Top

Quality of Life Research

Published in:

Open Access 01-07-2019

Patterns, trends and methodological associations in the measurement and valuation of childhood health utilities

Authors: Joseph Kwon, Sung Wook Kim, Wendy J. Ungar, Kate Tsiplova, Jason Madan, Stavros Petrou

Published in: Quality of Life Research | Issue 7/2019

Abstract

Purpose

To systematically assess patterns and temporal changes in the measurement and valuation of childhood health utilities and associations between methodological factors.

Methods

Studies reporting childhood health utilities using direct or indirect valuation methods, published by June 2017, were identified through PubMed, Embase, Web of Science, PsycINFO, EconLit, CINAHL, Cochrane Library and PEDE. The following were explored: patterns in tariff application; linear trends in numbers of studies/samples and paediatric cost–utility analyses (CUAs) and associations between them; changes in proportions of studies/samples within characteristic-based categories over pre-specified periods; impact of National Institute for Health and Care Excellence (NICE) guidance on primary UK research and associations between valuation method, age and methodological factors.

Results

335 studies with 3974 samples covering all ICD-10 chapters, 23 valuation methods, 12 respondent types and 42 countries were identified by systematic review. 34.0% of samples using indirect methods compatible with childhood applied childhood-derived tariffs. There was no association between numbers of studies/samples and numbers of CUAs. Compared to 1990–2008, 2009–June 2017 saw a significant fall in the proportion of studies using case series; significant compositional changes across ICD-10 chapters and significantly higher sample proportions using childhood-specific and adult-specific indirect valuation methods, and based on pre-adolescents, self-assessment, self-administration and experienced health states. NICE guidance was weakly effective in promoting reference methods. Associations between valuation method, age and methodological factors were significant.

Conclusion

1990–2017 witnessed significant changes in primary research on childhood health utilities. Health technology assessment agencies should note the equivocal effect of methodological guidance on primary research.

Available only for authorised users

Drummond, M. F., Sculpher, M. J., Claxton, K., Stoddart, G. L., & Torrance, G. W. (2015). Methods for the economic evaluation of health care programmes. Oxford: Oxford University Press.

NICE (2013). Guide to the methods of technology appraisal 2013.

SMC (2017). Working with SMC—A guide for manufacturers.

CADTH (2017). Guidelines for the economic evaluation of health technologies: Canada 4th Edition.

PBAC (2015). Guidelines for preparing submissions to the Pharmaceutical Benefits Advisory Committee (Version 4.5).

Neumann, P. J., Sanders, G. D., Russell, L. B., Siegel, J. E., & Ganiats, T. G. (2016). Cost-effectiveness in health and medicine. Oxford: Oxford University Press.CrossRef

Torrance, G. W., & Feeny, D. (1989). Utilities and quality-adjusted life years. International Journal of Technology Assessment in Health Care, 5(4), 559–575.CrossRef

Dolan, P., Gudex, C., Kind, P., & Williams, A. (1996). Valuing health states: A comparison of methods. Journal of Health Economics, 15(2), 209–231.CrossRef

Brooks, R. (1996). EuroQol: The current state of play. Health Policy, 37(1), 53–72.CrossRef

10.

Torrance, G. W., Furlong, W., Feeny, D., & Boyle, M. (1995). Multi-attribute preference functions. Health Utilities Index. Pharmacoeconomics, 7(6), 503–520.CrossRef

11.

Brazier, J., Roberts, J., & Deverill, M. (2002). The estimation of a preference-based measure of health from the SF-36. Journal of Health Economics, 21(2), 271–292.CrossRef

12.

Kaplan, R. M., Bush, J. W., & Berry, C. C. (1976). Health status: Types of validity and the index of well-being. Health Services Research, 11(4), 478–507.PubMedPubMedCentral

13.

Hawthorne, G., Richardson, J., & Osborne, R. (1999). The Assessment of Quality of Life (AQoL) instrument: A psychometric measure of health-related quality of life. Quality of Life Research, 8(3), 209–224.CrossRef

14.

