Hitect Report

HIE‐CT Evaluation Minakshi Tikoo, Ph.D. ONC Site Visit October 18, 2011 0

Connecticut’s Health Information Technology Exchange Evaluation Process: Baseline Assessments & Updates

Sponsored by: Connecticut Department of Public Health

Minakshi Tikoo, Ph.D., Director of Evaluation and Program Development, Biomedical Informatics Center, University of Connecticut Health Center, October 18, 2011


TABLE OF CONTENTS

EXECUTIVE SUMMARY .................................................................................................................................. 2

Physician Survey ........................................................................................................................................ 2

Pharmacy Survey ....................................................................................................................................... 2

Laboratory Survey ..................................................................................................................................... 3

Consumer Survey ...................................................................................................................................... 3

BACKGROUND ............................................................................................................................................... 4

Environmental Scan Submitted as Part of the Strategic and Operational Plan (September 2010) .......... 4

Evaluation Process .................................................................................................................................... 4

RESULTS ........................................................................................................................................................ 6

Survey with the DPH Advisory Committee Members (October 2010) ..................................................... 6

Key Stakeholder Interviews (May 2011‐ ongoing) .................................................................................... 8

Physician Survey (May 2011‐ ongoing) ..................................................................................................... 9

Baseline Pharmacy Survey (July 2011‐August 2011) .............................................................................. 18

Baseline Laboratory Survey (April 2011‐June 2011) ............................................................................... 26

Consumer Survey (August 2011‐ ) .......................................................................................................... 29


EXECUTIVE SUMMARY

Physician Survey 51% of the physicians practice in a single‐specialty group practice.

46% of the physicians practice at one site.

54% have a lot of experience using computers.

75% of the physicians have good internet access via T‐1, broadband cable, or broadband digital lines, though 18% stated that their organization needed additional high speed internet access.

62% practice in an office‐based outpatient setting and 21% practice in a hospital setting.

48% practice in an urban setting.

82% of physicians stated that their CIS captured patient demographics.

59% of physicians stated that their CIS was capable of e‐prescribing.

Of those that had access to an e‐prescribing system, 79% were sending prescriptions electronically.

46% of physicians stated that their CIS was capable of ordering labs.

70% of physicians stated that their CIS was capable of viewing labs.

38% of physicians stated that their CIS was capable of ordering radiology tests.

70% of physicians stated that their CIS was capable of viewing images.

48% of physicians stated that their CIS captured medication lists.

24% of physicians stated that their CIS was capable of sending them reminders for guideline‐based interventions and screening.

Most physicians believe that EHRs have had a positive impact on their practice in the areas of quality of decision‐making (51%); communication with other providers (71%); filling prescriptions (65%); timely access to medical records (89%); and avoiding medication errors (61%). They believe that EHRs have had no impact on communication with patients (49%); delivery of preventive care (49%); and delivery of chronic care (46%).

Pharmacy Survey 58.3% of the pharmacies were independent.

42% of the pharmacies estimated between 16‐50% adoption of e‐prescribing in the area.

57% of the pharmacies were dispensing between 101‐300 prescriptions daily.

78% of the pharmacies were enabled for e‐prescribing.

72% were using standards outlined in the HHS Final Rule.

33% were using the NCPDP codes for communication, while 48% did not know what terminology was being used.

90% of the pharmacies were using electronic transactions for filling new prescriptions; 80% for filling renewed prescriptions; and 50% for notifying the prescriber.

93% of the pharmacies receive prescriptions via fax; 90% of the pharmacies receive prescriptions over the phone; 80% receive requests on paper; and 72% of the requests used the e‐prescription system.

57% were paying a transaction fees to receive e‐prescriptions.

68% were not familiar with the Connecticut Health Information Exchange.

Most pharmacies believed that e‐prescribing had a positive impact on efficiency (82%), patient safety (80%), patient‐centered care (63%), effectiveness (75%), equal access to care (53%), and timeliness of care delivery (70%).


Laboratory Survey 14 of the 24 hospitals’ laboratories completed our survey.

Fourteen hospital laboratories use CPT codes, one uses LOINC®, and one mentioned other terminology used to code and communicate data. Fourteen hospitals responded that their laboratory systems were HL7‐compatible, but none of them could identify the version of HL7 in use.

When asked about with whom they exchanged data, these hospitals mentioned physicians (14), independent clinical pharmacies (12), physician office laboratories (5), hospital laboratories (4), blood bank laboratories (3), public health laboratories (3), insurance companies (3), no one (2), patients (2), Personal Health Record (2), and electronic health exchange (1).

Consumer Survey 33 randomly selected people have responded to our telephone survey.

51% report completing a college degree.

67% report being in good health and 30% report having a chronic condition.

Most (88%) people had seen a doctor at least once in the prior year.

85% were satisfied with the care that they received from their physician.

55% supported the opt‐in model.

48% were in favor of NHIN, while 45% were opposed to the idea.

39% did not know what an electronic health information exchange is and 82% had not heard about CT‐HITE.

67% agreed that adopting Health IT would improve quality of care; 61% agreed that it could improve doctor‐patient relationship; 64% thought it would reduce medical errors; and 64% agreed that it could reduce repeated tests and procedures.

76% had looked for medical information on the internet.


BACKGROUND

Environmental Scan Submitted as Part of the Strategic and Operational Plan (September 2010) In September 2010 the Office of the National Coordinator approved the Strategic and Operation Plan that was submitted by the Connecticut Department of Public Health under the State Health Information Exchange Cooperative Agreement Program. In that document, the following baselines were established based on the limited information that was available about Health Information Technology (HIT) adoption among hospitals and physicians practices.

Hospitals and Health Systems o Many of the 32 hospitals in Connecticut have sufficient information technology

adoption to support HIE activities in the State. 100% of responding hospitals (14 of 14) have functional EHRs in place, or were in the process of implementing one.

Provider Practices o Provider HIT adoption is fractured in Connecticut. In 2008, nearly 80% of practices had

electronic billing systems, while only 26% had an EHR. o Nationally, adoption is heavily skewed towards larger practices. Large practices have

three times more adoption in any EHR system, and seven times more adoption in fully functional systems.

o Small practices’ adoption of fully functional systems is not expected to reach 15% by 2015.

ePrescribing and Laboratories o In 2008, only 23% of CT physicians reported using ePrescribing, and 63% reported

having Electronic Labs functionality in their practice.

Government Agencies o Agencies have a large number of HIE systems existing partially in “silos”:

DPH has 55 different databases that have been identified. DSS has a portal for a single point of access to several different systems.

Evaluation Process The Connecticut Department of Public Health contracted with the University of Connecticut Health Center (UCHC) to evaluate its Health Information Technology and Exchange (HITE) Cooperative Agreement, funded by the Office of the National Coordinator (ONC). The contract period for this evaluation is 7/1/2010‐3/14/2014. This evaluation uses mixed methods, namely survey research and in‐depth interviews. A family of surveys is being undertaken to measure CT‐HITE's impact. Table 1 details the evaluation research design’s components. All studies were reviewed by the IRB at UCHC.


