Advertisement

Springer Nature is making SARS-CoV-2 and COVID-19 research free. View research | View latest news | Sign up for updates

Review of Valuation Methods of Preference-Based Measures of Health for Economic Evaluation in Child and Adolescent Populations: Where are We Now and Where are We Going?

Abstract

Methods for measuring and valuing health benefits for economic evaluation and health technology assessment in adult populations are well developed. In contrast, methods for assessing interventions for child and adolescent populations lack detailed guidelines, particularly regarding the valuation of health and quality of life in these age groups. This paper critically examines the methodological considerations involved in the valuation of child- and adolescent-specific health-related quality of life by existing preference-based measures. It also describes the methodological choices made in the valuation of existing generic preference-based measures developed with and/or applied in child and adolescent populations: AHUM, AQoL-6D, CHU9D, EQ-5D-Y, HUI2, HUI3, QWB, 16D and 17D. The approaches used to value existing child- and adolescent-specific generic preference-based measures vary considerably. While the choice of whose preferences and which perspective to use is a matter of normative debate and ultimately for decision by reimbursement agencies and policy makers, greater research around these issues would be informative and would enrich these discussions. Research can also inform the other methodological choices required in the valuation of child and adolescent health states. Gaps in research evidence are identified around the impact of the child described in health state valuation exercises undertaken by adults, including the possibility of informed preferences; the appropriateness and acceptability of valuation tasks for adolescents, in particular tasks involving the state ‘dead’; anchoring of adolescent preferences; and the generation and use of combined adult and adolescent preferences.

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

References

  1. 1.

    National Institute for Health and Care Excellence. Guide to the methods of technology appraisal. London: NICE; 2013.

  2. 2.

    Pharmaceutical Benefits Advisory Committee (PBAC). Guidelines for Preparing Submissions to the Pharmaceutical Benefits Advisory Committee. Canberra, ACT: Government Department of Health; 2013.

  3. 3.

    Brazier J, Ara R, Azzabi I, et al. Identification, review, and use of health state utilities in cost-effectiveness models: an ISPOR Good Practices for Outcomes Research Task Force Report. Value Health. 2019;22(3):267–75.

  4. 4.

    Wolowacz SE, Briggs A, Belozeroff V, et al. Estimating Health-state utility for economic models in clinical studies: an ISPOR Good Research Practices Task Force Report. Value Health. 2016;19(6):704–19.

  5. 5.

    Ungar W. Economic evaluation in child health. Oxford: Oxford University Press; 2009.

  6. 6.

    Stevens KJ. Assessing the performance of a new generic measure of health related quality of life for children and refining it for use in health state valuation. Appl Health Econ Health Policy. 2011;9(3):157–69.

  7. 7.

    Matza LS, Patrick D, Riley AW, et al. Pediatric patient-reported outcome instruments for research to support medical product labeling: report of the ISPOR PRO good research practices for the assessment of children and adolescents task force. Value Health. 2013;16:461–79.

  8. 8.

    Ungar WJ. Challenges in health state valuation in paediatric economic evaluation: are QALYs contraindicated? Pharmacoeconomics. 2011;29(8):641–52.

  9. 9.

    Prosser LA, Hammitt JK, Keren R. Measuring health preferences for use in cost-utility and cost-benefit analyses of interventions in children: theoretical and methodological considerations. Pharmacoeconomics. 2007;25(9):713–26.

  10. 10.

    Petrou S. Methodological issues raised by preference-based approaches to measuring the health status of children. Health Econ. 2003;12:697–702.

  11. 11.

    De Civita M, Regier D, Alamgir AH, Anis AH, FitzGerald MJ, Marra CA. evaluating health-related quality-of-life studies in paediatric populations some conceptual, methodological and developmental considerations and recent applications. Pharmacoeconomics. 2005;23(7):659–85.

  12. 12.

    Pickard S, Knight SJ. Proxy evaluation of health-related quality of life: a conceptual framework for understanding multiple proxy perspectives. Med Care. 2005;43(5):493–9.

