Advertisement

PharmacoEconomics

, Volume 31, Issue 8, pp 677–691 | Cite as

Incorporating Process Utility into Quality Adjusted Life Years: A Systematic Review of Empirical Studies

  • Victoria K. Brennan
  • Simon Dixon
Systematic Review

Abstract

Objective

This review aimed to identify published studies that provide an empirical measure of process utility, which can be incorporated into estimates of QALY calculations.

Methods

A literature search was conducted in PubMed to identify published studies of process utility. Articles were included if they were written in the English language and reported empirical measures of process utility that could be incorporated into the QALY calculation; those studies reporting utilities that were not anchored on a scale of 0 representing dead and 1 representing full health were excluded from the review.

Results

Fifteen studies published between 1996 and 2012 were included. Studies included respondents from the USA, Australia, Scotland and the UK, Europe and Canada. Eight of the included studies explored process utility associated with treatments; six explored process utility associated with screening procedures or tests; and one was performed in preventative care. A variety of approaches were used to detect and measure process utility: four studies used standard gamble techniques; four studies used time trade-off (TTO); one study used conjoint analysis and one used a combination of conjoint analysis and TTO; one study used SF-36 data; one study used both TTO and EQ-5D; and three studies used wait trade-off techniques. Measures of process utility for different drug delivery methods ranged from 0.02 to 0.27. Utility estimates associated with different dosing strategies ranged from 0.005 to 0.09. Estimates for convenience (able to take on an empty stomach) ranged from 0.001 to 0.028. Estimates of process utility associated with screening and testing procedures ranged from 0.0005 to 0.031. Both of these estimates were obtained for management approaches to cervical cancer screening.

Conclusion

The identification of studies through conventional methods was difficult due to the lack of consistent indexing and terminology across studies; however, the evidence does support the existence of process utility in treatment, screening and preventative care settings. There was considerable variation between estimates. The range of methodological approaches used to identify and measure process utility, coupled with the need for further research into, for example, the application of estimates in economic models, means it is difficult to know whether these differences are a true reflection of the amount of process utility that enters into an individual’s utility function, or whether they are associated with features of the studies’ methodological design. Without further work, and a standardised approach to the methodology for the detection and measurement of process utility, comparisons between estimates are difficult. This literature review supports the existence of process utility and indicates that, despite the need for further research in the area, it could be an important component of an individual’s utility function, which should at least be considered, if not incorporated, into cost-utility analyses.

Keywords

Magnetic Resonance Angiography Extracorporeal Shock Wave Lithotripsy Conjoint Analysis Utility Estimate Process Utility 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

Victoria K. Brennan and Simon Dixon received no funding for the preparation of this article and have no conflicts of interest that are directly relevant to its content.