All survey data were collected and managed using REDCap electronic data capture tools hosted at

UCHC.1 REDCap (Research Electronic Data Capture) is a secure, web‐based application designed to

support data capture for research studies, providing: 1) an intuitive interface for validated data entry; 2) audit trails for tracking data manipulation and export procedures; 3) automated export procedures for seamless data downloads to common statistical packages; and 4) procedures for importing data from external sources.

Table 1: Data Collection Timeline Target population Implementing

State HIE Method (data collected at baseline, 12‐, 24‐months)

Timeline

Staff DPH, DSS, e‐Health CT, and the newly established state authority

The State of Connecticut received funds from Office of the national Coordinator (ONC) to design and implement a statewide HIE. It is hoped that HIE will assist in the creation of a safe and seamless health care delivery system.

Survey A baseline was conducted before the establishment of the authority. First wave of data will be collected in late October 2011.

Key stakeholder staff in‐depth interviews

Semi‐structured interviews

Started in 5/27/11 and are ongoing

Licensed Physician practices in CT

Population based survey

Physician postcard mailed 5/15/11 Baseline Physician survey 7/29/11

Licensed Pharmacy practices in CT


Baseline data collected between 7/29/11‐9/14/11

Licensed Laboratories in CT


Baseline data collected between 4/25/11‐6/10/11

Consumer survey Random sample survey

Started 8/10/11

1 Paul A. Harris, Robert Taylor, Robert Thielke, Jonathon Payne, Nathaniel Gonzalez, Jose G. Conde, Research electronic data capture (REDCap) ‐ A metadata‐driven methodology and workflow process for providing translational research informatics support, J Biomed Inform. 2009 Apr;42(2):377‐81.


RESULTS The following section presents the preliminary results based on the data collected between the period of July 2010 and September 2011.

Survey with the DPH Advisory Committee Members (October 2010) The DPH Advisory Committee was tasked with guiding and advising DPH as it embarked on the development of the Health Information Exchange Strategic Plan. This advisory body was replaced by the HITE‐CT board on October 1, 2010 as a result of the establishment of a quasi‐private‐public agency that was given charge of HITE‐CT. An advisory committee survey was developed and posted online using SurveyGizmo.com in September 2010. The link to the survey was sent out by DPH to members of the advisory committee on October 6th, 2010. Five advisory committee members out of 30 invitees responded to the survey. Limited data is being presented in this report to maintain respondents’ confidentiality due to the low number of responses. Demographics: Of the five respondents that completed the survey, four were men, most had served on the advisory committee for 11‐13 months and had missed no more than three meetings, and all were involved in some sub‐committee work. The respondents’ mean age was 52 years. Table 2: Work Accomplished by the Advisory Committee and the Sub‐committee’s

Work Accomplished by the Advisory Committee N=5 Agree Somewhat Agree

Disagree

The advisory committee accomplished a significant amount 20.0%1

80.0% 4

0.0%0

The advisory committee was well constituted 60.0%3

40.0% 2

0.0%0

There were hidden agenda(s) present within the committee 0.0%0

0.0% 0

100.0%5

The charge of the committee was clear and well‐understood 60.0%3

40.0% 2

0.0%0

There was not enough time to get things done 40.0%2

20.0% 1

40.0%2

My input was incorporated into the final strategic and operational plan submitted to the Office of the National Coordinated (ONC)

80.0% 4

20.0% 1

0.0% 0

Gartner did a good job of listening to comments and putting the Strategic and Operational plan together

60.0% 3

40.0% 2

0.0% 0

Work accomplished by Subcommittees (N=5) Agree Somewhat Agree

Disagree

The sub‐committee accomplished a significant amount 60.0%3

40.0% 2

0.0%0

The sub‐committee was well constituted 80.0%4

20.0% 1

0.0%0

Most members of the sub‐committee worked hard 40.0%2

60.0% 3

0.0%0

There were hidden agendas within the subcommittee 0.0%0

40.0% 2

60.0%3

The charge of the sub‐committee was clear and well‐understood 60.0%3

20.0% 1

20.0%1

There was not enough time to get things done 60.0% 0.0% 40.0%


3 0 2

My input was incorporated into the final strategic and operational plan submitted to the Office of the National Coordinated (ONC)

100.0% 5

0.0% 0

0.0% 0

Gartner did a good job of listening to comments and putting the Strategic and Operational plan together

80.0% 4

20.0% 1

0.0% 0

Two members were satisfied and three members were ‘neither satisfied nor dissatisfied’ with the work accomplished by the Advisory Board. Additionally, committee members identified a list of “good” things that happened as a result of creating the advisory committee.

Development of a broad strategic plan

Development of consent model

Establishment of subcommittees for meaningful discussion

Improved understanding of challenges presented by the state laws

A great deal of stakeholder participation

Securing of initial funding from ONC

Beginning the education process As part of our survey, we asked advisory committee members to list five words that came to their mind when they thought about the work that they had done as a committee. This technique is called freelisting2, and has primarily been used by anthropologists. Given the low response rate, we used freelist itself as the object of the study. The five members generated 25 words, which have been grouped using a logic model framework. We grouped words into:

1. Words defining group characteristics 2. Words defining the input (process/method) made by the group to implement HIE 3. Words defining the outputs and outcomes of the work.

Table 3: Words Defining the Work Completed by the Advisory Committee

Group Characteristics Methodology to Implement the HIE Final Products of the Work (Outputs)

Consensus Deliberate Focused (2) Hard working Measured

Network Participatory Provide content Expertise Thoughtful

Consent Exploration Design Evaluate Modeling Stakeholder view‐point

Planning Preemption Process Reality testing React to proposals Research

Steering policy Education Complete

The last question on the survey asked the advisory committee members to share their thoughts and the likely challenges for the new HITE‐CT Board. The five members of the board shared the following thoughts.

Need a strong chairperson

2 Freelisting consists of asking a small group of respondents (>30) to name words matching a given description, in our case we asked them to describe a scribe. The analysis can be used to identify domains that are based on a core set of items that are mentioned by many respondents, plus a large number of items that are mentioned by few or just one person. It is assumed that, the core set of items reflect the existence of a shared cultural norm, while the additional items represent the idiosyncratic views of individuals. Some studies use freelist as a beginning to data collection and in some it is the end. Smith, J.J. 1993. "Using ANTHROPAC 3.5 and a spreadsheet to compute a freelist salience index." Cultural

Anthropology Methodology Newsletter 5(3):1‐3.


There is an immediate need for a CEO to set direction

They need to reserve enough time and resources to accomplish tasks quickly

They need to attend all meetings

It is important to quickly develop a functioning exchange

Need to create an executive committee

There is an immediate need for sophisticated legal counsel

Don't let the perfect impede the good (i.e. "something" is better than waiting for perfection)

There is still a huge knowledge/education gap about HIE and what it really is/should be ‐ even amongst Board members

Discussion and decision‐making needs to improve

Need to determine scope of services and how they relate to eHealth CT (REC)

Funding, Transition, Hiring a CEO

Meeting attendance, long‐term participation; funding; hiring Exec. Director.

Unwillingness of Board members to express views and make decisions. FUNDING is a significant impediment. Lack of vision. Lack of State support/resources.

