1932

Abstract

Patient-reported outcomes are recognized as essential for the evaluation of medical and public health interventions. Over the last 50 years, health-related quality of life (HRQoL) research has grown exponentially from 0 to more than 17,000 papers published annually. We provide an overview of generic HRQoL measures used widely in epidemiological studies, health services research, population studies, and randomized clinical trials [e.g., Medical Outcomes Study SF-36 and the Patient-Reported Outcomes Measurement Information System (PROMIS®)-29]. In addition, we review methods used for economic analysis and calculation of the quality-adjusted life year (QALY). These include the EQ-5D, the Health Utilities Index (HUI), the self-administered Quality of Well-being Scale (QWB-SA), and the Health and Activities Limitation Index (HALex). Furthermore, we consider hybrid measures such as the SF-6D and the PROMIS-Preference (PROPr). The plethora of HRQoL measures has impeded cumulative science because incomparable measures have been used in different studies. Linking among different measures and consensus on standard HRQoL measurement should now be prioritized. In addition, enabling widespread access to common measures is necessary to accelerate future progress.

Loading

Article metrics loading...

/content/journals/10.1146/annurev-publhealth-052120-012811
2022-04-05
2024-03-28
Loading full text...

Full text loading...

/deliver/fulltext/publhealth/43/1/annurev-publhealth-052120-012811.html?itemId=/content/journals/10.1146/annurev-publhealth-052120-012811&mimeType=html&fmt=ahah

Literature Cited

  1. 1. 
    Ambs A, Warren JL, Bellizzi KM, Topor M, Haffer SCC, Clauser SB. 2008. Overview of the SEER—Medicare Health Outcomes Survey linked dataset. Health Care Financ. Rev. 29:5–21
    [Google Scholar]
  2. 2. 
    Assi L, Chamseddine F, Ibrahim P, Sabbagh H, Rosman L et al. 2021. A global assessment of eye health and quality of life: a systematic review of systematic reviews. JAMA Ophthalmol. 139:526–41
    [Google Scholar]
  3. 3. 
    Bató A, Brodszky V, Gergely LH, Gáspár K, Wikonkál N et al. 2021. The measurement performance of the EQ-5D-5L versus EQ-5D-3L in patients with hidradenitis suppurativa. Qual. Life Res. 30:1477–90
    [Google Scholar]
  4. 4. 
    Baumhauer JF. 2017. Patient-reported outcomes—are they living up to their potential?. N. Engl. J. Med. 377:6–9
    [Google Scholar]
  5. 5. 
    Bentley TGK, Palta M, Paulsen AJ, Cherepanov D, Dunham NC et al. 2011. Race and gender associations between obesity and nine health-related quality-of-life measures. Qual. Life Res. 20:665–74
    [Google Scholar]
  6. 6. 
    Brazier J, Roberts J, Tsuchiya A, Busschbach J 2004. A comparison of the EQ-5D and SF-6D across seven patient groups. Health Econ. 13:873–84
    [Google Scholar]
  7. 7. 
    Broome L. 1993. The goal is quality improvement. Nurs. Manag. 24:51–52
    [Google Scholar]
  8. 8. 
    Cella D, Choi SW, Condon DM, Schalet B, Hays RD et al. 2019. PROMIS® adult health profiles: efficient short-form measures of seven health domains. Value Health 22:537–44
    [Google Scholar]
  9. 9. 
    Cella D, Riley W, Stone A, Rothrock N, Reeve B et al. 2010. Initial adult health item banks and first wave testing of the Patient-Reported Outcomes Measurement Information System (PROMIS™) network: 2005–2008. J. Clin. Epidemiol. 63:1179–94
    [Google Scholar]
  10. 10. 
    Clauser SB, Arora NK, Bellizzi KM, Haffer SCC, Topor M, Hays RD 2008. Disparities in HRQOL of cancer survivors and non-cancer managed care enrollees. Health Care Financ. Rev. 29:23–40
    [Google Scholar]
  11. 11. 
    Craig BM, Pickard AS, Stolk E, Brazier JE 2013. US valuation of the SF-6D. Med. Decis. Mak. 33:793–803
    [Google Scholar]
  12. 12. 
