Skip to main content
Log in

Pharmacoeconomic Models in Disease Management

A Guide for the Novice or the Perplexed

  • Primer
  • Published:
Disease Management and Health Outcomes

Abstract

Clinical trials and meta-analyses of trials are models of clinical reality. A pharmacoeconomic model is a logical, quantitative blend of therapeutic and/or disease management strategies, evidence-based clinical outcomes, patient survival data and/or quality-of-life (utility) data, epidemiological data and costs. Pharmacoeconomic models can link evidence-based medicine to the local environment. They require locally appropriate resource consumption and cost information, so that the economic outcomes (e.g. cost and cost-effectiveness of therapy) are current and locally relevant.

Decision analytical models represent a sequence of chance events and decisions over time and are appropriate for acute episodes of illness, whereas Markov models represent recurring health states and are useful in describing chronic illness. Epidemiological models combine clinical trial data with observational data, and can be used for predicting the efficiency of risk management strategies such as vaccination and antihypertensive therapy. User-friendly commercial modelling software is available.

For maximum credibility, pharmacoeconomic models should build on validated disease management protocols and/or landmark clinical trials or meta-analyses of trials. They should also adhere to published standards for economic analysis, including the use of locally relevant comparators, discounting to present value, extensive sensitivity analysis, and appropriate health utility values. Models should be presented fully with the logical structure plus all decision probabilities and/or state transition probabilities plus unit costs and resource consumption. A standard reporting format for publication in peer-reviewed journals has been suggested.

Models can be timely, adaptable, relatively inexpensive, and often the only way to obtain appropriate information on the clinical, economic and humanistic outcomes of disease management protocols. However, without due care they can be obscure and open to bias and misunderstanding. Both the analyst and the user must avoid mistaking obscurity for profundity.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Office of Health Economics. The pros and cons of modelling in economic evaluation. London: Office of Health Economics briefing, 1997 May: 33.

    Google Scholar 

  2. Nuijten MJC, Starzewski J. Applications of modelling studies. Pharmacoeconomics 1998; 13 (3): 289–91.

    Article  PubMed  CAS  Google Scholar 

  3. Bootman JL, Townsend RJ, McGhan WF. Principles of pharmacoeconomics. 2nd ed. Cincinnati (OH): Harvey-Whitney Book Company, 1995.

    Google Scholar 

  4. Drammond MF, Stoddart GL, Torrance GW. Methods for the economic evaluation of health care programmes. 2nd ed. Oxford: Oxford Medical Publications, 1997.

    Google Scholar 

  5. Freund DA, Dittus RS. Principles of pharmacoeconomic analysis of drug therapy. Pharmacoeconomics 1992; 1 (1): 21–32.

    Article  Google Scholar 

  6. Siegel JE, Torrance GW, Russell LB, at el. Guidelines for pharmacoeconomic studies: recommendations from the Panel on cost effectiveness in health and medicine. Pharmacoeconomics 1997; 11 (2): 158–68.

    Article  Google Scholar 

  7. Buxton MJ, Drammond MF, van Hout BA, et al. Modelling in economic evaluation: an unavoidable fact of life. Health Econ 1997; 6: 217–27.

    Article  PubMed  CAS  Google Scholar 

  8. Briggs A, Sculpher M. An introduction to Markov modelling for economic evaluation. Pharmacoeconomics 1998; 13 (4): 397–409.

    Article  PubMed  CAS  Google Scholar 

  9. Gold MR, Siegel JE, Russell LB, et al. Cost effectiveness in health and medicine. New York: Oxford University Press, 1996.

    Google Scholar 

  10. Sheldon TA. Problems of using modelling in the economic evaluation of health care. Health Econ 1996; 5: 1–11.

    Article  PubMed  CAS  Google Scholar 

  11. Weinstein MC, Fineburg HV. Clinical decision analysis. Philadelphia: WB Saunders, 1980.

    Google Scholar 

  12. Mauskopf JA, Paul JE, Grant DM, et al. The role of cost-consequence analysis in healthcare decision-making. Pharmacoeconomics 1998; 13 (3): 277–88.

    Article  PubMed  CAS  Google Scholar 

  13. Milne RJ, Wilcox J. Determinants of the cost of managing an episode of acute bronchitis or an infectious exacerbation of chronic bronchitis in the community: a decision analytic model. Pharmacoeconomics. In press.

  14. Scott WG, Tilyard MW, Dovey SM, et al. Roxithromycin versus cefaclor in lower respiratory tract infection. Ageneral practice pharmacoeconomic study. Pharmacoeconomics 1993; 4 (2): 122–30.

    Article  PubMed  CAS  Google Scholar 

  15. Milne RJ. Roxithromycin vs erythromycin in the treatment of acute bronchitis: a pharmacoeconomic threshold analysis. Pharmacoeconomics. In press.

