Cost-effectiveness and evidence evaluation as criteria for coverage policy

Health Affairs

Volumn 23, Issue SUPPL., 2004, Pages

  Garber, Alan M ^a,b,c  

^a VA PALO ALTO HEALTH CARE SYSTEM   (United States)

^b STANFORD UNIVERSITY SCHOOL OF MEDICINE   (United States)

^c STANFORD UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CONSUMER; COST EFFECTIVENESS ANALYSIS; DECISION MAKING; EMPLOYER; EVIDENCE BASED MEDICINE; GOVERNMENT; HEALTH CARE COST; HEALTH INSURANCE; REVIEW; UNITED STATES;

EID: 4644368843     PISSN: 02782715     EISSN: None     Source Type: Journal    
DOI: 10.1377/hlthaff.W4.284     Document Type: Review

References (51)

1. See A.M. Garber, "Evidence-Based Coverage Policy," Health Affairs 20, no. 5 (2001): 62-82.
2. Classic descriptions are in K.J. Arrow, "Uncertainty and the Welfare Economics of Medical Care," American Economic Review 53, no. 5 (1963): 941-973; and M.V. Pauly, "The Economics of Moral Hazard: Comment," American Economic Review 58, no. 3 (1968): 531-537.
3. Classic descriptions are in K.J. Arrow, "Uncertainty and the Welfare Economics of Medical Care," American Economic Review 53, no. 5 (1963): 941-973; and M.V. Pauly, "The Economics of Moral Hazard: Comment," American Economic Review 58, no. 3 (1968): 531-537.
4. See B.A. Weisbrod, "The Health Care Quadrilemma: An Essay on Technological Change, Insurance, Quality of Care and Cost Containment," Journal of Economic Literature 29, no. 2 (1991): 523-532; and S.T. Burner and D.R. Waldo, "National Health Expenditure Projections, 1994-2005," Health Care Financing Review 16, no. 4 (1995): 221-242.
5. See B.A. Weisbrod, "The Health Care Quadrilemma: An Essay on Technological Change, Insurance, Quality of Care and Cost Containment," Journal of Economic Literature 29, no. 2 (1991): 523-532; and S.T. Burner and D.R. Waldo, "National Health Expenditure Projections, 1994-2005," Health Care Financing Review 16, no. 4 (1995): 221-242.
6. See I. Ehrlich and G.S. Becker, "Market Insurance, Self-Insurance, and Self-Protection," Journal of Political Economy 80, no. 4 (1972): 623-648.
7. See discussions in L.A. Bergthold, "Medical Necessity: Do We Need It?" Health Affairs 14, no. 4 (1995): 180-190; S.J. Singer and L.A. Bergthold, "Prospects for Improved Decision Making about Medical Necessity," Health Affairs 20, no. 1 (2001): 200-206; and L.A. Bergthold et al., "Using Evidence and Cost in Managed Care Decision-Making" (Stanford, Calif.: Center for Health Policy/Center for Primary Care and Outcomes Research, Stanford University, 2002), available online at content. healthaffairs.org/cgi/content/full/hlthaff.w4.284v1/DC2.
8. See discussions in L.A. Bergthold, "Medical Necessity: Do We Need It?" Health Affairs 14, no. 4 (1995): 180-190; S.J. Singer and L.A. Bergthold, "Prospects for Improved Decision Making about Medical Necessity," Health Affairs 20, no. 1 (2001): 200-206; and L.A. Bergthold et al., "Using Evidence and Cost in Managed Care Decision-Making" (Stanford, Calif.: Center for Health Policy/Center for Primary Care and Outcomes Research, Stanford University, 2002), available online at content. healthaffairs.org/cgi/content/full/hlthaff.w4.284v1/DC2.
9. See discussions in L.A. Bergthold, "Medical Necessity: Do We Need It?" Health Affairs 14, no. 4 (1995): 180-190; S.J. Singer and L.A. Bergthold, "Prospects for Improved Decision Making about Medical Necessity," Health Affairs 20, no. 1 (2001): 200-206; and L.A. Bergthold et al., "Using Evidence and Cost in Managed Care Decision-Making" (Stanford, Calif.: Center for Health Policy/Center for Primary Care and Outcomes Research, Stanford University, 2002), available online at content. healthaffairs.org/cgi/content/full/hlthaff.w4.284v1/DC2.
