From Evidence-Based Economics to Economics-Based Evidence: Using Systematic Review to Inform the Design of Future Research

Evidence-Based Decisions and Economics: Health Care, Social Welfare, Education and Criminal Justice, Second Edition

Volumn , Issue , 2010, Pages 146-161

  Wilson, Ed ^a   Abrams, Keith ^b  

^a UNIVERSITY OF EAST ANGLIA   (United Kingdom)

^b UNIVERSITY OF LEICESTER   (United Kingdom)

Author keywords

CEAC cost effectiveness acceptability curve; Evidence gathering and decision making approaches; ICER incremental cost effectiveness ratio; Information analysis value; Informing future research design systematic review; QALY quality adjusted life year; Setting research priorities non economic and economic approaches

Indexed keywords

EID: 84886521587     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1002/9781444320398.ch12     Document Type: Chapter

References (63)

1. National Institute for Health and Clinical Excellence (NICE). Guide to the Methods of Technology Appraisal. London: National Institute for Health and Clinical Excellence, 2008.
2. Fenwick E, Claxton K, Sculpher M. Representing uncertainty: the role of cost-effectiveness acceptability curves. Health Economics 2001; 10(8): 779-787.
3. Claxton K. The irrelevance of inference: a decision-making approach to the stochastic evaluation of health care technologies. Journal of Health Economics 1999; 18(3): 341-364.
4. Raiffa H, Schlaifer R. Applied Statistical Decision Theory. Boston: Harvard Business School, 1961.
5. Claxton K, Posnett J. An economic approach to clinical trial design and research priority-setting. Health Economics 1996; 5(6): 513-524.
6. Willan AR, Pinto EM. The value of information and optimal clinical trial design. Statistics in Medicine 2005; 24(12): 1791-1806.
7. Ades AE, Lu G, Claxton K. Expected value of sample information calculations in medical decision modeling. Medical Decision Making 2004; 24(2): 207-227.
8. Banta HD, Thacker SB. The case for reassessment of heal th care technology: once is not enough. Journal of the American Medical Association 1990; 264(2): 235-240.
9. Fenwick E, Claxton K, Sculpher M, Briggs A. Improving the Efficiency and Relevance of Health Technology Assess ment: the role of decision analytic modelling (CHE Discussion Paper No. 179). York: Centre for Health Economics, 2000.
10. Sculpher M, Drummond M, Buxton M. The iterative use of economic evaluation as part of the process of health technology assessment. Journal of Health Services Research and Policy 1997; 2(1): 26-30.
11. Sculpher MJ, Claxton K, Drummond M, McCabe C. Whither trial-based economic evaluation for health care decision making? Health Economics 2006; 15(7): 677-687.
12. Griffin S, Claxton K, Sculpher M. Decision analysis for resource allocation in health care. Journal of Health Services Research and Policy 2008; 13(S3): 23-30.
13. Briggs AH. Handling uncertainty in cost-effectiveness models. Pharmacoeconomics 2000; 17(5): 479-500.
14. Buxton MJ, Drummond MF, van Hout BA, et al. Modelling in economic evaluation: an unavoidable fact of life. Health Economics 1997; 6(3): 221-227.
15. Fleurence RL, Torgerson DJ. Setting priorities for research. Health Policy 2004; 69(1): 1-10.
16. Gross CP, Anderson GF, Powe NR. The relation between funding by the National Institutes of Health and the burden of disease. New England Journal of Medicine 1999; 340(24): 1881-1887.
17. Michaud CM, Murray CJ, Bloom BR. Burden of disease-implications for future research. Journal of the American Medical Association 2001; 285(5): 535-539.
18. Wetterslev J, Thorlund K, Brok J, Gluud C. Trial sequential analysis may establish when firm evidence is reached in cumulative meta-analysis. Journal of Clinical Epidemiology 2008; 61(1): 64-75.
19. Armitage P. Sequential analysis in therapeutic trials. Annual Review of Medicine 1969; 20: 425-430.
20. Pocock S. Group sequential methods in the design and analysis of clinical trials. Biometrika 1977; 64(2): 191-199.
21. Townsend J, Buxton M. Cost effectiveness scenario analysis for a proposed trial of hormone replacement therapy. Health Policy 1997; 39(3): 181-194.
22. Eppel T, von Winterfeldt D. Value-of-information analysis for nuclear waste storage tanks. Decision Analysis 2008; 5(3): 157-167.
