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MGTECON 332/Health Research and Policy 392/Medical Information Science 432:
Analysis of Costs, Risks and Benefits of Health Care

This page provides readings in companion to your class reader.

Required text: Methods for the economic evaluation of health care programmes, 3rd ed. Jackson Library: 1 copy on Reserve; Lane Medical Library RA410.5.D77 2005

Recommended texts:
Cost-Effectiveness in Health and Medicine. Jackson Library: 2 copies on Reserve; Lane Medical Library RA410.5 .C688 1996
Health Economics, 3rd ed. Jackson Library: 1 copy on Reserve

The article assignments, by lecture topics:

• Valuing Output I
• Decision Analysis
• Introduction to Markov and Related Modeling Techniques
• Evaluating Efficacy
• Diagnosis of Coronary Artery Disease
• Probabilistic Sensitivity Analysis and Modeling
• HIV Detection Strategies
• Cost-Effectiveness of Implantable Cardioverter Defibrillators
• Cost-Effectiveness in Developing Countries
• Pharmaceutical Industry Perspective ON CEA
• Medicare Coverage Decision Making

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Valuing Output I

Tengs TO, Wallace A. One Thousand Health-Related Quality-of-Life Estimates. Medical Care, 2000; 38(6):583-637
Objective. Analysts performing cost-effectiveness analyses often do not have the resources to gather original quality-of-life (QOL) weights. Furthermore, variability in QOL for the same health state hampers the comparability of cost-effectiveness analyses. For these reasons, opinion leaders such as the Panel on Cost-Effectiveness in Health and Medicine have called for a national repository of QOL weights. Some authors have responded to the call by performing large primary studies of QOL. We take a different approach, amassing existing data with the hope that it will be combined responsibly in meta-analytic fashion. Toward the goal of developing a national repository of QOL weights to aid cost-effectiveness analysts, 1,000 health-related QOL estimates were gathered from publicly available source documents. Methods. To identify documents, we searched databases and reviewed the bibliographies of articles, books, and government reports. From each document, we extracted information on the health state, QOL weight, assessment method, respondents, and upper and lower bounds of the QOL scale. Detailed guidelines were followed to ensure consistency in data extraction. Results. We identified 154 documents yielding 1,000 original QOL weights. There was considerable variation in the weights assessed by different authors for the same health state. Methods also varied: 51% of authors used direct elicitation (standard gamble, time tradeoff, or rating scale), 32% estimated QOL based on their own expertise or that of others, and 17% used health status instruments. Conclusions. This comprehensive review of QOL data should lead to more consistent use of QOL weights and thus more comparable cost-effectiveness analyses.
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Bell CM, Chapman RH, Stone PW, Sadberg EA, Neuman PJ. An off-the-shelf help list: a comprehensive catalog of preference scores from published cost-utility analysis. Medical Decision Making, 2001; 21:288-294
Purpose. The Panel on Cost-Effectiveness in Health and Medicine recommends an organized collection of preference measure values for health states that can be used in cost utility analyses (CUAs). The authors sought to construct a catalog of preference scores from published CUAs, organize the catalog by clinical categories, and identify methods of preference score assessment. Method. The authors systematically searched Medline and other databases to identify original CUAs published through 1997. Information was abstracted on the health state descriptions, corresponding preference scores, method of preference score elicitation, and the source of the estimate. Results. Two hundred twenty-eight CUAs were appraised. The authors found 949 health states and corresponding preference scores. Most frequently, health states pertained to the circulatory system (21.7%), health states were valued by experts (35.8%), and values were derived through community-based preference scores (23.5%). Conclusion. A catalog of preference scores for health states can beconstructed. The catalog may provide a useful reference tool for producers and consumers of CUAs but also underscores the methodologic variation and inconsistencies present in the field.
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Decision Analysis

Detsky, AS, Naglie G, Krahn MD, Naimark D, Redelmeier DA. Primer on medical decision analysis: Part 1- Getting started. Medical Decision Making, 1997; 17:123-125
This paper is Part 1 of a five-part series covering practical issues in the performance of decision analysis. The intended audience is individuals who are teaming how to perform decision analyses, not just read them. The series assumes familiarity with the basic concepts of decision analysis. It imparts many of the recommendations the authors have learned in teaching a one-semester course in decision analysis to graduate students. Part 1 introduces the topic and covers questions such as choosing an appropriate question, determining the tradeoff between accuracy and simplicity, and deciding on a time frame.
View article [ PDF 75KB]