10. See D.M. Eddy, "Benefit Language: Criteria That Will Improve Quality While Reducing Costs," Journal of the American Medical Association 275, no. 8 (1996):650-657; and D.M. Eddy, "Investigational Treatments: How Strict Should We Be?" Journal of the American Medical Association 278, no. 3 (1997): 179-185.
11. See D.M. Eddy, "Benefit Language: Criteria That Will Improve Quality While Reducing Costs," Journal of the American Medical Association 275, no. 8 (1996):650-657; and D.M. Eddy, "Investigational Treatments: How Strict Should We Be?" Journal of the American Medical Association 278, no. 3 (1997): 179-185.
12. The processes Blue Cross Blue Shield uses are described in S. Gleeson, "Blue Cross and Blue Shield Association Initiatives in Technology Assessment," in Adopting New Medical Technology, ed. A.C. Gelijns and H.V. Dawkins (Washington: National Academies Press, 1994). The Medicare Coverage Advisory Committee (MCAC) is described in Health Care Financing Administration, "Procedures for Making Coverage Decisions," Federal Register 64, no. 80 (1999): 22619-22625. There are undoubtedly many reasons for the acceptance of evidence-based processes. Among them are the recognition that there are widespread variations in practice patterns that cannot be explained by patient characteristics alone and that clinical trials and other high-quality clinical studies are now common, so it seems more feasible than in the past to meet an evidence standard.
13. The processes Blue Cross Blue Shield uses are described in S. Gleeson, "Blue Cross and Blue Shield Association Initiatives in Technology Assessment," in Adopting New Medical Technology, ed. A.C. Gelijns and H.V. Dawkins (Washington: National Academies Press, 1994). The Medicare Coverage Advisory Committee (MCAC) is described in Health Care Financing Administration, "Procedures for Making Coverage Decisions," Federal Register 64, no. 80 (1999): 22619-22625. There are undoubtedly many reasons for the acceptance of evidence-based processes. Among them are the recognition that there are widespread variations in practice patterns that cannot be explained by patient characteristics alone and that clinical trials and other high-quality clinical studies are now common, so it seems more feasible than in the past to meet an evidence standard.
14. See U.S. Preventive Services Task Force, Guide to Clinical Preventive Services, 2d ed. (Baltimore: Williams and Wilkins, 1996); and Canadian Task Force on the Periodic Health Examination, "The Periodic Health Examination: Canadian Task Force on the Periodic Health Examination," Canadian Medical Association Journal 121, no. 9 (1979): 1193-1254.
15. See U.S. Preventive Services Task Force, Guide to Clinical Preventive Services, 2d ed. (Baltimore: Williams and Wilkins, 1996); and Canadian Task Force on the Periodic Health Examination, "The Periodic Health Examination: Canadian Task Force on the Periodic Health Examination," Canadian Medical Association Journal 121, no. 9 (1979): 1193-1254.
16. See J. Concato, N. Shah, and R.I. Horwitz, "Randomized, Controlled Trials, Observational Studies, and the Hierarchy of Research Designs," New England Journal of Medicine 342, no. 25 (2000): 1887-1892; K. Benson and A.J. Hartz, "A Comparison of Observational Studies and Randomized, Controlled Trials," New England Journal of Medicine 342, no. 25 (2000): 1878-1886; and M.A. Hlatky et al., "Comparison of Predictions Based on Observational Data with the Results of Randomized Controlled Clinical Trials of Coronary Artery Bypass Surgery," Journal of the American College of Cardiology 11, no. 2 (1988): 237-245.
17. See J. Concato, N. Shah, and R.I. Horwitz, "Randomized, Controlled Trials, Observational Studies, and the Hierarchy of Research Designs," New England Journal of Medicine 342, no. 25 (2000): 1887-1892; K. Benson and A.J. Hartz, "A Comparison of Observational Studies and Randomized, Controlled Trials," New England Journal of Medicine 342, no. 25 (2000): 1878-1886; and M.A. Hlatky et al., "Comparison of Predictions Based on Observational Data with the Results of Randomized Controlled Clinical Trials of Coronary Artery Bypass Surgery," Journal of the American College of Cardiology 11, no. 2 (1988): 237-245.