References

  1. 1.
    Oliver A. Prioritizing health care: IS “Health” always an appropriate maximand? Med Decis Making. 2004;24:272.CrossRefPubMedGoogle Scholar
  2. 2.
    Sussex J, Towse A, Devlin N. Operationalizing value-based pricing of medicines: a taxonomy of approaches. Pharmacoeconomics. 2013;31:1–10.CrossRefPubMedGoogle Scholar
  3. 3.
    Whitehead SJ, Ali S. Health outcomes in economic evaluation: the QALY and utilities. Br Med Bull. 2010;96:5–21.CrossRefPubMedGoogle Scholar
  4. 4.
    Brouwer WBF, Culyer AJ, van Exel NJA, et al. Welfarism vs. extra-welfarism. J Health Econ. 2008;27(2):325–38.Google Scholar
  5. 5.
    Gerard K, Mooney G. QALY league tables: handle with care. Health Econ. 1993;2:59–64.CrossRefGoogle Scholar
  6. 6.
    Mooney G. Beyond health outcomes: the benefits of health care. Health Care Anal. 1998;6(2):99–1.Google Scholar
  7. 7.
    McAlister D. Putting health economics into quality. Public Money Manage. 1994;14(2):15–22.CrossRefGoogle Scholar
  8. 8.
    Donaldson C, Shackley P. Does “process utility” exist? A case study of willingness to pay for laparoscopic cholecystectomy. Soc Sci Med. 1997;44:699–707.CrossRefPubMedGoogle Scholar
  9. 9.
    Swan J, Sainfort F. Process utility for imaging in cerebrovascular disease. Acad Radiol. 2003;10(3):266–74.Google Scholar
  10. 10.
    Opmeer BC, de Borgie CA, Mol BW, Bossuyt PM. Assessing preferences regarding healthcare interventions that involve non-health outcomes: an overview of clinical studies. Patient. 2010;3(1):1–10.CrossRefPubMedGoogle Scholar
  11. 11.
    Nord E, Pinto-Prades JL, Richardson J, et al. Incorporating societal concerns for fairness in numerical valuations of health programmes. Health Econ. 1999;8:25–39.CrossRefPubMedGoogle Scholar
  12. 12.
    Tsuchiya A. QALYs and ageism: philosophical theories and age weighting. Health Econ. 2000;9:57–68.CrossRefPubMedGoogle Scholar
  13. 13.
    Dolan P, Tsuchiya A. Determining the parameters in social welfare function using stated preference data: an application to health. Appl Econ. 2011;43(18):1466–4283.Google Scholar
  14. 14.
    Drummond MF, Sculpher MJ, Torrance GW, O’Brien BJ, et al. Methods for the economic evaluation of health care programmes. 3rd ed. Oxford: Oxford University Press; 2005.Google Scholar
  15. 15.
    Lloyd A, Nafees B, Bernett AH, et al. Willingness to pay for improvements in chronic long-acting insulin therapy in individuals with type 1 or type 2 diabetes mellitus. Clin Therap. 2011;33(9):1258–67.CrossRefGoogle Scholar
  16. 16.
    Cook J, Richardson J, Street A. A cost utility analysis of treatment options for gallstone disease: methodological issues and results. Health Econ. 1994;3:157–68.CrossRefPubMedGoogle Scholar
  17. 17.
    Schmier JK, Palmer CS, Flood EM, et al. Utility assessments of opioid treatment for chronic pain. Pain Med. 2002;3(3):218–30.CrossRefPubMedGoogle Scholar
  18. 18.
    Osborne RH, De Abreu Lourenço R, Dalton A, Houltram J, et al. Quality of life related to oral versus subcutaneous iron chelation: a time trade-off study. Value Health. 2007;10(6):51–6.Google Scholar
  19. 19.
    Osborne RH, Dalton A, Hertel J, Schrover R, Smith DK. Health-related quality of life advantage of long-acting injectable antipsychotic treatment for schizophrenia: a time-trade-off study. Health Qual Life Outcomes. 2012;10:35.CrossRefPubMedGoogle Scholar
  20. 20.
    Kauf TL, Roskell N, Shearer A, et al. A predictive model of health state utilities for HIV patients in the modern era of highly active antiretroviral therapy. Value Health. 2008;11(7):1144–53.CrossRefPubMedGoogle Scholar
  21. 21.
    Chancellor J, Aballéa S, Lawrence A, et al. Preferences of patients with diabetes mellitus for inhaled versus injectable insulin regimens. Pharmacoeconomics. 2008;26(3):217–34.CrossRefPubMedGoogle Scholar
  22. 22.
    Polster M, Zanutto E, McDonald S, et al. A comparison of preferences for two GLP-1 products—liraglutide and exenatide—for the treatment of type 2 diabetes. J Med Econ. 2010;13(4):655–61.CrossRefPubMedGoogle Scholar
  23. 23.