There is no current leader who is "devoted" to and knowledgeable about all the issues. Recruiting leadership and staff.

Developing, getting buy‐in for and establishing a sustainable business model. Meeting the timeline expected for ONC regarding having an HIE capable of supporting Meaningful Use by the 2012 timeframe required for Stage 2 ‐ so that providers can meet level 2 MU criteria

Key Stakeholder Interviews (May 2011 ongoing) Key stakeholder interviews are ongoing. The first wave of interviews with members of the established HITE‐CT Board spanned the period of May 2011‐ August 2011. Of the 16 members, nine board members agreed to be interviewed and completed interviews with us, six did not respond to our requests, and one member was unable to keep the appointment.


Physician Survey (May 2011 ongoing) Baseline Data: “According to a 2008 study3, Health Information Technology in Connecticut among providers has varying levels of adoption. Office technologies, including Practice Management Applications and Electronic Billing, are the two most utilized technologies with 63.5% and 77.5% adoption among practices, respectively. On the clinical side, Electronic Labs is the most utilized technology, with 63.0% practice adoption; however, only 26% of practices use an Electronic Medical Record (Strategic and Operational Plan, Sept. 2010).” Physician Survey: The physician survey was drafted based on a survey obtained from investigators who had previously implemented a survey of physicians regarding their adoption of health information technology (DesRoches, Campbell, Rao, Donelan, Ferris, Jha, et al., 2008)4. As this survey was based on a national sample of physicians, a modified survey containing questions specific to Connecticut was developed. This survey incorporated questions developed by investigators as well as those found in the DesRoches (2008) instrument. The survey was reviewed and approved by the University of Connecticut Health Center IRB in March of 2011. Methodology: Postcards were mailed out to 18,642 physicians to confirm valid addresses and to ask for their preferred method to receive the survey. Based on the 3,511 postcards that were returned; 2,527 surveys were either mailed or emailed to complete the baseline survey. So far we have received 613 completed surveys, resulting in a 34% response rate. The following results are based on these 613 responses. Figure 3 shows the representation of the physician responses by towns. Demographics: Age of the physicians ranged from 30‐86 years, representing a mean age of 54 years. The earliest year of starting practice after completing residency was 1960 and the most recent was 2011. Sixty‐five percent of the respondents were men and 27% were women. Seventy‐eight percent of the physicians selected white, while 8% selected Asian and 1% selected Black as their race. Most respondents (89%) were of non‐Hispanic origin. Practice Characteristics: More than half of the physicians’ practiced in a single specialty group/partnership, 20% practiced in a multi‐practice setting, and 18% were in solo practice. Forty‐six percent practiced at one site, 27% practiced at two sites, and 25% practiced in three or more sites. The number of physicians at a practice site ranged from 1‐2,500, with a mean of 20 physicians (median =4 physicians). Similarly, the patient volume had a wide range of 1‐7,500, with a mean of 214 patients (median =80 patients). Sixty‐two percent of the physicians were practicing in an office practice and outpatient setting and 21% were practicing in a hospital setting. About half of the practices were located in an urban area. Physician demographics and other practice characteristics are summarized in Table 4. The higher the number of physicians in a practice, the higher the rate of EHR implementation. EHR implementation rates by size of physician practice are presented in Figure 1.

3 Aseltine, R H., et al. Connecticut Physician Workforce Survey 2008: Final Report on Physician Perceptions and Potential Impact on Access to Medical Care. Connecticut State Medical Society, 2008. 11. 4 DesRoches, C.M., Campbell, E.G., Rao, S.R., Donelan, K., Ferris, T.G., Jha, A., Kaushal, R., Levy, D.E., Rosenbaum, S., Shields, A.E. & Blumenthal, D. (2008). Electronic health records in ambulatory care – A national survey of physicians. The New England Journal of Medicine, 359, 50‐60.


Figure 1: EHR Implementation by Size of Practice

Characteristics of Current Computerized Clinical System: Most (82%) physician practices had a computerized system for collecting patient demographics, but only 47% had problem lists, and 48% had medication lists available in an electronic format. Of the physicians that responded, 59% had an e‐prescribing system, 46% had an electronic laboratory system, and 6% had an electronic public health reporting system. Characteristics of the current computerized systems available to physicians are summarized in Table 5.

18.1%

29.7%

41.8% 41.4%

51.3%

10.2%

18.9%

13.5%

20.7%23.9%

5.5% 5.4% 4.3%6.9% 8.0%

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

Solo 2 3‐5 6‐10 11 or More

Percent of Practices

Number of Physicians in Practice

Have Implemented EHR EHR Implementation In‐Process Aquired but Have Not Implemented EHR


Figure 2: Physician Responses by Town


Table 4: Physician Demographics and Practice Characteristics

Total Respondents (N) 613 Computers and Hardware N %

Age Experience with computers

Range 30‐86 years a lot 330 54%

Mean Age (SD) 54 (12) some 227 37%

Gender N % a little 40 7%

Male 401 65% none 6 1%

Female 164 27% missing 10 2%

Missing 48 8% Type of internet access

Race No internet access 15 2%

White 481 78% Dial‐up/Broadband 11 2%

Asians 51 8% T‐1 115 19%

Blacks 8 1% Broadband cable/digital 334 54%

Other 1 ‐ Broadband ‐ satellite 14 2%

Missing 72 12% Other 33 5%

Ethnicity Missing 91 15%

Non‐Hispanic 543 89%Organization need for additional high speed internet access

Hispanic 13 2% Yes 110 18%

Missing 57 9% No 328 54%

Main Practice Site Unsure 108 18%

Single Specialty Group/Partnership 312 51% Missing 67 11%

Multi‐Specialty Group/Partnership 120 20% Practice Setting

Solo Practice 109 18% Outpatient 381 62%

Other 61 10% Hospital 130 21%

Missing 11 2% Long‐term care facility 7 1%

Number of Practice Site Outpatient ancillary 19 3%

One 283 46% Other 73 12%

Two 165 27% Prison/Jail/Correctional 3 ‐

Three or more 153 25% Practice Location

Missing 12 2% Urban 296 48%

Patient Vol. ‐ During last full week number of patient visits Rural 63 10%

Range 0‐7,500 Neither/Suburban 235 38%

Mean (SD) 214 (553) Missing 19 3%

Median 80


Table 5: Characteristics of Current Computerized Clinical System

Does your computerized clinical system collect…

Availability Use

Yes No Don't Know

Missing Do not use

Use sometimes

Use most/ all the time

NA to practice

Missing

Patient demographics 503 72 10 28 73 142 247 6 35

82% 12% 2% 5% 15% 28% 49% 1% 7%

Patient problem lists 285 295 8 25 27 55 179 2 22

46% 48% 1% 4% 9% 19% 63% 1% 8%

Orders for prescription 364 207 13 29 27 63 249 0 25

59% 34% 2% 5% 7% 17% 68% 0% 7%

If yes, are there warnings for drug interactions

290 49 21 4

80% 13% 6% 1%

Are prescriptions sent electronically?

