, Volume 7, Issue 6, pp 490–502 | Cite as

Multi-Attribute Health Status Classification Systems

Health Utilities Index
  • David Feeny
  • William Furlong
  • Michael Boyle
  • George W. Torrance
Review Article Health Status Classification Systems


In this article, multi-attribute approaches to the assessment of health status are reviewed with a special focus on 2 recently developed systems, the Health Utilities Index (HUI) Mark II and Mark III systems. The Mark II system consists of 7 attributes: sensation, mobility, emotion, cognition, self-care, pain and fertility. The Mark III system contains 8 attributes: vision, hearing, speech. ambulation, dexterity, emotion, cognition and pain. Each attribute consists of multiple levels of functioning. A combination of levels across Ihe attributes constitutes a health state.

The HUI systems are deliberately focused on the fundamental core attributes of health status. and on the capacity of individuals to function with respect to these aHributes. Thus, the measure obtained constitutes a pure description of health status. uncontaminated by differential opportunity or preference.

Multi-attribute systems provide a compact but comprehensive framework for describing health status for use in population health and programme evaluation studies. An important advantage of such systems is their ability 10 simultaneously provide detail on an allribute-by-attribute basis and to capture combinations of deficits among attributes. An additional advantage is their compatibility with multi-attribute preference functions. which provide a method for computing a summary health-related quality-of-life score for each health state


General Social Survey Health Utility Index Sickness Impact Profile Health Status Classification System Unique Health State 
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.


