A Review of Heterogeneity in Comparative Economic Analysis, with Specific Considerations for the Decentralized US Setting and Patient-Centered Care.

Abstract

Patient-centered care emphasizes individual preferences, but insurer coverage decisions-based on population-level evidence-may restrict treatment options for patients who differ from the average. This highlights the importance of considering heterogeneity, which refers to differences in health and cost outcomes that are systematically linked to variations in factors like patient characteristics, insurer policies, and provider practices. Failing to account for heterogeneity in economic evaluations can lead to suboptimal decisions, inferior outcomes, and inefficiency. This study aimed to assess the tools and methods for addressing heterogeneity in economic evaluations, examine the extent to which, and how, heterogeneity has been addressed in US cost-utility studies, and provide insights and recommendations to promote more fuller consideration of heterogeneity in US economic evaluations. We reviewed and adapted a seminal taxonomy of heterogeneity to the US setting, highlighting key drivers like patient preferences and insurance design. Methods for addressing heterogeneity in economic evaluations were also reviewed and summarized. We used data from the Tufts Medical Center Cost-Effectiveness Analysis Registry to assess empirical practices in US cost-utility applications, specifically the frequency, types, and impact of a subgroup analysis, and whether rationales for including or excluding subgroups were provided. The revised taxonomy highlights key drivers of heterogeneity in the diverse and decentralized US healthcare ecosystem, such as the diversity of patient preferences and in non-patient factors like access to healthcare providers and insurance coverage. Methods to explore, confirm, and incorporate heterogeneity into a comparative economic analysis exist, but are often challenged by data availability. In addition to the trade-off between potential efficiency gains and increasing uncertainty in comparative value estimates, ethical implications of stratified decisions were highlighted in the literature. We found that a subgroup analysis was rare, and primarily performed for clinical factors like age and disease severity. Only 2 of the 85 studies published between 2015 and 2022 with subgroup-level results were found to consider non-patient factors, and none considered preferences. One-third of studies reported incremental cost-effectiveness ratios differing by more than 50% from the unstratified estimate. No studies provided a rationale for omitting a subgroup analysis, and only two motivated inclusion of a subgroup analysis, limiting our ability to assess the appropriateness of these decisions. Despite well-documented methods to address heterogeneity, its application is limited in US cost-utility studies, especially regarding patient preferences and non-patient factors. As these factors often drive real-world health outcomes and costs in the USA, proper consideration of, and reporting on, heterogeneity is essential to avoid erroneous market access decisions, suboptimal patient outcomes, and economic inefficiency. Future efforts, including work by an upcoming Professional Society of Pharmacoeconomics and Outcomes Research Task Force, should continue to refine taxonomies and emphasize the importance of addressing heterogeneity.