288 59 9 8

79% 16% 2% 2%

Orders for laboratory tests 284 293 7 29 33 32 189 5 25

46% 48% 1% 5% 12% 11% 67% 2% 9%

If yes, are orders sent electronically

214 58 6 6

75% 20% 2% 2%

Orders for radiology tests 230 342 11 30 28 24 154 3 21

38% 56% 2% 5% 12% 10% 67% 1% 9%

If yes, are orders sent electronically

162 56 6 6

70% 24% 3% 3%

Viewing Lab results 427 144 4 38 12 82 293 1 39

70% 23% 1% 6% 3% 19% 69% 0% 9%

If yes, are electronic images returned

227 120 62 18

52% 28% 15%

Viewing imaging results 336 219 14 44 18 89 191 3 35

55% 36% 2% 7% 5% 26% 57% 1% 10%

If yes, are electronic images returned

191 48 61 36

57% 14% 18% 11%

Clinical Notes 315 256 5 37 9 30 244 1 31

51% 42% 1% 6% 3% 10% 77% 0% 10%

If yes, do they include medical history and follow‐up

292 15 4 4

93% 5% 1% 1%

Electronic lists of medications 298 265 11 39 5 43 212 4 34

48% 43% 2% 6% 2% 14% 71% 1% 11%

Reminders for guideline‐based interventions or screening

151 361 60 41 29 38 68 3 13

24% 56% 9% 6% 19% 25% 45% 2% 9%

Public Health Reporting 33 417 124 39 11 5 8 3 6

5% 67% 20% 6% 33% 15% 24% 9% 18%

If yes, notifiable diseases are sent electronically

11 11 9 2

33% 33% 27% 6%

Generating CCD 66 352 151 44 12 20 21 2 11

11% 57% 25% 7% 18% 30% 32% 3% 17%

Receiving CCD 40 358 168 47 11 9 13 1 6

7% 58% 27% 8% 28% 23% 33% 3% 15%

Generating CCR 52 341 173 47 13 17 13 1 8


8% 54% 28% 8% 25% 33% 25% 2% 15%

Receiving CCR 38 351 179 45 13 7 10 2 6

6% 56% 29% 7% 34% 18% 26% 5% 16%

Acquisition and Implementation of EHR System: Of the physicians that responded, 36% had an EHR, 15% were in the process of implementation, and 5% had acquired an EHR. The mean time to go live from the time of acquisition was estimated at 12 months. Of the physicians that reported using an EHR, the average length of use was 4.7 years. There were a variety of EHRs in use, with 26% using Allscripts, 9% using eClinicalWorks, 5% using Meditech, 4% using NextGen and VISTA, and 24% using unique EHR systems. Impact of EHR on clinical practice: More than half of the physicians agreed that their EHRs had a positive impact on the quality of decision making, communication between providers, filling prescriptions, and timely access to records. Sixty‐one percent of the physicians were satisfied with their EHR, but many complained about additional time of about 1‐2 hours that was being added to their day to complete documentation. Details of EHRs’ impact on practice are summarized in Table 6. Table 6: Impact of EHR on Clinical Practice

Impact of EHR on Major positive impact

Positive Impact

No impact Negative Impact

Major negative impact

NA Missing

Quality of clinical decisions 35 76 82 12 2 3 7

16% 35% 38% 6% 1% 1% 3%

Communication with other providers

49 104 48 7 1 3 5

23% 48% 22% 3% 0% 1% 2%

Communication with patients 19 68 106 7 4 8 5

9% 31% 49% 3% 2% 4% 2%

Prescription refills 84 57 39 5 2 24 6

39% 26% 18% 2% 1% 11% 3%

Timely access to medical records 111 82 9 6 1 2 6

51% 38% 4% 3% 0% 1% 3%

Avoiding medication errors 38 93 60 7 2 9 8

18% 43% 28% 3% 1% 4% 4%

Delivery of preventive care 23 51 107 1 1 29 5

11% 24% 49% 0% 0% 13% 2%

Delivery of chronic disease care 19 56 100 0 1 34 7

9% 26% 46% 0% 0% 16% 3%

Barriers and Incentives to EHR Adoption: Physicians identified financial, organizational, technological, and legal and regulatory barriers to adoption of EHRs. The leading barrier was the cost of the EHRs and the uncertainty about the return on their investments. They also believed that incentives in the same areas could potentially help in EHR adoption among physicians. A summary of their identified barriers and incentives is presented in Table 7 and 8.


Table 7: Barriers to EHR Adoption

Major Barrier

Minor Barrier

Not a Barrier

Missing

Financial Barriers 394 112 39 68

Capital needed to buy an EHR 64% 18% 6% 11%

Uncertain about ROI 304 147 77 85

49% 24% 13% 14%

Organizational Barriers 194 241 104 74

Resistance to adoption among physicians 32% 39% 17% 12%

Capacity to select, contract, install, & Implement 254 219 73 67

40% 37% 13% 10%

Concern about loss of productivity during transition 314 179 50 70

51% 29% 9% 11%

Legal or Regulatory Barriers 110 221 210 72

Concerns about inappropriate disclosure of patient info. 17% 37% 35% 11%

Concerns about illegal record tampering 98 217 226 72

16% 36% 37% 11%

Concerns about the legality of accepting an EHR that is donated from the hospital

54 166 310 83

8% 28% 50% 13%

Concerns about physicians' legal liability if patients have more access to information in their medical records

71 218 248 76

11% 36% 40% 12%

State of the Technology 334 145 56 78

Finding an EHR that meets providers' needs 55% 24% 9% 12%

Concern that the system will become obsolete 240 221 76 76

39% 36% 13% 12%

Table 8: Incentives for EHR Adoption

Major positive impact

Positive Impact

No impact

Negative Impact

Major negative impact

Missing

Financial Incentives 268 162 71 8 3 101

Incentives for EHR Adoption 44% 26% 12% 1% 0% 16%

Additional payment for use of EHR 299 130 67 7 11 99

49% 21% 11% 1% 2% 16%

Legal or Regulatory Incentives 215 198 104 5 4 87

Change the law to protect physicians from personal liability for record tampering by external parties

35% 32% 17% 1% 1% 14%

Legal liability as a result of NOT using the latest technology

112 127 111 69 105 89

18% 21% 18% 11% 17% 15%

State of the Technology 188 206 101 15 13 90

Published certification standards that indicate whether an EHR has the necessary capabilities and functions

31% 34% 16% 2% 2% 15%


Familiarity with Connecticut’s HIE initiative: Of the physicians that responded, 66% were not familiar with the HIE initiative, while 10% were somewhat familiar with the HIE initiative. Changes from baseline: Based on the data reported in the environmental scan section of the strategic and operational plan, there is one change worth mentioning. The rate of EHR implementation has increased from 26% in 2008 to 37% in 2011 (Figure 3). Figure 3: Change in EHR Implementation Between 2008 and 2011 Among Connecticut Physicians

Figure 4: Characteristics of Clinical Systems among Connecticut’s Physicians

26.0%

36.8%

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

35.0%

40.0%

2008 2011

Percent of Practices with EHR

Implemented

37%

59%

48%

46%

82%

55%

46%

38%

11%

7%

8%

6%

5%

10%

26%

23%

63%

64%

78%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90%

Secure Website

EMR

E‐script/E‐prescribing

Medication Lists

Electronic Labs

Practice Management Application/Patient …

Electronic Billing

Order for Laborator tests

Orders for Radiology

Generating CCD

Receiving CCD

Generating CCR

Receiving CCR

Public Health Reporting

2008

2011


Summary

In summary, based on the limited data available from 2008 for comparison, Connecticut’s physicians

were showing change in adoption of Health IT technologies in 2011. Based on the 2011 physician

survey, the capabilities of the clinical information systems (CIS) that are in use is as follows:

82% of physicians stated that their CIS captured patient demographics.