Sculpher M, Fenwick E, Claxton K. Assessing Quality in Decision Analytic Cost-Effectiveness Models: A Suggested Framework and Example of Application. PharmacoEconomics, 2000; 17(5): 461-477
Despite the growing use of decision analytic modelling in cost-effectiveness analysis, there is a relatively small literature on what constitutes good practice in decision analysis. The aim of this paper is to consider the concept of 'validity' and 'quality' in this area of evaluation, and to suggest a framework by which quality can be demonstrated on the part of the analyst and assessed by the reviewer and user. The paper begins by considering the purpose of cost-effectiveness models and argues that the their role is to identify optimum treatment decisions in the context of uncertainty about future states of the world. The issue of whether such models can be defined as 'scientific' is considered. The notion that decision analysis undertaken at time t can only be considered scientific if its outputs closely predict the results of a trial undertaken at time t+1 is rejected as this ignores the need to make decisions on the basis of currently available evidence. Rather, the scientific characteristic of decision models is based on the fact that, in principle at least, such analyses can be falsified by comparison of two states of the world, one where resource allocation decisions are based on formal decision analysis and the other where such decisions are not. This section of the paper also rejects the idea of exact codification of scientific method in general, and of decision analysis in particular, as this risks rejecting potentially valuable models, may discourage the development of novel methods and can distort research priorities. However, the paper argues that it is both possible and necessary to develop a framework for assessing quality in decision models. Building on earlier work, various dimensions of quality in decision modelling are considered: model structure (disease states, options, time horizon and cycle length); data (identification, incorporation, handling uncertainty); and consistency (internal and ...
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Introduction to Markov and Related Modeling Techniques

Optional reading: Naimark D, Krahn MD, Naglie G, Redelmeier DA, Detsky AS. Primer onmedical decision analysis: Part 5- Working with Markov processes. Medical Decision Making, 1997; 178:152-159
Clinical decisions often have long-term implications. Analysts encounter difficulties when employing conventional decision-analytic methods to model these scenarios. This occurs because probability and utility variables often change with time and conventional decision trees do not easily capture this dynamic quality. A Markov analysis performed with current computer software programs provides a flexible and convenient means of modeling long-term scenarios. However, novices should be aware of several potential pitfalls when attempting to use these programs. When deciding how to model a given clinical problem, the analyst must weigh the simplicity and clarity of a conventional tree against the fidelity of a Markov analysis. In direct comparisons, both approaches gave the same qualitative answers
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Evaluating Efficacy

Optional reading: Phelps C. The methodologic foundations of studies of the appropriateness of medical care. New England Journal of Medicine, 1993; 329:1241-5
As health care costs continue to increase rapidly, both health care providers and consumers have expressed concern that the additional resources used for health services do not provide commensurate increases in health benefits. Adding fuel to this concern, a number of disquieting studies have estimated the rates of "inappropriate" use in a variety of settings of a variety of procedures such as coronary angiography, carotid endarterectomy, endoscopy, and coronary-artery bypass graft surgery. The estimated rates of inappropriate treatment have ranged from about 15 to 30 percent, reaching as high as 40 percent …
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Diagnosis of Coronary Artery Disease

