Cost-effectiveness and the Medicare budget

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PAYERS/RESEARCHERS: How should Medicare decide whether to expand coverage to its beneficiaries to include a new medical technology, or a new application of an existing technology? According to the Centers for Medicare & Medicaid Services (CMS), Medicare coverage is “limited to items and services that are reasonable and necessary for the diagnosis or treatment of an illness or injury.”[1] Millions of lives and billions of dollars can be at stake, depending on how CMS determines whether a technology is reasonable and necessary.

Although the effectiveness of a technology in diagnosing or treating a disease is an important factor in a coverage decision, cost-effectiveness analysis is not formally considered by CMS, despite the long-standing concern that Medicare spending is growing at an unsustainable rate. The concerns range from skepticism about the methods used in cost-effectiveness analyses to fears that such analyses could be used to ration care.

Perhaps the best-known critique of cost-effectiveness methodology was delivered by Kassirer and Angell in a 1994 editorial in the New England Journal of Medicine.[2] They pointed out that cost-effectiveness analysis is a modeling exercise that depends critically on the data and the assumption used. Consequently, there can be ambiguity in the results, and various studies could yield different conclusions about the cost-effectiveness of a particular technology.

That is certainly true, but hardly a disqualification. The study by Pyenson and colleagues in this issue of American Health & Drug Benefits is a case in point.[3] Their meticulous analysis depends critically on assumptions regarding the incidence of disease, the rate at which high-risk individuals would use low-dose computed tomography (LDCT) screening for lung cancer, the rate of subsequent treatment, the cost of such screening and subsequent treatment, and other factors. Different assumptions—such as those regarding the rate of overdiagnosis[4] and subsequent testing and treatment that could have been avoided—could result in higher estimated costs than these investigators find.

Clinical trials are not immune to such uncertainty, despite their methodologic purity. Actual patient populations and providers who care for them cannot be counted on to do everything according to the research protocol. Any analysis of the costs and benefits of a technology before its general adoption is a prediction, not a certainty.

POLICYMAKERS: The real issue is how the results of a cost-effectiveness analysis are used. Policymakers have distanced themselves from any hint of government rationing of health care. In establishing the Patient-Centered Outcomes Research Institute, Congress prohibited the US Secretary of Health and Human Services from using a cost-effectiveness standard to determine coverage or payment by Medicare.[5] Nonetheless, there remains a concern that budgetary pressures could increasingly favor technologies with low estimated costs per quality-adjusted life-year, without sufficient flexibility to account for variations in the health needs of patients.

Ironically, cost-effectiveness analyses may not lead to reductions in Medicare spending.[6] The coverage process is like an iceberg: it focuses on new technologies, which are likely to account for a small fraction of Medicare spending, while largely ignoring services that are already covered and account for the bulk of its spending. It is simply not feasible to do a full review of all past coverage decisions. As a result, there is a built-in bias toward more—not less—spending, regardless of the analytic tools used to drive coverage decisions.

The best strategy is the obvious one. Medicare should use all of the information that is available in its coverage decisions, including cost-effectiveness analysis. For technologies that offer great potential benefits but also great potential cost, coverage with evidence development—temporary coverage targeted at specific patient populations, which allows detailed data collection on all aspects of the treatment—could be a useful approach.

The present study by Pyenson and colleagues, which is focused on patients with lengthy histories of heavy smoking who are most likely to develop lung cancer, demonstrates the need for Medicare coverage to pair the LDCT technology with the population most likely to benefit from it. The coverage decision takes us only part of the way to that goal. Both patients and the Medicare program rely on the physician to make that judgment at the point of service.

1. Centers for Medicare & Medicaid Services. Medicare coverage determination process. Updated November 27, 2013. www.cms.gov/Medicare/Coverage/DeterminationProcess/index.html. Accessed August 9, 2014.
2. Kassirer JP, Angell M. The Journal’s policy on cost-effectiveness analyses. N Engl J Med. 1994;331:669-670.
3. Pyenson BS, Henschke CI, Yankelevitz DF, et al. Offering lung cancer screening to high-risk Medicare beneficiaries saves lives and is cost-effective: an actuarial analysis. Am Health Drug Benefits. 2014;7:272-282.
4. Patz EF Jr, Pinsky P, Gatsonis C, et al; for the NLST Overdiagnosis Manuscript Writing Team. Overdiagnosis in low-dose computed tomography screening for lung cancer. JAMA Intern Med. 2014;174:269-274. Erratum in: JAMA Intern Med. 2014;174:828.
5. The Patient Protection and Affordable Care Act, HR 3590, 111th Congress, 2nd Session (2010), §6301.
6. Neumann PJ, Rosen AB, Weinstein MC. Medicare and cost-effectiveness analysis. N Engl J Med. 2005;353:1516-1522.

 

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