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  1. 1.
    Cadman D, Goldsmith C, Torrance GW, et al. Development of a health status index for Ontario children. Final report to the Ontario Ministry of Health on reseach grant DM648(00633). Hamilton, Ont.: McMaster University, 1986Google Scholar
  2. 2.
    Cadman D, Goldsmith C, Bashim P. Values, preferences, and decisions in the care of children with developmental disabilities. Dev Behav Pediatr 1984; 5: 60–4CrossRefGoogle Scholar
  3. 3.
    Cadman D, Goldsmith C. Construction of social value or utility–based health indices: the usefulness of factorial experimental design plans. J Chronic Dis 1986; 39: 643–51PubMedCrossRefGoogle Scholar
  4. 4.
    Rosenbaum P, Cadman D, Kirpalani H. Pediatrics: assessing quality of life In: Spilker B. editor. Quality of life assessmentin Clinical trials. New York: Raven Press, 1990: 205–15Google Scholar
  5. 5.
    Feeny DH, Furlong W, Barr RD. et al. A comprehensive multi–attribute system for classifying the health status of survivors of childhood cancer. J Clin Oncol 1992; 10: 923–8PubMedGoogle Scholar
  6. 6.
    Torrance GW, Boyle MH, Horwood SP. Application of multiattribute utility theory to measure social preferences forhealth states. Operations Res 1982; 30: 1043–69CrossRefGoogle Scholar
  7. 7.
    Guyatt GH, Feeny DH, Patrick DL. Measuring health–related quality of life. Ann intern Med 1993; 118: 622–9PubMedGoogle Scholar
  8. 8.
    Torrance G, Furlong W, Feeny D, et al. Multi–attribute preference functions: health utilities index. PharmacoEconomics 1995; 7 (6): 503–20PubMedCrossRefGoogle Scholar
  9. 9.
    Kirshner B, Guyatt G. A methodological framework for assessing health indices. J Chronic Dis 1985; 38: 27–36PubMedCrossRefGoogle Scholar
  10. 10.
    Patrick DL, Erickson P. Health status and health policy: quality of life in health care evaluation and resource allocation. NewYork: Oxford University Pres, 1993Google Scholar
  11. 11.
    Ware JE, Sherbourne CD. The MOS 36–item short from health survey (SF–36). Med Care 1992; 30: 473–83PubMedCrossRefGoogle Scholar
  12. 12.
    WHO. Measuring quality of life: the development of World Health Organization Quality of Life instrument (WHOQOL). Geneva: WHO. 1992Google Scholar
  13. 13.
    Bergner M, Bobbit RA, Carter WB, et al. The Sickness Impact Profile: development and final revision of a health Status measure. Med Care 1981; 19: 787–805PubMedCrossRefGoogle Scholar
  14. 14.
    Ware JE, Brook RH, Davies AR, et al. Choosing meaSureS of health status for individuals in general populations. Am J Public Health 1981; 71: 620–5PubMedCrossRefGoogle Scholar
  15. 15.
    Fanshel S, Bush JW. A health status index and its application to health services outcomes. Operations Res 1970; 18: 1021–66CrossRefGoogle Scholar
  16. 16.
    Bush JW, Chen MM, Patrick DL. Social indicators of health based on function status and prognosis. Proceedings of the American Statistical Association,Social Statistics Section:1978 Aug: Montreal. Washington, DC: American Statistical Association. 1972: 71–80Google Scholar
  17. 17.
    Kaplan RM, Bush JW, Berry CC. The reliabilit, stability and generalizability of a health status index. Procceedings of the American Statistical Association, Social Statistics Seetion;1978. Washington, DC: American Statistical Association. 1978: 704–9Google Scholar
  18. 18.
    Kaplan RM, Bush JW. Health related quality of life measurement for evaluation research and policy analysis. Health Psychol 1982; 1: 61–80CrossRefGoogle Scholar
  19. 19.
    Patrick DL, Bush JW, Chen MM. Methods for measuring levels of well being for a health status index. Health Services Res 1973; 8: 228–45Google Scholar
  20. 20.
    Patrick DL, Bush JW, Chen MM. Toward an operational definition of health. J Health Soc Behav 1973; 14: 6–23PubMedCrossRefGoogle Scholar
  21. 21.
    Patrick DL, Bergner M. Measurement of health status in the 1990s. Ann Rev Public Health 1990; 11: 165–83CrossRefGoogle Scholar
  22. 22.
    Rosser RM, Watts V. The sanative output of a health care system. Paper presented at the Conference of the Operations Research Society of America: 1971 May 5–7; DallasGoogle Scholar
  23. 23.
    Rosser RM. Recent studies using a global approach to measuring illness. Med Care 1976; 14 Suppl. 5: 138–47Google Scholar
  24. 24.
    Kind P, Rosser R. The quantification of health. Eur J Soc Psycho1 1988; 18: 63–77CrossRefGoogle Scholar
  25. 25.
    Rosser R, Watts V. The measurement of illness. J Operations Res Soc 1978; 29: 529–609Google Scholar
  26. 26.
    Rosser R, Kind P. A scale of valuations of states of illness: is there a social consensus. Int J Epidemiol 1978; 7: 347–58PubMedCrossRefGoogle Scholar
  27. 27.
    Rosser RM, WattS V. A clinical classification of disability and distress and its application to the awards made by the court in personal injury cases. New Law J 1975; 125: 323–6Google Scholar
  28. 28.
    Sintonen H. An approach to measuring and valuing health states. Soc Sci Med 1981; 15C: 55–65Google Scholar
  29. 29.
    Sintonen H, Pekurinen M. 15D: a 15 dimension measure of health. Presented at the Health Economists Study Group Meeting: 1988 Jul 18–22; Brunei University, LondonGoogle Scholar
  30. 30.
    Boyle MH, Torrance GW, Sinclair JC, et al. Economic evaluation of neonatal intensive care of very–low–birt–weight infants. N Engl J Med 1983; 308: 1330–7PubMedCrossRefGoogle Scholar
  31. 31.
    Boyle MH, Torrance GW. Developing multi–attribute health indexes. Med Care 1984; 22: 1045–57PubMedCrossRefGoogle Scholar
  32. 32.
    Feeny DH, Leiper A, Barr RD, et al. The comprehensive assessment of health status in survivors of childhood cancer: application to high–risk acute lymphoblastic leukaemia. Br J Cancer 1993; 67: 1047–52PubMedCrossRefGoogle Scholar
  33. 33.
    Furlong W, Feeny D, Torrance G. et al. Design and pilot testing of comprehensive health–status measurement system for the Ontario Health Survey. Final report for the Ontario Ministry of Health. Hamilton, Ontario: Ontario Ministry of Health, 1989Google Scholar