Garber, AM, Solomon NA. Cost-effectiveness of alternative test strategies for the diagnosis of coronary artery disease. Annals of Internal Medicine, 1999; 130(9):719-728
Background: The appropriate roles for several diagnostic tests for coronary disease are uncertain. Objective: To evaluate the cost-effectiveness of alternative approaches to diagnosis of coronary disease. Design: Meta-analysis of the accuracy of alternative diagnostic tests plus decision analysis to assess the health outcomes and costs of alternative diagnostic strategies for patients at intermediate pretest risk for coronary disease. Data Sources: Studies of test accuracy that met inclusion criteria; published information on treatment effectiveness and disease prevalence. Target Population: Men and women 45, 55, and 65 years of age with a 25% to 75% pretest risk for coronary disease. Time Horizon: 30 years. Perspective: Societal. Interventions: Diagnostic strategies were initial angiography and initial testing with one of five noninvasive tests-exercise treadmill testing, planar thallium imaging, single-photon emission computed tomography (SPECT), stress echocardiography, and positron emission tomography (PET)-followed by coronary angiography if noninvasive test results were positive. Testing was followed by observation, medical treatment, or revascularization. Outcome Measures: Life-years, quality-adjusted lifeyears (QALYs), costs, and costs per QALY. Results of Base-Case Analysis: Life expectancy varied little with the initial diagnostic test; for a 55-year-old man, the best-performing test increased life expectancy by 7 more days than the worst-performing test. More sensitive tests increased QALYs more. Echocardiography improved health outcomes and reduced costs relative to stress testing and planar thallium imaging. The incremental costeffectiveness ratio was $75 000/ QALY for SPECT relative to echocardiography and was greater than $640 000 for PET relative to SPECT. Compared with SPECT, immediate angiography had an incremental cost-effectiveness ratio of $94 000/QALY. Results of Sensitivity Analysis: Qualitative findings varied little with age, sex, pretest probability of disease, or the test indeterminacy rate. Results varied most with sensitivity to severe coronary disease. Conclusions: Echocardiography, SPECT, and immediate angiography are cost-effective alternatives to PET and other diagnostic approaches. Test selection should reflect local variation in test accuracy.
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Probabilistic Sensitivity Analysis and Modeling

Briggs AH, Goeree R, Blackhouse G, and O'Brien, B. Probabilistic Analysis of Cost-Effectiveness Models: Choosing between Treatment Strategies for Gastroesophageal Reflux Disease. Medical Decision Making, 2002; 22: 290-308
When choosing between mutually exclusive treatment options,it is common to construct a cost-effectiveness frontieron the cost-effectiveness plane that represents efficientpoints from among the treatment choices. Treatment optionsinternal to the frontier are considered inefficient and are excludedeither by strict dominance or by appealing to the principleof extended dominance. However, when uncertainty isconsidered, options excluded under the baseline analysismay form part of the cost-effectiveness frontier. By adopting aBayesian approach, where distributions for model parametersare specified, uncertainty in the decision concerningwhich treatment option should be implemented is addresseddirectly. The approach is illustrated using an example from arecently published cost-effectiveness analysis of differentpossible treatment strategies for gastroesophageal reflux disease.It is argued that probabilistic analyses should be encouragedbecause they have potential to quantify the strengthof evidence in favor of particular treatment choices.
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Claxton K, Sculpher M, McCabe C, Briggs A, Akehurst R, Buxton M, Brazier J and O'Hagan T. Probabilistic sensitivity analysis for NICE technology assessment: not an optional extra. Health Economics, 2005; 14: 339-347
Recently the National Institute for Clinical Excellence (NICE) updated its methods guidance for technology assessment. One aspect of the new guidance is to require the use of probabilistic sensitivity analysis with all cost-effectiveness models submitted to the Institute. The purpose of this paper is to place the NICE guidance on dealing with uncertainty into a broader context of the requirements for decision making; to explain the general approach that was taken in its development; and to address each of the issues which have been raised in the debate about the role of probabilistic sensitivity analysis in general. The most appropriate starting point for developing guidance is to establish what is required for decision making. On the basis of these requirements, the methods and framework of analysis which can best meet these needs can then be identified. It will be argued that the guidance on dealing with uncertainty and, in particular, the requirement for probabilistic sensitivity analysis, is justified by the requirements of the type of decisions that NICE is asked to make. Given this foundation, the main issues and criticisms raised during and after the consultation process are reviewed. Finally, some of the methodological challenges posed by the need fully to characterise decision uncertainty and to inform the research agenda will be identified and discussed.
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Detsky AS, Naglie G, Krahn MD, Redelmeier DA, Naimark D. Primer on medical decision analysis: Part 2- Building a tree. Medical Decision Making, 1997; 17:126-135
This part of a five-part series covering practical issues in the performance of decision analysis outlines the basic strategies for building decision trees. The authors offer six recommendations for building and programming decision trees. Following these six recommendations will facilitate performance of the sensitivity analyses required to achieve two goals. The first is to find modeling or programming errors, a process known as "debugging" the tree. The second is to determine the robustness of the qualitative conclusions drawn from the analysis.
View article [ PDF 320KB]