59% of physicians stated that their CIS was capable of e‐prescribing.

Of those that had access to an e‐prescribing system, 79% were sending prescriptions

electronically.

46% of physicians stated that their CIS was capable of ordering labs.

70% of physicians stated that their CIS was capable of viewing labs.

38% of physicians stated that their CIS was capable of ordering radiology tests.

70% of physicians stated that their CIS was capable of viewing images.

48% of physicians stated that their CIS captured medication lists.

24% of physicians stated that their CIS was capable of sending them reminders for guideline‐

based interventions and screening.


Baseline Pharmacy Survey (July 2011August 2011) The sample of active pharmacies in Connecticut (CT) was obtained from three sources: a list of Connecticut‐based pharmacies participating in SureScripts technology, an online list of pharmacies in the state of Connecticut, and a list of Connecticut pharmacies provided by the Department of Consumer Protection. This process yielded an unduplicated list of 697 pharmacies, representing 147 (21%) independent pharmacies, 12 (2%) franchise pharmacies, and 538 (77%) chain stores. Two franchises and 24 chains were represented in the universe of pharmacies. Given that one response was expected from each franchise and chain, these counts yielded a total of 174 expected responses (148 independent pharmacies, two franchises, and 24 chains). An initial survey developed by the evaluators was modified upon receiving additional information from an ONC sponsored “Pharmacy Communities of Practice.” The survey was approved by the IRB in July 2011. Sixty survey responses were received either on‐line or via a telephone interview. Of these responses, 56 (93%) were completed. Of the 147 independent pharmacies, 38 (26%) submitted complete survey responses, while two (1%) submitted incomplete responses. Of the two pharmacy franchises in the universe, both submitted a complete survey response. Of the 24 pharmacy chains in the universe, 15 (63%) submitted at least one complete survey response. One chain (4%) submitted two complete responses, while one chain (4%) submitted one complete response and one incomplete response. Table 9: Characteristics of Pharmacies Responding to Survey

Total Respondents (N) 60

Community Setting Count Percent

Urban 16 26.7%

Suburban 29 48.3%

Rural 10 16.7%

Other 2 3.3%

No Response 3 5.0%

Respondent's Title Count Percent

Clinical Pharmacist 2 3.3%

Director 3 5.0%

Manager 27 45.0%

Manager/Owner 2 3.3%

Manager/Pharmacist/Owner 1 1.7%

Managing Pharmacist 1 1.7%

Owner 6 10.0%

Owner/Pharmacist 1 1.7%

Pharmacist 9 15.0%

Staff Pharmacist 5 8.3%

No Response 3 5.0%

Self‐Reported Pharmacy Grouping Count Percent

Chain 16 26.7%

Franchise 1 1.7%


Independent 35 58.3%

Other 6 10.0%

No Response 2 3.3%

Experience with Computers Count Percent

Deep understanding 19 31.7%

Familiar with broad e‐prescribing terms/concepts 30 50.0%

Know some e‐prescribing terms/concepts 9 15.0%

Have not heard anything about e‐prescribing 0 0.0%

No Response 2 3.3%

Estimate of Prescriber Adoption of E‐Prescribing in Area Count Percent

0% 1 1.7%

1‐5% 5 8.3%

6‐15% 14 23.3%

16‐50% 25 41.7%

51‐75% 6 10.0%

76‐99% 1 1.7%

100% 1 1.7%

Unsure 5 8.3%

No Response 2 3.3%

Average Prescription Dispensing Volume Per Day Count Percent

0‐50 3 5.0%

51‐100 8 13.3%

101‐300 34 56.7%

301‐500 5 8.3%

Over 500 5 8.3%

Unsure 3 5.0%

No Response 2 3.3%

Enabled for E‐Prescribing Count Percent

Yes 47 78.3%

No 8 13.3%

Don't Know 3 5.0%

No Response 2 3.3%

Timeline for Enabling E‐Prescribing (N = 8 Pharmacies w/o E‐Prescribing) Count Percent

Within 6 months 1 12.5%

Within 1 year 1 12.5%

Within 2 years 0 0.0%

More than 2 years 0 0.0%

No plans to enable e‐prescribing 6 75.0%

Level of E‐Prescribing in Area Which Would Prompt Implementation (N = 8 Pharmacies w/o E‐Prescribing) Count Percent

0% 3 37.5%


1‐5% 1 12.5%

6‐15% 0 0.0%

16‐50% 2 25.0%

51‐75% 1 12.5%

76‐99% 0 0.0%

100% 1 12.5%

Unsure 0 0.0%

No Response 0 0.0%

Likelihood of Implementing E‐Prescribing with Technical Assistance (N = 8 Pharmacies w/o E‐Prescribing) Count Percent

Significantly Likely 1 12.5%

Somewhat Likely 1 12.5%

Neutral 2 25.0%

Somewhat Unlikely 2 25.0%

Significantly Unlikely 2 25.0%

No Response 0 0.0%

Uses Standards for E‐Prescribing (N = 47 Pharmacies w. E‐Prescribing) Count Percent

Yes 29 48.3%

No 2 3.3%

Don't Know 16 26.7%

No Response 0 0.0%

Are Standards Used Outlined in HHS Final Rule? (N = 29 Pharmacies Using E‐Prescribing Standards) Count Percent

Yes 21 72.4%

No 1 3.4%

Don't Know 7 24.1%

No Response 0 0.0%

Terminology Used to Code and Communicate Data Count Percent

CPT 3 5.0%

LOINC 0 0.0%

SNOMED 0 0.0%

RXNORM 0 0.0%

NCPDP 20 33.3%

Other 8 13.3%

Don't Know 29 48.3%

No Response 0 0.0%

Electronic Transactions Used by Pharmacy Count Percent

New prescriptions 54 90.0%

Renewal prescriptions 48 80.0%

Controlled substances 23 38.3%

Fill notifications (to prescriber) 30 50.0%

Medication history (send) 21 35.0%


Medication history (receive) 20 33.3%

Ways in Which Pharmacy Can Receive Prescriptions Count Percent

Phone 54 90.0%

Voice Mail 41 68.3%

Interactive Voice Mail 28 46.7%

Fax 56 93.3%

E‐Prescription System 43 71.7%

Paper 48 80.0%

Other 5 8.3%

Is Pharmacy's System HL7 Compatible? Count Percent

Yes 7 11.7%

No 3 5.0%

Don't Know 48 80.0%

No Response 2 3.3%

Network Used for E‐Prescription Transactions (N = 47 Pharmacies w. E‐Prescribing) Count Percent