    Dewitt B, Feeny D, Fischhoff B, Cella D, Hays RD et al. 2018. Estimation of a preference-based summary score for the Patient-Reported Outcomes Measurement Information System: The PROMIS®-Preference (PROPr) scoring system. Med. Decis. Mak. 38:683–98
    [Google Scholar]
  13. 13. 
    Dubois RW. 2016. Cost-effectiveness thresholds in the USA: Are they coming? Are they already here?. J. Comp. Eff. Res. 5:9–12
    [Google Scholar]
  14. 14. 
    El Achhab Y, Nejjari C, Chikri M, Lyoussi B 2008. Disease-specific health-related quality of life instruments among adults diabetic: a systematic review. Diabetes Res. Clin. Pract. 80:171–84
    [Google Scholar]
  15. 15. 
    Erickson P. 1998. Evaluation of a population-based measure of quality of life: the Health and Activity Limitation Index (HALex). Qual. Life Res. 7:101–14
    [Google Scholar]
  16. 16. 
    Erickson P, Kendall EA, Anderson JP, Kaplan RM 1989. Using composite health status measures to assess the nation's health. Med. Care 27:S66–76
    [Google Scholar]
  17. 17. 
    Erickson P, Wilson R, Shannon I 1995. Years of healthy life. Healthy People 2000 Stat. Notes 1995:71–15
    [Google Scholar]
  18. 18. 
    Farivar SS, Cunningham WE, Hays RD. 2007. Correlated physical and mental health summary scores for the SF-36 and SF-12 Health Survey, V. 1. Health Qual. Life Outcomes 5:54
    [Google Scholar]
  19. 19. 
    Feeny D, Furlong W, Mulhern RK, Barr RD, Hudson M 1999. A framework for assessing health-related quality of life among children with cancer. Int. J. Cancer Suppl. 12:2–9
    [Google Scholar]
  20. 20. 
    Feeny D, Furlong W, Torrance GW, Goldsmith CH, Zhu Z et al. 2002. Multiattribute and single-attribute utility functions for the health utilities index mark 3 system. Med. Care 40:113–28
    [Google Scholar]
  21. 21. 
    Feeny D, Spritzer K, Hays RD, Liu H, Ganiats TG et al. 2012. Agreement about identifying patients who change over time: cautionary results in cataract and heart failure patients. Med. Decis. Mak. 32:273–86
    [Google Scholar]
  22. 22. 
    Ferreira LN, Ferreira PL, Pereira LN, Brazier J, Rowen D. 2010. A Portuguese value set for the SF-6D. Value Health 13:624–30
    [Google Scholar]
  23. 23. 
    Froberg DG, Kane RL. 1989. Methodology for measuring health-state preferences—II: scaling methods. J. Clin. Epidemiol. 42:459–71
    [Google Scholar]
  24. 24. 
    Fryback DG, Dunham NC, Palta M, Hanmer J, Buechner J et al. 2007. US norms for six generic health-related quality-of-life indexes from the National Health Measurement Study. Med. Care 45:1162–70
    [Google Scholar]
  25. 25. 
    Fryback DG, Palta M, Cherepanov D, Bolt D, Kim J-S. 2007. Cross-walks among five self-reported summary health utility indexes: progress and prospects Presented at Annual Meeting of the Society for Medical Making Pittsburgh, PA: Oct. 20–24
  26. 26. 
    Fryback DG, Palta M, Cherepanov D, Bolt D, Kim J-S. 2010. Comparison of 5 health-related quality-of-life indexes using item response theory analysis. Med. Decis. Mak. 30:5–15
    [Google Scholar]
  27. 27. 
    Ganiats TG, Palinkas LA, Kaplan RM. 1992. Comparison of Quality of Well-Being scale and Functional Status Index in patients with atrial fibrillation. Med. Care 30:958–64
    [Google Scholar]
  28. 28. 
    Garin O, Ferrer M, Pont À, Rué M, Kotzeva A et al. 2009. Disease-specific health-related quality of life questionnaires for heart failure: a systematic review with meta-analyses. Qual. Life Res. 18:71–85
    [Google Scholar]
  29. 29. 
    Gold M, Franks P, Erickson P. 1996. Assessing the health of the nation. The predictive validity of a preference-based measure and self-rated health. Med. Care 34:163–77
    [Google Scholar]
  30. 30. 