18. See J. Concato, N. Shah, and R.I. Horwitz, "Randomized, Controlled Trials, Observational Studies, and the Hierarchy of Research Designs," New England Journal of Medicine 342, no. 25 (2000): 1887-1892; K. Benson and A.J. Hartz, "A Comparison of Observational Studies and Randomized, Controlled Trials," New England Journal of Medicine 342, no. 25 (2000): 1878-1886; and M.A. Hlatky et al., "Comparison of Predictions Based on Observational Data with the Results of Randomized Controlled Clinical Trials of Coronary Artery Bypass Surgery," Journal of the American College of Cardiology 11, no. 2 (1988): 237-245.
19. Cost estimates are from J.A. DiMasi, R.W. Hansen, and H.G. Grabowski, "The Price of Innovation: New Estimates of Drug Development Costs," Journal of Health Economics 22, no. 3 (2003): 151-185.
20. See D. Moher, C.S. Dulberg, and G.A. Wells, "Statistical Power, Sample Size, and Their Reporting in Randomized Controlled Trials," Journal of the American Medical Association 272, no. 2 (1994): 122-124.
21. Increasing the number of patients enrolled is only one of the mechanisms to ensure a large enough number of observed events, which drive the power of the trial. For example, investigators can make great efforts to improve the completeness of reporting of all health events, and they can work to minimize the number of people who drop out of a trial or are lost to follow-up. Investigators also try to enroll only those patients who are likely to adhere to all aspects of demanding protocols for participation in the trial, improving the chances that the treatment will be used properly and its effects observed. These and other aspects of trial design that tend to increase statistical power, while increasing the credibility of study results, are labor-intensive.
22. For many devices, the evidence barrier (both to approval and to the entry of new competitors) has been much lower than for pharmaceuticals, so large, well-designed randomized trials are more common for drugs than for devices.
23. Evidence from the past ten to fifteen years suggests that team care - or "disease management" - is often the most effective approach to the management of chronic diseases. Chronic disease management typically requires selecting a portfolio of diagnostic, monitoring, and treatment strategies, tailored to the individual patient, rather than simply dispensing a medication and obtaining occasional laboratory tests. Although some programs use proprietary software or are provided by dedicated disease management companies, the key features of disease management are matters of public knowledge. Because the benefits of research in these strategies are difficult for any individual firm to capture, randomized trials of disease management are less common than trials of drugs and medical devices. Furthermore, reimbursement for disease management was slow to develop, especially among fee-for-service insurers. According to the McKinsey Global Health Care Productivity study, disease management for diabetes reduced costs of care and improved outcomes. Such programs were adopted earlier in the United Kingdom than in the United States; slower U.S. adoption seemed to reflect the absence of reimbursement for components of diabetes team care. See M.N. Baily and A.M. Garber, "Health Care Productivity," Brookings Papers on Economic Activity: Microeconomics (1997): 143-202.
24. See M.V. Pauly, "Should We Be Worried about High Real Medical Spending Growth in the United States?" Health Affairs, 8 January 2003, content.healthaffairs.org/cgi/content/abstract/hlthaff.w3.15 (7 April 2004); and Burner and Waldo, "National Health Expenditure Projections, 1994-2005."
25. See M.V. Pauly, "Should We Be Worried about High Real Medical Spending Growth in the United States?" Health Affairs, 8 January 2003, content.healthaffairs.org/cgi/content/abstract/hlthaff.w3.15 (7 April 2004); and Burner and Waldo, "National Health Expenditure Projections, 1994-2005."
26. See M.C. Weinstein and W.B. Stason, "Foundations of Cost-Effectiveness Analysis for Health and Medical Practices," New England Journal of Medicine 296, no. 13 (1977): 716-721; and D.M. Eddy, "Cost-Effectiveness Analysis: A Conversation with My Father," Journal of the American Medical Association 267, no. 12 (1992): 1669-1675.
