Explicit inference: A meta‐replication of SEER cancer registry research evaluating the Affordable Care Act's Medicaid expansion

Abstract

AbstractObjectivesAmong the provisions within the Affordable Care Act (ACA), expanding Medicaid was arguably the greatest contributor to increasing access to care. For over a decade, researchers have investigated how Medicaid expansion impacted cancer outcomes. Over this same decade, statistical theory illuminated how state‐based policy research could be compromised by invalid inference. After reviewing the literature to identify the inference strategies of state‐based cancer registry Medicaid expansion research, this study aimed to assess how inference decisions could change the interpretation of Medicaid expansion's impact on staging, treatment, and mortality in cancer patients.Data sourcesCancer case data (2000–2019) was obtained from the Surveillance, Epidemiology, End Results (SEER) programme. Cases included all cancer sites combined, top 10 cancer sites combined, and three screening amenable cancers (colorectal, female breast, female cervical).Study designA Difference‐in‐Differences design estimated the association between Medicaid expansion and four binary outcomes: distant stage, initiating treatment >1 month after diagnosis, no surgery recommendation, and death. Three inference techniques were compared: (1) traditional, (2) cluster, and (3) Wild Cluster Bootstrap.Data collectionData was accessed via SEER*Stat.Principal findingsEstimating standard errors via traditional inference would suggest that Medicaid expansion was associated with delayed treatment initiation and surgery recommendations. Traditional and clustered inference also suggested that Medicaid expansion reduced mortality. Inference using Wild Cluster Bootstrap techniques never rejected the null hypotheses.ConclusionsThis study reiterates the importance of explicit inference. Future state‐based, cancer policy research can be improved by incorporating emerging techniques. These findings warrant caution when interpreting prior SEER research reporting significant effects of Medicaid expansion on cancer outcomes, especially studies that did not explicitly define their inference strategy.