Health Care Analysis

, Volume 22, Issue 3, pp 255–271

Priority Setting and Patient Adaptation to Disability and Illness: Outcomes of a Qualitative Study

  • John McKie
  • Rosalind Hurworth
  • Bradley Shrimpton
  • Jeff Richardson
  • Catherine Bell
Original Article

Abstract

The study examined the question of who should make decisions for a National Health Scheme about the allocation of health resources when the health states of beneficiaries could change because of adaptation. Eight semi-structured small group discussions were conducted. Following focus group theory, interviews commenced with general questions followed by transition questions and ended with a ‘focus’ or ‘key’ question. Participants were presented with several scenarios in which patients adapted to their health states. They were then asked their views about the appropriate role of the public, patients and health professionals in making social judgements of quality of life. After discussion and debate, all groups were asked the key question: ‘In light of adaptation, who should evaluate quality of life for the purpose of setting priorities in the allocation of health care?’ In all groups participants presented strong arguments for and against decision making by patients, the public and health professionals. However, most groups thought a representative body which included a range of perspectives should make the relevant judgements. This is at odds with the recommendations in most national pharmaceutical guidelines. The main conclusion of the paper is that health economists and other researchers should explore the possibility of adopting a deliberative, consensus-based approach to evaluating health-related quality of life when such judgements are to be used to inform priority setting in a public system.

Keywords

Adaptation Priority setting Health-related quality of life Focus groups Qualitative research 