  34. 34.
    Euroqol Group. Euroqol–a new facility for the measurement of health–related quality of life. Health Policy 1990; 16: 199–208Google Scholar
  35. 35.
    Nord E. EuroQol: health–related quality of life measurement. Valuations of health states by the general public in Norway. Health Policy 1991; 18: 25–36PubMedCrossRefGoogle Scholar
  36. 36.
    Essink-Bot ML, Stouthard MEA, Bonsel GJ. Generalizability of valuations on health states collected wilh the Euroqoquestionnaire. Helth Econ 1993; 2: 237–46CrossRefGoogle Scholar
  37. 37.
    Hunt SM, McKenna SP, McEwen J. et al. A quantitative approach to perceived health Status: a validation study. J Epidemiol Community Health 1980; 34: 281–6PubMedCrossRefGoogle Scholar
  38. 38.
    McKenna SP, Hunt S, Tennant A. The development ofa patient completed index of distress from the Nottingham health profile: a new measure for use in cost–utility studies. Br J Med Econ 1993; 6: 13–24Google Scholar
  39. 39.
    Nelson EC, Landgraf JM, Hays RD, et al. The functional status of patients. How Can it be measured in physicians’ offices? Med Care 1990; 28: 1111–26PubMedCrossRefGoogle Scholar
  40. 40.
    Ministry of Health, Ontario; Ontario Health Survey 1990. User’s guide, Vol. 1: documentation. Toronto: Ministry of Health, Ontario and Premiers Council on Health, Well–Being and Social Justice, 1993Google Scholar
  41. 41.
    Berthelot J-M, Roberge R, Wolfson M. The calculation of health–adjusted life expectancy for a Canadian province using a multi–attribute utility function: a first attempt. In: Robine JM, Mathers CD, Bone MR, et al., editors. Calculation of health expectancies: harmonization. consensus achieved and future perspectives. Vol 226. Montrouge, France: Colloque INSERM fJohn Libbey Eurotext LId, 1993: 161–72Google Scholar
  42. 42.
    Strike C. Overview of 1991 General Social Survey on Health (GSS–6). Statistics Canada General Social Survey WorkingPaper No. I. Ottawa: Statistics Canada, 1991Google Scholar
  43. 43.
    Statistics Canada. Health status of Canadians: report of the 1991 General Social Survey. Ottawa: Statistics Canada, 1994Google Scholar
  44. 44.
    Cartwright A. The effect of obtaining information from different informants on a family morbidity inquiry. Appl statistics 1957; 6; 18–25CrossRefGoogle Scholar
  45. 45.
    Clarridge BR, Massagli MP. The use of female spouse proxies in common symptom reporting. Med Care 1989; 27: 352–6PubMedCrossRefGoogle Scholar
  46. 46.
    Magaziner J, Simonsick EM, Kashner TM, et al. Patient proxy response comparability on measures of patient health status and functional status. J Clin Epidemiol 1988; 41: 1065–74PubMedCrossRefGoogle Scholar
  47. 47.
    Rotham ML, Hedrick SC, Bulcroft KA, et al. The validity of proxy–generated scores as measures of patient health status. Med Care 1991; 29: 115–24CrossRefGoogle Scholar
  48. 48.
    Barr RD, Furlong W, Dawson S, et al. An assessment of global health status in survivors of acute lymphoblastic leukemia in childhood. Am J Pediatrtr Hematol Oncol 1993; 15: 284–90Google Scholar
  49. 49.
    Barr RD, Pai MKR, Weitzman J, et al. A multi–attribute approach to health status measurement and clinical management–illustrated by an application to brain tumors in childhood. Int J Oncol 1994; 4: 639–48PubMedGoogle Scholar
  50. 50.
    Barr RD, Feeny DH, Furlong W, et al. Health–related quality of life in children with cancer. Int J Pediatr Hematol Oncol In pressGoogle Scholar
  51. 51.
    Billson A, Walker DA. Assessment of health Status in survivors of cancer. Arch Dis Child 1994; 70; 200–4PubMedCrossRefGoogle Scholar
  52. 52.
    Kanabar DJ, Attard-Montalto S, Saha V, et al. Quality of life in survivors of childhood cancer after megatherapy with autologous bone marrow rescue. Pediatr Hematol Oncol 1995; 12: 29–36PubMedCrossRefGoogle Scholar
  53. 53.
    Saigal S, Rosenbaum P, Stoskopf B, et al. Comprehensive assessment of the health status of extremely low birth eight children at eight years of age: comparison with a reference group. J Pediatr 1994; 125: 411–7PubMedCrossRefGoogle Scholar
  54. 54.
    Saigal S, Feeny D, Furlong W, et al. Comprehensive asscssment of the health–relaled quality of life of extremely low birth weight children and a reference group of children at eigh tyears of age. J Pedialr 1994: 125: 418–25CrossRefGoogle Scholar
  55. 55.
    Gortner S, Jaeger AA, Harr J, et al. Elders’ expected and realized benefits from cardiac surgery. Cardiaovasc Nurs 1994 Mar/Apr; 30(2): 91–94Google Scholar
  56. 56.
    Statistics Canada. The 1991 General Social Survey–Cycle 6: health–public uSe microdata file documentation and user’s guide. Ottawa: Statistics Canada, 1992Google Scholar
  57. 57.
    Boyle MH, Furlong W, Feeny D, et al. Reliability of the Health Utililies Index–Mark III used in the 1991 Cycle 6 General Social Survey health questionnaire. Qual Life Res. In press, 1992Google Scholar
  58. 58.
    Feeny DH, Torrance GW, Goldsmith CH, et al. A multi–attribute approach to population health satutus. Proceedings of the 153rd Annual Meeting of the American Statistical Association, 1993 Aug 8–12; San Francisco. Alexandria, VA: American Statistical Association. 1994: 161–6Google Scholar

Copyright information

© Adis International Limited 1995

Authors and Affiliations

  • David Feeny
    • 1
    • 3
  • William Furlong
    • 1
    • 2
  • Michael Boyle
    • 1
    • 4
  • George W. Torrance
    • 1
    • 2
    • 5
  1. 1.Department of Clinical Epidemiology and Biostatistics, Centre for Health Economics and Policy AnalysisMcMaster UniversityHamiltonCanada
  2. 2.Centre for Health Economics and Policy AnalysisMcMaster UniversityHamiltonCanada
  3. 3.Department of EconomicsMcMaster UniversityHamiltonCanada
  4. 4.Department of PsychiatryMcMaster UniversityHamiltonCanada
  5. 5.Department of Management ScienceMcMaster UniversityHamiltonCanada

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