Ungar, W., & Gerber, A. (2010). The uniqueness of child health and challenges to measuring costs and consequences. Economic Evaluation in Child Health, 3–32.

15.

Ungar, W. J. (2011). Challenges in health state valuation in paediatric economic evaluation: Are QALYs contraindicated? Pharmacoeconomics, 29(8), 641–652. https://doi.org/10.2165/11591570.CrossRefPubMed

16.

Petrou, S. (2003). Methodological issues raised by preference-based approaches to measuring the health status of children. Health Economics, 12(8), 697–702. https://doi.org/10.1002/hec.775.CrossRefPubMed

17.

Ravens-Sieberer, U., Wille, N., Badia, X., Bonsel, G., Burstrom, K., Cavrini, G., et al. (2010). Feasibility, reliability, and validity of the EQ-5D-Y: Results from a multinational study. Quality of Life Research, 19(6), 887–897. https://doi.org/10.1007/s11136-010-9649-x.CrossRefPubMedPubMedCentral

18.

Apajasalo, M., Sintonen, H., Holmberg, C., Sinkkonen, J., Aalberg, V., Pihko, H., et al. (1996). Quality of life in early adolescence: A sixteen-dimensional health-related measure (16D). Quality of Life Research, 5(2), 205–211.CrossRef

19.

Apajasalo, M., Rautonen, J., Holmberg, C., Sinkkonen, J., Aalberg, V., Pihko, H., et al. (1996). Quality of life in pre-adolescence: A 17-dimensional health-related measure (17D). Quality of Life Research, 5(6), 532–538.CrossRef

20.

Richardson, J. R., Peacock, S. J., Hawthorne, G., Iezzi, A., Elsworth, G., & Day, N. A. (2012). Construction of the descriptive system for the Assessment of Quality of Life AQoL-6D utility instrument. Health Qual Life Outcomes, 10, 38. https://doi.org/10.1186/1477-7525-10-38.CrossRefPubMedPubMedCentral

21.

Stevens, K. J. (2010). Working with children to develop dimensions for a preference-based, generic, pediatric, health-related quality-of-life measure. Qualitative Health Research, 20(3), 340–351. https://doi.org/10.1177/1049732309358328.CrossRefPubMed

22.

Chen, G., & Ratcliffe, J. (2015). A review of the development and application of generic multi-attribute utility instruments for paediatric populations. Pharmacoeconomics, 33(10), 1013–1028. https://doi.org/10.1007/s40273-015-0286-7.CrossRefPubMed

23.

Montgomery, S. M., & Kusel, J. (2016). The prevalence of child-specific utilities in NICE appraisals for paediatric indications: Rise of the economic orphans? Expert Review of Pharmacoeconomics & Outcomes Research, 16(3), 347–350. https://doi.org/10.1080/14737167.2016.1179116.CrossRef

24.

Sullivan, S. M., Tsiplova, K., & Ungar, W. J. (2016). A scoping review of pediatric economic evaluation 1980–2014: Do trends over time reflect changing priorities in evaluation methods and childhood disease? Expert Review of Pharmacoeconomics & Outcomes Research, 16(5), 599–607.CrossRef

25.

Kromm, S. K., Bethell, J., Kraglund, F., Edwards, S. A., Laporte, A., Coyte, P. C., et al. (2012). Characteristics and quality of pediatric cost-utility analyses. Quality of Life Research, 21(8), 1315–1325. https://doi.org/10.1007/s11136-011-0049-7.CrossRefPubMed

26.

