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The Generalisability of Pharmacoeconomic Studies

Issues and Challenges Ahead

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Abstract

Developing from a previous review, this article revisits the generalisability theme to summarise recent advances in methodology and provide an update of challenges faced by producers and users of pharmacoeconomic data. Our original evaluative criteria encompassed technical issues, applicability and transferability.

The technical elements of best practice are comparatively uncontroversial: choosing relevant alternatives; transparent reporting of methods and findings; accessing and applying the best-quality evidence; using best methods to synthesise data; and using deterministic sensitivity analysis to explore potential systematic bias whilst employing probabilistic sensitivity analysis to explore the influence of random error at the whole model level. The applicability of economic findings within their original policy context (e.g. national analyses based on generalisable within-country data) can be determined, provided that best practice guidelines for economic modelling are adhered to. The transferability of economic findings (from one policy setting to another, e.g. country, region, clinical setting or patient population) requires careful exploration of changes in resource implications, unit prices and outcomes, a process facilitated again by transparent reporting of methods, adjustment for baseline risk and potentially by recent statistical developments intended to deal with hierarchically structured data.

Although there is considerable consensus in the published literature about these key issues, limitations remain for economic analysis as implemented because of its opaqueness of method, failure to reflect the opportunity cost of decisions and lack of societal mandate. If the primary purpose of health economic evaluation is to help society to obtain the best value from limited resources, then, at a time when most technologically advanced societies need to engage with the realities of limited healthcare funding, technocratic solutions alone appear insufficient. Making health economic findings accessible to patients, clinicians and society, in the form of relevant narratives, will help this essential debate and expose assumptions underpinning economic analysis to broader critical inspection.

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References

  1. Mason J. The generalisability of pharmacoeconomic studies. Pharmacoeconomics 1997; 11: 503–514

    Article  PubMed  CAS  Google Scholar 

  2. Secretary of State for Health. National Health Service Act, 1977: directions to health authorities, primary care trusts and NHS trusts in England. London: Her Majesty’s Stationery Office (HMSO), 2001

    Google Scholar 

  3. Mason J, Drummond M, Torrance G. Some guidelines on the use of cost effectiveness league tables. BMJ 1993; 306: 570–572

    Article  PubMed  CAS  Google Scholar 

  4. Birch S, Gafni A. The ‘NICE’ approach to technology assessment: an economics perspective. Health Care Manag Sci 2004; 7: 35–41

    Article  PubMed  Google Scholar 

  5. Boulenger S, Nixon J, Drummond M, et al. Can economic evaluations be made more transferable? Eur J Health Econ 2005; 6: 334–336

    Article  PubMed  Google Scholar 

  6. Drummond MF, Jefferson TO. Guidelines for authors and peer reviewers of economic submissions to the BMJ: the BMJ Economic Evaluation Working Party. BMJ 1996; 313: 275–283

    Article  PubMed  CAS  Google Scholar 

  7. Garrison LP. The ISPOR Good Practice Modeling Principles: a sensible approach: be transparent, be reasonable. Value Health 2003; 6: 6–8

    Article  PubMed  Google Scholar 

  8. Bäumler E. In search of the magic bullet: great adventures in modern drug research. London: Thames and Hudson, 1966

  9. Drummond M, Sculpher MJ, Torrance GW, et al. Methods for the economic evaluation of health care programmes. 3rd ed. Oxford: Oxford University Press, 2005

    Google Scholar 

  10. Philips Z, Ginnelly L, Sculpher M, et al. Review of guidelines for good practice in decision-analytic modelling in health technology assessment. Health Technol Assess 2004; 8: iii–iv, ix-xi, 1-158

    PubMed  CAS  Google Scholar 

  11. Spiegelhalter DJ, Best NG. Bayesian approaches to multiple sources of evidence and uncertainty in complex cost-effectiveness modelling. Stat Med 2003; 22: 3687–3709

    Article  PubMed  Google Scholar 

  12. Briggs AH, Goeree R, Blackhouse G, et al. Probabilistic analysis of cost-effectiveness models: choosing between treatment strategies for gastroesophageal reflux disease. Med Decis Mak 2002; 22: 290–308

    Google Scholar 

  13. Bell CM, Urbach DR, Ray JG, et al. Bias in published cost effectiveness studies: systematic review. BMJ 2006; 332: 699–703

    Article  PubMed  Google Scholar 

  14. Kennedy WA, Laurier C, Malo JL, et al. Does clinical trial subject selection restrict the ability to generalize use and cost of health services to ‘real life’ subjects? Int J Technol Assess Health Care 2003; 19: 8–16

    Article  PubMed  Google Scholar 

  15. Raftery J, Roderick P, Stevens A. Potential use of routine databases in health technology assessment. Health Technol Assess 2005; 9: 1–106

    CAS  Google Scholar 

  16. Devlin N, Parkin D. Does NICE have a cost-effectiveness threshold and what other factors influence its decisions? A binary choice analysis. Health Econ 2004; 13: 437–452

    Article  PubMed  Google Scholar 

  17. Miners AH, Garau M, Fidan D, et al. Comparing estimates of cost effectiveness submitted to the National Institute for Clinical Excellence (NICE) by different organisations: retrospective study. BMJ 2005; 330: 65