  13. 13.

    Chen G, Ratcliffe J. A review of the development and application of generic multi-attribute utility instruments for paediatric populations. Pharmacoeconomics. 2015;33:1013–28.

  14. 14.

    Beusterien KM, Yeung JE, Pang F, Brazier J. Development of the multi-attribute Adolescent Health Utility Measure (AHUM). Health Qual Life Outcomes. 2012;10:102.

  15. 15.

    Richardson J, Day N, Peacock S, et al. Measurement of the quality of life for economic evaluation and the Assessment of Quality of Life (AQoL) Mark 2 instrument. Aust Econ Hist Review. 2004;37:62–88.

  16. 16.

    Moodie M, Richardson J, Rankin B, et al. Predicting time trade-off health state valuations of adolescents in four pacific countries using the AQoL-6D instrument. Value Health. 2010;13:1014–27.

  17. 17.

    Stevens KJ. Developing a descriptive system for a new preference-based measure of health-related quality of life for children. Qual Life Res. 2009;18(8):1105–13.

  18. 18.

    Stevens KJ. Working with children to develop dimensions for a preference-based, generic, pediatric health-related quality-of-life measure. Qual Health Res. 2010;20:340–51.

  19. 19.

    Ratcliffe J, Couzner L, Flynn T, Sawyer M, Stevens K, Brazier J, Burgess L. Valuing child health utility 9D health states with a young adolescent sample: a feasibility study to compare best-worst discrete choice experiment, standard gamble and time trade off methods. Appl Health Econ Health Policy. 2011;9(1):15–27.

  20. 20.

    Ratcliffe J, Flynn T, Terlich F, Brazier J, Stevens K, Sawyer M. Developing adolescent specific health state values for economic evaluation: an application of profile case best worst scaling to the Child Health Utility-9D. Pharmacoeconomics. 2012;30:713–27.

  21. 21.

    Ratcliffe J, Chen G, Stevens K, Bradley S, Couzner L, Brazier J, et al. Valuing child health utility 9D health states with young adults: insights from a time trade-off study. Appl Health Econ Health Policy. 2015;13:485–92.

  22. 22.

    Ratcliffe J, Huynh E, Stevens K, Brazier J, Sawyer M, Flynn T. Nothing about us without us? A comparison of adolescent and adult health-state values for the child health utility-9D using profile case best-worst scaling. Health Econ. 2016;25:486–96.

  23. 23.

    Chen G, Xu F, Huynh E, Zhiyong W, Stevens K, Ratcliffe J. Scoring the Child Health Utility 9D instrument: estimation of a Chinese child and adolescent-specific tariff. Qual Life Res. 2019;28:163–76.

  24. 24.

    Rowen DL, Mulhern B, Stevens K, Vermaire E. Estimating a Dutch value set for the paediatric preference-based CHU9D using a discrete choice experiment with duration. Value Health. 2018;21:1234–42.

  25. 25.

    Stevens K. Valuation of the child health utility 9D Index. Pharmacoeconomics. 2012;30(8):729–47.

  26. 26.

    Devlin N, Brooks R. EQ-5D and the EuroQol Group: past, Present and Future. Appl Health Econ Health Policy. 2017;15:127–37.

  27. 27.

    Ravens-Sieberer U, Wille N, Badia X, et al. Feasibility, reliability and validity of the EQ-5D-Y: results from a multinational study. Qual Life Res. 2010;19:87–897.

  28. 28.

    Wille N, Badia X, Bonsel G, et al. Development of the EQ-5D-Y: a child-friendly version of the EQ-5D. Qual Life Res. 2010;19:875–86.

  29. 29.

    Craig B, Greiner W, Brown DS, Reeve BB. Valuation of child-related quality of life in the United States. Health Econ. 2016;25:768–77.

  30. 30.

    Torrance G, Feeny D, Furling W, et al. Multiattribute utility function for a comprehensive health status classification system: health Utilities Index Mark 2. Med Care. 1996;34:702–22.

  31. 31.