Weinstein, M. C., O’Brien, B., Hornberger, J., Jackson, J., Johannesson, M., McCabe, C., et al. (2003). Principles of good practice for decision analytic modeling in health-care evaluation: Report of the ISPOR Task Force on Good Research Practices–Modeling Studies. Value Health, 6(1), 9–17.CrossRef

27.

van Litsenburg, R. R., Kunst, A., Huisman, J., Ket, J. C., Kaspers, G. J., & Gemke, R. J. (2014). Health status utilities in pediatrics: A systematic review of acute lymphoblastic leukemia. Medical Decision Making, 34(1), 21–32. https://doi.org/10.1177/0272989X13497263.CrossRefPubMed

28.

Pickard, A. S., Topfer, L. A., & Feeny, D. H. (2004). A structured review of studies on health-related quality of life and economic evaluation in pediatric acute lymphoblastic leukemia. JNCI Monographs 33, 102–125, https://doi.org/10.1093/jncimonographs/lgh002.CrossRef

29.

Kua, W. S., & Davis, S. (2016). Systematic review of health state utilities in children with asthma. Value in Health, 19(7), A557–A557. https://doi.org/10.1016/j.jval.2016.09.1218.CrossRef

30.

Janssens, A., Rogers, M., Gumm, R., Jenkinson, C., Tennant, A., Logan, S., et al. (2016). Measurement properties of multidimensional patient-reported outcome measures in neurodisability: A systematic review of evaluation studies. Developmental Medicine & Child Neurology, 58(5), 437–451. https://doi.org/10.1111/dmcn.12982.CrossRef

31.

Brown, V., Tan, E. J., Hayes, A. J., Petrou, S., & Moodie, M. L. (2018). Utility values for childhood obesity interventions: A systematic review and meta-analysis of the evidence for use in economic evaluation. Obesity Reviews, 19(7), 905–916. https://doi.org/10.1111/obr.12672.CrossRefPubMed

32.

Noyes, J., & Edwards, R. T. (2011). EQ-5D for the assessment of health-related quality of life and resource allocation in children: A systematic methodological review. Value Health, 14(8), 1117–1129. https://doi.org/10.1016/j.jval.2011.07.011.CrossRefPubMed

33.

Mittmann, N., Trakas, K., Risebrough, N., & Liu, B. A. (1999). Utility scores for chronic conditions in a community-dwelling population. Pharmacoeconomics, 15(4), 369–376.CrossRef

34.

Carroll, A. E., & Downs, S. M. (2009). Improving decision analyses: Parent preferences (utility values) for pediatric health outcomes. The Journal of Pediatrics, 155(1), 21–25. https://doi.org/10.1016/j.jpeds.2009.01.040.CrossRef

35.

Ungar, W. J., & Santos, M. T. (2003). The pediatric economic database evaluation (PEDE) project: Establishing a database to study trends in pediatric economic evaluation. Medical Care, 41(10), 1142–1152. https://doi.org/10.1097/01.MLR.0000088451.56688.65.CrossRefPubMed

36.

Ungar, W. J. (2016). The pediatric economic database evaluation (PEDE) project. Toronto: The Hospital for Sick Children.

37.

Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & Group, P. (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. Annals of Internal Medicine, 151(4), 264–269, W264.CrossRef

38.

Kwon, J., Kim, S. W., Ungar, W. J., Tsiplova, K., Madan, J., & Petrou, S. (2018). A systematic review and meta-analysis of childhood health utilities. Medical Decision Making, 38(3), 277–305. https://doi.org/10.1177/0272989x17732990.CrossRefPubMed

39.

Parkin, D., & Devlin, N. (2006). Is there a case for using visual analogue scale valuations in cost-utility analysis? Health Economics, 15(7), 653–664. https://doi.org/10.1002/hec.1086.CrossRefPubMed

40.

WorldBank (2018). Low & middle income countries.

41.

Juniper, E. F., Guyatt, G. H., Feeny, D. H., Griffith, L. E., & Ferrie, P. J. (1997). Minimum skills required by children to complete health-related quality of life instruments for asthma: Comparison of measurement properties. European Respiratory Journal, 10(10), 2285–2294. https://doi.org/10.1183/09031936.97.10102285.CrossRefPubMed

42.

