WHOSE QALYS COUNT IN COST-EFFECTIVENESS ANALYSES? EVALUATING INTERVENTIONS THAT AFFECT FERTILITY AND CHILDBEARING
Method: We developed a clinically informed framework for interventions that have direct and/or indirect effects on fertility and childbearing. We defined a set of health interventions that span the combinations in the framework (e.g., in vitrofertilization, selective embryo reduction, chlamydia screening and treatment, prenatal genetic testing). We performed a targeted literature review, searching for articles presenting CEAs of the interventions. For each article, we identified the health outcomes stemming from potential benefits and harms of the intervention that were considered, with particular focus on QALYs associated with current and future fertility and childbearing. We also reviewed relevant economic, legal, and ethical theoretical work.
Result: Our framework included interventions with direct and indirect effects on fertility, miscarriage, and birth defects as they related to women’s current pregnancies and women’s and men’s future fertility. We identified nearly 150 studies that illustrated current practice for CEAs of interventions in the framework including 12 papers providing theoretical guidance underpinning such analyses. We observed four patterns: 1) Studies examining interventions whose intended impact was to increase/decrease fertility tended to include/ignore QALYs that could accrue to offspring; 2) Studies examining interventions with indirect effects on fertility tended to ignore such QALYs; 3) Studies often avoided the issue by reporting incremental costs per outcome (e.g., birth defects avoided) as opposed to per QALY gained; 4) Even within categories (e.g., interventions intended to increase fertility), studies took heterogeneous approaches.
Conclusion: Current practice of considering QALYs from current pregnancies and future fertility is inconsistent and frequently appears biased towards the interventions considered. As the Panel on Cost-Effectiveness in Health and Medicine updates its guidelines, making the practice of CEA more consistent is a priority. Analysts risk having their work dismissed as biased if consistent and transparent standards are not followed. The framework we have developed contributes to harmonizing methods in this respect.