    Article  PubMed  CAS  Google Scholar 

  18. Cairns J. Providing guidance to the NHS: the Scottish Medicines Consortium and the National Institute for Clinical Excellence compared. Health Policy 2006; 76: 134–143

    Article  PubMed  Google Scholar 

  19. Palmer S, Sculpher M, Philips Z, et al. Management of non-ST-elevation acute coronary syndromes: how cost-effective are glycoprotein IIb/IIIA antagonists in the UK National Health Service? Int J Cardiol 2005; 100: 229–240

    Article  PubMed  Google Scholar 

  20. Manca A, Rice N, Sculpher MJ, et al. Assessing generalisability by location in trial-based cost-effectiveness analysis: the use of multilevel models. Health Econ 2005; 14: 471–485

    Article  PubMed  Google Scholar 

  21. Grieve R, Nixon R, Thompson SG, et al. Using multilevel models for assessing the variability of multinational resource use and cost data. Health Econ 2005; 14: 185–196

    Article  PubMed  Google Scholar 

  22. Willan AR, Pinto EM, O’Brien BJ, et al. Country specific cost comparisons from multinational clinical trials using empirical Bayesian shrinkage estimation: the Canadian ASSENT-3 economic analysis. Health Econ 2005; 14: 327–338

    Article  PubMed  Google Scholar 

  23. Reed SD, Dillingham PW, Briggs AH, et al. A Bayesian approach to aid in formulary decision making: incorporating institution-specific cost-effectiveness data with clinical trial results. Med Decis Making 2003; 23: 252–264

    Article  PubMed  Google Scholar 

  24. Birch S, Gafni A. Economics and the evaluation of health care programmes: generalisability of methods and implications for generalisability of results. Health Policy 2003; 64: 207–219

    Article  PubMed  Google Scholar 

  25. Barbieri M, Drummond M, Willke R, et al. Variability of cost-effectiveness estimates for pharmaceuticals in Western Europe: lessons for inferring generalizability. Value Health 2005; 8: 10–23

    Article  PubMed  Google Scholar 

  26. Lang DL, Lopert R, Hill SR. Use of pharmacoeconomics in prescribing research: part 5. Modelling: beyond clinical trials. J Clin Pharm Ther 2003; 28: 433–439

    Article  PubMed  CAS  Google Scholar 

  27. Glenny AM, Altman DG, Song F, et al. Indirect comparisons of competing interventions. Health Technol Assess 2005; 9: 1–134

    PubMed  CAS  Google Scholar 

  28. Claxton K. Efficient fourth hurdle regulation: an application of value of information analysis to a sample of health technologies [abstract]. Med Decis Making 2001; 6: 530

    Google Scholar 

  29. Maynard A, Bloor K, Freemantle N. Challenges for the National Institute for Clinical Excellence. BMJ 2004; 329: 227–229

    Article  PubMed  Google Scholar 

  30. Weinstein MC, O’Brien B, Hornberger J, et al. Principles of good practice for decision analytic modeling in health-care evaluation. Report of the ISPOR task force on good research practices: modeling studies. Value Health 2003; 6: 9–17

    Article  PubMed  Google Scholar 

  31. Detsky AS. Guidelines for economic analysis of pharmaceutical products: a draft document for Ontario and Canada. Pharmacoeconomics 1993; 3: 354–361

    Article  PubMed  CAS  Google Scholar 

  32. Evers S, Goossens M, de Vet H, et al. Criteria list for assessment of methodological quality of economic evaluations: consensus on health economic criteria. Int J Technol Assess Health Care 2005; 21: 240–245

    PubMed  Google Scholar 

  33. Mullins CD, Ogilvie S. Emerging standardization in pharmacoeconomics. Clin Ther 1998; 20: 1194–1202

    Article  PubMed  CAS  Google Scholar 

  34. Williams A. Health economics: the end of clinical freedom? BMJ 1988; 297: 1183–1186

    Article  PubMed  CAS  Google Scholar 

  35. Eddy DM. A manual for assessing health practices and designing practice policies: the explicit approach. Philadelphia (PA): American College of Physicians, 1992

    Google Scholar 

  36. National Institute for Clinical Excellence. Guide to the methods of technology appraisal. London: NICE, 2004

    Google Scholar 

Download references

Acknowledgements

The authors received no funding in the preparation of this article. Professor J.M. Mason received funding from the NICE between 2001 and 2004 to provide advice on methodological issues and develop clinical guidelines for the NHS in England and Wales. The authors have no conflicts of interest that are directly relevant to the content of this article.

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Authors and Affiliations

  1. School for Health, Wolfson Research Unit, University of Durham, Queen’s Campus, University Boulevard, Stockton-on-Tees, TS17 6BH, UK

    James M. Mason

  2. Centre for Health Economics, University of York, Heslington, York, UK

    Anne R. Mason

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  1. James M. Mason
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  2. Anne R. Mason
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Correspondence to James M. Mason.

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Mason, J.M., Mason, A.R. The Generalisability of Pharmacoeconomic Studies. Pharmacoeconomics 24, 937–945 (2006). https://doi.org/10.2165/00019053-200624100-00001

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