Exceptions to outpatient quality measures for coronary artery disease in electronic health records.

BACKGROUND: Physicians report outpatient quality measures from data in electronic health records to facilitate care improvement and qualify for incentive payments. OBJECTIVE: To determine the frequency and validity of exceptions to quality measures and to test a system for classifying the reasons for these exceptions. DESIGN: Cross-sectional observational study. SETTING: 5 internal medicine or cardiology practices. PARTICIPANTS: 47,075 patients with coronary artery disease between 2006 and 2007. MEASUREMENTS: Counts of adherence with and exceptions to 4 quality measures, on the basis of automatic reports of recommended drug therapy by computer software and separate manual reviews of electronic health records. RESULTS: 3.5% of patients who had a drug recommended had an exception to the drug and were not prescribed it (95% CI, 3.4% to 3.7%). Clinicians did prescribe the recommended drug for many other patients with exceptions. In 538 randomly selected records, 92.6% (CI, 90.3% to 94.9%) of the exceptions reported automatically by computer software were also exceptions during manual review. Most medical exceptions were clinical contraindications, drug allergies, or drug intolerances. In 592 randomly selected records, an unreported exception or a drug prescription was found during manual review for 74.6% (CI, 71.1% to 78.1%) of patients for whom automatic reporting recorded a quality failure. LIMITATION: The study used a convenience sample of practices, nonstandardized data extraction methods, only drug-related quality measures, and no financial incentives. CONCLUSION: Exceptions to recommended therapy occur infrequently and are usually valid. Physicians frequently prescribed drugs even when exceptions were present. Automated reports of quality failure often miss critical information. PRIMARY FUNDING SOURCE: Agency for Healthcare Research and Quality.

Using electronic health records to measure physician performance for acute conditions in primary care: empirical evaluation of the community-acquired pneumonia clinical quality measure set.

BACKGROUND: Electronic health records (EHRs) have the potential to facilitate performance measurement for acute conditions. OBJECTIVE: To evaluate the reliability and feasibility-of-use of a performance measure set for community-acquired pneumonia in an ambulatory EHR. DESIGN: Retrospective, cross-sectional electronic chart review. SETTING: Primary Care Clinics. PATIENTS: Adults with an administrative claims diagnosis of pneumonia during a 14-month period. MEASUREMENTS: Two reviewers independently examined data in the EHR to determine if (1) the encounter was a visit for acute pneumonia; (2) there was documentation for each of 12 performance measures; and (3) such information was in coded form. RESULTS: Of 688 encounters with a claim diagnosis of pneumonia, 210 (31%) were identified by either reviewer as a primary care acute pneumonia visit. The 2 reviewers agreed that 198 encounters to 71 different clinicians were visits for acute pneumonia [kappa, 0.96; 95% confidence interval (CI), 0.93-0.98]. Measure performance ranged from 10% for providing location of care rationale to 91% for documenting blood pressure, averaging 52% across all 12 measures. Inter-rater reliability ranged from 0.66 (95% CI, 0.47-0.84) for providing a location of care rationale to 0.97 (95% CI, 0.91-1.0) for vital sign assessment. The proportion of data that was in coded form ranged from 0% for mental status, hydration status, chest x-ray performance, and location of care to 100% for medications and immunizations. CONCLUSIONS: Although EHRs offer potential advantages for performance measurement for acute conditions, accurate identification of pneumonia visits was challenging, performance generally appeared poor, and much of the data were not in coded form.

Automated review of electronic health records to assess quality of care for outpatients with heart failure.

