Published online by Cambridge University Press: 08 May 2019
It is important to capture all health effects of interventions in cost-utility analyses conducted under a societal or healthcare perspective. However, this is rarely done. Household spillovers (health effects on patients’ other household members) may be particularly likely in the context of technologies and interventions to change behaviors that are interdependent in the household. Our objective was to prospectively collect outcome data from household members and illustrate how these can be included in a cost-utility analysis of a behavior change intervention in chronic obstructive pulmonary disease (COPD).
Data were collected from patients’ household members (n = 153) alongside a randomized controlled trial of a COPD self-management intervention. The impact of the intervention on household members’ EQ-5D-5L scores (primary outcome), was evaluated. Analyses were then carried out to estimate household members’ quality-adjusted life-years (QALYs) and assess the impact of including these QALYs on cost-effectiveness.
The intervention had a negligible spillover on household members’ EQ-5D-5L scores (−0.007; p = .75). There were also no statistically significant spillovers at the 5 percent level in household member secondary outcomes. In the base-case model, the inclusion of household member QALYs in the incremental cost-effectiveness ratio (ICER) denominator marginally increased the ICER from GBP 10,271 (EUR 13,146) to GBP 10,991 (EUR 14,068) per QALY gained.
This study demonstrates it is feasible to prospectively collect and include household members’ outcome data in cost utility analysis, although the study highlighted several methodological issues. In this case, the intervention did not impact significantly on household members’ health or health behaviors, but inclusion of household spillovers may make a difference in other contexts.
Informed consent was obtained from all participants of this study. The models and methodology used in the research are not proprietary. The data used in this research are under the management of Kate Jolly.