A Practical Guide to Conducting a Systematic Review and Meta-analysis of Health State Utility Values
Economic analysts are increasingly likely to rely on systematic reviews and meta-analyses of health state utility values to inform the parameter inputs of decision-analytic modelling-based economic evaluations. Beyond the context of economic evaluation, evidence from systematic reviews and meta-analyses of health state utility values can be used to inform broader health policy decisions. This paper provides practical guidance on how to conduct a systematic review and meta-analysis of health state utility values. The paper outlines a number of stages in conducting a systematic review, including identifying the appropriate evidence, study selection, data extraction and presentation, and quality and relevance assessment. The paper outlines three broad approaches that can be used to synthesise multiple estimates of health utilities for a given health state or condition, namely fixed-effect meta-analysis, random-effects meta-analysis and mixed-effects meta-regression. Each approach is illustrated by a synthesis of utility values for a hypothetical decision problem, and software code is provided. The paper highlights a number of methodological issues pertinent to the conduct of meta-analysis or meta-regression. These include the importance of limiting synthesis to ‘comparable’ utility estimates, for example those derived using common utility measurement approaches and sources of valuation; the effects of reliance on limited or poorly reported published data from primary utility assessment studies; the use of aggregate outcomes within analyses; approaches to generating measures of uncertainty; handling of median utility values; challenges surrounding the disentanglement of utility estimates collected serially within the context of prospective observational studies or prospective randomised trials; challenges surrounding the disentanglement of intervention effects; and approaches to measuring model validity. Areas of methodological debate and avenues for future research are highlighted.
We are grateful to departmental colleagues for their comments on the paper and suggestions provided. SP receives financial support as a National Institute for Health Research Senior Investigator. No specific funding was obtained to produce this paper. The authors do not have any conflicts of interest to declare.
All authors contributed to the conception, design and drafting of the paper. All authors reviewed and approved the final version of the paper. SP is the guarantor of the overall content.
- 1.PBAC (Pharmaceutical Benefits Advisory Committee). Guidelines for preparing submissions to the pharmaceutical benefits advisory committee. Australia: Australian Government Department of Health; 2013.Google Scholar
- 2.CADTH (Canadian Agency for Drugs and Technologies in Health). Guidelines for the economic evaluation of health technologies. Canada: CADTH; 2006.Google Scholar
- 3.HAS (Haute Autorité de Santé). Choices in methods for economic evaluation. France: HAS; 2012.Google Scholar
- 4.CVZ (College voor zorgverzekeringen). Guidelines for pharmacoeconomic research: evaluation and actualisation. Diemen: CVZ; 2006.Google Scholar
- 5.CatSalut. Guia I Recomanacions Per A La Realització I Presentació D’avaluacions Econòmiques I Anàlisis D’impacte Pressupostari De Medicaments En L’àmbit Del Catsalut. Catalonia: CatSalut; 2014.Google Scholar
- 6.NICE (National Institute of Health and Care Excellence). Guide to the methods of technology appraisal. London: NICE; 2013.Google Scholar
- 7.SMC (Scottish Medicines Consortium). Guidance to manufacturers for completion of new product assessment form (NPAF). Scotland: NHS Scotland; 2016.Google Scholar
- 11.Brazier J, Ratcliffe J, Salomon J, Tsuchiya A. Measuring and valuing health benefits for economic evaluation. Oxford: Oxford University Press; 2007.Google Scholar
- 15.Bell CM, Chapman RH, Stone PW, Sandberg EA, Neumann PJ. An off-the-shelf help list: a comprehensive catalog of preference scores from published cost-utility analyses. Med Decis Mak. 2001;21(4):288–94.Google Scholar
- 30.Papaioannou D, Brazier J, Paisley S. NICE DSU Technical Support Document 9: The identification, review and synthesis of health state utility values from the literature. London: NICE Decision Support Unit Technical Support Documents; 2010.Google Scholar
- 34.NHS Economic Evaluation Database [database on the Internet]. Centre for Reviews and Dissemination. 2010. http://www.york.ac.uk/inst/crd. Accessed: Dec 2017.
- 35.CEA Registry [database on the Internet]. Tufts Medical Centre. 2010. Accessed Dec 2017.Google Scholar
- 36.Higgins JPT. Cochrane handbook for systematic reviews of interventions. www.handbook.cochrane.org: The Cochrane Collaboration; 2011.
- 40.Husereau D, Drummond M, Petrou S, Carswell C, Moher D, Greenberg D, et al. Consolidated health economic evaluation reporting standards (CHEERS)-explanation and elaboration: a report of the ISPOR health economic evaluation publication guidelines good reporting practices task force. Value Health. 2013;16(2):231–50.CrossRefPubMedGoogle Scholar
- 43.Weinstein MC, O’Brien B, Hornberger J, Jackson J, Johannesson M, McCabe C, et al. 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. 2003;6(1):9–17.CrossRefPubMedGoogle Scholar
- 56.Sutton AJ, Abrams KR, Jones DR, Sheldon TA, Song F. Methods for meta-analysis in medical research. Chichester: John Wiley & Sons; 2000.Google Scholar
- 63.Bland M. An introduction to medical statistics. 3rd ed. USA: Oxford University Press; 2000.Google Scholar
- 66.Dias S, Sutton AJ, Welton NJ, Ades AE. Heterogeneity: subgroups, meta-regression, bias and bias-adjustment. London: NICE Decision Support Unit Technical Support Documents; 2012.Google Scholar
- 67.Han PP, Holbrook TL, Sise MJ, Sack DI, Sise CB, Hoyt DB, et al. Postinjury depression is a serious complication in adolescents after major trauma: injury severity and injury-event factors predict depression and long-term quality of life deficits. J Trauma. 2011;70(4):923–30.CrossRefPubMedGoogle Scholar
- 68.Braam KI, van Dijk-Lokkart EM, van Dongen JM, van Litsenburg RRL, Takken T, Huisman J, et al. Cost-effectiveness of a combined physical exercise and psychosocial training intervention for children with cancer: Results from the quality of life in motion study. Eur J Cancer Care (Engl). 2017. https://doi.org/10.1111/ecc.12586.Google Scholar
- 70.Dias S, Welton NJ, Sutton AJ, Ades AE. A generalised linear modelling framework for pairwise and network meta-analysis of randomised controlled trials. London: NICE Decision Support Unit Technical Support Documents; 2014.Google Scholar