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AJMC
Implementation of EHR-Based Strategies to Improve Outpatient CAD Care
Published Online: October 25, 2012
Stephen D. Persell, MD, MPH; Janardan Khandekar, MD; Thomas Gavagan, MD; Nancy C. Dolan, MD; Sue Levi, RN, MBA; Darren Kaiser, MS; Elisha M. Friesema, BA, CCRP; Ji Young Lee, MS; and David W. Baker, MD, MPH
Objectives: To evaluate the effects of a multifaceted quality improvement intervention during 2 time periods on 4 coronary artery disease [CAD] measures in 4 primary care practices. During the first phase, electronic reminders prompted physicians to order indicated medications or record contraindications and refusals (exceptions). In the second phase, physicians also received reports about their performance (including lists of patients not satisfying these measures), and financial incentives were announced.
Study Design: Time series analysis.
Methods: Adult CAD patients seen within the preceding 18 months were included. The primary outcome was the performance on each measure (proportion of eligible patients satisfying each measure after removing those with exceptions). Secondary outcomes were the proportion with the medication on their medication list, and the proportion with exceptions.
Results: Median performance at baseline was 78.8% for antiplatelet treatment, 85.1% for statin treatment, 77.0% for beta-blocker after myocardial infarction (MI), and 67.1% for angiotensinconverting enzyme inhibitor or angiotensin receptor blocker after MI. Performance improved slightly for 3 measures during the first phase and improved more substantially for all 4 measures during the second phase. For 3 of 4 measures, however, documentation of exceptions increased but not medication prescribing. Most exceptions were judged to be appropriate by peer review.
Conclusions: Physicians responded more to the combination of feedback and financial incentives than they had to electronic reminders alone. High performance was only achieved for 1 of 4 measures and recording of exceptions rather than increases in medication prescribing accounted for most of the observed improvements.
(Am J Manag Care. 2012;18(10):603-610)
Study Design: Time series analysis.
Methods: Adult CAD patients seen within the preceding 18 months were included. The primary outcome was the performance on each measure (proportion of eligible patients satisfying each measure after removing those with exceptions). Secondary outcomes were the proportion with the medication on their medication list, and the proportion with exceptions.
Results: Median performance at baseline was 78.8% for antiplatelet treatment, 85.1% for statin treatment, 77.0% for beta-blocker after myocardial infarction (MI), and 67.1% for angiotensinconverting enzyme inhibitor or angiotensin receptor blocker after MI. Performance improved slightly for 3 measures during the first phase and improved more substantially for all 4 measures during the second phase. For 3 of 4 measures, however, documentation of exceptions increased but not medication prescribing. Most exceptions were judged to be appropriate by peer review.
Conclusions: Physicians responded more to the combination of feedback and financial incentives than they had to electronic reminders alone. High performance was only achieved for 1 of 4 measures and recording of exceptions rather than increases in medication prescribing accounted for most of the observed improvements.
(Am J Manag Care. 2012;18(10):603-610)
Quality improvement techniques that leverage an electronic health record (EHR) have been shown to improve care in many cases.1 However, EHR-based quality improvement has not been universally successful, and even in many instances where study results were positive, the magnitude of the improvement was small.2-4 Furthermore, observational data do not suggest that simply having an EHR improves quality in outpatient settings.5-7 In contrast, we have shown in the UPQUAL study (Utilizing Precision Performance Measurement for Focused Quality Improvement) that interconnected EHR-based tools can improve quality for multiple process of care measures in a large urban, single-site, university-affiliated practice.8 This intervention was designed to improve quality measurement (including capture of contraindications and patient refusals), make point-of-care reminders more accurate, and provide more valid and responsive feedback to clinicians (including lists of patients not receiving essential medications).
In this current study, we applied these principles—improve quality measurement in order to enable more accurate point-of-care reminders and feedback—to coronary artery disease (CAD) care in 4 suburban primary care group practices (2 family medicine and 2 internal medicine) that belong to the same health system and use the same EHR. We selected CAD care as our study objective because it is a common and important chronic disease and because implementing CAD measures in this setting was more feasible than several other candidate chronic disease and prevention topics. In this health system, point-of-care reminders were implemented first in July 2008 (Phase 1). Starting September to November 2009 (Phase 2), feedback was given to physicians and the medical group publicized to physicians that financial incentives would be tied to performance measures (including the 4 measures studied here). Both the reminders and physician feedback portions of the interventions were planned prior to Phase 1 by the study team. The financial incentives were initiated independently by leadership in the organization that was not directly associated with this study. This sequential implementation provides an opportunity to observe the additional effects of adding the combination of feedback and announcing financial incentives to electronic reminders on measured performance.
METHODS
Setting and Eligible Patients
We performed this study at 4 primary care practices in the northern suburbs of Chicago, Illinois, that use the same commercial EHR (EpicCare, Epic Systems Corporation, Verona, Wisconsin). Northwestern University’s and Northshore University HealthSystem’s institutional review boards approved the study. All patients eligible for 1 or more quality measures cared for by 33 attending physicians (10 family medicine and 23 internal medicine) and 15 family medicine resident physicians were included. The practices had used the EHR for 5 years before the start of the first intervention examined in the study.