23. Yokota F, Thompson KM. Value of information analysis in environmental health risk management decisions: past, present, and future. Risk Analysis 2004; 24(3): 635-650.
24. Yokota F, Gray G, Hammitt JK, Thompson KM. Tiered chemical testing: a value of information approach. Risk Analysis 2004; 24(6): 1625-1639.
25. Forsberg O, Guttormsen A. The value of information in salmon farming. Harvesting fish at the right time. Aquaculture Economics and Management 2006; 10(3): 183-200.
26. Oksendal B. The value of information in stochastic control and finance. Australian Economic Papers 2005; 44(4): 352-364.
27. Claxton K, Ginnelly L, Sculpher M, Philips Z, Palmer S. A pilot study on the use of decision theory and value of information analysis as part of the NHS Health Technology Assessment programme. Health Technology Assessment 2004; 8(31): 1-103.
28. Claxton K, Eggington S, Ginnelly L, et al. A Pilot Study of Value of Information Analysis to Support Research Recommendations for NICE (CHE Research Paper No. 4). York: Centre for Health Economics, 2005.
29. Colbourn TE, Asseburg C, Bojke L, et al. Preventive strategies for group B streptococcal and other bacterial infections in early infancy: cost effectiveness and value of information analyses. British Medical Journal 2007; 335(7621): 655.
30. Bojke L, Hornby E, Sculpher M. A comparison of the cost effectiveness of pharmacotherapy or surgery (laparoscopic fundoplication) in the treatment of GORD. Pharmacoeconomics 2007; 25(10): 829-841.
31. Wailoo AJ, Sutton AJ, Cooper NJ, et al. Cost-effectiveness and value of information analyses of neuraminidase inhibitors for the treatment of influenza. Value in Health 2008; 11(2): 160-171.
32. Grant A, Wileman S, Ramsay C, et al., on behalf of the REFLUX Trial Group. The effectiveness and cost-effectiveness of minimal access surgery amongst people with gastrooesophageal reflux disease-a UK collaborative study. The REFLUX Trial. Health Technology Assessment 2008; 12(31): 1-181.
33. Castelnuovo E, Thompson-Coon J, Pitt M, et al. The costeffectiveness of testing for hepatitis C in former injecting drug users. Health Technology Assessment 2006; 10(32): 1-93.
34. Garside R, Pitt M, Somerville M, Stein K, Price A, Gilbert N. Surveillance of Barrett's oesophagus: exploring the uncertainty through systematic review, expert workshop and economic modelling. Health Technology Assessment 2006; 10(8): 1-158.
35. Ginnelly L, Claxton K, Sculpher MJ, Golder S. Using value of information analysis to inform publicly funded research priorities. Applied Health Economics and Health Policy 2005; 4(1): 37-46.
36. Henriksson M, Lundgren F, Carlsson P. Informing the efficient use of health care and health care research resources-the case of screening for abdominal aortic aneurysm in Sweden. Health Economics 2006; 15(12): 1311-1322.
37. Iglesias CP, Claxton K. Comprehensive decision-analytic model and Bayesian value-of-information analysis: pentoxifylline in the treatment of chronic venous leg ulcers. Pharmacoeconomics 2006; 24(5): 465-478.
38. Philips Z, Claxton KP, Palmer S, Bojke L, Sculpher MJ. Priority setting for research in health care: an application of value of information analysis to glycoprotein IIb/Illa antagonists in non-ST elevation acute coronary syndrome. International Journal of Technology Assessment in Health care 2006; 22(3): 379-387.
39. Robinson M, Palmer S, Sculpher M, et al. Cost-effectiveness of alternative strategies for the initial medical management of non-ST elevation acute coronary syndrome: systematic review and decision-analytical modelling. Health Technology Assessment 2005; 9(27): 1-158.
40. Spiegelhalter DJ, Abrams KR, Myles JP. Bayesian approaches to clinical trials and health care evaluation. In: Senn S, Barnett V (eds) Statistics in Practice. Chichester: John Wiley, 2004.
41. Claxton KP, Sculpher MJ. Using value of information analysis to prioritise health research: some lessons from recent UK experience. Pharmacoeconomics 2006; 24(11): 1055-1068.
42. Bojke L, Claxton K, Palmer S, Sculpher M. Defining and Characterising Structural Uncertainty in Decision Analytic Models (CHE Research Paper No. 9). York: Centre for Health Economics, 2006.