Oostenbrink, R., HA, A. M., & Essink-Bot, M. L. (2002). The EQ-5D and the Health Utilities Index for permanent sequelae after meningitis: A head-to-head comparison. Journal of Clinical Epidemiology, 55(8), 791–799.CrossRef

43.

Raspa, M., Sacco, P., Candrilli, S. D., Bishop, E., & Petrillo, J. (2016). Validity of a condition specific outcome measure for fragile X syndrome: The Aberrant Behaviour Checklist-utility index. Journal of Intellectual Disability Research, 60(9), 844–855. https://doi.org/10.1111/jir.12264.CrossRefPubMed

44.

Chiou, C. F., Weaver, M. R., Bell, M. A., Lee, T. A., & Krieger, J. W. (2005). Development of the multi-attribute Pediatric Asthma Health Outcome Measure (PAHOM). International Journal for Quality in Health Care, 17(1), 23–30. https://doi.org/10.1093/intqhc/mzh086.CrossRefPubMed

45.

Kang, E. (2016). Validity of child health-6 dimension(Ch-6d) for adolescents. Value in Health, 19(7), A854–A854. https://doi.org/10.1016/j.jval.2016.08.458.CrossRef

46.

Lynch, F. L., Hornbrook, M., Clarke, G. N., Perrin, N., Polen, M. R., O’Connor, E., et al. (2005). Cost-effectiveness of an intervention to prevent depression in at-risk teens. Archives of General Psychiatry, 62(11), 1241–1248. https://doi.org/10.1001/archpsyc.62.11.1241.CrossRefPubMed

47.

Domino, M. E., Burns, B. J., Silva, S. G., Kratochvil, C. J., Vitiello, B., Reinecke, M. A., et al. (2008). Cost-effectiveness of treatments for adolescent depression: Results from TADS. The American Journal of Psychiatry, 165(5), 588–596. https://doi.org/10.1176/appi.ajp.2008.07101610.CrossRefPubMed

48.

Domino, M. E., Foster, E. M., Vitiello, B., Kratochvil, C. J., Burns, B. J., Silva, S. G., et al. (2009). Relative cost-effectiveness of treatments for adolescent depression: 36-week results from the TADS randomized trial. Journal of the American Academy of Child and Adolescent Psychiatry, 48(7), 711–720. https://doi.org/10.1097/CHI.0b013e3181a2b319.CrossRefPubMed

49.

McBain, R. K., Salhi, C., Hann, K., Salomon, J. A., Kim, J. J., & Betancourt, T. S. (2016). Costs and cost-effectiveness of a mental health intervention for war-affected young persons: decision analysis based on a randomized controlled trial. Health Policy and Planning, 31(4), 415–424. https://doi.org/10.1093/heapol/czv078.CrossRefPubMed

50.

Hartman, J. D., Craig, B. M., Blackburn, C., & Simmons, V. (2016). The Association between Maternal Smoking during Pregnancy and Child Quality-Adjusted Life Years. Value in Health, 19(3), A117–A117. https://doi.org/10.1016/j.jval.2016.03.463.CrossRef

51.

Barr, R. D., Furlong, W., Dawson, S., Whitton, A. C., Strautmanis, I., Pai, M., et al. (1993). An assessment of global health status in survivors of acute lymphoblastic leukemia in childhood. The American Journal of Pediatric Hematology/Oncology, 15(3), 284–290.PubMed

52.

Barr, R., Pai, M., Weitzman, S., Feeny, D., Furlong, W., Rosenbaum, P., et al. (1994). A multiattribute approach to health-status measurement and clinical management illustrated by an application to brain-tumors in childhood. International Journal of Oncology, 4(3), 639–648.PubMed

53.