    McCabe C, Stevens K, Roberts J, Brazier J. Health state values for the HUI 2 descriptive system: results from a UK survey. Health Econ. 2005;14:231–44.

  32. 32.

    Feeny D, Furlong W, Torrance GW, Goldsmith CH, Zhu Z, DePauw S, Denton M, Boyle M. Multiattribute and Single-attribute utility functions for the health utilities index mark 3 system. Med Care. 2002;40(2):113–28.

  33. 33.

    Seiber WJ, Groessl EJ, David KM, Ganiats TG, Kaplan RM. Quality of well being self-administered (QWB-SA) scale: user’s manual. San Diego: Health Services Research Center, University of California; 2008.

  34. 34.

    Apajasalo M, et al. Quality of life in early adolescence: a sixteen-dimensional health-related measure (16D). Qual Life Res. 1996;5:205–11.

  35. 35.

    Apajasalo M, et al. Quality of life in pre-adolescence: a 17-dimensional health-related measure (17D). Qual Life Res. 1996;5:532–8.

  36. 36.

    Stevens KJ, et al. The development of a preference-based measure of health in children with atopic dermatitis. Br J Dermatol. 2005;153(2):372–7.

  37. 37.

    Choiu CF, et al. Development of the multi-attribute Paediatric Asthma Health Outcome Measure (PAHOM). Int J Qual Health Care. 2005;17(1):23–30.

  38. 38.

    Saigal S, Stoskopf BL, Feeny D, et al. Differences in preferences for neonatal outcomes among health care professionals, parents, and adolescents. JAMA. 1999;281(21):1991–7.

  39. 39.

    Mott DJ, Rivero-Arias O, Shah K, Ramos-Goñi JM, Devlin NJ. Valuing the EQ-5D-Y using a discrete choice experiment: do adult and adolescent preferences differ? OHE Research Paper. London: Office of Health Economics; 2019.

  40. 40.

    Lipstein EA, Brinkman WB, Fiks AG, Hendrix KS, Kryworuchko J, Miller VA, et al. An emerging field of research: challenges in pediatric decision making. Med Decis Making. 2015;35(3):403–8.

  41. 41.

    United Nations. Convention on the rights of the child. London: United Nation; 1989.

  42. 42.

    Department of Health Chief Medical Officer’s annual report. Our Children Deserve Better: Prevention Pays. Department of Health; 2012.

  43. 43.

    National Health and Hospital Report Commission. A healthier future for all Australians: final report of the National Health and Hospital Reform Commission. 2009.

  44. 44.

    Ministerio de Sanidad y Consumo. Ganar Salud con la Juventud. Madrid Ministerio de Sanidad y Consumol 2008.

  45. 45.

    Stevens KJ. Because that’s what matters to me. A pilot study to test the feasibility and reliability of ordinal valuation methods for health state valuation with children. HEDS Discussion Paper, 2015. https://www.shef.ac.uk/scharr/sections/heds/discussion-papers/15-05-1.526948. Accessed 17 Dec 2019.

  46. 46.

    Norman R, Viney R, Aaronson NK, Brazier JE, Cella D, Costa DSJ, et al. Using a discrete choice experiment to value the QLU-C10D: feasibility and sensitivity to presentation format. Qual Life Res. 2016;25(3):637–49.

  47. 47.

    Mott DJ, Shah K, Ramos-Goñi J, Devlin N, Rivero-Arias O. Valuing EQ-5D-Y health states using a discrete choice experiment: do adult and adolescent preferences differ? OHE Research Paper. London: Office of Health Eco; 2019.

  48. 48.

    Dalziel K, Catchpool M, Garcia-Lorenzo B, Gorostiza I, Norman R, Rivero-Arias O. Feasibility and validity of adolescent and adult health state preferences for EQ-5D-Y states in Australia and Spain: an application of best-worst scaling. (in press).

  49. 49.

    Yi MS, Britto MT, Wilmott RW, Kotagal UR, Eckman MH, Nielson DW, et al. Health values of adolescents with cystic fibrosis. J Pediatrics. 2003;142(2):133–40.

