Patients Government Providers Payers Quality · Managing Clinical Knowledge for Health care...
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Capturing EHR Enabled Quality Improvement- Decision Support, Measurement, and Reporting REQUIRES an
understanding of context February 23, 2014
John Chuo, MD, MS Children’s Hospital of Philadelphia
Neonatal Quality Officer Medical director, Telemedicine
DISCLAIMER: The v iews and opinions expressed in this presentation are those of the author and do not necessarily represent of f icial policy or position of HIMSS.
Recognizing a bad care delivery system does not mean you know how to
improve it.
CQM measures how good or bad healthcare delivery
is
but
Poor understanding of system = Poor implementation of best practices
Managing Clinical Knowledge for Health care Improvement, EA Balas, 2000
Using clinical quality measures to drive improvement in
healthcare delivery requires
understanding of context.
Use of clinical decision support system
Principles of best practice for CDS implementation
Evidence, expert, experience
Compliance with Using CDS intervention
Implementation Outcome
CQM Outcome
(Prophylactic antibiotic received within 1 hour prior to surgery)
CDS as a means for improving CQM
Can it work?
(Efficacy)
Does it work In MY
context? (Effectivenes
s)
© John Chuo, manuscript in progress
Successful Change Management
Knoster, T., Villa R., & Thousand, J. (2000) A framework for thinking about systems change.
Is the desired patient
outcome clear?
Does user have the
skills to use the CDS? (training)
Why would the user use the
CDS, why not override?
Do you have resources to react
to feedback Promptly
What is the action plan for improving the
CDS?
FOR CDS IMPLEMENTATION
Admin
Medical Team
Computer system
1. Runs the rounding tool
system each am
QI Student intern
2. Print out QI reminders depending on patient conditions (by searching thru previous day notes)
3. Delivers the paper QI tool with the reminders to each of the rounding teams
Conducts patient rounds
4. Student ask reminders during rounds and record
answers
5. Updates data repository
Rounding tool workflow
Results
% of time assigned questions were
applicable to patient
% of times assigned question needed
prompting by intern
% times assigned question had
Response unfavorable to patient
(Importance factor)
% of time assigned question not asked, Unfavorable and an
Action Was Prompted (Impact factor)
AVG. 93% 11% 10% 6% (600 actions)
0.00%
20.00%
40.00%
60.00%
80.00%"Third Trimester HIVResults" (7/11)
"Social History" (3/5)
"Family History" (1/2)
"O2 Sat. Limits" (1/7)
"Immunizations" (1/8)
Top 5 questions that needed prompting by intern, response
unfavorable to patient, prompted Action
© John Chuo, manuscript in progress
Conflict of Interest Disclosure
John Chuo, MD, MS
• No conflicts of interest to disclose
© 2014 HIMSS
Capturing EHR Enabled Quality Improvement- Decision Support, Measurement, and Reporting
February 23, 2014 Floyd Eisenberg, MD, MPH, FACP
iParsimony, LLC The presentation includes content from the American Hospital Association. A Study of the Impact of Meaningful Use Clinical Quality Measures. July 2013.
DISCLAIMER: The v iews and opinions expressed in this presentation are those of the author and do not necessarily represent of f icial policy or position of HIMSS.
© 2013 American Hospital Association
eCQM implementation process – Eligible Hospitals
Common implementation steps observed at all sites Iterative, non-linear process
Gap analysis
Data capture and workflow
redesign
Data extraction and eCQM calculation
Validation Downstream
uses of eCQM results
American Hospital Association. A Study of the Impact of Meaningful Use Clinical Quality Measures. July 2013. Available at: http://www.aha.org/content/13/13ehrchallenges-report.pdf.
eCQM implementation experience – Eligible Hospitals
Gap analysis
Data capture and workflow
redesign
Data extraction and eCQM calculation
Validation Downstream
uses of eCQM results
Largely prescribed by EHR/eCQM reporting tool
Workarounds and successive iterations • 80% of effort entailed changes to hospital workflow
solely to accommodate eCQM data capture
Innacurate eCQM results • Sensitivity issues causing under reporting:
• Data not in prescribed location (as expected by eCQM tool) • Internal systems with needed data not interoperable with EHR
• Usability affecting data quality
No trust or reliance in eCQM results
American Hospital Association. A Study of the Impact of Meaningful Use Clinical Quality Measures. July 2013. Available at: http://www.aha.org/content/13/13ehrchallenges-report.pdf.