Lee, D., Gladwell, D., Batty, A. J., Brereton, N., & Tate, E. (2013). The cost effectiveness of licensed oromucosal midazolam (Buccolam((R))) for the treatment of children experiencing acute epileptic seizures: An approach when trial evidence is limited. Pediatric Drugs, 15(2), 151–162. https://doi.org/10.1007/s40272-013-0009-5.CrossRefPubMed

54.

Tarride, J. E., Burke, N., Bischof, M., Hopkins, R. B., Goeree, L., Campbell, K., et al. (2010). A review of health utilities across conditions common in paediatric and adult populations. Health and Quality of Life Outcomes, 8, 12. https://doi.org/10.1186/1477-7525-8-12.CrossRefPubMedPubMedCentral

55.

Thorrington, D., & Eames, K. (2015). Measuring health utilities in children and adolescents: A systematic review of the literature. PLoS ONE, 10(8), e0135672. https://doi.org/10.1371/journal.pone.0135672.CrossRefPubMedPubMedCentral

56.

Brazier, J., Roberts, J., Tsuchiya, A., & Busschbach, J. (2004). A comparison of the EQ-5D and SF-6D across seven patient groups. Health Economics, 13(9), 873–884. https://doi.org/10.1002/hec.866.CrossRefPubMed

57.

Petrou, S., Kwon, J., & Madan, J. (2018). A practical guide to conducting a systematic review and meta-analysis of health state utility values. Pharmacoeconomics. https://doi.org/10.1007/s40273-018-0670-1.CrossRefPubMed

58.

Peasgood, T., Ward, S. E., & Brazier, J. (2010). Health-state utility values in breast cancer. Expert Review of Pharmacoeconomics & Outcomes Research, 10(5), 553–566.CrossRef

59.

McLernon, D., Dillon, J., & Donnan, P. (2006). Health-state utilities in liver disease: A systematic review and meta-analysis. Value in Health, 9(6), A245–A246.CrossRef

60.

Wyld, M., Morton, R. L., Hayen, A., Howard, K., & Webster, A. C. (2012). A systematic review and meta-analysis of utility-based quality of life in chronic kidney disease treatments. PLoS Medicine, 9(9), e1001307.CrossRef

61.

Bremner, K. E., Chong, C. A., Tomlinson, G., Alibhai, S. M., & Krahn, M. D. (2007). A review and meta-analysis of prostate cancer utilities. Medical Decision Making, 27(3), 288–298.CrossRef

62.

Van Osch, S. M., Wakker, P. P., Van Den Hout, W. B., & Stiggelbout, A. M. (2004). Correcting biases in standard gamble and time tradeoff utilities. Medical Decision Making, 24(5), 511–517.CrossRef

63.

Were, W. M., Daelmans, B., Bhutta, Z., Duke, T., Bahl, R., Boschi-Pinto, C., et al. (2015). Children’s health priorities and interventions. BMJ, 351, h4300.CrossRef

64.

Laski, L., & Expert Consultative Group for Every Woman Every Child on Adolescent (2015). Realising the health and wellbeing of adolescents. BMJ, 351, h4119. https://doi.org/10.1136/bmj.h4119.CrossRefPubMed

65.

Sullivan, S. M., & Ungar, W. J. (2016). Will the growth spurt continue? Trends in child health economic evaluation: 1980 to 2013.

66.

Adlard, N., Kinghorn, P., & Frew, E. (2014). Is the UK NICE “Reference Case” influencing the practice of pediatric quality-adjusted life-year measurement within economic evaluations? Value in Health, 17(4), 454–461.CrossRef

67.

Ratcliffe, J., Stevens, K., Flynn, T., Brazier, J., & Sawyer, M. G. (2012). Whose values in health? An empirical comparison of the application of adolescent and adult values for the CHU-9D and AQOL-6D in the Australian adolescent general population. Value in Health, 15(5), 730–736.CrossRef

68.

Ungar, W. J., & Zur, R. M. (2015). Health economic evaluation for improving child health in low-and middle-income countries. In Optimizing treatment for children in the developing world (pp. 213–224). Berlin: Springer.