27. See M.C. Weinstein and W.B. Stason, "Foundations of Cost-Effectiveness Analysis for Health and Medical Practices," New England Journal of Medicine 296, no. 13 (1977): 716-721; and D.M. Eddy, "Cost-Effectiveness Analysis: A Conversation with My Father," Journal of the American Medical Association 267, no. 12 (1992): 1669-1675.
28. See A.M. Garber et al., "Theoretical Foundations of Cost-Effectiveness Analysis," in Cost-Effectiveness in Health and Medicine, ed. M.R. Gold et al. (New York: Oxford University Press, 1996); and C.E. Phelps and A.I. Mushlin, "On the (Near) Equivalence of Cost Effectiveness and Cost Benefit Analysis," International Journal of Technology Assessment in Health Care 7, no. 1 (1991): 12-21.
29. See A.M. Garber et al., "Theoretical Foundations of Cost-Effectiveness Analysis," in Cost-Effectiveness in Health and Medicine, ed. M.R. Gold et al. (New York: Oxford University Press, 1996); and C.E. Phelps and A.I. Mushlin, "On the (Near) Equivalence of Cost Effectiveness and Cost Benefit Analysis," International Journal of Technology Assessment in Health Care 7, no. 1 (1991): 12-21.
30. A.M. Garber and C.E. Phelps, "Economic Foundations of Cost-Effectiveness Analysis," Journal of Health Economics 16, no. 1 (1997): 1-31.
31. S. Birch and A. Gafni, "Cost-Effectiveness Ratios: In a League of Their Own," Health Policy 28, no. 2 (1994): 133-141; and M. Drummond, J. Mason, and G. Torrance, "Cost-Effectiveness League Tables: Think of the Fans," Health Policy 31, no. 3 (1995): 231-238.
32. S. Birch and A. Gafni, "Cost-Effectiveness Ratios: In a League of Their Own," Health Policy 28, no. 2 (1994): 133-141; and M. Drummond, J. Mason, and G. Torrance, "Cost-Effectiveness League Tables: Think of the Fans," Health Policy 31, no. 3 (1995): 231-238.
33. A comprehensive listing of cost-effectiveness ratios, with comments on characteristics of the studies used to generate the numbers, can be found at the Harvard Center for Risk Analysis Web site, www.hsph.harvard.edu/cearegistry/ (6 May 2004).
34. See J.A. Kitzhaber, "Prioritising Health Services in an Era of Limits: The Oregon Experience," British Medical Journal 307, no. 6900 (1993): 373-377; D.M. Eddy, "Oregon's Methods: Did Cost-Effectiveness Analysis Fail?" Journal of the American Medical Association 266, no. 15 (1991): 2135-2141; and T.O. Tengs et al., "Oregon's Medicaid Ranking and Cost-Effectiveness: Is There Any Relationship?" Medical Decision Making 16, no. 2 (1996): 99-107.
35. See J.A. Kitzhaber, "Prioritising Health Services in an Era of Limits: The Oregon Experience," British Medical Journal 307, no. 6900 (1993): 373-377; D.M. Eddy, "Oregon's Methods: Did Cost-Effectiveness Analysis Fail?" Journal of the American Medical Association 266, no. 15 (1991): 2135-2141; and T.O. Tengs et al., "Oregon's Medicaid Ranking and Cost-Effectiveness: Is There Any Relationship?" Medical Decision Making 16, no. 2 (1996): 99-107.
36. See J.A. Kitzhaber, "Prioritising Health Services in an Era of Limits: The Oregon Experience," British Medical Journal 307, no. 6900 (1993): 373-377; D.M. Eddy, "Oregon's Methods: Did Cost-Effectiveness Analysis Fail?" Journal of the American Medical Association 266, no. 15 (1991): 2135-2141; and T.O. Tengs et al., "Oregon's Medicaid Ranking and Cost-Effectiveness: Is There Any Relationship?" Medical Decision Making 16, no. 2 (1996): 99-107.