BACKGROUND: Electronic health records (EHRs) may be used to assess quality of care. OBJECTIVE: To evaluate the accuracy of automated review of EHR data to measure quality of care for outpatients with heart failure. DESIGN: Observational study of quality of care for heart failure comparing automated review of EHR data with automated review followed by manual review of electronic notes for patients with apparent quality deficits (hybrid review). SETTING: An academic general internal medicine clinic with several years' experience using a commercial EHR. PATIENTS: 517 adults with a qualifying International Classification of Diseases, Ninth Revision, diagnosis of heart failure in their EHR data and 2 or more clinic visits over the past 18 months. MEASUREMENTS: Left ventricular ejection fraction (LVEF), prescription of a beta-blocker and an angiotensin-converting enzyme (ACE) inhibitor or angiotensin-receptor blocker (ARB) for patients with left ventricular systolic dysfunction (LVEF <0.40) and prescription of warfarin for patients with comorbid atrial fibrillation. RESULTS: Performance based on automated review of EHR data was similar to that based on hybrid review for assessing LVEF measurement (94.6% vs. 97.3%), prescription of beta-blockers (90.9% vs. 92.8%), and prescription of ACE inhibitors or ARBs (93.9% vs. 98.7%). However, performance based on automated review was lower than that based on hybrid review for prescription of warfarin for atrial fibrillation (70.4% vs. 93.6%), primarily because automated review did not detect documentation of accepted reasons for not prescribing warfarin. LIMITATIONS: The findings may not be applicable to other practices and other EHRs. The authors used EHR data to identify eligible patients, so the study may have excluded some patients with heart failure. Patient charts were manually reviewed only if a provider appeared to fail a quality measure on automated review and did not determine the sensitivity and specificity of automated review according to standard definitions. CONCLUSIONS: Automated review of EHR data to measure the quality of care of outpatients with heart failure missed many exclusion criteria for medications documented only in providers' notes. As a result, it sometimes underestimated performance on medication-based quality measures.

Assessing the validity of national quality measures for coronary artery disease using an electronic health record.

BACKGROUND: Nationally endorsed, clinical performance measures are available that allow for quality reporting using electronic health records (EHRs). To our knowledge, how well they reflect actual quality of care has not been studied. We sought to evaluate the validity of performance measures for coronary artery disease (CAD) using an ambulatory EHR. METHODS: We performed a retrospective electronic medical chart review comparing automated measurement with a 2-step process of automated measurement supplemented by review of free-text notes for apparent quality failures for all patients with CAD from a large internal medicine practice using a commercial EHR. The 7 performance measures included the following: antiplatelet drug, lipid-lowering drug, beta-blocker following myocardial infarction, blood pressure measurement, lipid measurement, low-density lipoprotein cholesterol control, and angiotensin-converting enzyme inhibitor or angiotensin receptor blocker for patients with diabetes mellitus or left ventricular systolic dysfunction. RESULTS: Performance varied from 81.6% for lipid measurement to 97.6% for blood pressure measurement based on automated measurement. A review of free-text notes for cases failing an automated measure revealed that misclassification was common and that 15% to 81% of apparent quality failures either satisfied the performance measure or met valid exclusion criteria. After including free-text data, the adherence rate ranged from 87.5% for lipid measurement and low-density lipoprotein cholesterol control to 99.2% for blood pressure measurement. CONCLUSIONS: Profiling the quality of outpatient CAD care using data from an EHR has significant limitations. Changes in how data are routinely recorded in an EHR are needed to improve the accuracy of this type of quality measurement. Validity testing in different settings is required.

Electronic health record systems: the vehicle for implementing performance measures.

Advances in information technology and recent national directives have the potential to support dramatic improvements in health care. Two key components are the implementation of functional electronic health record systems and widely accepted, evidence-based clinical performance measures for physicians. Midwest Heart Specialists, a 55-physician cardiovascular group at 14 locations in northern Illinois, has utilized an outpatient electronic health record system since 1997. Since 2003, the group has integrated cardiovascular measurement sets developed by the American Medical Association-convened Physician Consortium for Performance Improvement into its electronic health record system. With this integration, the group was able to capture data needed for internal quality assessment and improvement as part of routine outpatient care without the need for additional resources. Critical disease-management data for decision support are available continuously, resulting in improvements in health care. The reporting of these standardized data could be the foundation to support quality-based reimbursement strategies and physician office-based disease-management strategies.