    Gold MR, Siegel JE, Russell LB, Weinstein MC 1996. Cost-Effectiveness in Health and Medicine Oxford, UK: Oxford Univ. Press
  31. 31. 
    Gudex C, Dolan P, Kind P, Williams A 1996. Health state valuations from the general public using the visual analogue scale. Qual. Life Res. 5:521–31
    [Google Scholar]
  32. 32. 
    Guertin JR, Humphries B, Feeny D, Tarride J-E. 2018. Health Utilities Index Mark 3 scores for major chronic conditions: population norms for Canada based on the 2013–2014 Canadian Community Health Survey. Health Rep. 29:12–19
    [Google Scholar]
  33. 33. 
    Hanmer J. 2021. Cross-sectional validation of the PROMIS-Preference scoring system by its association with social determinants of health. Qual. Life Res. 30:881–89
    [Google Scholar]
  34. 34. 
    Hanmer J, Dewitt B, Yu L, Tsevat J, Roberts M et al. 2018. Cross-sectional validation of the PROMIS-Preference scoring system. PLOS ONE 13:e0201093
    [Google Scholar]
  35. 35. 
    Hays RD 2011. Applying item response theory for questionnaire evaluation. Question Evaluation Methods: Contributing to the Science of Data Quality J Madans, K Miller, A Maitland, G Willis 125–35 Hoboken, NJ: Wiley
    [Google Scholar]
  36. 36. 
    Hays RD, Fayers PM. 2021. Overlap of depressive symptoms with health-related quality-of-life measures. Pharmacoeconomics 39:627–30
    [Google Scholar]
  37. 37. 
    Hays RD, Kim S, Spritzer KL, Kaplan RM, Tally S et al. 2009. Effects of mode and order of administration on generic health-related quality of life scores. Value Health 12:1035–39
    [Google Scholar]
  38. 38. 
    Hays RD, Morales LS, Reise SP. 2000. Item response theory and health outcomes measurement in the 21st century. Med. Care 38:II28–42
    [Google Scholar]
  39. 39. 
    Hays RD, Reeve BB, Smith AW, Clauser SB. 2014. Associations of cancer and other chronic medical conditions with SF-6D preference-based scores in Medicare beneficiaries. Qual. Life Res. 23:385–91
    [Google Scholar]
  40. 40. 
    Hays RD, Sherbourne CD, Mazel RM. 1993. The RAND 36-item health survey 1.0. Health Econ. 2:217–27
    [Google Scholar]
  41. 41. 
    Hays RD, Spritzer KL, Schalet BD, Cella D. 2018. PROMIS®-29 v2.0 profile physical and mental health summary scores. Qual. Life Res. 27:1885–91
    [Google Scholar]
  42. 42. 
    Hays RD, Spritzer KL, Thompson WW, Cella D. 2015. U.S. general population estimate for “excellent” to “poor” self-rated health item. J. Gen. Intern. Med. 30:1511–16
    [Google Scholar]
  43. 43. 
    Hays RD, Weech-Maldonado R, Teresi JA, Wallace SP, Stewart AL 2018. Commentary: copyright restrictions versus open access to survey instruments. Med. Care 56:107–10
    [Google Scholar]
  44. 44. 
    Hołownia-Voloskova M, Tarbastaev A, Golicki D 2021. Population norms of health-related quality of life in Moscow, Russia: the EQ-5D-5L-based survey. Qual. Life Res. 30:831–40
    [Google Scholar]
  45. 45. 
    Hurst NP, Kind P, Ruta D, Hunter M, Stubbings A. 1997. Measuring health-related quality of life in rheumatoid arthritis: validity, responsiveness and reliability of EuroQol (EQ-5D). Br. J. Rheumatol. 36:551–59
    [Google Scholar]
  46. 46. 
    Kaplan RM. 1993. Allocating health resources in California: learning from the Oregon experiment Calif. Policy Semin. Brief , Vol. 5 Calif. Policy Semin. Berkeley:
  47. 47. 
    Kaplan RM. 1993. Quality of life assessment for cost/utility studies in cancer. Cancer Treat. Rev. 19:Suppl. A85–96
    [Google Scholar]
  48. 48. 