SureScripts 33 70.2%

Emdeon 0 0.0%

Proprietary (Private) 1 2.1%

Other 4 8.5%

No Response 9 19.1%

Recipient of Transactions Via E‐Prescription Network (N = 47 Pharmacies w. E‐Prescribing) Count Percent

Health Information Exchange (HIE) 5 10.6%

Physicians, Physicians' Assistants, Nurse Practitioners 27 57.4%

Electronic Health Records (EHR or EMR) 4 8.5%

Patients 2 4.3%

Pharmacy Pays Transaction Fee to Receive E‐Prescription Transactions (N = 47 Pharmacies w. E‐Prescribing) Count Percent

Yes 27 57.4%

No 4 8.5%

Don't Know 16 34.0%

Barriers to Implementing E‐Prescribing Count Percent

Start‐up costs and converting existing data into the e‐prescribing system 17 28.3%

Maintenance costs 22 36.7%

Potential for an incomplete patient medication list 16 26.7%

Changes to existing workflow 13 21.7%

Prescription transaction fees 25 41.7%

Low prescriber activity 26 43.3%

Poor network connections in area and/or network costs 8 13.3%

Bugs in e‐prescribing process 14 23.3%

Concerns about security of patient data 6 10.0%


Concerns about privacy of patient data 8 13.3%

Other 5 8.3%

Familiarity with Connecticut Health Information Exchange Count Percent

Very familiar 1 1.7%

Somewhat familiar 9 15.0%

A little familiar 6 10.0%

Not familiar at all 41 68.3%

No Response 3 5.0%

Satisfaction with Connecticut Health Information Exchange (N = 16 Pharmacies Familiar w. CT‐HIE) Count Percent

Very dissatisfied 0 0.0%

Dissatisfied 1 6.3%

Neutral 8 50.0%

Satisfied 4 25.0%

Very satisfied 0 0.0%

No Response 3 18.8%

Will CT Be Successful in Implementing a Statewide HIE by 2014? Count Percent

Yes 8 13.3%

No 2 3.3%

Not Sure 6 10.0%

No Response 44 73.3%

Table 10: Impact of E‐Prescribing on Various Components of Practice

Very Positively

Somewhat Positively Neutral

Somewhat Negatively

Very Negatively Unsure

No Response

Efficiency 25 24 3 2 0 4 2

41.7% 40.0% 5.0% 3.3% 0.0% 6.7% 3.3%

Patient Safety 22 26 5 1 2 1 3

36.7% 43.3% 8.3% 1.7% 3.3% 1.7% 5.0%

Patient‐Centeredness 17 21 8 3 4 3 4

28.3% 35.0% 13.3% 5.0% 6.7% 5.0% 6.7%

Effectiveness 19 26 10 1 0 1 3

31.7% 43.3% 16.7% 1.7% 0.0% 1.7% 5.0%

Equity 9 23 9 2 1 13 3

15.0% 38.3% 15.0% 3.3% 1.7% 21.7% 5.0%

Timeliness 23 19 9 1 3 2 3

38.3% 31.7% 15.0% 1.7% 5.0% 3.3% 5.0%

SureScripts data: We have obtained a total of six datasets from SureScripts listing pharmacies in Connecticut. These datasets cover the years 2008 through 2011. 2010 and 2011 were each represented by two datasets; for purposes of our analysis, we used the most recent dataset for each of these years.


The total number of pharmacies listed for each year remained fairly consistent. The total only increased from 673 in 2008 to 687 in 2011. In each year, the majority of the pharmacies represented belonged to chains (e.g. CVS, Rite‐Aid, etc.). In 2008 chains accounted for 80.8% of the total pharmacies; in 2011 they accounted for 77.9% of the total. Independent pharmacies accounted for 18.1% of the total pharmacies in 2008; this increased to 21.1% of the total in 2011. A total of 7 franchise pharmacies (represented by Arrow Prescriptions and The Medicine Shoppe appeared in each dataset. These accounted for only 1.0% of the total pharmacies in both 2008 and 2011.

Each dataset contained two yes/no flags for each pharmacy. These indicated whether or not the pharmacy participated in the SureScripts network, and whether or not the pharmacy used e‐prescribing. In 2008 94.3% of the chain pharmacies were SureScripts participants; this rose to 99.3% in 2010, then dropped back to 92.7% in 2011. Only 71.4% of franchise pharmacies participated in 2008; this rose to 100% in 2009 and has remained at that level. Independent pharmacies’ participation rose from 58.2% in 2008 to 82.1% in 2011.

In 2008, 86.4% of chain pharmacies used e‐prescribing; this rose to 92.2% by 2011. Only 71.4% of franchise pharmacies used e‐prescribing in 2008; this rose to 100% in 2009 and has remained at this level. Independent pharmacies have lagged in using e‐prescribing. 57.4% used e‐prescribing in 2008, rising to 80.7% in 2011.

Figure 5: Connecticut Pharmacies in SureScripts Datasets

544 539 532 535

7 7 7 7

122 129 144 145

0

100

200

300

400

500

600

2008 2009 2010 2011

Year

Chain Franchise Independent


Figure 6: Rates of SureScripts Network Participation for Connecticut Pharmacies in SureScripts Datasets

Figure 7: Rates of E‐Prescription Usage for Connecticut Pharmacies in SureScripts Datasets

Summary

58.3% of the pharmacies were independent.

42% of the pharmacies estimated that there was between a 16‐50% e‐prescribing adoption rate in their area.

57% of the pharmacies were dispensing between 101‐300 prescriptions daily.

78% of the pharmacies were enabled for e‐prescribing.

86.4%91.7% 92.1%

92.2%

71.4%

100.0% 100.0%100.0%

57.4%

69.8%

81.9%80.7%

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

80.0%

90.0%

100.0%

2008 2009 2010 2011

Year


94.3% 98.7% 99.2% 92.7%

71.4%

100.0% 100.0%100.0%

58.2%

72.1%

81.9%82.1%

0.0%

20.0%

40.0%

60.0%

80.0%

100.0%

2008 2009 2010 2011

Year



72% were using standards outlined in the HHS Final Rule.

33% were using the NCPDP codes for communication, while 48% did not know what terminology was being used.

90% of the pharmacies were using electronic transaction for filling new prescriptions; 80% for filling renewed prescriptions; and 50% for notifying the prescriber.

93% of the pharmacies receive prescriptions via fax; 90% of the pharmacies receive prescriptions over the phone; 80% receive requests on paper; and 72% of the requests used the e‐prescription system.

57% were paying transaction fees to receive e‐prescriptions.

68% were not familiar with the Connecticut Health Information Exchange.

Most pharmacies believed that e‐prescribing had a positive impact on efficiency (82%), patient‐safety (80%), patient‐centered care (63%), effectiveness (75%), equal access to care (53%), and timeliness of care delivery (70%).