  50. 50.

    Wu XY, Ohinmaa A, Johnson JA, Veugelers PJ. Assessment of children’s own health status using visual analogue scale and descriptive system of the EQ-5D-Y: linkage between two systems. Qual Life Res. 2014;23:393–402.

  51. 51.

    Brazier J, Rowen DL, Karimi M, Peasgood T, Tsuchiya A, Ratcliffe J. Experience-based utility and own health state valuation for a health state classification system: why do it and how to do it. Eur J Health Econ. 2018;19:881–91.

  52. 52.

    Brouwer W, Versteegh M. Patient and general public preferences for health states: a call to reconsider current guidelines. Soc Sci Med. 2016;165:66–74.

  53. 53.

    Sanders GD, Neumann PJ, Basu A, Brock DQ, Feeny D, Krahn M, et al. Recommendations for conduct, methodological practices, and reporting of cost-effectiveness analyses: second panel on cost-effectiveness in health and medicine. JAMA. 2016;316:1093–103.

  54. 54.

    McTaggart-Cowan H. Elicitation of informed general population health state utility values: a review of the literature. Value in Health. 2011;14:1153–7.

  55. 55.

    Kreimeier S, Oppe M, Ramos-Goni JM, Cole A, Devlin N, Herdman M, et al. Valuation of EuroQol Five-Dimensional Questionnaire, Youth Version (EQ-5D-Y) and EuroQol Five-Dimensional Questionnaire, Three-Level Version (EQ-5D-3L) Health States: the Impact of wording and perspective. Value in Health. 2018;21:1291–8.

  56. 56.

    Bansback N, Brazier J, Tsuchiya A, Anis A. Using a discrete choice experiment to estimate societal health state utility values. J Health Econ. 2012;31:306–18.

  57. 57.

    Norman R, Mulhern B, Viney R. The impact of different DCE-based approaches when anchoring utility scores. Pharmacoeconomics. 2016;34(8):805–14.

  58. 58.

    Krucien N, Watson V, Ryan M. Is best-worst scaling suitable for health state valuation? A comparison with discrete choice experiments. Health Econ. 2017;26:12.

  59. 59.

    Krucien N, Sicsic J, Ryan M. For better or worse? Investigating the validity of best-worst discrete choice experiments in health. Health Econ. 2019;28:572–86.

  60. 60.

    Parkin D, Devlin N. Is there a case for using visual analogue scale valuations in cost utility analysis? Health Econ. 2006;15:653–64.

  61. 61.

    Brazier J, Ratcliffe J, Saloman J, Tsuchiya A. Measuring and Valuing Health Benefits for Economic Evaluation. Oxford: Oxford University Press; 2016.

  62. 62.

    Kind P, Klose K, Gusi N, Olivares PR, Greiner W. Can adult weights be used to value child health states? Testing the influence of perspective in valuing EQ-5D-Y. Qual Life Res. 2015;24:2519–39.

  63. 63.

    Rowen D, Brazier J, Van Hout B. A comparison of methods for converting DCE values onto the full health-dead QALY Scale. Med Decis Mak. 2015;35:328–40.

  64. 64.

    Hill H, Rowen D, Pennington D, Wong R, Wailoo A. NICE DSU Report. A review of the methods used to estimate and model utility values in NICE technology appraisals for paediatric populations. 2019.

  65. 65.

    Kromm SK, Bethell J, Kraglund F, et al. Characteristics and quality of pediatric cost-utility analyses. Qual Life Res. 2012;21:1315.

  66. 66.

    Herdman M, Cole A, Hoyle CK, Coles V, Carroll S, Devlin N. Sources and characteristics of utility weights for economic evaluation of pediatric vaccines: a systematic review. Value Health. 2016;19:255–66.

  67. 67.

    Kwon J, Wook Kim S, Ungar WJ, Tsiplova K, Madan J, Petrou S. A systematic review and meta-analysis of childhood health utilities. Med Decis Maki 2018;38(3):277–305.

