1,726 79 .72% 742 92 .52% 748 93 .27% 468 96 .89% 470 97 .31% 302 96 .79% 303 97 .12% 186 98 .94% 186 98 .94% 115 99 .14% 115 99 .14% 151 100 .00% 151 100 .00%

radiology information system 1,960 90 .53% 2,024 93 .49% 793 57 .73% 482 60 .10% 482 99 .79% 481 99 .59% 311 99 .68% 311 99 .68% 188 100 .00% 188 100 .00% 116 100 .00% 116 100 .00% 151 100 .00% 151 100 .00%

respiratory care information system 849 39 .21% 999 46 .14% 455 56 .73% 500 62 .34% 290 60 .04% 316 65 .42% 187 59 .94% 203 65 .06% 130 69 .15% 141 75 .00% 74 63 .79% 81 69 .83% 114 75 .50% 120 79 .47%

single sign-on 506 23 .37% 604 27 .90% 352 43 .89% 389 48 .50% 245 50 .72% 261 54 .04% 150 48 .08% 174 55 .77% 86 45 .74% 96 51 .06% 59 50 .86% 65 56 .03% 92 60 .93% 100 66 .23%

spam Filter/ spyware 1,244 57 .46% 1,317 60 .83% 568 70 .82% 596 74 .31% 366 75 .78% 384 79 .50% 233 74 .68% 241 77 .24% 145 77 .13% 152 80 .85% 82 70 .69% 86 74 .14% 122 80 .79% 127 84 .11%

staff scheduling 655 30 .25% 735 33 .95% 443 55 .24% 460 57 .36% 311 64 .39% 327 67 .70% 222 71 .15% 232 74 .36% 129 68 .62% 137 72 .87% 80 68 .97% 87 75 .00% 118 78 .15% 123 81 .46%

telemedicine 574 26 .51% 662 30 .58% 204 25 .44% 236 29 .43% 128 26 .50% 140 28 .99% 91 29 .17% 102 32 .69% 59 31 .38% 65 34 .57% 43 37 .07% 47 40 .52% 68 45 .03% 79 52 .32%

time and Attendance 1,953 90 .21% 1,985 91 .69% 785 97 .88% 785 97 .88% 474 98 .14% 474 98 .14% 306 98 .08% 306 98 .08% 186 98 .94% 185 98 .40% 113 97 .41% 115 99 .14% 150 99 .34% 150 99 .34%

virtualization software 671 30 .99% 790 36 .49% 348 43 .39% 414 51 .62% 239 49 .48% 265 54 .87% 160 51 .28% 175 56 .09% 103 54 .79% 113 60 .11% 58 50 .00% 71 61 .21% 91 60 .26% 102 67 .55%

next Generation rcM


2011 2012 2011 2012 2011 2012 2011 2012 2011 2012 2011 2012 2011 2012


biller’s dash board 271 12 .52% 294 13 .58% 212 26 .43% 217 27 .06% 130 26 .92% 142 29 .40% 81 25 .96% 83 26 .60% 45 23 .94% 51 27 .13% 34 29 .31% 36 31 .03% 39 25 .83% 41 27 .15%

claims Attachment rules 68 3 .14% 108 4 .99% 70 8 .73% 83 10 .35% 60 12 .42% 70 14 .49% 44 14 .10% 50 16 .03% 16 8 .51% 22 11 .70% 12 10 .34% 21 18 .10% 22 14 .57% 31 20 .53%

claims remittance updates Ar 542 25 .03% 641 29 .61% 338 42 .14% 373 46 .51% 182 37 .68% 223 46 .17% 124 39 .74% 143 45 .83% 77 40 .96% 86 45 .74% 53 45 .69% 66 56 .90% 55 36 .42% 72 47 .68%

denial rules 350 16 .17% 378 17 .46% 244 30 .42% 273 34 .04% 145 30 .02% 150 31 .06% 95 30 .45% 103 33 .01% 64 34 .04% 65 34 .57% 30 25 .86% 34 29 .31% 48 31 .79% 51 33 .77%

direct payer claims 730 33 .72% 748 34 .55% 346 43 .14% 365 45 .51% 208 43 .06% 215 44 .51% 144 46 .15% 153 49 .04% 93 49 .47% 88 46 .81% 46 39 .66% 52 44 .83% 63 41 .72% 67 44 .37%