Naglie G, Krahn MD, Naimark D, Redelmeier DA, Detsky AS. Primer on medical decision analysis: Part 3- Estimating probabilities and utilities. Medical Decison Making, 1997; 17:136-141
This paper describes how to estimate probabilities and outcome values for decision trees. Probabilities are usually derived from published studies, but occasionally are derived from existing databases, primary data collection, or expert judgment. Outcome values represent quantitative estimates of the desirability of the outcome states, and are often expressed as utility values between 0 and 1. Utility values for different health states can be derived from the published literature, from direct measurement in appropriate subjects, or from expert opinion. Methods for assigning utilities to complex outcome states are described, and the concept of quality-adjusted life years is introduced.
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Krahn MD, Naglie G, Naimark D, Redelmeier DA, Detsky AS. Primer on medical decision analysis: Part 4- Analyzing the model and interpreting the results. Medical Decision Making, 1997; 17: 142-151
This paper is the fourth of a five-part series that describes the principles of construction and evaluation of valid decision models. In this review, the authors describe the key principles of detecting and eliminating structural and programming errors in decision trees (debugging). In addition, they ffer guidelines to facilitate the interpretation of analytic results of decision models.
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HIV Detection Strategies

Sanders GD, Bayoumi AM, SundaramV, Bilir SP, Neukermans CP, Rydzak CE, Douglass LR, Lazzeroni LC, Holodniy M, Owens DK. Cost effectiveness of screening for HIV in the era of highly active antiretroviral therapy. New England Journal of Medicine, 2005; 352(6): 570-85
Background. The costs, benefits, and cost-effectiveness of screening for human immunodeficiency virus (HIV) in health care settings during the era of highly active antiretroviral therapy (HAART) have not been determined. Methods. We developed a Markov model of costs, quality of life, and survival associated with an HIV-screening program as compared with current practice. In both strategies, symptomatic patients were identified through symptom-based case finding. Identified patients
started treatment when their CD4 count dropped to 350 cells per cubic millimeter. Disease progression was defined on the basis of CD4 levels and viral load. The likelihood of sexual transmission was based on viral load, knowledge of HIV status, and efficacy of counseling. Results. Given a 1 percent prevalence of unidentified HIV infection, screening increased life expectancy by 5.48 days, or 4.70 quality-adjusted days, at an estimated cost of $194 per screened patient, for a cost-effectiveness ratio of $15,078 per quality-adjusted life-year. Screening cost less than $50,000 per quality-adjusted life-year if the prevalence of unidentified HIV infection exceeded 0.05 percent. Excluding HIV transmission, the costeffectiveness of screening was $41,736 per quality-adjusted life-year. Screening every five years, as compared with a one-time screening program, cost $57,138 per quality adjusted life-year, but was more attractive in settings with a high incidence of infection. Our results were sensitive to the efficacy of behavior modification, the benefit of early identification and therapy, and the prevalence and incidence of HIV infection. Conclusions. The cost-effectiveness of routine HIV screening in health care settings, even in relatively low-prevalence populations, is similar to that of commonly accepted interventions, and such programs should be expanded.
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Owens DK, Harris RA, Scott P, Nease RF: Screening surgeons for HIV infection: a cost-effectiveness analysis. Annals of International Medicine, 1995; 122:641-652
Objective. To determine the cost-effectiveness of a policy to screen surgeons for human immunodeficiency virus (HIV) infection to prevent transmission of HIV to patients having invasive procedures. Design. Cost-effectiveness analysis. Results. A one-time national screening program would identify approximately 37 surgeons with HIV infection (range, 28 to 423 surgeons) and would prevent approximately 4.3 infections (range, 1.9 to 21.3 infections) in patients treated by infected surgeons and 0.9 infections (range, 0 to 12.9 infections) in sexual partners of infected surgeons at a direct cost of $8.1 million and an induced cost of approximately $44 million. It would result in expenditures of $458 000 per year of life saved (range, $147 000 to $687 000 per year of life saved), whereas an annual screening program would result in expenditures of approximately $1.1 million per year of life saved (range, $338 000 to $1 886 000 per year of life saved). If the prevalence of HIV infection in surgeons is estimated to be three times our base-case estimate (an increase from 0.1% to 0.3%), annual screening would result in expenditures of approximately $741 000 per year of life saved. If the probability of seroconversion after a patient is exposed to a contaminated instrument is increased to 5.0% from our base-case estimate of 0.29%, an annual screening program would still cost more than $228 000 per year of life saved. Conclusion. Screening surgeons for HIV to prevent transmission of HIV to patients having invasive procedures requires expenditures per year of life saved that are considerably in excess of those of most accepted health interventions. Surveillance studies of patients treated by surgeons infected with HIV should be continued to confirm that transmission of HIV to patients having invasive procedures is rare.
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Cost-Effectiveness of Implantable Cardioverter Defibrillators