37. The definition of "cost" often determines whether an intervention is considered "expensive," and to whom. Most pharmaceutical products have prices that are very high compared with the marginal cost of production. If "cost" in the cost-effectiveness analysis refers to the retail price, such a drug will often pass an evidence criterion more readily than a cost-effectiveness criterion. If the cost of production is high relative to the price, as would often be the case for a complex surgical procedure, it may be relatively difficult to pass an evidence criterion, since there would be so little return to an investment in studies demonstrating effectiveness. This would even be true for a procedure that was highly cost-effective.
38. The survey was mailed to the medical directors of 346 eligible managed care plans in 49 states and the District of Columbia; the 66 percent of plans that responded were responsible for the care of 77 percent of the members of the 346 plans in the sample. The survey instrument was a closed-ended mail questionnaire consisting of forty-two questions divided into seven topic areas, including evaluation of clinical effectiveness and evaluation of cost and cost-effectiveness. Details of the survey and its methods are in Bergthold et al., "Using Evidence and Cost."
39. D.M. Eddy, "The Use of Evidence and Cost-Effectiveness by the Courts: How Can It Help Improve Health Care?" Journal of Health Politics, Policy and Law 26, no. 2 (2001): 387-408; and P.D. Jacobson and M.L. Kanna, "Cost-Effectiveness Analysis in the Courts: Recent Trends and Future Prospects," Journal of Health Politics, Policy and Law 25, no. 2 (2001): 291-326.
40. D.M. Eddy, "The Use of Evidence and Cost-Effectiveness by the Courts: How Can It Help Improve Health Care?" Journal of Health Politics, Policy and Law 26, no. 2 (2001): 387-408; and P.D. Jacobson and M.L. Kanna, "Cost-Effectiveness Analysis in the Courts: Recent Trends and Future Prospects," Journal of Health Politics, Policy and Law 25, no. 2 (2001): 291-326.
41. The recommendations of the federally sponsored Panel on Cost-Effectiveness in Health and Medicine appear in Gold et al., eds., Cost-Effectiveness in Health and Medicine.
42. Leading studies of methods for valuing uncertainty appear in J. Mullahy and W.G. Manning, "Statistical Issues in Cost-Effectiveness Analysis," in Valuing Health Care: Costs, Benefits, and Effectiveness of Pharmaceuticals and Other Medical Technologies, ed. F. Sloan (New York: Cambridge University Press, 1994); B.J. O'Brien et al., "In Search of Power and Significance: Issues in the Design and Analysis of Stochastic Cost-Effectiveness Studies in Health Care," Medical Care 32, no. 2 (1994): 150-163; P. Wakker and M.P. Klaassen, "Confidence Intervals for Cost/Effectiveness Ratios," Health Economics 4, no. 5 (1995): 373-381; A. Briggs and M. Sculpher, "Sensitivity Analysis in Economic Evaluation: A Review of Published Studies," Health Economics 4, no. 5 (1995): 355-371; and A. Briggs, M. Sculpher, and M. Buxton, "Uncertainty in the Economic Evaluation of Health Care Technologies: The Role of Sensitivity Analysis," Health Economics 3, no. 2 (1994): 95-104.
43. Leading studies of methods for valuing uncertainty appear in J. Mullahy and W.G. Manning, "Statistical Issues in Cost-Effectiveness Analysis," in Valuing Health Care: Costs, Benefits, and Effectiveness of Pharmaceuticals and Other Medical Technologies, ed. F. Sloan (New York: Cambridge University Press, 1994); B.J. O'Brien et al., "In Search of Power and Significance: Issues in the Design and Analysis of Stochastic Cost-Effectiveness Studies in Health Care," Medical Care 32, no. 2 (1994): 150-163; P. Wakker and M.P. Klaassen, "Confidence Intervals for Cost/Effectiveness Ratios," Health Economics 4, no. 5 (1995): 373-381; A. Briggs and M. Sculpher, "Sensitivity Analysis in Economic Evaluation: A Review of Published Studies," Health Economics 4, no. 5 (1995): 355-371; and A. Briggs, M. Sculpher, and M. Buxton, "Uncertainty in the Economic Evaluation of Health Care Technologies: The Role of Sensitivity Analysis," Health Economics 3, no. 2 (1994): 95-104.