Sequential Implementation of Quality Improvement Techniques
Measure Selection
We selected for consideration 4 measures of CAD care quality that were based on national measures: antiplatelet drug and lipid-lowering drug treatment in all patients with CAD, beta-blocker use in patients with prior myocardial infarction (MI), and angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) for diabetes or left ventricular systolic dysfunction.9 Health system clinicians, including cardiologists, discussed and modified the measures for local use, changing the lipid-lowering drug measure to statin treatment in CAD and changing the ACE inhibitor or ARB measure to apply to patients with prior MI only.
Electronic Clinical Decision Support (Phase 1)
Prior to these interventions, there were no other clinical decision support tools in use that addressed these topics. We added electronic point-of-care reminders that appeared during patient encounters when an apparently eligible patient did not have an indicated medication on their current medication list and had no exception recorded. These alerts were minimally intrusive (they did not interrupt clinicians’ work flow and the alert was indicated only by a single yellow highlighted tab that appeared on the left side of the screen when any clinical reminder criteria were present, and physicians had to select this tab to see the individual reminders). These alerts were displayed using existing EpicCare functionality. These electronic reminders included standardized ways to capture patient reasons (eg, refusals) or medical reasons that were exceptions for individual reminders within the reminder system of the EHR. These reminders were implemented in July 2008. We sent physicians educational e-mails with brief training materials to introduce the new alerts and to show how to record patient or medical exceptions.
Implementation of Feedback Reports and Announcement of Incentives (Phase 2)
Starting in September 2009, on a monthly basis, we gave physicians printed reports indicating their overall performance on each of the 4 measures for all their eligible patients and lists of individual patients who appeared to be eligible for an indicated medication but were not receiving it and had no exception recorded.
In October and November of 2009, the medical group leadership announced to physicians that a small portion of their compensation (1.5% of total compensation, which constituted 25% of the incentive-based compensation) would be tied to their performance on quality metrics, including the 4 metrics covered in this study.
Evaluation and Outcomes
Measure Calculation
In this current study, we applied these principles—improve quality measurement in order to enable more accurate point-of-care reminders and feedback—to coronary artery disease (CAD) care in 4 suburban primary care group practices (2 family medicine and 2 internal medicine) that belong to the same health system and use the same EHR. We selected CAD care as our study objective because it is a common and important chronic disease and because implementing CAD measures in this setting was more feasible than several other candidate chronic disease and prevention topics. In this health system, point-of-care reminders were implemented first in July 2008 (Phase 1). Starting September to November 2009 (Phase 2), feedback was given to physicians and the medical group publicized to physicians that financial incentives would be tied to performance measures (including the 4 measures studied here). Both the reminders and physician feedback portions of the interventions were planned prior to Phase 1 by the study team. The financial incentives were initiated independently by leadership in the organization that was not directly associated with this study. This sequential implementation provides an opportunity to observe the additional effects of adding the combination of feedback and announcing financial incentives to electronic reminders on measured performance.
METHODS
Setting and Eligible Patients
We performed this study at 4 primary care practices in the northern suburbs of Chicago, Illinois, that use the same commercial EHR (EpicCare, Epic Systems Corporation, Verona, Wisconsin). Northwestern University’s and Northshore University HealthSystem’s institutional review boards approved the study. All patients eligible for 1 or more quality measures cared for by 33 attending physicians (10 family medicine and 23 internal medicine) and 15 family medicine resident physicians were included. The practices had used the EHR for 5 years before the start of the first intervention examined in the study.
Sequential Implementation of Quality Improvement Techniques
Measure Selection
We selected for consideration 4 measures of CAD care quality that were based on national measures: antiplatelet drug and lipid-lowering drug treatment in all patients with CAD, beta-blocker use in patients with prior myocardial infarction (MI), and angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) for diabetes or left ventricular systolic dysfunction.9 Health system clinicians, including cardiologists, discussed and modified the measures for local use, changing the lipid-lowering drug measure to statin treatment in CAD and changing the ACE inhibitor or ARB measure to apply to patients with prior MI only.
Electronic Clinical Decision Support (Phase 1)
Prior to these interventions, there were no other clinical decision support tools in use that addressed these topics. We added electronic point-of-care reminders that appeared during patient encounters when an apparently eligible patient did not have an indicated medication on their current medication list and had no exception recorded. These alerts were minimally intrusive (they did not interrupt clinicians’ work flow and the alert was indicated only by a single yellow highlighted tab that appeared on the left side of the screen when any clinical reminder criteria were present, and physicians had to select this tab to see the individual reminders). These alerts were displayed using existing EpicCare functionality. These electronic reminders included standardized ways to capture patient reasons (eg, refusals) or medical reasons that were exceptions for individual reminders within the reminder system of the EHR. These reminders were implemented in July 2008. We sent physicians educational e-mails with brief training materials to introduce the new alerts and to show how to record patient or medical exceptions.
Implementation of Feedback Reports and Announcement of Incentives (Phase 2)
Starting in September 2009, on a monthly basis, we gave physicians printed reports indicating their overall performance on each of the 4 measures for all their eligible patients and lists of individual patients who appeared to be eligible for an indicated medication but were not receiving it and had no exception recorded.
In October and November of 2009, the medical group leadership announced to physicians that a small portion of their compensation (1.5% of total compensation, which constituted 25% of the incentive-based compensation) would be tied to their performance on quality metrics, including the 4 metrics covered in this study.
Evaluation and Outcomes
Measure Calculation
PDF is available on the last page.
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