69.

Moodie, M., Richardson, J., Rankin, B., Iezzi, A., & Sinha, K. (2010). Predicting time trade-off health state valuations of adolescents in four Pacific countries using the Assessment of Quality-of-Life (AQoL-6D) instrument. Value Health, 13(8), 1014–1027. https://doi.org/10.1111/j.1524-4733.2010.00780.x.CrossRefPubMed

70.

Richardson, J., Atherton Day, N., Peacock, S., & Iezzi, A. (2004). Measurement of the quality of life for economic evaluation and the Assessment of Quality of Life (AQoL) Mark 2 instrument. Australian Economic Review, 37(1), 62–88.CrossRef

71.

Ratcliffe, J., Flynn, T., Terlich, F., Stevens, K., Brazier, J., & Sawyer, M. (2012). Developing adolescent-specific health state values for economic evaluation: an application of profile case best-worst scaling to the Child Health Utility 9D. Pharmacoeconomics, 30(8), 713–727. https://doi.org/10.2165/11597900-000000000-00000.CrossRefPubMed

72.

Ratcliffe, J., Huynh, E., Chen, G., Stevens, K., Swait, J., Brazier, J., et al. (2016). Valuing the Child Health Utility 9D: Using profile case best worst scaling methods to develop a new adolescent specific scoring algorithm. Social Science & Medicine, 157, 48–59. https://doi.org/10.1016/j.socscimed.2016.03.042.CrossRef

73.

Stevens, K., Brazier, J., McKenna, S., Doward, L., & Cork, M. (2005). The development of a preference-based measure of health in children with atopic dermatitis. British Journal of Dermatology, 153(2), 372–377.CrossRef

74.

Wu, X., Ohinmaa, A., Johnson, J., & Veugelers, P. (2014). Assessment of children’s own health status using visual analogue scale and descriptive system of the EQ-5D-Y: Linkage between two systems. Quality of Life Research, 23(2), 393–402.CrossRef

75.

Dolan, P. (1997). Modeling valuations for EuroQol health states. Medical Care, 35(11), 1095–1108.CrossRef

76.

Lamers, L. M., Stalmeier, P. F., McDonnell, J., Krabbe, P. F., & van Busschbach, J. J. (2005). [Measuring the quality of life in economic evaluations: the Dutch EQ-5D tariff]. Ned Tijdschr Geneeskd, 149(28), 1574–1578.PubMed

77.

Oppe, M., Devlin, N. J., & Szende, A. (2007). EQ-5D value sets: Inventory, comparative review and user guide. Berlin: Springer.

78.

Viney, R., Norman, R., King, M. T., Cronin, P., Street, D. J., Knox, S., et al. (2011). Time trade-off derived EQ-5D weights for Australia. Value Health, 14(6), 928–936. https://doi.org/10.1016/j.jval.2011.04.009.CrossRefPubMed

79.

Chevalier, J., & de Pouvourville, G. (2013). Valuing EQ-5D using Time Trade-Off in France. European Journal of Health Economics, 14(1), 57–66. https://doi.org/10.1007/s10198-011-0351-x.CrossRefPubMed

80.

Burström, K., Sun, S., Gerdtham, U.-G., Henriksson, M., Johannesson, M., Levin, L., et al. (2014). Swedish experience-based value sets for EQ-5D health states. Quality of Life Research, 23(2), 431–442.CrossRef

81.

Greiner, W., Weijnen, T., Nieuwenhuizen, M., Oppe, S., Badia, X., Busschbach, J., et al. (2003). A single European currency for EQ-5D health states. Results from a six-country study. European Journal of Health Economics, 4(3), 222–231. https://doi.org/10.1007/s10198-003-0182-5.CrossRefPubMed

82.

Shaw, J. W., Johnson, J. A., & Coons, S. J. (2005). US valuation of the EQ-5D health states: development and testing of the D1 valuation model. Medical Care, 43(3), 203–220.CrossRef

83.