References

  1. 1.
    Abelson, J., et al. (2003). Deliberations about deliberative methods: Issues in the design and evaluation of public participation processes. Social Science and Medicine, 57(2), 239–251.PubMedCrossRefGoogle Scholar
  2. 2.
    Borkman, T. (1976). Experiential knowledge: A new concept for the analysis of self-help groups. The Social Service Review, 50(3), 445–456.CrossRefGoogle Scholar
  3. 3.
    Boyd, N. F., et al. (1990). Whose utilities for decision analysis? Medical Decision Making, 10(1), 58–67.PubMedCrossRefGoogle Scholar
  4. 4.
    Cheung, K., et al. (2009). EQ-5D User guide: basic information on how to use EQ-5D, version 2.0. EuroQoL Group.Google Scholar
  5. 5.
    Damschroder, L. J., Zikmund-Fisher, B. J., & Ubel, P. A. (2005). The impact of considering adaptation in health state valuation. Social Science and Medicine, 61(2), 267–277.PubMedCrossRefGoogle Scholar
  6. 6.
    Dolan, P. (2000). The measurement of health-related quality of life. In A. J. Culyer & J. P. Newhouse (Eds.), Handbook of health economics (Vol. 1B, pp. 1723–1760). Amsterdam: Elsevier.Google Scholar
  7. 7.
    Dolan, P., & Cookson, R. (2000). A qualitative study of the extent to which health gain matters when choosing between groups of patients. Health Policy, 51(1), 19–30.PubMedCrossRefGoogle Scholar
  8. 8.
    Edwards, A., & Elwyn, G. (2001). Understanding risk and lessons for clinical risk communication about treatment preferences. Quality in Health Care, 10(Supplement 1), i9–i13.PubMedCentralPubMedGoogle Scholar
  9. 9.
    Entwistle, V. A., et al. (1998). Developing information materials to present the findings of technology assessments to consumers: The experience of the NHS centre for reviews and dissemination. International Journal of Technology Assessment in Health Care, 14(1), 47–70.PubMedCrossRefGoogle Scholar
  10. 10.
    Finch, H., & Lewis, J. (2003). Focus groups. In J. Ritchie & J. Lewis (Eds.), Qualitative research practice. Chap 7. Thousand Oaks, CA: Sage Publications.Google Scholar
  11. 11.
    Frankish, C. J., et al. (2002). Challenges of citizen participation in regional health authorities. Social Science and Medicine, 54(10), 1471–1480.PubMedCrossRefGoogle Scholar
  12. 12.
    Gold, M. R., et al. (Eds.). (1996). Cost-effectiveness in health and medicine. New York: Oxford University Press.Google Scholar
  13. 13.
    Gregory, J., Hartz-Karp, J., & Watson, R. (2008). Using deliberative techniques to engage the community in policy development. Australia and New Zealand Health Policy, 5(1), 16.PubMedCentralPubMedCrossRefGoogle Scholar
  14. 14.
    Hawthorne, G., & Richardson, J. (2001). Measuring the value of program outcomes: A review of multiattribute utility measures. Expert Review of Pharmacoeconomics Outcomes Research, 1(2), 215–228.PubMedCrossRefGoogle Scholar
  15. 15.
    Hesse-Biber, S. N., & Leavy, P. (2006). The practice of qualitative research. Thousand Oaks, CA: Sage Publications.Google Scholar
  16. 16.
    Hurst, N. P., et al. (1994). Validity of euroqol—A generic health status instrument—In patients with rheumatoid arthritis. British Journal of Rheumatology, 33(7), 655–662.PubMedCrossRefGoogle Scholar
  17. 17.
    Krueger, R. (2003). Focus group methods. Thousand Oaks, CA: Sage Publications.Google Scholar
  18. 18.
    Litva, A., et al. (2002). “The public is too subjective”: Public involvement at different levels of health-care decision making. Social Science and Medicine, 54(12), 1825–1837.PubMedCrossRefGoogle Scholar
  19. 19.
    Lloyd, A. J. (2003). Threats to the estimation of benefit: Are preference elicitation methods accurate? Health Economics, 12(5), 393–402.PubMedCrossRefGoogle Scholar
  20. 20.
    McKie, J., et al. (2008). Who should be involved in health care decision making? A qualitative study. Health Care Analysis, 16(2), 114–126.PubMedCrossRefGoogle Scholar
  21. 21.
    McNamee, P., & Seymour, J. (2005). Comparing generic preference-based health-related quality-of-life measures: Advancing the research agenda. Expert Review of Pharmacoeconomics and Outcomes Research, 5(5), 567–581.PubMedCrossRefGoogle Scholar
  22. 22.
    McTaggart-Cowan, H., et al. (2011). Understanding the effect of disease adaptation information on general population values for hypothetical health states. Social Science and Medicine, 72(11), 1904–1912.PubMedCrossRefGoogle Scholar
  23. 23.
    Menzel, P., et al. (2002). The role of adaptation to disability and disease in health state valuation: A preliminary normative analysis. Social Science and Medicine, 55(12), 2149–2158.PubMedCrossRefGoogle Scholar
  24. 24.
