Can Risk Score Alerts Improve Office Care for Chest Pain?

The evaluation of ambulatory patients with chest pain is a challenging and serious problem, accounting for a significant proportion of all outpatient visits. High risk patients may go undetected, resulting in missed diagnoses of acute myocardial ischemia, while low risk patients may be subject to unnecessary evaluations. To substantially improve the evaluation and treatment of outpatients with acute chest pain syndromes, new strategies need to be developed in the primary care setting to risk stratify symptomatic patients and direct appropriate care. Our prior work demonstrates that an elevated Framingham Risk Score (at least 10%) reliably identifies patients with chest pain in the primary care setting who are at high risk for acute myocardial infarction.

This study will implement and evaluate electronic risk alerts to risk stratify outpatients with chest pain and present this information to primary care clinicians within the context of an electronic health record. The intervention will take place within Harvard Vanguard Medical Associates, a multispecialty integrated group practice with 140 primary care physicians caring for approximately 300,000 patients at 14 centers in eastern Massachusetts. With a randomized, controlled study design, the study has three specific aims:

• To identify predictors of risk-appropriate evaluation and treatment of patients presenting to primary care offices with acute chest pain, including race and sex.
• To determine whether rates of appropriate evaluation and treatment of patients with acute chest pain can be improved through the use of point-of-care electronic risk alerts that provide individual patient cardiac risk profiles and tailored evaluation and treatment recommendations to primary care clinicians.
• To perform a cost analysis for the provision of electronic decision support for patients with acute chest pain.

This study has important implications for determining how the treatment of outpatients with chest pain syndromes can be optimized through the innovative use of electronic decision support, while documenting the cost implications of such a strategy. This work will also provide a model for how ambulatory practices across the country can use electronic health records to present real-time patient risk information to clinicians with the goal of improving patient safety and quality, which has important implications for both acute and chronic care.