    Kaplan RM. 1994. Value judgment in the Oregon Medicaid experiment. Med. Care 32:975–88
    [Google Scholar]
  49. 49. 
    Kaplan RM 1995. Utility assessment for estimating quality-adjusted life years. Valuing Health Care: Costs, Benefits, and Effectiveness of Pharmaceuticals and Other Medical Technologies FA Sloan 31–60 Cambridge, UK: Cambridge Univ. Press
    [Google Scholar]
  50. 50. 
    Kaplan RM, Alcaraz JE, Anderson JP, Weisman M 1996. Quality-adjusted life years lost to arthritis: effects of gender, race, and social class. Arthritis Care Res. 9:473–82
    [Google Scholar]
  51. 51. 
    Kaplan RM, Anderson JP. 1988. A general health policy model: update and applications. Health Serv. Res. 23:203–35
    [Google Scholar]
  52. 52. 
    Kaplan RM, Anderson JP, Patterson TL, McCutchan JA, Weinrich JD et al. 1995. Validity of the Quality of Well-Being Scale for persons with human immunodeficiency virus infection. HNRC Group. HIV Neurobehavioral Research Center. Psychosom. Med. 57:138–47
    [Google Scholar]
  53. 53. 
    Kaplan RM, Atkins CJ, Timms R. 1984. Validity of a quality of well-being scale as an outcome measure in chronic obstructive pulmonary disease. J. Chronic Dis. 37:85–95
    [Google Scholar]
  54. 54. 
    Kaplan RM, Bush JW, Berry CC. 1976. Health status: types of validity and the Index of Well-being. Health Serv. Res. 11:478–507
    [Google Scholar]
  55. 55. 
    Kaplan RM, Ernst JA. 1983. Do category rating scales produce biased preference weights for a health index?. Med. Care 21:193–207
    [Google Scholar]
  56. 56. 
    Kaplan RM, Feeny D, Revicki DA 1993. Methods for assessing relative importance in preference based outcome measures. Qual. Life Res. 2:467–75
    [Google Scholar]
  57. 57. 
    Kaplan RM, Ganiats TG, Sieber WJ, Anderson JP. 1998. The Quality of Well-Being Scale: critical similarities and differences with SF-36. Int. J. Qual. Health Care 10:509–20
    [Google Scholar]
  58. 58. 
    Kaplan RM, Hartwell SL, Wilson DK, Wallace JP 1987. Effects of diet and exercise interventions on control and quality of life in non-insulin-dependent diabetes mellitus. J. Gen. Intern. Med. 2:220–28
    [Google Scholar]
  59. 59. 
    Kaplan RM, Patterson TL, Kerner DN, Atkinson JH, Heaton RK, Grant I. 1997. The Quality of Well-Being scale in asymptomatic HIV-infected patients. HNRC Group. HIV Neural Behavioral Research Center. Qual. Life Res. 6:507–14
    [Google Scholar]
  60. 60. 
    Kaplan RM, Schmidt SM, Cronan TA. 2000. Quality of well being in patients with fibromyalgia. J. Rheumatol. 27:785–89
    [Google Scholar]
  61. 61. 
    Kaplan RM, Sieber WJ, Ganiats TG. 1997. The Quality of Well-being Scale: comparison of the interviewer-administered version with a self-administered questionnaire. Psychol. Health 12:783–91
    [Google Scholar]
  62. 62. 
    Kaplan RM, Sun Q, Naunheim KS, Ries AL. 2014. Long-term follow-up of high-risk patients in the National Emphysema Treatment Trial. Ann. Thorac. Surg. 98:1782–89
    [Google Scholar]
  63. 63. 
    Kaplan RM, Tally S, Hays RD, Feeny D, Ganiats TG et al. 2011. Five preference-based indexes in cataract and heart failure patients were not equally responsive to change. J. Clin. Epidemiol. 64:497–506
    [Google Scholar]
  64. 64. 
    Kattan MW, Fearn PA, Miles BJ. 2001. Time trade-off utility modified to accommodate degenerative and life-threatening conditions. Proc. AMIA Symp. 2001:304–8
    [Google Scholar]
  65. 65. 
