Bending the Medicare Cost Curve for Physicians' Services: Lessons Learned from Canada
Department of Pediatrics, Stanford University School of Medicine, c/o Program in Human Biology Building 20, Main Quad Stanford University, Stanford, CA, 94305-2160, USA, .Journal of General Internal Medicine (Impact Factor: 3.42). 05/2012; 27(11):1555-9. DOI: 10.1007/s11606-012-2091-8
In 1997 Congress created the Sustainable Growth Rate (SGR) formula for the payment of physicians under Part B of Medicare. SGR established a target rate of growth for aggregate costs of physician services under Part B, linked to growth in overall GDP. If growth in aggregate Part B costs exceeds the target, the rate at which physicians are paid in the following year is to be reduced by a corresponding amount. In SGR, Congress and the U.S. medical profession jointly confront a policy dilemma with no clear solution. For several years running, Congress has elected to postpone cuts in payment to physicians required under SGR. Absent further Congressional action, in 2013 physicians' fees under Part B of Medicare will be reduced by more than 30 %. The historical roots of SGR suggest that a potential solution lies in shifting to regional expenditure targets-an approach applied successfully in Canada in the 1970s when Canadian Medicare confronted rising physician fees. The commission that created what was to become SGR was aware of the lessons learned in Canada, and recommended that they also be applied to U.S. Medicare.
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ABSTRACT: Although the analysis of real-world data is the foundation of comparative effectiveness analysis, not all clinical questions are easily approached with patient-derived information. Decision analysis is a set of modeling and analytic tools that simulate treatment and disease processes, including the incorporation of patient preferences, thus generating optimal treatment strategies for varying patient, disease, and treatment conditions. Although decision analysis is informed by evidence-derived outcomes, its ability to test treatment strategies under different conditions that are realistic but not necessarily reported in the literature makes it a useful and complementary technique to more standard data analysis. Similarly, cost-effectiveness analysis is a discipline in which the relative costs and benefits of treatment alternatives are rigorously compared. With the well-recognized increase in highly technical, costly radiation therapy technologies, the cost-effectiveness of these different treatments would come under progressively more scrutiny. In this review, we discuss the theoretical and practical aspects of decision analysis and cost-effectiveness analysis, providing examples that highlight their methodology and utility.
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