Electronic health records and ambulatory quality of care

Abstract

Context: The US Federal Government is investing up to $29 billion in incentives for meaningful use of electronic health records (EHRs). However, the effect of EHRs on ambulatory quality is unclear, with several large studies finding no effect.

Objective: To determine the effect of EHRs on ambulatory quality in a community-based setting.

Design: Cross-sectional study, using data from 2008.

Setting: Ambulatory practices in the Hudson Valley of New York, with a median practice size of four physicians.

Participants: We included all general internists, pediatricians and family medicine physicians who: were members of the Taconic Independent Practice Association, had patients in a data set of claims aggregated across five health plans, and had at least 30 patients per measure for at least one of nine quality measures selected by the health plans.

Intervention: Adoption of an EHR.

Main outcome measures: We compared physicians using EHRs to physicians using paper on performance for each of the nine quality measures, using t-tests. We also created a composite quality score by standardizing performance against a national benchmark and averaging standardized performance across measures. We used generalized estimation equations, adjusting for nine physician characteristics.

Key results: We included 466 physicians and 74,618 unique patients. Of the physicians, 204 (44 %) had adopted EHRs and 262 (56 %) were using paper. Electronic health record use was associated with significantly higher quality of care for four of the measures: hemoglobin A1c testing in diabetes, breast cancer screening, chlamydia screening, and colorectal cancer screening. Effect sizes ranged from 3 to 13 percentage points per measure. When all nine measures were combined into a composite, EHR use was associated with higher quality of care (sd 0.4, p = 0.008).

Conclusions: This is one of the first studies to find a positive association between EHRs and ambulatory quality in a community-based setting.

Figure 1.

Derivation of the study sample. * The 7 Hudson Valley counties were: Dutchess, Orange, Putnam, Rockland, Sullivan, Ulster and Westchester. † Primary Care Providers were MDs or DOs in General Internal Medicine, Pediatrics and Family Medicine.

Figure 2.

Logic for attributing patients to primary care physicians. *See Figure 1 for a derivation of the study sample.