Baseline Laboratory Survey (April 2011June 2011) Contact information for potential respondents to the survey of laboratories in Connecticut was obtained from the Connecticut Hospital Association. The information provided in this list pertained to 24 hospital‐based laboratories in Connecticut with email addresses, which were used to distribute the survey. The survey was developed by investigators in October of 2010. A final version was revised and approved by the IRB in April of 2011. In late April of 2011, the first survey invitation was sent out to laboratory administrators at all 24 hospitals contained within the list. A second follow‐up attempt was made in May and a third in June of 2011. The laboratory survey was completed in June of 2011. The response rate for the survey was 66% (n=16). Practice Characteristics: Most (N=10) respondents identified themselves as Administrative Directors, followed by microbiology supervisors (n=2), chief technologists, lab managers, lab supervisors, and quality assurance. These labs served between 750 and 1,850,000 individuals. Table 11 summarizes the insurance status of the people served in these laboratories. Table 11: Percent of Patients Served by Hospitals by Insurance Type

Type of Insurance (N=16)

% patients Medicare Medicaid Private Self‐pay Other

0‐10% 1 6 13 4

11‐20% 7

21‐30% 1 4

31‐40% 2 7

41‐50% 10 1 2

51‐60% 1 2

61% or more

Missing 1 3 12

Terminology in Use: Fourteen hospital laboratories use CPT codes, one uses LOINC®, and one mentioned other terminology used to code and communicate data. Fourteen hospitals responded that their laboratory systems were HL7‐compatible, but none of them could identify the version of HL7 in use. Exchanging Data: When asked about with whom they exchanged data, these hospitals mentioned physicians (14), independent clinical pharmacies (12), physician office laboratories (5), hospital laboratories (4), blood bank laboratories (3), public health laboratories (3), insurance companies (3), no one (2), patients (2), Personal Health Record (2), and electronic health exchange (1). Security and Privacy Concerns: When asked about their concerns related to security and privacy, most respondents’ comments were similar to those being heard in other states.

Table 12: Security and Privacy concerns of Hospital Laboratory Administrators Security Concerns Privacy Concerns

How will the gate keeper activities be managed? Will the data be stored in a central repository?

Information systems may be "hacked" into

Confidentiality

Laws at some later time may reduce the privacy protections that were originally built in


Secure access

use a licensed vendor as a repository

Maintaining HIPAA compliance is always a concern

People will always talk. Whoever has access can use it however they choose whether or not they are sworn to HIPAA compliance. Here violating privacy means your job so in this institution I am comfortable about my staff.

The laws need to be re‐worded for compliance with data exchange

Importance of Health Information Exchange: Most (n=15) hospital staff that responded to the survey believed that HIE could be very useful (12) or somewhat useful (3). Some examples of use that were mentioned were:

Continuum of care for the patient would be improved.

I really would like to report to the state electronically. We will have a health system connection through our software soon, so it will happen in the YNHHS.

If properly implemented and protected, the rapid data exchange could be beneficial to patients by allowing whole health histories to be viewed by any clinician seeing the patient.

It will depend on the degree of difficulty to receive patient data. How secure the site will be is a major concern,

It would be useful because the information will be available faster,

It would hasten the ability of agencies to intercede in emergent situations.

Making the process of delivering health care more efficient should be the goal.

Must have it to qualify for funding. Ease of use for the patient to monitor and maintain the personal health record online.

Too much bureaucracy for the state. Needs to be managed by a private vendor. The state does not make anything easy, they are technologically disadvantaged.

When asked to rate their satisfaction with the HITE‐CT initiative, most (7) chose the neutral response, five chose not applicable, two were very dissatisfied, one was satisfied, and one was very satisfied. Comments included:

I did not know much about it prior to this survey.

I have not been given the details of the HIE so cannot form an opinion.

I know very little about it at this point.

I think it would increase ACCURACY AND TIMELINESS.

I'm pleased this effort is beginning ‐ hopefully, it will be completed in a timely manner and be effective.

Lab doesn't use it.

Very limited knowledge about it. Additionally, when asked “whether or not CT would have a successful HIE by 2014,” nine hospitals responded with a “yes” and six responded “no.” Table 13 summarizes some examples of why they answered one way or another.

Table 13: Comments by Hospital Opinion of HIE Success by 2014

Yes, HIE will be implemented successfully No, HIE will not be implemented successfully


I think we are ready to have this information at our fingertips. I am concerned that it will be bogged down at the institutional level as IT resources are very short.

I'm saying yes ‐ however, I know the budget constraints DPH is working under now ‐ getting this done will be a challenge.

Most Hospitals are very actively working on this initiative today as they implement Meaningful Use regulations.

Any former computer projects (i.e. State of CT DPH) have always been delayed or put on a back burner.

It seems unlikely all issues from all stakeholders can be legally and politically rectified by then.

State bureaucracy, budget issues

there has been no info exchanged with me as the Laboratory Director as of yet.

Other general comments include:

I think the state should prepare a scope document for all of us to see. It may be that the senior staff at most hospitals have a good idea about this project but not at the middle management level.

Many of these questions would be better answered by finance and IT personnel than by laboratory personnel.

Summary

14 of the 24 hospitals laboratories completed our survey.

Fourteen hospital laboratories use CPT codes, one uses LOINC®, and one mentioned other terminology used to code and communicate data. Fourteen hospitals responded that their laboratory systems were HL7‐compatible, but none of them could identify the version of HL7 in use.

When asked about who they exchanged data with, these hospitals mentioned physicians (14), independent clinical pharmacies (12), physician office laboratories (5), hospital laboratories (4), blood bank laboratories (3), public health laboratories (3), insurance companies (3), no one (2), patients (2), Personal Health Record (2), and electronic health exchange (1).


Consumer Survey (August 2011 ) Methodology: A random sample of 2,845 working household telephone numbers was purchased from Marketing Systems Group (Genesys Sampling Systems). This sample is a randomly‐generated list of telephone numbers of Connecticut residents; it has been screened to rule out most non‐working or business numbers. This survey was approved by the UCHC IRB in August 2011. The data collection for this survey started in August 2011 and is ongoing. We have completed 33 surveys as of October 14, 2011. Consumer Characteristics: Age of the respondents for the consumer survey ranged from 34‐80 years, representing a mean age of 60 years. Almost eighty percent of the respondents were women and 12% were men. Eighty‐eight percent of the consumers selected white and 3% selected black as their race. Most respondents (91%) were of non‐Hispanic origin. The average income per household was $85,000. Thirty‐three percent of the respondents reported having some college, 27% reported having a college degree, 24% had graduate degrees, and 9% had a high school diploma. Table 14 summarizes consumer characteristics. Health Status and Physician Interactions: Sixty‐seven percent of the people reported being in excellent or very good health. Thirty percent reported having a chronic condition. About one‐fifth of the people had visited their physician 1‐2 or 5‐6 times, while most people had visited a physician 3‐4 times. Eighty‐five percent of the people were satisfied with the care they received from their physician. Table 14: Consumer Demographics and Health Status


Age

Range 34‐80 years

Mean Age (SD) 60 yrs. (12 yrs)

Gender N %

Male 4 12%

Female 26 79%

Missing 3 9%

Race

White 29 88%

Blacks 1 3%

Other 3 9%

Ethnicity

Non‐Hispanic 30 91%

Missing 3 9%

Income

Range 10,800‐225,000

Mean Income (SD) 85,305 (62,361)

Median Income 80,000

Missing 14 42%

Education

High School Diploma 3 9%


General Health

Excellent 5 15%

Very Good 17 52%

Good 5 15%

Fair 4 12%

Missing 2 6%

Have you been diagnosed with a chronic condition?