44. Leading studies of methods for valuing uncertainty appear in J. Mullahy and W.G. Manning, "Statistical Issues in Cost-Effectiveness Analysis," in Valuing Health Care: Costs, Benefits, and Effectiveness of Pharmaceuticals and Other Medical Technologies, ed. F. Sloan (New York: Cambridge University Press, 1994); B.J. O'Brien et al., "In Search of Power and Significance: Issues in the Design and Analysis of Stochastic Cost-Effectiveness Studies in Health Care," Medical Care 32, no. 2 (1994): 150-163; P. Wakker and M.P. Klaassen, "Confidence Intervals for Cost/Effectiveness Ratios," Health Economics 4, no. 5 (1995): 373-381; A. Briggs and M. Sculpher, "Sensitivity Analysis in Economic Evaluation: A Review of Published Studies," Health Economics 4, no. 5 (1995): 355-371; and A. Briggs, M. Sculpher, and M. Buxton, "Uncertainty in the Economic Evaluation of Health Care Technologies: The Role of Sensitivity Analysis," Health Economics 3, no. 2 (1994): 95-104.
45. Leading studies of methods for valuing uncertainty appear in J. Mullahy and W.G. Manning, "Statistical Issues in Cost-Effectiveness Analysis," in Valuing Health Care: Costs, Benefits, and Effectiveness of Pharmaceuticals and Other Medical Technologies, ed. F. Sloan (New York: Cambridge University Press, 1994); B.J. O'Brien et al., "In Search of Power and Significance: Issues in the Design and Analysis of Stochastic Cost-Effectiveness Studies in Health Care," Medical Care 32, no. 2 (1994): 150-163; P. Wakker and M.P. Klaassen, "Confidence Intervals for Cost/Effectiveness Ratios," Health Economics 4, no. 5 (1995): 373-381; A. Briggs and M. Sculpher, "Sensitivity Analysis in Economic Evaluation: A Review of Published Studies," Health Economics 4, no. 5 (1995): 355-371; and A. Briggs, M. Sculpher, and M. Buxton, "Uncertainty in the Economic Evaluation of Health Care Technologies: The Role of Sensitivity Analysis," Health Economics 3, no. 2 (1994): 95-104.
46. Leading studies of methods for valuing uncertainty appear in J. Mullahy and W.G. Manning, "Statistical Issues in Cost-Effectiveness Analysis," in Valuing Health Care: Costs, Benefits, and Effectiveness of Pharmaceuticals and Other Medical Technologies, ed. F. Sloan (New York: Cambridge University Press, 1994); B.J. O'Brien et al., "In Search of Power and Significance: Issues in the Design and Analysis of Stochastic Cost-Effectiveness Studies in Health Care," Medical Care 32, no. 2 (1994): 150-163; P. Wakker and M.P. Klaassen, "Confidence Intervals for Cost/Effectiveness Ratios," Health Economics 4, no. 5 (1995): 373-381; A. Briggs and M. Sculpher, "Sensitivity Analysis in Economic Evaluation: A Review of Published Studies," Health Economics 4, no. 5 (1995): 355-371; and A. Briggs, M. Sculpher, and M. Buxton, "Uncertainty in the Economic Evaluation of Health Care Technologies: The Role of Sensitivity Analysis," Health Economics 3, no. 2 (1994): 95-104.
47. Bergthold et al., "Using Evidence and Cost."
48. See N. Daniels and J.E. Sabin, Setting Limits Fairly: Can We Learn to Share Medical Resources? (New York: Oxford University Press, 2002).
49. M.V. Pauly and P.J. Held, "Benign Moral Hazard and the Cost-Effectiveness Analysis of Insurance Coverage," Journal of Health Economics 9, no. 4 (1990): 447-461.
50. B. Motheral and K. Fairman, "Effect of a Three-Tier Prescription Copay on Pharmaceutical and Other Medical Utilization," Medical Care 39, no. 12 (2001): 1293-1304.
51. A.M. Fendrick et al., "A Benefit-Based Copay for Prescription Drugs: Patient Contribution Based on Total Benefits, Not Drug Acquisition Cost," American Journal of Managed Care 7, no. 9 (2001): 861-867.