  16. Backhouse R, Shakespeare A, Hutton J. Economic evaluation of alternative antibiotic regimens in the management of acute exacerbations of chronic bronchitis. Br J Med Econ 1995; 8: 11–25.

    Google Scholar 

  17. Sonnenberg FA, Beck JR. Markov models in medical decision making: a practical guide. Med Decis Making 1993; 13: 322–38.

    Article  PubMed  CAS  Google Scholar 

  18. Hutton J, Brown R, Borowitz M, et al. A new decision model for cost-utility comparisons of chemotherapy in recurrent metastatic breast cancer. Pharmacoeconomics 1996; 9 Suppl. 2: 8–22.

    Article  Google Scholar 

  19. Psaty BM, Smith NL, Siscovick DS, et al. Health outcomes associated with antihypertensive therapeis used as first-time agents: a systemic review and meta-analysis. JAMA 1997; 277 (9): 739–45.

    Article  PubMed  CAS  Google Scholar 

  20. Sacks FM, Pfeffer MA, Moye LA, et al. The effect of pravastatin on coronary events after myocardial infarction in patients with average cholesterol levels. New Engl J Med 1996 Oct 3; 335 (14): 1001–9.

    Article  PubMed  CAS  Google Scholar 

  21. Randomised trial of cholesterol lowering in 4444 patients with coronary heart disease: the Scandinavian Simvastatin Survival Study (4S). Lancet 1994; 344: 1383–9.

  22. Shepherd J, Cobbe SM, Ford I, et al. Prevention of coronary heart disease with pravastatin in men with hypercholesterolemia. New Engl J Med 1995 Nov 16; 333 (20): 1301–7.

    Article  PubMed  CAS  Google Scholar 

  23. Anderson KM. A nonproportional hazards Weibull accelerated time regression model. Biometrics 1991; 47 (Pt A): 281–8.

    Article  PubMed  CAS  Google Scholar 

  24. Anderson KM, Wilson WF, Odell PM, et al. An updated coronary risk profile: a statement for health professionals. Circulation 1991; 83 (1 Pt B): 356–62.

    Article  PubMed  CAS  Google Scholar 

  25. Jönsson B, Johannesson M, Kjekshus J, et al. Cost-effectiveness of cholesterol lowering. Results from the Scandinavian Simvastatin Survival Study (4S). Eur Heart J 1996; 17: 1001–7.

    Article  PubMed  Google Scholar 

  26. Caro J, Klittich W, McGuire A, et al. The West of Scotland coronary prevention study: economic benefit analysis of primary prevention with pravastatin. BMJ 1997; 315: 1577–82.

    Article  PubMed  CAS  Google Scholar 

  27. Milne RJ, Vander Hoom S, Jackson RT. A predictive model of the health benefits and costs of celiprolol and atenolol in primary prevention of cardiovascular disease in hypertensive patients. Pharmacoeconomics 1997; 12 (3): 384–408.

    Article  PubMed  CAS  Google Scholar 

  28. Basskin L. Discounting in pharmacoeconomic analyses: when and how to do it. Formulary 1996; 31: 1217–25.

    Google Scholar 

  29. Nuijten MJC. The selection of data sources for use in modelling studies. Pharmacoeconomics 1998; 13 (3): 305–16.

    Article  PubMed  CAS  Google Scholar 

  30. Lewis NJW, Patwell JT, Briesacher BA. The role of insurance claims databases in drag therapy outcomes research. Pharmacoeconomics 1993; 4 (5): 323–30.

    Article  PubMed  CAS  Google Scholar 

  31. Revicki DA, Shakespeare A, Hind P. Preferences for schizophrenia-related health states: a comparison of patients, caregivers and psychiatrists. Int J Clin Psychopharmacol 1996; 11: 101–8.

    CAS  Google Scholar 

  32. Nuijten MJC, Pronk MH, Brorens MJA, et al. Reporting format for economic evaluation: part II. Focus on modelling studies. Pharmacoeconomics 1998 Sep; 14 (3): 259–68.

    Article  PubMed  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Richard J. Milne.

Additional information

About the Author: Richard Milne, founding editor of PharmacoEconomics, is now the Managing Director of Health Outcomes Associates Ltd, a New Zealand consultancy company. He also holds appointments at the University of Auckland and the University of Otago where he teaches graduate students and conducts research in applied pharmacoeconomics.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Milne, R.J. Pharmacoeconomic Models in Disease Management. Dis-Manage-Health-Outcomes 4, 119–134 (1998). https://doi.org/10.2165/00115677-199804030-00001

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.2165/00115677-199804030-00001

Keywords

Navigation