Incorporating quality indicators in electronic health record development

Background: Currently, an estimated 5% of hospitals in the United States use electronic health records (EHRs). Performance measurement is statutorily required for services provided by hospital outpatient department and ambulatory surgical center services. The U.S. Department of Health and Human Services has taken the lead in creating medical chart-based measures. However, given the plans of the newly created White House Office of Health Reform to accelerate nationwide adoption of EHRs in hospitals by 2014, there is a need to move from manual to electronic chart abstraction.

Objective/Purpose: This study evaluated the technical feasibility of using electronic systems in hospitals nationwide to collect data for performance measurements. We also identified the potential impacts that the use of these interim systems may have on improving the healthcare of Medicare patients.

Methods: We conducted a systematic review of peer-reviewed journal articles, conference summaries, and other publications on methods of health quality measurement. Our search queries in PUBMED, MEDLINE, and EBSCO provided publications dating back to 1999. We further supplemented database searches with informal interviews with clinical and technical experts who provided additional insight on ongoing research on electronic hospital performance measures.

Results: We found that claims data and medical registries to be the most common forms of public health informatics widely used by hospitals in the United States. But these two data sources cannot be used concurrently in quality measure algorithms because they are not interoperable. Variation in the assignment of diagnostic and procedural codes further undermines the comparability of hospital performance data.

Conclusions: Claims-based measures do not capture clinical information surrounding care encounter. Hybrid measures that supplement claims data with limited chart reviews may provide hospitals an economically feasible method of submitting performance data without seriously compromising the validity of reported data.