eFt transaction 538 24 .85% 606 27 .99% 239 29 .80% 268 33 .42% 164 33 .95% 185 38 .30% 100 32 .05% 111 35 .58% 73 38 .83% 79 42 .02% 42 36 .21% 48 41 .38% 55 36 .42% 62 41 .06%

eligibility transaction with payer 581 26 .84% 650 30 .02% 256 31 .92% 288 35 .91% 160 33 .13% 183 37 .89% 101 32 .37% 114 36 .54% 75 39 .89% 81 43 .09% 42 36 .21% 49 42 .24% 63 41 .72% 69 45 .70%

eMr documentation for claims 535 24 .71% 583 26 .93% 188 23 .44% 206 25 .69% 135 27 .95% 153 31 .68% 85 27 .24% 99 31 .73% 66 35 .11% 74 39 .36% 35 30 .17% 41 35 .34% 46 30 .46% 49 32 .45%

necessity Alert @ registration 42 1 .94% 39 1 .80% 24 2 .99% 21 2 .62% 18 3 .73% 19 3 .93% 16 5 .13% 14 4 .49% 9 4 .79% 7 3 .72% 5 4 .31% 7 6 .03% 11 7 .28% 12 7 .95%

necessity Alert @ scheduling 247 11 .41% 252 11 .64% 90 11 .22% 100 12 .47% 67 13 .87% 71 14 .70% 52 16 .67% 57 18 .27% 38 20 .21% 38 20 .21% 21 18 .10% 21 18 .10% 29 19 .21% 34 22 .52%

Web preregister 329 15 .20% 349 16 .12% 122 15 .21% 132 16 .46% 89 18 .43% 95 19 .67% 58 18 .59% 67 21 .47% 48 25 .53% 49 26 .06% 25 21 .55% 25 21 .55% 37 24 .50% 40 26 .49%

Web schedule 366 16 .91% 379 17 .51% 122 15 .21% 130 16 .21% 82 16 .98% 87 18 .01% 46 14 .74% 52 16 .67% 43 22 .87% 44 23 .40% 24 20 .69% 25 21 .55% 31 20 .53% 35 23 .18%

Web self-pay 542 25 .03% 565 26 .10% 198 24 .69% 221 27 .56% 130 26 .92% 145 30 .02% 86 27 .56% 97 31 .09% 66 35 .11% 69 36 .70% 28 24 .14% 30 25 .86% 50 33 .11% 56 37 .09%

▶ Appendix continued

AMbuL Atory2011 2012

% of 19,649 Ambulatory Facilities


Ambulatory eMr 12,321 62 .71% 13,762 70 .04%

practice Management 19,139 97 .40% 19,145 97 .43%

AMbuL Atory2011 2012



Ambulatory pAcs* 2,080 60 .10% 2,057 59 .43%

*Only includes ambulatory facilities doing imaging on site


Applications


2011 2012 2011 2012 2011 2012 2011 2012 2011 2012 2011 2012 2011 2012


operating room (surgery)–post-operative 987 45 .59% 1,109 51 .22% 633 78 .93% 656 81 .80% 409 84 .68% 420 86 .96% 277 88 .78% 282 90 .38% 170 90 .43% 175 93 .09% 107 92 .24% 108 93 .10% 146 96 .69% 148 98 .01%

operating room (surgery)–pre-operative 1,037 47 .90% 1,149 53 .07% 660 82 .29% 678 84 .54% 434 89 .86% 443 91 .72% 287 91 .99% 290 92 .95% 178 94 .68% 181 96 .28% 110 94 .83% 111 95 .69% 148 98 .01% 149 98 .68%

or scheduling 1,078 49 .79% 1,185 54 .73% 696 86 .78% 705 87 .91% 452 93 .58% 458 94 .82% 295 94 .55% 294 29 .23% 183 97 .34% 186 98 .94% 114 98 .28% 114 98 .28% 151 100 .00% 151 100 .00%

order entry (includes order communications) 1,928 89 .05% 1,990 91 .92% 780 97 .26% 784 97 .76% 588 98 .76% 480 99 .38% 310 99 .36% 309 99 .04% 187 99 .47% 187 99 .47% 116 100 .00% 116 100 .00% 151 100 .00% 151 100 .00%