Sanders GD, Hlatky MA, Owens DK. Cost-effectiveness of implantable cardioverter defibrillators. New England Journal of Medicine, 2005; 353(14):1471-80
Background. Eight randomized trials have evaluated whether the prophylactic use of an implantable cardioverter–defibrillator (ICD) improves survival among patients who are at risk for sudden death due to left ventricular systolic dysfunction but who have not had a life-threatening ventricular arrhythmia. We assessed the cost-effectiveness of the ICD in the populations represented in these primary-prevention trials. Methods. We developed a Markov model of the cost, quality of life, survival, and incremental cost-effectiveness of the prophylactic implantation of an ICD, as compared with control therapy, among patients with survival and mortality rates similar to those in each of the clinical trials. We modeled the efficacy of the ICD as a reduction in the relative risk of death on the basis of the hazard ratios reported in the individual clinical trials. Results. Use of the ICD increased lifetime costs in every trial. Two trials — the Coronary Artery Bypass Graft (CABG) Patch Trial and the Defibrillator in Acute Myocardial Infarction Trial (DINAMIT) — found that the prophylactic implantation of an ICD did not reduce the risk of death and thus was both more expensive and less effective than control therapy. For the other six trials — the Multicenter Automatic Defibrillator Implantation Trial (MADIT) I, MADIT II, the Multicenter Unsustained Tachycardia Trial (MUSTT), the Defibrillators in Non-Ischemic Cardiomyopathy Treatment Evaluation (DEFINITE) trial, the Comparison of Medical Therapy, Pacing, and Defibrillation in Heart Failure (COMPANION) trial, and the Sudden Cardiac Death in Heart Failure Trial (SCD-HeFT) — the use of an ICD was projected to add between 1.01 and 2.99 quality-adjusted life-years (QALY) and between $68,300 and $101,500 in cost. Using base-case assumptions, we found that the cost-effectiveness of the ICD as compared with control therapy in these six populations ranged from $34,000 to $70,200 per QALY gained. Sensitivity analyses showed that this cost-effectiveness ratio would remain below $100,000 per QALY as long as the ICD reduced mortality for seven or more years. Conclusions. Prophylactic implantation of an ICD has a cost-effectiveness ratio below $100,000 per QALY gained in populations in which a significant device-related reduction in mortality has been demonstrated.
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Cost-Effectiveness in Developing Countries

43 Way to save the world. The Economist, July 2, 2005; 376(8433): 69-70
Half a billion dollars is not to be sneezed at, even when divided 43 ways. And that, give or take a few million, was the sum at stake when a committee of the medical world's great and good decided who will take on what have become known as the Grand Challenges in Global Health. Most of the money to meet these challenges--$450m of it--comes from the Bill and Melinda Gates Foundation, the world's richest charity. The Wellcome Trust, Britain's richest, has chipped in $27m, and the Canadian government has added $4.5m. The 43 winners were announced on June 28th. The Grand Challenges are 14 serious technical obstacles to a healthier world that were picked by the committee in the autumn of 2003, after its members had gone through several thousand submissions from the world's medical scientists. The winning projects are all, if not entirely new, at least still in their preliminary phases, and the sponsors expect a lot of attrition along the way. The Grand Challenge winners are being developed specifically for use in poor countries.
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Pharmaceutical Industry Perspective on CEA

