Pay-for-Performance Incentive Program Linked to Improved CV Outcomes in Small EHR-Enabled Practices

Cardiovascular outcomes are modestly improved in small electronic health record (EHR)-enabled clinics participating in pay-for-performance incentive programs, according to a study published Sept. 10 in the Journal of the American Medical Association (JAMA).

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Previous research on pay-for-performance programs has focused on large-group practices. With new payment models evolving as part of health care reform, the authors of the study set out to determine the impact of financial incentive models in the small practice setting, where the majority of the country’s patients receive care.

The cluster-randomized study looked at 84 New York City primary care clinics with under 10 clinicians from April 2009 to March 2010. The intervention group clinics (n=42) had a combined total of 179,094 patients (mean, 4,592) and the control group clinics (n=42) had a total of 118,626 patients (mean, 3,042). All participating clinics were provided the same EHR software and assistance from quality improvement specialists as part of a New York City program.

Incentives for the intervention group were aligned with individual patient performance on clinical preventive services. These measures included aspirin or antithrombotic prescription, blood pressure control, cholesterol control and smoking cessation, also known as the “ABCS.”

Results showed that after a year, both the intervention group and the control group saw improved performance on all measures. However the intervention group performed significantly better on the aspirin or antithrombotic prescription for patients with diabetes or ischemic vascular disease (6 percent difference). As for blood pressure control, the incentivized clinics saw improved outcomes in hypertensive patients who did not have diabetes or ischemic vascular disease (5.5 percent difference); patients with hypertension and diabetes (7.8 percent difference); and hypertensive patients with diabetes or ischemic vascular disease (7.8 percent difference). Smoking cessation interventions were also improved in the intervention group (4.7 percent difference). The study did not find a statistically significant difference in cholesterol control for the two groups.

“An important aspect of this study was providing incentives to improve intermediate outcomes, rather than just processes, and doing so specifically in patients with more risk factors,” noted the authors. As for the impact of pay-for-performance for uninsured or Medicaid non-HMO patients, the study found that clinics in the intervention group performed better on all measures except cholesterol control; however, the differences were not statistically significant.

The authors concluded that “in the context of increasing uptake of EHRs with robust clinical management tools, small practices may be able to improve their quality performance in response to an incentive.”

Two additional articles published Sept. 10 in JAMA also focused on EHRs and physician incentives. The first study  found that the use of outpatient EHR systems among diabetes patients treated in an integrated delivery system reduced emergency department visits and hospitalizations, but not office visit rates.

Meanwhile, the second study  examined the impact of financial incentives on hypertension care and found that individual financial incentives, as compared to practice-level or combined incentives, were most effective in addressing blood pressure control. Additionally, guideline-recommended medication use was not improved with any of the three financial incentive models.

In a related editorial comment, Rowena J. Dolor, MD, MHS, and Kevin A. Schulman, MD, of the Duke University School of Medicine, Durham, NC, note “These results suggest that although there is some room for improvement of individual performance, these gaps represent systematic shortcomings rather than an issue with performance at the individual clinician level.”

Keywords: Health Care Reform, Medicaid, Risk Factors, Reimbursement, Incentive, Electronic Health Records, Quality Improvement, Cholesterol, Medically Uninsured, Hospitalization, Hypertension, Diabetes Mellitus, Primary Health Care, Smoking Cessation, Group Practice

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