outcomes and Quality Management 1,247 57 .60% 1,330 61 .43% 660 82 .29% 677 84 .41% 407 84 .27% 417 86 .34% 259 83 .01% 264 84 .62% 160 85 .11% 163 86 .70% 95 81 .90% 98 84 .48% 137 90 .73% 137 90 .73%

patient Acuity (formerly nurse Acuity) 474 21 .89% 548 25 .31% 286 35 .66% 290 36 .16% 196 40 .58% 203 42 .03% 124 39 .74% 130 41 .67% 91 48 .40% 92 48 .94% 51 43 .97% 53 45 .69% 73 48 .34% 77 50 .99%

patient billing 2,158 99 .68% 2,159 99 .72% 802 100 .00% 802 100 .00% 482 99 .79% 483 100 .00% 312 100 .00% 312 100 .00% 188 100 .00% 188 100 .00% 116 100 .00% 116 100 .00% 151 100 .00% 151 100 .00%

patient portal 807 37 .27% 896 41 .39% 489 60 .97% 515 64 .21% 310 64 .18% 334 69 .15% 202 64 .74% 218 69 .87% 125 66 .49% 135 71 .81% 80 68 .97% 87 75 .00% 110 72 .85% 117 77 .48%

patient scheduling 2,043 94 .36% 2,066 95 .43% 794 99 .00% 797 99 .38% 480 99 .38% 482 99 .79% 311 99 .68% 311 99 .68% 188 100 .00% 188 100 .00% 116 100 .00% 116 100 .00% 151 100 .00% 151 100 .00%

payroll 2,125 98 .15% 2,134 98 .57% 800 99 .75% 800 99 .75% 482 99 .79% 482 99 .79% 312 100 .00% 312 100 .00% 188 100 .00% 188 100 .00% 116 100 .00% 116 100 .00% 151 100 .00% 151 100 .00%

personnel Management 1,762 81 .39% 1,795 82 .91% 785 97 .88% 785 97 .88% 477 98 .76% 478 98 .96% 312 100 .00% 312 100 .00% 188 100 .00% 188 100 .00% 116 100 .00% 116 100 .00% 151 100 .00% 151 100 .00%

pharmacy Management system 1,996 92 .19% 2,043 94 .36% 801 99 .88% 802 100 .00% 483 100 .00% 483 100 .00% 312 100 .00% 312 100 .00% 188 100 .00% 188 100 .00% 116 100 .00% 116 100 .00% 151 100 .00% 151 100 .00%

physician documentation 1,124 51 .92% 1,336 61 .71% 529 65 .96% 566 70 .57% 366 75 .78% 384 79 .50% 220 70 .51% 238 76 .28% 136 72 .34% 256 77 .13% 96 82 .76% 100 86 .21% 135 89 .40% 140 92 .72%

physician portal 819 37 .83% 951 43 .93% 457 56 .98% 488 60 .85% 312 64 .60% 340 70 .39% 213 68 .27% 227 72 .76% 143 76 .06% 151 80 .32% 83 71 .55% 90 77 .59% 113 74 .83% 126 83 .44%

radiology–Angiography 926 42 .77% 960 44 .34% 649 80 .92% 661 82 .42% 442 91 .51% 447 92 .55% 289 92 .63% 292 93 .59% 182 96 .81% 182 96 .81% 113 97 .41% 113 97 .41% 151 100 .00% 151 100 .00%

radiology–computed radiography (cr) 1,673 77 .27% 1,751 80 .88% 748 93 .27% 753 93 .89% 457 94 .62% 460 95 .24% 301 69 .47% 303 97 .17% 182 97 .34% 183 97 .34% 115 99 .14% 115 99 .14% 150 99 .34% 150 99 .34%

radiology–computerized tomography (ct) 1,697 78 .38% 1,760 81 .29% 749 93 .39% 755 94 .14% 469 97 .10% 472 97 .72% 304 97 .44% 305 97 .76% 186 98 .94% 186 98 .94% 115 99 .14% 115 99 .14% 151 100 .00% 151 100 .00%

radiology–digital Fluoroscopy (dF) 1,240 57 .27% 1,301 60 .09% 705 87 .91% 720 89 .78% 447 92 .55% 450 93 .17% 295 94 .55% 298 95 .51% 180 95 .74% 180 95 .74% 114 98 .28% 114 92 .28% 147 97 .35% 151 100 .00%