    Khanna D, Krishnan E, Dewitt EM, Khanna PP, Spiegel B, Hays RD. 2011. The future of measuring patient-reported outcomes in rheumatology: Patient-Reported Outcomes Measurement Information System (PROMIS). Arthritis Care Res 63:Suppl. 11S486–90
    [Google Scholar]
  66. 66. 
    Kharroubi SA, Beyh Y, El Harake MD, Dawoud D, Rowen D, Brazier J. 2020. Examining the feasibility and acceptability of valuing the Arabic version of SF-6D in a Lebanese population. Int. J. Environ. Res. Public Health 17:1037
    [Google Scholar]
  67. 67. 
    Kim S-H, Lee S-I, Jo M-W. 2017. Feasibility, comparability, and reliability of the standard gamble compared with the rating scale and time trade-off techniques in Korean population. Qual. Life Res. 26:3387–97
    [Google Scholar]
  68. 68. 
    Kind P. 1997. The performance characteristics of EQ-5D, a measure of health related quality of life for use in technology assessment [abstract]. Annu. Meet. Int. Soc. Technol. Assess. Health Care 13:81
    [Google Scholar]
  69. 69. 
    Klapproth CP, Fischer F, Merbach M, Matthias R, Obbarius A 2021. Validity, reliability, and ceiling and floor effects of the PROMIS Preference score (PROPr) in patients with rheumatological and psychosomatic conditions. Research Square https://doi.org/10.21203/rs.3.rs-478767/v1
    [Crossref] [Google Scholar]
  70. 70. 
    Lam CLK, Brazier J, McGhee SM. 2008. Valuation of the SF-6D health states is feasible, acceptable, reliable, and valid in a Chinese population. Value Health 11:295–303
    [Google Scholar]
  71. 71. 
    Landfeldt E, Lindberg C, Sejersen T. 2020. Improvements in health status and utility associated with ataluren for the treatment of nonsense mutation Duchenne muscular dystrophy. Muscle Nerve 61:363–68
    [Google Scholar]
  72. 72. 
    Lipman SA, Brouwer WB, Attema AE. 2020. What is it going to be, TTO or SG? A direct test of the validity of health state valuation. Health Econ. 29:1475–81
    [Google Scholar]
  73. 73. 
    Loken E, Gelman A. 2017. Measurement error and the replication crisis. Science 355:584–85
    [Google Scholar]
  74. 74. 
    Lugnér AK, Krabbe PF. 2020. An overview of the time trade-off method: concept, foundation, and the evaluation of distorting factors in putting a value on health. Expert Rev. Pharmacoecon. Outcomes Res. 20:331–42
    [Google Scholar]
  75. 75. 
    Makarov DV, Holmes-Rovner M, Rovner DR, Averch T, Barry MJ et al. 2018. Quality Improvement Summit 2016: shared decision making and prostate cancer screening. Urol. Pract. 5:44451
    [Google Scholar]
  76. 76. 
    Marrie RA, Dufault B, Tyry T, Cutter GR, Fox RJ, Salter A. 2020. Developing a crosswalk between the RAND-12 and the health utilities index for multiple sclerosis. Multiple Scler. J. 26:1102–10
    [Google Scholar]
  77. 77. 
    Meenan RF, Mason JH, Anderson JJ, Guccione AA, Kazis LE. 1992. AIMS2. The content and properties of a revised and expanded Arthritis Impact Measurement Scales Health Status Questionnaire. Arthritis Rheum. 35:1–10
    [Google Scholar]
  78. 78. 
    Mischel W. 2008. The toothbrush problem. APS Observer 21: https://www.psychologicalscience.org/observer/the-toothbrush-problem
    [Google Scholar]
  79. 79. 
    Mischel W. 2009. Becoming a cumulative science. APS Observer 22: https://www.psychologicalscience.org/observer/becoming-a-cumulative-science
    [Google Scholar]
  80. 80. 
    Młyńczak K, Golicki D. 2021. Validity of the EQ-5D-5L questionnaire among the general population of Poland. Qual. Life Res. 30:817–29
    [Google Scholar]
  81. 81. 
    Montazeri A. 2008. Health-related quality of life in breast cancer patients: a bibliographic review of the literature from 1974 to 2007. J. Exp. Clin. Cancer Res. 27:32
    [Google Scholar]
  82. 82. 
