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Applying a Risk-Adjustment Framework to Primary Care: Can We Improve on Existing Measures?

¹ Center for Health Quality, Outcomes and Economic Research, Bedford, Mass; Boston University School of Public Health, Department of Health Services, Boston, Mass
² Center for Health Services and Policy Research, University of British Columbia, Vancouver, British Columbia
³ Department of Health Care and Epidemiology, University of British Columbia, Vancouver, British Columbia
⁴ Academic Technology Center, Bentley College, Waltham, Mass

CORRESPONDING AUTHOR Amy K. Rosen, PhD, Senior Research Scientist, Center for Health Quality, Outcomes and Economic Research, Bedford VAMC (152), 200 Springs Road, Bedford MA 01730, akrosen{at}bu.edu.

ABSTRACT

Outcome-based performance measurement and prospective payment are common features of the current managed care environment. Increasingly, primary care clinicians and health care organizations are being asked to assume financial risk for enrolled patients based on negotiated capitation rates. Therefore, the need for methods to account for differences in risk among patients enrolled in primary care organizations has become critical.

Although current risk-adjustment measures represent significant advances in the measurement of morbidity in primary care populations, they may not adequately capture all the dimensions of patient risk relevant to primary care. We propose a risk-adjustment framework for primary care that incorporates clinical features related to patients’ health status and nonclinical factors related to patients’ health behaviors, psychosocial factors, and social environment.

Without this broad perspective, clinicians with more unhealthy and more challenging populations are at risk of being inadequately compensated and inequitably compared with peers. The risk-adjustment framework should also be of use to health care organizations that have been mandated to deliver high-quality primary care but are lacking the necessary tools.

Key Words: Primary Care • Risk Adjustment • Managed Care • Case-mix • Provider Profiling

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