  68. 68.

    Thorrington d, Eames K. Measuring health utilities in children and adolescents: a systematic review of the literature. PLoS One. 2015;18(8):e013567.

  69. 69.

    Brazier JE, Rowen D, Mavranezouli I, Tsuchiya A, Young T, Yang Y, et al. Developing and testing methods for deriving preference-based measures of health from condition-specific measures (and other patient-based measures of outcome). Health Technol Assess. 2012;16(32):1–114.

  70. 70.

    Varni JW, Seid M, Rode CA. The PedsQL™: measurement model for the pediatric quality of life inventory. Med Care. 1999;37(2):126–39.

  71. 71.

    DeWalt DA, Gross HE, Gipson DS, Selewski DT, DeWitt EM, Dampier CD, et al. PROMIS pediatric self report scales distinguish subgroups of children within and across six common pediatric chronic health conditions. Qual Life Res. 2015;24(9):2195–208.

  72. 72.

    Ramos-Goñi JM, Shah K, Kreimeier S, Devlin NJ. Anchoring latent scale values for the EQ-5D-Y at 0 = dead. OHE Research Paper. London: Office of Health Econ; 2019.

  73. 73.

    Lavelle TA, D’Cruz BN, Mohit B, Ungar WJ, Prosser LA, Tsiplova K, et al. Family Spillover Effects in Pediatric Cost-Utility Analyses. Appl Health Econ Health Policy. 2019;17:163–74.

  74. 74.

    Tilford JM, Payakachat N. Progress in measuring family spillover effects for economic evaluations. Expert Rev Pharmacoecon Outcomes Res. 2015;15(2):195–8.

  75. 75.

    Prosser LA, Wittenberg E. Advances in methods and novel applications for measuring family spillover effects of illness. Pharmacoeconomics. 2019;37:447–50.

  76. 76.

    Brouwer WR. The inclusion of spillover effects in economic evaluations: not an optional extra. Pharmacoeconomics. 2019;37:451–6.

  77. 77.

    Raat H, Landgraf JM, Oostenbrink R, Moll HA, Essink-Bot ML. Reliability and validity of the Infant and Toddler Quality of Life Questionnaire (ITQOL) in a general population and respiratory disease sample. Qual Life Res. 2007;16:445–60.

  78. 78.

    Landgraf JM, Vogel I, Oostenbrink R, van Baar ME, Raat H. Parent-reported health outcomes in infants/toddlers: measurement properties and clinical validity of the ITQOL-SF47. Qual Life Res. 2013;22(3):635–46.

  79. 79.

    Volger S, Landgraf JM, Mao M, Ge J, Northington R, Hays NP. Feasibility and Psychometric Properties of the Infant Toddler Quality of Life (ITQOL) questionnaire in a community-based sample of healthy infants in China. Matern Child Health J. 2018;22(5):702–12.

Download references

Author information

DR lead the manuscript and wrote the first draft. All authors contributed to the planning of the manuscript, revisions to the manuscript, and approved the final version.

Correspondence to Donna Rowen.

Ethics declarations

Funding

No funding was received for the preparation of this manuscript.

Conflicts of Interest

Donna Rowen lead the valuation of the CHU9D in The Netherlands, and, at the time of writing this manuscript, was leading a new valuation of the CHU9D in the UK. Julie Ratcliffe lead the valuation of the CHU9D in Australia. Oliver Rivero-Arias and Nancy Devlin are members of the EuroQol Group and, at the time of writing of this manuscript, were leading a programme working towards the development of a value set for the EQ-5D-Y in the UK and contributing to the development of an international protocol for valuation of the EQ-5D-Y.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Rowen, D., Rivero-Arias, O., Devlin, N. et al. Review of Valuation Methods of Preference-Based Measures of Health for Economic Evaluation in Child and Adolescent Populations: Where are We Now and Where are We Going?. PharmacoEconomics (2020). https://doi.org/10.1007/s40273-019-00873-7

Download citation