43. Drummond M, Sculpher M, Torrance G, O'Brien B, Stoddart G. Chapter 9.2.2: Economic evaluation using decision analytic modelling: the need to reflect all appropriate evidence. In: Methods for the Economic Evaluation of Health care Programmes, 3rd edn. Oxford: Oxford University Press, 2005.
44. Sackett DL, Rosenberg WM, Gray JA, Haynes RB, Richardson WS. Evidence based medicine: what it is and what it isn't. British Medical Journal 1996; 312(7023): 71-72.
45. O'Connor D, Green S, Higgins JPT (eds). Defining the review question and developing criteria for including studies. In: Higgins JPT, Green S (eds) Cochrane Handbook of Systematic Reviews of Interventions. Version 5.0.1 (updated September 2008). Oxford: Cochrane Collaboration, 2008.
46. Gurusamy K, Samraj K, Gluud C, Wilson E, Davidson BR. Meta-analysis of randomised controlled trials on the safety and effectiveness of early versus delayed laparoscopic cholecystectomy for acute cholecystitis. British Journal of Surgery 2010; 97(2):141-50.
47. Wilson EC, Gurusamy K, Samraj K, Davidson BR. Cost-utility and value of information analysis of early versus delayed laparoscopic cholecystectomy for acute cholecystitis. British Journal of Surgery 2010; 97(2):210-9
48. O'Hagan A, Oakley J. SHELF: the Sheffield Elicitation Framework. Sheffield: SHELF, 2008. Available from: http://tonyohagan.co.uk/shelf.
49. Cooper NJ, Sutton AJ, Abrams KR, Turner D, Wailoo A. Comprehensive decision analytical modelling in economic evaluation: a Bayesian approach. Health Economics 2004; 13(3): 203-226.
50. Philips Z, Claxton K, Palmer S. The half-life of truth: what are appropriate time horizons for research decisions? Medical Decision Making 2008; 28(3): 287-299.
51. Eckermann S, Willan AR. Time and expected value of sample information wait for no patient. Value in Health 2008; 11(3): 522-526.
52. Brennan A, Kharroubi S, O'Hagan A, Chilcott J. Calculating partial expected value of perfect information via Monte Carlo sampling algorithms. Medical Decision Making 2007; 27(4): 448-470.
53. Tappenden P, Chilcott JB, Eggington S, Oakley J, McCabe C. Methods for expected value of information analysis in complex health economic models: developments on the health economics of interferon-beta and glatiramer acetate for multiple sclerosis. Health Technology Assessment 2004; 8(27): 1-78.
54. Karnon J. Planning the efficient allocation of research funds: an adapted application of a non-parametric Bayesian value of information analysis. Health Policy 2002; 61(3): 329-347.
55. Stevenson MD, Oakley J, Chilcott JB. Gaussian process modeling in conjunction with individual patient simulation modeling: a case study describing the calculation of costeffectiveness ratios for the treatment of established osteoporosis. Medical Decision Making 2004; 24(1): 89-100.
56. Griffin S, Claxton K, Hawkins N, Sculpher M. Probabilistic analysis and computationally expensive models: necessary and required? Value in Health 2006; 9(4): 244-252.
57. Eckermann S, Willan AR. The option value of delay in health technology assessment. Medical Decision Making 2008; 28(3): 300-305.
58. Eckermann S, Willan AR. Expected value of information and decision making in HTA. Health Economics 2007; 16(2): 195-209.
59. Eckermann S, Willan AR. Globally optimal trial design for local decision making. Health Economics 2009; 18(2): 203-216.
60. Deeks JJ, Dinnes J, d'Amico R, et al., for the International Stroke Trial Collaborative Group, European Carotid Surgery Trial Collaborative Group. Evaluating non-randomised intervention studies. Health Technology Assessment 2003; 7(27): 1-173.
61. MacLehose RR, Reeves BC, Harvey IM, Sheldon TA, Russell IT, Black AM. A systematic review of comparisons of effect sizes derived from randomised and non-randomised studies. Health Technology Assessment 2000; 4(34): 1-154.
62. Shavit O, Leshno M, Goldberger A, Shmueli A, Hoffman A. It's time to choose the study design! Net benefit analysis of alternative study designs to acquire information for evaluation of health technologies. Pharmacoeconomics 2007; 25(11): 903-911.
63. Rossouw JE, Anderson GL, Prentice RL, et al., for the Writing Group for the Women's Health Initiative Investigators. Risks and benefits of estrogen plus progestin in healthy postmenopausal women: principal results from the Women's Health Initiative randomized controlled trial. Journal of the American Medical Association 2002; 288(3): 321-333.