Gerald, J. K., McClure, L. A., Harrington, K. F., Moore, T., Hernandez-Martinez, A. C., & Gerald, L. B. (2012). Measurement characteristics of the pediatric asthma health outcome measure. Journal of Asthma, 49(3), 260–266. https://doi.org/10.3109/02770903.2012.656863.CrossRefPubMed

84.

Torrance, G. W., Feeny, D. H., Furlong, W. J., Barr, R. D., Zhang, Y., & Wang, Q. (1996). Multiattribute utility function for a comprehensive health status classification system: Health Utilities Index Mark 2. Medical Care, 34, 702–722.CrossRef

85.

Cadman, D., Goldsmith, C., Torrance, G., Boyle, M., & Furlong, W. (1986). Development of a health status index for Ontario children. Final Report to the Ontario Ministry of Health on Research Grant DM, 648, 00633.

86.

Wang, Q. N., Furlong, W., Feeny, D., Torrance, G., & Barr, R. (2002). How robust is the Health Utilities Index Mark 2 utility function? Medical Decision Making, 22(4), 350–358. https://doi.org/10.1177/027298902400448911.CrossRefPubMed

87.

McCabe, C. J., Stevens, K. J., & Brazier, J. E. (2005). Utility scores for the health utilities index mark 2—An empirical assessment of alternative mapping functions. Medical Care, 43(6), 627–635. https://doi.org/10.1097/01.mlr.0000163666.00471.8e.CrossRefPubMed

88.

Feeny, D., Furlong, W., Torrance, G. W., Goldsmith, C. H., Zhu, Z., DePauw, S., et al. (2002). Multiattribute and single-attribute utility functions for the health utilities index mark 3 system. Med Care, 40(2), 113–128.CrossRef

89.

Kaplan, R. M., Anderson, J. P., Wu, A. W., Mathews, W. C., Kozin, F., & Orenstein, D. (1989). The Quality of Well-being Scale. Applications in AIDS, cystic fibrosis, and arthritis. Medical Care, 27(3 Suppl), S27–S43.CrossRef

90.

Kerr, C., Breheny, K., Lloyd, A., Brazier, J., Bailey, D. B. Jr., Berry-Kravis, E., et al. (2015). Developing a utility index for the Aberrant Behavior Checklist (ABC-C) for fragile X syndrome. Quality of Life Research, 24(2), 305–314. https://doi.org/10.1007/s11136-014-0759-8.CrossRefPubMed

91.

Ungar, W. (2007). Paediatric health economic evaluations: a world view. Healthcare Quarterly, 10(1), 134–140. 142 – 135; discussion 145 – 136.PubMed

Title: Patterns, trends and methodological associations in the measurement and valuation of childhood health utilities
Authors: Joseph Kwon
Sung Wook Kim
Wendy J. Ungar
Kate Tsiplova
Jason Madan
Stavros Petrou
Publication date: 01-07-2019
Publisher: Springer International Publishing
Published in: Quality of Life Research / Issue 7/2019
Print ISSN: 0962-9343
Electronic ISSN: 1573-2649
DOI: https://doi.org/10.1007/s11136-019-02121-z

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

Patterns, trends and methodological associations in the measurement and valuation of childhood health utilities

Abstract

Purpose

Methods

Results

Conclusion

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

Abstract

Purpose

Methods

Results

Conclusion

Please log in to get access to this content

Other articles of this Issue 7/2019

EQ-5D-Y-5L: developing a revised EQ-5D-Y with increased response categories

Relationship between paid leave, financial burden, and patient-reported outcomes among employed patients who have undergone bone marrow transplantation

Comparative study of PROMISⓇ self-efficacy for managing chronic conditions across chronic neurologic disorders

Quality of life of cancer patients living in Trinidad and Tobago

The effect of nature exposure on the mental health of patients: a systematic review

Longitudinal validity of the hemophilia caregiver impact measure