    Mulhern BJ, Bansback N, Norman R, Brazier J 2020. Valuing the SF-6Dv2 classification system in the United Kingdom using a discrete-choice experiment with duration. Med. Care 58:566–73
    [Google Scholar]
  83. 83. 
    Natl. Emphysema Treat. Trial Res. Group 2001. Patients at high risk of death after lung-volume–reduction surgery. N. Engl. J. Med. 345:1075–83
    [Google Scholar]
  84. 84. 
    Natl. Emphysema Treat. Trial Res. Group 2003. Cost effectiveness of lung-volume–reduction surgery for patients with severe emphysema. N. Engl. J. Med. 348:2092–102
    [Google Scholar]
  85. 85. 
    Nelson EC, Eftimovska E, Lind C, Hager A, Wasson JH, Lindblad S. 2015. Patient reported outcome measures in practice. BMJ 350:g7818
    [Google Scholar]
  86. 86. 
    Neumann PJ, Kim DD, Trikalinos TA, Sculpher MJ, Salomon JA et al. 2018. Future directions for cost-effectiveness analyses in health and medicine. Med. Decis. Mak. 38:767–77
    [Google Scholar]
  87. 87. 
    Neumann PJ, Sanders GD, Russell LB, Siegel JE, Ganiats TG. 2016. Cost-Effectiveness in Health and Medicine Oxford, UK: Oxford Univ. Press
  88. 88. 
    Nortvedt MW, Riise T, Myhr K-M, Nyland HI. 2000. Performance of the SF-36, SF-12, and RAND-36 summary scales in a multiple sclerosis population. Med. Care 38:1022–28
    [Google Scholar]
  89. 89. 
    Noto S, Shiroiwa T, Kobayashi M, Murata T, Ikeda S, Fukuda T. 2020. Development of a multiplicative, multi-attribute utility function and eight single-attribute utility functions for the Health Utilities Index Mark 3 in Japan. J. Patient-Rep. Outcomes 4:23
    [Google Scholar]
  90. 90. 
    Orenstein DM, Kaplan RM. 1991. Measuring the quality of well-being in cystic fibrosis and lung transplantation. The importance of the area under the curve. Chest 100:1016–18
    [Google Scholar]
  91. 91. 
    Orenstein DM, Pattishall EN, Nixon PA, Ross EA, Kaplan RM 1990. Quality of well-being before and after antibiotic treatment of pulmonary exacerbation in patients with cystic fibrosis. Chest 98:1081–84
    [Google Scholar]
  92. 92. 
    Øvretveit J, Zubkoff L, Nelson EC, Frampton S, Knudsen JL, Zimlichman E. 2017. Using patient-reported outcome measurement to improve patient care. Int. J. Qual. Health Care 29:874–79
    [Google Scholar]
  93. 93. 
    Palta M, Chen H-Y, Kaplan RM, Feeny D, Cherepanov D, Fryback DG 2011. Standard error of measurement of 5 health utility indexes across the range of health for use in estimating reliability and responsiveness. Med. Decis. Mak. 31:260–69
    [Google Scholar]
  94. 94. 
    Park H, Roubal AM, Jovaag A, Gennuso KP, Catlin BB. 2015. Relative contributions of a set of health factors to selected health outcomes. Am. J. Prev. Med. 49:961–69
    [Google Scholar]
  95. 95. 
    Pereira EV, Tonin FS, Carneiro J, Pontarolo R, Wiens A 2020. Evaluation of the application of the Diabetes Quality of Life Questionnaire in patients with diabetes mellitus. Arch. Endocrinol. Metab. 64:59–65
    [Google Scholar]
  96. 96. 
    Pyne JM, Patterson TL, Kaplan RM, Gillin JC, Koch WL, Grant I. 1997. Assessment of the quality of life of patients with major depression. Psychiatr. Serv. 48:224–30
    [Google Scholar]
  97. 97. 
    Pyne JM, Patterson TL, Kaplan RM, Ho S, Gillin JC et al. 1997. Preliminary longitudinal assessment of quality of life in patients with major depression. Psychopharmacol. Bull. 33:23–29
    [Google Scholar]
  98. 98. 
    Pyne JM, Sieber WJ, David K, Kaplan RM, Rapaport MH, Williams DK. 2003. Use of the quality of well-being self-administered version (QWB-SA) in assessing health-related quality of life in depressed patients. J. Affect. Disord. 76:237–47
    [Google Scholar]
  99. 99. 