radiology–digital Mammography 956 44 .16% 1,087 50 .21% 558 69 .58% 592 73 .82% 343 71 .01% 396 75 .16% 236 75 .64% 252 80 .77% 147 78 .19% 150 79 .79% 95 81 .90% 101 87 .07% 128 84 .77% 131 86 .75%

radiology–digital radiography (dr) 1,355 62 .59% 1,404 64 .85% 713 88 .90% 716 89 .28% 444 91 .93% 442 91 .51% 295 94 .55% 299 95 .83% 182 96 .81% 182 96 .81% 114 98 .28% 111 95 .69% 149 98 .68% 150 99 .34%

radiology–Magnetic resonance imaging (Mri) 1,492 68 .91% 1,549 71 .55% 734 91 .52% 739 92 .14% 461 95 .45% 465 96 .27% 302 96 .79% 304 97 .44% 184 97 .87% 185 98 .40% 115 99 .14% 115 99 .14% 150 99 .34% 150 99 .34%

radiology–nuclear Medicine 1,268 58 .57% 1,318 60 .88% 729 90 .90% 733 91 .40% 459 95 .03% 462 95 .65% 299 95 .83% 302 96 .79% 183 97 .34% 184 97 .87% 113 97 .41% 113 97 .41% 147 97 .35% 147 97 .35%

radiology–orthopedic 706 32 .61% 770 35 .57% 463 57 .73% 482 60 .10% 295 61 .08% 306 63 .35% 193 61 .86% 207 66 .35% 139 73 .94% 143 76 .06% 79 68 .10% 79 68 .10% 121 80 .13% 121 80 .13%

radiology–ultrasound (us) 1,667 77 .00% 1,726 79 .72% 742 92 .52% 748 93 .27% 468 96 .89% 470 97 .31% 302 96 .79% 303 97 .12% 186 98 .94% 186 98 .94% 115 99 .14% 115 99 .14% 151 100 .00% 151 100 .00%

radiology information system 1,960 90 .53% 2,024 93 .49% 793 57 .73% 482 60 .10% 482 99 .79% 481 99 .59% 311 99 .68% 311 99 .68% 188 100 .00% 188 100 .00% 116 100 .00% 116 100 .00% 151 100 .00% 151 100 .00%

respiratory care information system 849 39 .21% 999 46 .14% 455 56 .73% 500 62 .34% 290 60 .04% 316 65 .42% 187 59 .94% 203 65 .06% 130 69 .15% 141 75 .00% 74 63 .79% 81 69 .83% 114 75 .50% 120 79 .47%

single sign-on 506 23 .37% 604 27 .90% 352 43 .89% 389 48 .50% 245 50 .72% 261 54 .04% 150 48 .08% 174 55 .77% 86 45 .74% 96 51 .06% 59 50 .86% 65 56 .03% 92 60 .93% 100 66 .23%

spam Filter/ spyware 1,244 57 .46% 1,317 60 .83% 568 70 .82% 596 74 .31% 366 75 .78% 384 79 .50% 233 74 .68% 241 77 .24% 145 77 .13% 152 80 .85% 82 70 .69% 86 74 .14% 122 80 .79% 127 84 .11%

staff scheduling 655 30 .25% 735 33 .95% 443 55 .24% 460 57 .36% 311 64 .39% 327 67 .70% 222 71 .15% 232 74 .36% 129 68 .62% 137 72 .87% 80 68 .97% 87 75 .00% 118 78 .15% 123 81 .46%

telemedicine 574 26 .51% 662 30 .58% 204 25 .44% 236 29 .43% 128 26 .50% 140 28 .99% 91 29 .17% 102 32 .69% 59 31 .38% 65 34 .57% 43 37 .07% 47 40 .52% 68 45 .03% 79 52 .32%

time and Attendance 1,953 90 .21% 1,985 91 .69% 785 97 .88% 785 97 .88% 474 98 .14% 474 98 .14% 306 98 .08% 306 98 .08% 186 98 .94% 185 98 .40% 113 97 .41% 115 99 .14% 150 99 .34% 150 99 .34%

virtualization software 671 30 .99% 790 36 .49% 348 43 .39% 414 51 .62% 239 49 .48% 265 54 .87% 160 51 .28% 175 56 .09% 103 54 .79% 113 60 .11% 58 50 .00% 71 61 .21% 91 60 .26% 102 67 .55%