Program Challenges
1. eCQMs were not tested for validity, accuracy and feasibility
2. eCQMs were hard to find, lengthy, and often contained errors
3. MU eCQMs require understanding of unfamiliar terminologies
4. Guidance to ignore data accuracy and focus on the ability to report undermines goals for quality improvement
eCQM Impact Study: Challenges
American Hospital Association. A Study of the Impact of Meaningful Use Clinical Quality Measures. July 2013. Available at: http://www.aha.org/content/13/13ehrchallenges-report.pdf.
Technical Challenges
Expectations that existing EHR data would suffice to calculate the eCQMs were not realized
1. EHRs do not store entered data in readily retrievable form
2. EHRs are not designed to capture many of the elements in structured form to enable re-use for eCQM reporting
3. EHRs are not designed to capture information from other department information systems at the level of detail needed for eCQM reporting
eCQM Impact Study: Challenges
American Hospital Association. A Study of the Impact of Meaningful Use Clinical Quality Measures. July 2013. Available at: http://www.aha.org/content/13/13ehrchallenges-report.pdf.
Clinical Challenges
1. EHRs and certification requirements are not designed to support end-to-end patient care workflows to draw data as expressed in eCQMs
2. Hospitals were unable to validate the eCQM results
3. Some eCQM specifications were out of date
Strategic Challenges
1. Time and personnel requirements to implement eCQMs were excessive and far beyond expectations
2. The time and effort provided no return on investment as results could not be validated and were therefore not useful for quality management.
eCQM Impact Study: Challenges
American Hospital Association. A Study of the Impact of Meaningful Use Clinical Quality Measures. July 2013. Available at: http://www.aha.org/content/13/13ehrchallenges-report.pdf.
eCQM Impact Study: Recommendations
American Hospital Association. A Study of the Impact of Meaningful Use Clinical Quality Measures. July 2013. Available at: http://www.aha.org/content/13/13ehrchallenges-report.pdf.
Updated Process: A World of Dependencies
Standard Vocabulary
Quality Data
Model
Measure Authorin
g Tool
Value Set Authority
Center
Health Quality Measure Format
Quality Report Document
Architecture
Clinical Document
Architecture
Review Oversight - HHS
American Hospital Association. A Study of the Impact of Meaningful Use Clinical Quality Measures. July 2013. Available at: http://www.aha.org/content/13/13ehrchallenges-report.pdf.
Courtesy: The Joint Commission
eCQM to CDS Example: Measure CMS 165 (NQF 0018)
CONDITION: All are true: Patient is 18 - 84 years Patient has diagnosis = Hypertension [“Active”] Patient does not have diagnosis = Pregnancy Patient does not have diagnosis = End Stage Renal Disease Patient has not had procedure during the measurement year = ESRD-related procedures
APPLIES WHEN: Diastolic Blood Pressure > 90 OR Systolic Blood Pressure > 140 during the last visit Advice: Provide list of patients with possible need for follow up AND hyperlink to NHLBI Guidelines http://www.nhlbi.nih.gov/guidelines/hypertension/index.htm And provide patient education resources: http://www.nhlbi.nih.gov/health/health-topics/topics/hbp/
APPLIES WHEN: Diastolic Blood Pressure OR Systolic Blood Pressure are absent during the last visit Advice: Provide list of patients with indication blood pressure should be taken at each visit AND hyperlink to NHLBI Guidelines http://www.nhlbi.nih.gov/guidelines/hypertension/index.htm And provide patient education resources: http://www.nhlbi.nih.gov/health/health-topics/topics/hbp/
Trigger
Condition
Actions
New data: Query Patient Registry q30 Days
Evaluate: 1. Currency of evidence 2. Feasibility of elements in clinical workflow 3. Value set content
Floyd Eisenberg [email protected]
Contact Info
23
This presentation includes content from the American Hospital Association. A Study of the Impact of Meaningful Use Clinical Quality Measures. July 2013.