Sharpe P, Keelin T. How SmithKline Beecham Makes Better Resource-Allocation Decisions. Harvard Business Review, March-April 1998:76(2):45-57
This article reports that Smithkline Beecham Corp. (SB)was spending more than half a billion dollars per year on research and development, the lifeblood of any pharmaceuticals company. Ever since the 1989 merger that created the company, however, SB believed that it had been spending too much time arguing about how to value its research and development projects and not enough time figuring out how to make them more valuable. With more projects successfully reaching late-stage development, where the resource requirements are greatest, the demands for funding were growing. SB's executives felt an acute need to rationalize their portfolio of development projects. The patent on its blockbuster drug Tagamet was about to expire, and the company was preparing for the impending squeeze: it had to meet current earnings targets and at the same time support the research and evelopment that would create the company's future revenue streams. A critical company process can become politicized when strong-willed, charismatic project leaders heat out their less competitive colleagues for resources.
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Pharmacoeconomic Guidelines Around the World

From International Society for Pharmacoeconomics & Outcomes Research.

Medicare Coverage Decision Making

Garber AM, Cost-effectiveness and evidence evaluation as criteria for coverage decisions and benefit design. Health Affairs Web Exclusive, May 19, 2004
Private health plans and government health insurance programs in the United States base their coverage decisions on evidence criteria, rather than explicit cost-effectiveness criteria. As health spending continues to grow rapidly, however, approaches to coverage policy that ignore costs fail to meet the needs of consumers, employers, health plans, and federal and state governments. I describe the role of evidence-based criteria in formal coverage decision making and contrast the ways that these criteria differ from cost-effectiveness criteria. Finally, I discuss options for incorporating considerations of cost-effectiveness into coverage policy and other aspects of benefit design.
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Tunis SR. Economic analysis in healthcare decisions. American Journal of Managed Care, 2004; 10(5):301-304
The potential use of economic analysis in healthcare decision making has strong natural appeal as it becomes clear how an individual's healthcare decisions can affect, through insurance coverage, the ability of others to obtain the care they need. Healthcare spending in the United States continues to ise faster than inflation and worker salaries. Financial pressures force difficult decisions about whether to increase premiums, reduce benefits, or reallocate resources. Using analytic methods that are designed to maximize the value of the health services purchased for a given level of spending makes intuitive sense. The failure to adopt such a framework given the current economic realities in healthcare seems, at best, unwise. The two articles by Neumann and Bloom that appear elsewhere in this issue illustrate this point quite well. The application of economic analysis in healthcare decision making, however, particularly with regard to medical necessity, has proven to be highly controversial. Evidence varies regarding the extent to which decision makers actually use economic analysis, a point that Bernard Bloom discusses in this issue of the Journal. The reluctance to explicitly address financial issues in this context may well reflect a "deep-seated abhorrence of limits and of the corporate or government officials who impose them," and Peter Neumann's article cogently presents this case.1 In addition, the discussion of the use of cost-effectiveness analysis (CEA) can benefit from a broader understanding of other important sources of tension within the policy process through which decisions are made about coverage of specificitems and services. Significant disagreement exists over the appropriate locus for medical decision making, the integrity of the process used by payers to make these decisions, and the proper role of scientific evidence.
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Tunis SR. Why Medicare has not established criteria for coverage decisions.New England Journal of Medicine, May 20, 2004; 350(21):2196-2198
Decisions about medical coverage by Medicare specify the forms of technology and services that the program will pay for on behalf of its 42 million beneficiaries. These decisions often have far-reaching effects through their influence on the policies of other public and private payers in determining medical necessity. For the nearly four decades since Medicare was created in 1965, coverage decisions have been based on section 1862(a)(1)(A) of the statute that enacted the program: "Notwithstanding any other provision of this title, no payment may be made … for any expenses incurred for items or services which … are not reasonable and necessary for the diagnosis or treatment of illness or injury." No additional language from Congress explaining "reasonable and necessary" accompanied the 1965 law, and no documents providing any interpretation were issued until 1977. There is a common understanding among federal officials who participated in drafting the legislation that the "reasonable and necessary" provision was modeled on language from an Aetna health insurance policy for federal employees. Although there was concern at the time that services of unknown value would sometimes be used, payers generally accepted the judgments of physicians at face value. 1 Therefore, a precise definition of medical necessity would not be required.
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