    Rector TS, Cohn JN. 1992. Assessment of patient outcome with the Minnesota Living with Heart Failure questionnaire: reliability and validity during a randomized, double-blind, placebo-controlled trial of pimobendan. Am. Heart J. 124:1017–25
    [Google Scholar]
  100. 100. 
    Reeve BB, Hays RD, Bjorner JB, Cook KF, Crane PK et al. 2007. Psychometric evaluation and calibration of health-related quality of life item banks: plans for the Patient-Reported Outcomes Measurement Information System (PROMIS). Med. Care 45:5 Suppl. 1S22–31
    [Google Scholar]
  101. 101. 
    Reise SP. 1990. A comparison of item- and person-fit methods of assessing model-data fit in IRT. Appl. Psychol. Meas. 14:127–37
    [Google Scholar]
  102. 102. 
    Richardson J. 1994. Cost utility analysis: What should be measured?. Soc. Sci. Med. 39:7–22
    [Google Scholar]
  103. 103. 
    Riley W, Hays RD, Kaplan RM, Cella D. 2013. Sources of comparability between probability sample estimates and nonprobability web sample estimates Presented at Proceedings of the 2013 Federal Committee on Statistical Methodology (FCSM) Research Conference Washington, DC: Nov. 4–6. https://nces.ed.gov/FCSM/pdf/B4_Riley_2013FCSM.pdf
  104. 104. 
    Rocco MV, Gassman JJ, Wang SR, Kaplan RM 1997. Cross-sectional study of quality of life and symptoms in chronic renal disease patients: the Modification of Diet in Renal Disease Study. Am. J. Kidney Dis. 29:888–96
    [Google Scholar]
  105. 105. 
    Romanens M, Sudano I, Szucs T, Adams A 2017. Medical costs per QALY of statins based on Swiss Medical Board assumptions. Cardiovasc. Med. 20:96–100
    [Google Scholar]
  106. 106. 
    Rosen PN, Kaplan RM, David K. 2005. Measuring outcomes of cataract surgery using the Quality of Well-Being Scale and VF-14 Visual Function Index. J. Cataract Refract. Surg. 31:369–78
    [Google Scholar]
  107. 107. 
    Sanders GD, Neumann PJ, Basu A, Brock DW, Feeny D et al. 2016. Recommendations for conduct, methodological practices, and reporting of cost-effectiveness analyses: second panel on cost-effectiveness in health and medicine. JAMA 316:1093–103
    [Google Scholar]
  108. 108. 
    Schalet BD, Lim S, Cella D, Choi SW 2021. Linking scores with patient-reported health outcome instruments: a validation study and comparison of three linking methods. Psychometrika 86:3717–46
    [Google Scholar]
  109. 109. 
    Selim A, Rogers W, Qian S, Rothendler JA, Kent EE, Kazis LE 2018. A new algorithm to build bridges between two patient-reported health outcome instruments: the MOS SF-36® and the VR-12 Health Survey. Qual. Life Res. 27:2195–206
    [Google Scholar]
  110. 110. 
    Setodji CM, Reise SP, Morales LS, Fongwa MN, Hays RD. 2011. Differential item functioning by survey language among older Hispanics enrolled in Medicare managed care: a new method for anchor item selection. Med. Care 49:461–68
    [Google Scholar]
  111. 111. 
    Shallcross AJ, Lu NY, Hays RD. 2020. Evaluation of the psychometric properties of the Five Facet of Mindfulness Questionnaire. J. Psychopathol. Behav. Assess. 42:271–80
    [Google Scholar]
  112. 112. 
    Shiroiwa T, Ikeda S, Noto S, Fukuda T, Stolk E 2021. Valuation Survey of EQ-5D-Y based on the international common protocol: development of a value set in Japan. Med. Decis. Mak. 41:597–606
    [Google Scholar]
  113. 113. 
    Simon GE, Revicki DA, Grothaus L, Vonkorff M. 1998. SF-36 summary scores: Are physical and mental health truly distinct?. Med. Care 36:567–72
    [Google Scholar]
  114. 114. 
