IngentaConnect Getting Real Performance Out of Pay-for-Performance

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Abstract:

Context: Most private and public health insurers are implementing pay-for-performance (P4P) programs in an effort to improve the quality of medical care. This article offers a paradigm for evaluating how P4P programs should be structured and how effective they are likely to be.

Methods: This article assesses the current comprehensiveness of evidence-based medicine by estimating the percentage of outpatient medical spending for eighteen medical processes recommended by the Institute of Medicine.

Findings: Three conditions must be in place for outcomes-based P4P programs to improve the quality of care: (1) health insurers must not fully understand what medical processes improve health (i.e., the health production function); (2) providers must know more about the health production function than insurers do; and (3) health insurers must be able to measure a patient's risk-adjusted health. Only two of these conditions currently exist. Payers appear to have incomplete knowledge of the health production function, and providers appear to know more about the health production function than payers do, but accurate methods of adjusting the risk of a patient's health status are still being developed.

Conclusions: This article concludes that in three general situations, P4P will have a different impact on quality and costs and so should be structured differently. When information about patients' health and the health production function is incomplete, as is currently the case, P4P payments should be kept small, should be based on outcomes rather than processes, and should target physicians' practices and health systems. As information improves, P4P incentive payments could be increased, and P4P may become more powerful. Ironically, once information becomes complete, P4P can be replaced entirely by “optimal fee-for-service.”

Keywords: Pay-for-performance; reimbursement; quality

Document Type: Research article

DOI: 10.1111/j.1468-0009.2008.00528.x

Affiliations: 1: Cornell University; University of Pennsylvania; Nationwide Better Health; Merck; Eli Lilly