The Value of Further Research: The Added Value of Individual-Participant Level Data
Judgements based on average cost-effectiveness estimates may disguise significant heterogeneity in net health outcomes. Decisions about coverage of new interventions are often more efficient when they consider between-patient heterogeneity, which is usually operationalized as different selections for different subgroups. While most model-based cost-effectiveness studies are populated with aggregated-level sub-group estimates, individual-level data are recognized as the best source of evidence to produce unbiased and efficient estimates to explore this heterogeneity. This paper extends a previously published framework to assesses the added value of having access to individual-level data, compared to using aggregate-level data only, in the absence/presence of mutually exclusive population subgroups. Supported by a case study on the cost-effectiveness of interventions to increase uptake of smoke-alarms, the extended framework provided a quantification of the benefits foregone of not using individual-level data, pointed to the optimal number of subgroups and where further research should be undertaken. Although not indicating changes in reimbursement decisions, results showed that irrespective of using aggregate or individual-level data, no substantial additional gains are obtained if more than two subgroups are taken into account. However, depending on the evidence type used, different subgroups are revealed as warranting larger research funds. The use of individual-level data, rather than aggregate, may however influence not only the extent to which an appropriate understanding of existing heterogeneity is attained, but, more importantly, it may shape approval decisions for particular population subgroups and judgements of future research.
We would like to thank members of the Keeping Children Safe study  for providing the case study data. In addition, we acknowledge Professor Mark Sculpher and Cynthia Iglesias for useful comments and suggestions as Thesis Advisory Group members of Dr. Pedro Saramago’s PhD.
PS, MAE and KC conceptually developed the framework. PS and MAE were responsible for the analysis, interpretation of the findings and writing of the manuscript. AJS and AM contributed to the interpretation of results and commented on drafts of the manuscript. KC oversaw the work and commented on drafts of the manuscript. All authors contributed to the editing of this manuscript. All authors read and approved the final manuscript.
Compliance with Ethical Standards
Pedro Saramago was funded through a Medical Research Council Capacity Building Grant (Grant number G0800139) and the Portuguese Fundacao para a Ciencia e a Tecnologia (Grant number SFRH/BD/61448/2009).
Conflict of interest
Pedro Saramago, Manuel A. Espinoza, Alex J Sutton, Andrea Manca and Karl Claxton: None to declare.
- 4.Claxton K, Posnett J. An economic approach to clinical trial design and research priority-setting. Health Econ. 1996;5(6):513–24. https://doi.org/10.1002/(sici)1099-1050(199611)5:6%3c513:aid-hec237%3e3.0.co;2-9.CrossRefGoogle Scholar
- 6.NICE. Guide to the methods of thechnology appraisal. London: NICE, NHS2013.Google Scholar
- 21.Basu A, Meltzer D. Quantitative methods for valuing comparative effectiveness information. Biopharm Rep. 2010;17(2):2–10.Google Scholar
- 26.Kendrick D, Ablewhite J, Achana F, Benford P, Clacy R, Coffey F, et al. Keeping Children Safe: a multicentre programme of research to increase the evidence base for preventing unintentional injuries in the home in the under-fives. Southampton: Programme Grants for Applied Research; 2017.Google Scholar
- 29.ONS. Office for national statistics, household projections, 2008 to 2033. Office for National Statistics—Communities and Local Government, Newport; 2010.Google Scholar
- 31.Claxton K, editor. Heterogeneity in the cost-effectiveness of medical interventions: the challenge of matching patients to appropriate care. ISPOR, Madrid; 2011.Google Scholar