    Snyder CF, Aaronson NK, Choucair AK, Elliott TE, Greenhalgh J et al. 2012. Implementing patient-reported outcomes assessment in clinical practice: a review of the options and considerations. Qual. Life Res. 21:1305–14
    [Google Scholar]
  115. 115. 
    Squier HC, Ries AL, Kaplan RM, Prewitt LM, Smith CM et al. 1995. Quality of well-being predicts survival in lung transplantation candidates. Am. J. Respir. Crit. Care Med. 152:2032–36
    [Google Scholar]
  116. 116. 
    Teresi JA, Wang C, Kleinman M, Jones RN, Weiss DJ. 2021. Differential item functioning analyses of the Patient-Reported Outcomes Measurement Information System (PROMIS®) measures: methods, challenges, advances, and future directions. Psychometrika 86:3674–711
    [Google Scholar]
  117. 117. 
    Thompson AJ, Turner AJ. 2020. A comparison of the EQ-5D-3L and EQ-5D-5L. Pharmacoeconomics 38:575–91
    [Google Scholar]
  118. 118. 
    Uy V, Hays RD, Xu JJ, Fayers PM, Auerbach AD et al. 2020. Do the unlabeled response categories of the Minnesota Living with Heart Failure Questionnaire satisfy the monotonicity assumption of simple-summated scoring?. Qual. Life Res. 29:1349–60
    [Google Scholar]
  119. 119. 
    Voshaar MO, Vonkeman H, Courvoisier D, Finckh A, Gossec L et al. 2019. Towards standardized patient reported physical function outcome reporting: linking ten commonly used questionnaires to a common metric. Qual. Life Res. 28:187–97
    [Google Scholar]
  120. 120. 
    Ware J, Kosinski M, Keller S. 1994. SF-36 Physical and Mental Health Summary Scales: A User's Manual Boston: Health Inst.
  121. 121. 
    Wasson J, Hays R, Rubenstein L, Nelson E, Leaning J et al. 1992. The short-term effect of patient health status assessment in a health maintenance organization. Qual. Life Res. 1:99–106
    [Google Scholar]
  122. 122. 
    Weinberger M, Samsa GP, Hanlon JT, Schmader K, Doyle ME et al. 1991. An evaluation of a brief health status measure in elderly veterans. J. Am. Geriatr. Soc. 39:691–94
    [Google Scholar]
  123. 123. 
    Weinstein MC, Stason WB. 1985. Cost-effectiveness of interventions to prevent or treat coronary heart disease. Annu. Rev. Public Health 6:41–63
    [Google Scholar]
  124. 124. 
    Whang KA, Khanna R, Williams KA, Mahadevan V, Semenov Y, Kwatra SG. 2021. Health-related QOL and economic burden of chronic pruritus. J. Investig. Dermatol. 141:754–60.e1
    [Google Scholar]
  125. 125. 
    WHO (World Health Organ.) 2015. Global reference list of 100 core health indicators Rep. WHO Geneva:
  126. 126. 
    Wilson N, Davies A, Brewer N, Nghiem N, Cobiac L, Blakely T 2019. Can cost-effectiveness results be combined into a coherent league table? Case study from one high-income country. Popul. Health Metrics 17:10
    [Google Scholar]
  127. 127. 
    Wolfson M. 2014. Measuring the health component of quality of life. Stat. J. IAOS 30:193–207
    [Google Scholar]
  128. 128. 
    Zhang J, Dewitt B, Tang E, Breitner D, Saqib M et al. 2021. Evaluation of PROMIS Preference Scoring System (PROPr) in patients undergoing hemodialysis or kidney transplant. Clin. J. Am. Soc. Nephrol. 16:1328–36
    [Google Scholar]
  129. 129. 
    Zhang P, Atkinson KM, Bray GA, Chen H, Clark JM et al. 2021. Within-trial cost-effectiveness of a structured lifestyle intervention in adults with overweight/obesity and type 2 diabetes: results from the Action for Health in Diabetes (Look AHEAD) Study. Diabetes Care 44:67–74
    [Google Scholar]
/content/journals/10.1146/annurev-publhealth-052120-012811
Loading
/content/journals/10.1146/annurev-publhealth-052120-012811
Loading

Data & Media loading...

  • Article Type: Review Article
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error