next Generation rcM


2011 2012 2011 2012 2011 2012 2011 2012 2011 2012 2011 2012 2011 2012


biller’s dash board 271 12 .52% 294 13 .58% 212 26 .43% 217 27 .06% 130 26 .92% 142 29 .40% 81 25 .96% 83 26 .60% 45 23 .94% 51 27 .13% 34 29 .31% 36 31 .03% 39 25 .83% 41 27 .15%

claims Attachment rules 68 3 .14% 108 4 .99% 70 8 .73% 83 10 .35% 60 12 .42% 70 14 .49% 44 14 .10% 50 16 .03% 16 8 .51% 22 11 .70% 12 10 .34% 21 18 .10% 22 14 .57% 31 20 .53%

claims remittance updates Ar 542 25 .03% 641 29 .61% 338 42 .14% 373 46 .51% 182 37 .68% 223 46 .17% 124 39 .74% 143 45 .83% 77 40 .96% 86 45 .74% 53 45 .69% 66 56 .90% 55 36 .42% 72 47 .68%

denial rules 350 16 .17% 378 17 .46% 244 30 .42% 273 34 .04% 145 30 .02% 150 31 .06% 95 30 .45% 103 33 .01% 64 34 .04% 65 34 .57% 30 25 .86% 34 29 .31% 48 31 .79% 51 33 .77%

direct payer claims 730 33 .72% 748 34 .55% 346 43 .14% 365 45 .51% 208 43 .06% 215 44 .51% 144 46 .15% 153 49 .04% 93 49 .47% 88 46 .81% 46 39 .66% 52 44 .83% 63 41 .72% 67 44 .37%

eFt transaction 538 24 .85% 606 27 .99% 239 29 .80% 268 33 .42% 164 33 .95% 185 38 .30% 100 32 .05% 111 35 .58% 73 38 .83% 79 42 .02% 42 36 .21% 48 41 .38% 55 36 .42% 62 41 .06%

eligibility transaction with payer 581 26 .84% 650 30 .02% 256 31 .92% 288 35 .91% 160 33 .13% 183 37 .89% 101 32 .37% 114 36 .54% 75 39 .89% 81 43 .09% 42 36 .21% 49 42 .24% 63 41 .72% 69 45 .70%

eMr documentation for claims 535 24 .71% 583 26 .93% 188 23 .44% 206 25 .69% 135 27 .95% 153 31 .68% 85 27 .24% 99 31 .73% 66 35 .11% 74 39 .36% 35 30 .17% 41 35 .34% 46 30 .46% 49 32 .45%

necessity Alert @ registration 42 1 .94% 39 1 .80% 24 2 .99% 21 2 .62% 18 3 .73% 19 3 .93% 16 5 .13% 14 4 .49% 9 4 .79% 7 3 .72% 5 4 .31% 7 6 .03% 11 7 .28% 12 7 .95%

necessity Alert @ scheduling 247 11 .41% 252 11 .64% 90 11 .22% 100 12 .47% 67 13 .87% 71 14 .70% 52 16 .67% 57 18 .27% 38 20 .21% 38 20 .21% 21 18 .10% 21 18 .10% 29 19 .21% 34 22 .52%

Web preregister 329 15 .20% 349 16 .12% 122 15 .21% 132 16 .46% 89 18 .43% 95 19 .67% 58 18 .59% 67 21 .47% 48 25 .53% 49 26 .06% 25 21 .55% 25 21 .55% 37 24 .50% 40 26 .49%

Web schedule 366 16 .91% 379 17 .51% 122 15 .21% 130 16 .21% 82 16 .98% 87 18 .01% 46 14 .74% 52 16 .67% 43 22 .87% 44 23 .40% 24 20 .69% 25 21 .55% 31 20 .53% 35 23 .18%

Web self-pay 542 25 .03% 565 26 .10% 198 24 .69% 221 27 .56% 130 26 .92% 145 30 .02% 86 27 .56% 97 31 .09% 66 35 .11% 69 36 .70% 28 24 .14% 30 25 .86% 50 33 .11% 56 37 .09%

▶ Appendix continued

HoMe He ALtH2011 2012

% of 1,782 Home Health Facilities

% of 1,782 Home Health Facilities

Home Health Administrative 1,723 96 .69% 1,733 97 .25%

Home Health clinical 1,593 89 .39% 1,629 91 .41%

About HiMss

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2013 Annual Report of the U.S. Hospital IT Market

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