The impacts of disease and treatment on a patient's family members and informal caregivers are known as "family spillover effects." Although many formal value frameworks call for the consideration of these effects, they are often not included in health technology assessments (HTAs) and cost-effectiveness analyses (CEAs). A formal evaluation of stakeholder perspectives may help address the disconnect for inclusion of family spillover effects observed in practice. To develop stakeholder-driven recommendations for the measurement and use of family spillover effects in the United States and to identify research opportunities. We first conducted a targeted literature review of US-based CEAs and HTA reports from the past 10 years to assess the current use of family spillover effects. We then used a purposeful sampling technique to conduct 25 qualitative interviews with outcomes researchers, patient advocates, health economists, and health policy and payer experts to gather perspectives on when and how family spillover effects should be considered in HTA processes. We conducted a thematic analysis of the interview transcripts to identify key themes and develop preliminary recommendations. Finally, we conducted an online workshop with 8 stakeholders to discuss, rate, and refine preliminary recommendations to develop final recommendations. A key theme identified in the stakeholder interviews was the role that data availability, analyst preferences, and prior precedence play in limiting the inclusion of spillover effects in HTAs. Additional themes included support for the inclusion of both qualitative and quantitative spillover effects and the need to capture broad and diverse impacts across populations. We developed 15 recommendations from the consensus building workshop addressing measurement, CEA modeling, and HTA processes. Key recommendations included (1) a transparent process for deciding when family spillover effects should be included, (2) measurement of direct and indirect costs with priority based on the magnitude of impact, (3) the use of validated measures, (4) the use of proxy information and expert elicitation when quality data are unavailable, and (5) the use of a modified impact inventory table for transparency of included effects. Research opportunities included patient involvement in family spillover effect research and HTAs, mapping algorithms and non-preference-based caregiver measures to generate utilities, and consensus best practices for modeling. The inconsistent inclusion of family spillover effects in HTAs and CEAs remains a persistent challenge. The stakeholder-driven recommendations and research opportunities identified in this study may help improve the transparency, measurement, and use of family spillover effects in assessing the clinical and economic value of novel medical technologies.
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