    Boye KS, Matza LS, Walter KN, et al. Utilities and disutilities for attributes of injectable treatments for type 2 diabetes. Eur J Health Econ. 2011;12(3):219–30.CrossRefPubMedGoogle Scholar
  24. 24.
    Birch S, Melnikow J, Kuppermann M. Conservative versus aggressive follow up of mildly abnormal Pap smears: testing for process utility. Health Econ. 2003;12(10):879–84.CrossRefPubMedGoogle Scholar
  25. 25.
    Howard K, Salkeld G, McCaffery K, et al. HPV triage testing or repeat Pap smear for the management of atypical squamous cells (ASCUS) on Pap smear: is there evidence of process utility? Health Econ. 2008;17(5):593–605.CrossRefPubMedGoogle Scholar
  26. 26.
    Cairns J, Shackley P, Hundley V. Decision making with respect to diagnostic testing: a method of valuing the benefits of antenatal screening. Med Decis Making. 1996;16:61.CrossRefGoogle Scholar
  27. 27.
    Swan JS, Fryback DG, Lawrence WF, et al. A time-trade-off method for cost effectiveness models applied to radiology. Med Decis Making. 2000;20:79.CrossRefPubMedGoogle Scholar
  28. 28.
    Swan JS, Lawrence WF, Roy J. Process utility in breast biopsy. Med Decis Making. 2006;26(4):347–59.CrossRefPubMedGoogle Scholar
  29. 29.
    Salkeld G, Quine S, Cameron ID. What constitutes success in preventive health care? A case study in assessing the benefits of hip protectors. Soc Sci Med. 2004;59(8):1593–601.CrossRefPubMedGoogle Scholar
  30. 30.
    Torrance GW. Measurement of health state utilities for economic appraisal. J Health Econ. 1986;5:1–30.CrossRefPubMedGoogle Scholar
  31. 31.
    Walters SJ, Brazier JE. What is the relationship between the minimally important difference and health state utility values? The case of the SF-6D. Health Qual Life Outcomes. 2003;1:4.CrossRefPubMedGoogle Scholar
  32. 32.
    Stouthard MEA, Essink-Bot ML, Bonsel GJ, Barendregt JJ, Kramer PG, van de Water HPA, Gunning-Schepers LJ, van der Maas PJ. Disability weights for diseases in the Netherlands. Rotterdam: Erasmus University; 1997.Google Scholar
  33. 33.
    Boyd NF, Sutherland HJ, Heasman DL, et al. Whose utilities for decision analysis? Med Dec Making. 1990;10:58.CrossRefGoogle Scholar
  34. 34.
    Gold MR, Siegel JE, Russell LB, et al., editors. Cost-effectiveness in health and medicine. Oxford: Oxford University Press; 1996.Google Scholar
  35. 35.
    Brazier J, Akehurst R, Brennan A, Dolan P, Claxton K, McCabe C, Sculpher M, Tsuchyia A. Should patients have a greater role in valuing health states? Appl Health Econ Health Policy. 2005;4(4):201–8.Google Scholar
  36. 36.
    Gafni A, Zylak CJ. Ionic versus non-ionic contrast media: a burden or a bargain? Can Med Assoc J. 1990;143(6):475–8.Google Scholar
  37. 37.
    Brazier JE, Rowen D. NICE DSU Technical Support Document 11: Alternatives to EQ-5D for generating health state utility values. 2011. http://www.nicedsu.org.uk. Accessed 18 Sept 2012.
  38. 38.
    Krabbe P, Stouthard M, Essink-Bot M, et al. The effect of adding a cognitive dimension to the EuroQol Multiattribute Health-Status Classification System. J Clin Epidemiol. 1999;52(4):293–301.CrossRefPubMedGoogle Scholar
  39. 39.
    Yang Y, Brazier J, Tsuchiya. The effect of adding a ‘sleep’ dimension to EQ-5D. In: Health Economists’ Group meeting. January 2008.Google Scholar
  40. 40.
    Brazier J, Rowen D, Tsuchiya A, Yang Y, Young T. What a pain: adding a generic dimension to a condition-specific preference-based measure. In: HESG Abstract. 2010.Google Scholar
  41. 41.
    Steine S, Finset A, Laerum E. A new, brief questionnaire (PEQ) developed in primary health care for measuring patients’ experience of interaction, emotion and consultation outcome. Family Practice. 2001;18:410–8.Google Scholar
  42. 42.
    Baron J. Biases in the quantitative measurement of values for public decisions. Psychol Bull. 1997;122:72–88.Google Scholar
  43. 43.
    Dolan P, Kahneman D. Interpretations of utility and their implications for the valuation of health. Econ J. 2008;118(525):215–34.Google Scholar

Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  1. 1.RTI-Health SolutionsSheffieldUK
  2. 2.HEDS, ScHARRThe University of Sheffield Regent CourtSheffieldUK

Personalised recommendations