© 2013 American Hospital Association
Conflict of Interest Disclosure
Floyd Eisenberg, MD, MPH, FACP
• No conflicts of interest to disclose
© 2014 HIMSS
Capturing EHR Enabled Quality Improvement- Decision Support, Measurement, and Reporting
February 23, 2014
Ferdinand Velasco, M.D., FHIMSS Chief Health Information Officer, Texas Health Resources
Chair, HIMSS Quality Cost Safety Committee DISCLAIMER: The v iews and opinions expressed in this presentation are those of the author and do not necessarily represent of f icial policy or position of HIMSS.
One of the largest faith-based, nonprofit health care delivery systems in the United States and the largest in North Texas in terms of patients
served. The system's primary service area consists of 16 counties in north central Texas, home to more than 6.2 million people.
www.texashealth.org
Organizational Background
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Texas Health Resources
• EHR highlights – 2013 Davies Award – All hospitals at HIMSS EMRAM Stage 6 or 7 – Attested to Meaningful Use Stage 1 (3 years)
We are here…
• Received 80% of anticipated EHR incentive funding from 3 years of Stage 1 MU
• Addressing challenges of meeting Stage 2 MU objectives
• Utilizing historical methods for HIQR and PQRS reporting
• Shifting organizational focus from acute care to population health management
Case studies
• Purpose: to illustrate the considerations of transitioning from Chart Abstracted Measures to eMeasures
• ED throughput: median time from ED arrival to departure for admitted patients
• Ischemic Stroke: anticoagulation therapy for atrial fibrillation/flutter
ED throughput (NQF 0495)
Source: CMS, http://www.cms.gov/Regulations-and-Guidance/Legislation/EHRIncentivePrograms/Downloads/2014_CQM_EH_FinalRule.pdf
ED throughput (NQF 0495)
• Measure output relevant and meaningful both internally and externally
• eMeasure specification relative simple
• Documentation of workflows able to capture discrete EHR
• Excellent correlation between manual abstraction and EHR method
ED throughput (NQF 0495)
• Measure output relevant and meaningful both internally and externally
• eMeasure specification relative simple
• Documentation of workflows able to capture discrete EHR
• Excellent correlation between manual abstraction and EHR method
Potential opportunities for improvement • More meaningful segmentation • Correlation with
– ED / hospital census – ED wait times – ED staffing ratios – Syndromic surveillance – Patient satisfaction
• Use of realtime location sensing technology to eliminate manual time stamps in EHR
• Consider similar measures for inpatient, OR, ambulatory throughput
Stroke: anticoagulation therapy for atrial fibrillation/flutter (NQF 0436)
Source: CMS, http://www.cms.gov/Regulations-and-Guidance/Legislation/EHRIncentivePrograms/Downloads/2014_CQM_EH_FinalRule.pdf
Stroke: anticoagulation therapy for atrial fibrillation/flutter (NQF 0436) • Measure output relevant and
meaningful both internally and externally
• Measure logic complex
• Documentation of workflows uneven
• Challenges with translating EHR data into discrete variables needed to generate CQM
• Modest success with reconciling abstracted and EHR-derived data
Stroke: anticoagulation therapy for atrial fibrillation/flutter (NQF 0436)
Source: AHRQ United States Health Information Knowledgebase, http://ushik.org/mdr/portals
Stroke: anticoagulation therapy for atrial fibrillation/flutter (NQF 0436) • Measure output relevant and
meaningful both internally and externally
• Measure logic complex
• Documentation of workflows uneven
• Challenges with translating EHR data into discrete variables needed to generate CQM
• Modest success with reconciling abstracted and EHR-derived data
Potential opportunities for improvement • Reduce measure logic complexity
– Fewer exclusions – Be more parsimonious and
prescriptive about definitive data sources
• Correlation with – Patient education – Use of secure messaging – Long term anticoagulation
effectiveness and safety • Possible CDS application
– Checklist (pre-discharge)
Lessons learned / considerations
• Process – Build CQM logic manually from measure specifications OR… – Utilize eMeasure specifications from certified EHR technology provider – Validation of CQMs
• Prioritization: CQM reporting for… – Internal process improvement – External reporting
• Pay for performance • Pay for reporting
• Measure overlap vs. separation – EH: HIQR / VBP / MU – EP: PQRS / ACO / MU
Conclusions
• Transition from manually abstracted measures to eMeasures will be a long journey
– Approach needs to be meticulous and systematic – Some eMeasures are usable; most are not
• Abstraction will likely never be completely eliminated, at least for CQMs with complex measure logic
– Shift focus from retrospective chart abstraction to concurrent care management
Ferdinand Velasco [email protected]
HIMSS Quality Cost Safety Committee http://www.himss.org/get-
involved/committees/quality-cost-and-safety
Contact Info
44
Conflict of Interest Disclosure
Ferdinand Velasco, MD
• No conflicts of interest to disclose
© 2014 HIMSS
Integrating Quality Measurement and CDS-enabled Quality Improvement
February 23, 2014 Jerome A. Osheroff, MD, FACP, FACMI
Principal, TMIT Consulting, LLC Adjunct Associate Professor of Medicine, University of Pennsylvania
DISCLAIMER: The v iews and opinions expressed in this presentation are those of the author and do not necessarily represent of f icial policy or position of HIMSS.