    Miles, M. B., & Huberman, A. M. (1994). Qualitative data analysis: An expanded sourcebook (2nd ed.). Thousand Oaks: Sage Publications.Google Scholar
  25. 25.
    Murray, C. J. L., & Lopez, A. D. (Eds.). (1996). The global burden of disease: A comprehensive assessment of mortality and disability from diseases, injuries, and risk factors in 1990 and projected to 2020. Cambridge, MA: Harvard University Press.Google Scholar
  26. 26.
    NICE. (2008). Guide to the methods of technology appraisal. London: National Institute for Health and Clinical Excellence.Google Scholar
  27. 27.
    Nord, E. (1999). Cost-value analysis in health care. Cambridge: Cambridge University Press.Google Scholar
  28. 28.
    Nord, E., et al. (1999). Incorporating societal concerns for fairness in numerical valuations of health programmes. Health Economics, 8(1), 25–39.PubMedCrossRefGoogle Scholar
  29. 29.
    Patton, M. Q. (2002). Qualitative research and evaluation methods (3rd ed.). Thousand Oaks, CA: Sage Publications.Google Scholar
  30. 30.
    Payne, J., Bettman, J., & Johnson, E. (1993). The adaptive decision maker. Cambridge, MA: Cambridge University Press.CrossRefGoogle Scholar
  31. 31.
    Pharmaceutical Benefits Board (LFNAR). (2003). General guidelines for economic evaluations. Sweden.Google Scholar
  32. 32.
    Prades, J.-L. P. (1997). Is the person trade-off a valid method for allocating health care resources? Health Economics, 6(1), 71–81.CrossRefGoogle Scholar
  33. 33.
    Redelmeier, D. A., Rozin, P., & Kahneman, D. (1993). Understanding patients decisions: Cognitive and emotional perspectives. Journal of the American Medical Association, 270(1), 72–76.PubMedCrossRefGoogle Scholar
  34. 34.
    Riis, J., et al. (2005). Ignorance of hedonic adaptation to hemodialysis: A study using ecological momentary assessment. Journal of Experimental Psychology: General, 134(1), 3–9.CrossRefGoogle Scholar
  35. 35.
    Sackett, D. L., & Torrance, G. W. (1978). The utility of different health states as perceived by the general public. Journal of Chronic Diseases, 31(11), 697–704.PubMedCrossRefGoogle Scholar
  36. 36.
    Shiell, A., et al. (2000). Are preferences over health states complete? Health Economics, 9(1), 47–55.PubMedCrossRefGoogle Scholar
  37. 37.
    Sieff, E. M., Dawes, R. M., & Loewenstein, G. (1999). Anticipated versus actual reaction to HIV test results. American Journal of Psychology, 112(2), 297–311.PubMedCrossRefGoogle Scholar
  38. 38.
    Smith, D. M., et al. (2006). Misremembering colostomies? Former patients give lower utility ratings than do current patients. Health Psychology, 25(6), 688–695.PubMedCrossRefGoogle Scholar
  39. 39.
    Tsuchiya, A. (2000). QALYs and ageism: Philosophical theories and age weighting. Health Economics, 9(1), 57–68.PubMedCrossRefGoogle Scholar
  40. 40.
    Tsuchiya, A., Dolan, P., & Shaw, R. (2003). Measuring people’s preferences regarding ageism in health: Some methodological issues and some fresh evidence. Social Science and Medicine, 57(4), 687–696.PubMedCrossRefGoogle Scholar
  41. 41.
    Ubel, P. A., et al. (2001). Do nonpatients underestimate the quality of life associated with chronic health conditions because of a focusing illusion? Medical Decision Making, 21(3), 190–199.PubMedCrossRefGoogle Scholar
  42. 42.
    Ubel, P. A., Richardson, J., & Baron, J. (2002). Exploring the role of order effects in person trade-off elicitations. Health Policy, 61(2), 189–199.PubMedCrossRefGoogle Scholar
  43. 43.
    Ubel, P. A., et al. (1998). Public preferences for prevention versus cure: What if an ounce of prevention is worth only an ounce of cure? Medical Decision Making, 18(2), 141–148.PubMedGoogle Scholar
  44. 44.
    Walmsley, H. L. (2011). Stock options, tax credits or employment contracts please! The value of deliberative public disagreement about human tissue donation. Social Science and Medicine, 73(2), 209–216.PubMedCrossRefGoogle Scholar
  45. 45.
    Warr, P., Jackson, P., & Banks, M. (1988). Unemployment and mental health: Some British studies. Journal of Social Issues, 44(4), 47–68.CrossRefGoogle Scholar
  46. 46.
    Wilson, T. D., & Gilbert, D. T. (2005). Affecting forecasting: Knowing what to want. Current Directions in Psychological Science, 14(3), 131–134.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • John McKie
    • 1
  • Rosalind Hurworth
    • 2
  • Bradley Shrimpton
    • 2
  • Jeff Richardson
    • 1
  • Catherine Bell
    • 2
  1. 1.Centre for Health EconomicsMonash UniversityClaytonAustralia
  2. 2.Centre for Program EvaluationUniversity of MelbourneParkvilleAustralia

Personalised recommendations