Yes 10 30%

No 21 64%

Missing 2 6%

In the past 12 months , how many times did you see a doctor or a PA

Did not see a doctor 2 6%

1‐2 times 7 21%

3‐4 times 9 27%

5‐6 times 7 21%

more than 6 times 6 18%

missing 2 6%

How satisfied are you with the care you receive?


Some College 11 33%

College Degree 9 27%

Graduate School 8 24%

Missing 2 6%

Very satisfied 21 64%

Mostly satisfied 7 21%

Slightly satisfied 2 6%

Not at all satisfied 1 3%

Do not regularly visit a doctor 2 6%

Health Information Exchange and Patient‐Consent: When asked their opinion about a National Health Information Exchange (NHIE) for citizens, 45% were opposed and 48% were in favor of such an exchange. Most respondents cited privacy (48%) followed by cost (21%) as barriers to NHIE. When asked about their preference for a consent model 55% supported the opt‐in model and 21% supported the opt‐out model. Refer to Table 15 for responses to people’s opinion about NHIE. Table 15: Support and Barriers for the National Health Information and Consent Models

Support for national health information exchange

N %

Strongly oppose 7 21%

Oppose 8 24%

Favor 11 33%

Strongly favor 5 15%

Missing 2 6%

Barriers to achieve national health information exchange

Privacy concerns 16 48%

Cost 7 21%

Don't know 5 15%

Liability 1 3%

Limited public support 1 3%

None of the above 2 6%

Missing 1 3%

Support for Consent Model

Opt‐in 18 55%

Opt‐out 7 21%

Don't know 7 21%

Missing 1 3%

Awareness about Health IT: When asked about whether or not they had heard Health Information technology terms; 54% had heard the term electronic health information exchange; 79% had heard the term electronic medical records; 45% had heard about personal health records; and only 15% had heard about the Connecticut Health Information Exchange. Table 16: Awareness of Health IT


Have you heard about the A lot Some Not at all Unsure Missing

Electronic Health Information Exchange

7 11 13 1 1

21% 33% 39% 3% 3%

Electronic Medical Records

9 17 5 2

27% 52% 15% 6%

Personal Health Records (PHRs)

6 9 18

18% 27% 55% 0%

The Connecticut Health information Exchange

2 3 27 1

6% 9% 82%

When people were asked about their agreement with the benefits of Health IT, 67% agreed that it would improve quality of care; 61% agreed that it would improve doctor‐patient interactions; 64% agreed that it would avoid medical errors; and 64% agreed that it would reduce repeating tests and procedures. Refer to Table 17 for consumer support for Health IT. Table 17: Level of Agreement with Adoption of Health IT

Level of agreement with Adoption of Health IT Disagree Neutral Agree Missing

Improve Quality of care

7 3 22 1

21% 9% 67% 3%

Improve doctor‐patient interaction

9 3 20 1

27% 9% 61% 3%

Avoid medial errors

4 5 21 3

12% 15% 64% 9%

Reduce repeated tests & procedures

8 2 21 2

24% 6% 64% 6%

An equal number of people were interested and disinterested in owning a Personal Health Record (PHR), as well as giving permission to have their health information shared. Respondents identified privacy and the lack of pressing need for this information as the barriers to accessing an online PHR. Refer to Table 18 for responses to consumer interest in adopting PHRs and sharing health information and Table 19 for the identified barriers to accessing PHRs. Table 18: Level of Interest in Accessing PHRs and Sharing Health Information

Level of interest… Very interested Somewhat interested

Not very interested

Not at all interested

in having access to online electronic PHR

10 7 9 7

30% 21% 27% 21%

in giving permission to share health related information electronic

6 10 7 10

18% 30% 21% 30%

Table 19: Barriers to Using PHRs and Giving Permission to Share Health Information

Barriers to …

Concerned

about

privacy

Unfamiliar

with

technology

No

internet

access

Don't feel

it's

necessary

Too much

responsibility

Might

cost too

much

Don't

know Other


Accessing online electronic PHR

8 0 1 4 0 1 1 3

50% 0% 6% 25% 0% 6% 6% 19%

share health related information electronic

10 1 0 3 1 0 1 3

59% 6% 0% 18% 6% 0% 6% 18% Use of Internet to Access Health Related Information: Most people (88%) had sought information about health and other medical topics. Three‐fourths of the people looked up information on the internet, with 54% having looked up information in the last 30 days and 39% having looked up information in the last seven days. Table 20 summarizes the pattern of use of internet searching for health‐related information. Table 20: Use of internet to Search for Medical Information

Have you ever looked for information about health or medial topics

Yes 29 88%

No 2 6%

Missing 2 6%

Most recent time looked for medical information from

Physician 2 6%

Another doctor 2 6%

The internet 25 76%

Magazine 1 3%

Book 3 9%

Journal 1 3%

Lecture 1 3%

In the past 30 days, how many time did you go to the internet to access health‐related information

None 13 39%

Between 1 & 5 times 12 36%

6 or more times 6 18%

Missing 2 6%

In the past 7 days, how many time did you go to the internet to access health‐related information

None 18 55%

Between 1 & 5 times 10 30%

6 or more times 3 9%

Missing 2 6%

Health Literacy: A majority (57%) of the people reported reading printed information that they received about health‐related topics. Only 6% of the people reported finding this information difficult to understand. Table 21: Health Literacy in Connecticut

Last time you received printed information, how much did you read N %

A lot 12 36%


Some 7 21%

None 10 30%

Don't remember 1 3%

Missing 3 9%

Yes No Not Sure Missing

Was information difficult to understand?

2 21 7 3

6% 64% 21% 9%

Were any of the words in the material unfamiliar to you?

3 19 8 3

9% 58% 24% 9%

Last time you visited your doctor, did the doctor use any words that you did not understand.

1 29 1 2

3% 88% 3% 6%

Due to the small number of completed consumer surveys, it is early to start using these results for decision‐making. Once we have reached a sufficient sample size, this information will very useful for decision‐making as it relates to the sustainability of Connecticut’s Health Information exchange. Summary

33 randomly selected people have responded to our telephone survey.

51% report completing a college degree.

67% report being in good health and 30% report having a chronic condition.

Most (88%) people had seen a doctor at least once in the prior year.

85% were satisfied with the care that they received from their physician.

55% supported he opt‐in model.

48% were in favor of NHIN, while 45% were opposed to the idea.

39% did not know what a electronic health information exchange is and 82% had not heard about CT‐HITE.

67% agreed that adopting Health IT would improve quality of care; 61% agreed that it could improve the doctor‐patient relationship; 64% thought it would reduce medical errors; and 64% agreed that it could reduce repeated tests and procedures.

76% had looked for medical information on the internet.

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