We are Here… • Strong/mounting pressure for measurable improvements
• Sub-optimal data to understand care process/outcomes
• Difficulty enhancing measurement/performance
QM & CDS worlds both working on these Turn challenges to joint opportunities!
CDS Definition
“A process for enhancing health-related decisions and actions with pertinent, organized clinical knowledge and patient information to improve health and healthcare delivery.”
Improving outcomes with CDS, 2nd Ed. HIMSS 2012
Reinforces inter-dependence of QM and QI
QI Success Framework: CDS Five Rights
To improve targeted care processes/outcomes, get:
• the right information evidence-based, actionable… [what]
• to the right people clinicians and patients… [who]
• in the right formats documentation tools, data display, answers, order sets, alerts… [how]
• through the right channels EHR, portals, smartphones, smart pill bottles/monitors… [where]
• at the the right times key decision/action … [when]
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ONC Toolkit: Resources for Improving Care with CDS*
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*Posted at: bit.ly/CDS4MU
Warm-up Questions (To Engage Site Leads)
1. What % of our HTN patients have BP<140/90?
2. How are we supporting patient and clinician decisions and actions to drive improvement?
3. Are we using our EHRs (and other tools) to greatest benefit for workflow and outcomes?
4. How can we work as a group to get more efficient at Quality Improvement (QI) and Collaboration?
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Improving BP Control
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• What needs to happen? ‒ Decisions ‒ Actions ‒ Communication ‒ Data gathering
• In RCH health centers, today ‒ What information, ‒ Flows through which people, ‒ In what formats/channels, ‒ At which times?
Patient List/Registry: Powerful Non-Alert CDS Tools
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From Dr. Chris Tashjian, Ellsworth Medical Clinic, with permission
• Document target-focused information flow – Invariably suggests potential enhancements – Helps get QI team/practice ‘on the same page’
• Foster collaboration
– Provider <-> Provider (via Collaborative private site) – Vendor <-> Provider client – QI Experts (Million Hearts) <-> Implementers/Vendors
QI/CDS Worksheets: Tool to Get “CDS 5 Rights” Right
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Measure Developers <-> Others?!
Steps for CDS-enabled QI*
1. Shared understanding of CDS/QI concepts 2. Select improvement targets 3. Envision successful target-focused CDS/QI 4. Use CDS/QI worksheets 5. Make enhancements (“Plan-Do-Study-Adjust”) 6. Collaborate
*See bit.ly/CDSQISteps
Role for QM Community?!
Jerry Osheroff [email protected]
ONC CDS for MU/QI Tools and Resources bit.ly/CDS4MU
CDS/PI Collaborative (Public) bit.ly/CDSPICollab
Contact Info
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Additional slide follows:
Inpatient example of CDS/QM interplay: Clinical intervention contraindications (and CQM measure exclusion) captured during care delivery in a ‘smart order set’: simultaneously serves QI/CDS/QM purposes
An Inpatient Example: VTE Prophylaxis • Best practice CDS/QI recommendations • Based on Society of Hospital Medicine expertise • Anchored by order sets that provide:
– Risk stratification (Hi/Med/Low) – Orders pertinent to risk strata – Opportunity to document contraindications – Uses unit dashboards analogous to registry
Simultaneously support best care, measurement, reporting
For recommendations see: https://sites.google.com/site/cdsforpiimperativespublic/projects/vte-best-practices