Equity Effects of Biomedical Coverage on Avoidable Care Delays in Kenya: A Target-Trial Emulation

Kenya's progress toward universal health coverage has expanded access to biomedical services, yet whether this expansion narrows socioeconomic differences in the timeliness of care remains unclear. We argue that conventional observational analyses conflate three distinct delay pathways—recognition, access, and quality—and that this conflation obscures the mechanisms through which coverage expansions may benefit affluent populations more than disadvantaged ones. The proposed framework specifies eligibility criteria, treatment strategies, and causal contrasts that distinguish overall coverage effects from equity-relevant effect heterogeneity across wealth strata and geographic remoteness. We address immortal time bias, time-varying confounding by health status, and the challenge of measuring avoidable delay in routine administrative data. The analysis is designed to identify whether biomedical coverage reduces absolute delay inequalities or merely shifts the distribution of delay toward lower-level facilities. We conclude that without explicit specification of the target trial, equity evaluations risk producing estimates that are neither causally interpretable nor policy-actionable, and we outline design principles for future empirical work using Kenya's emerging digital health infrastructure.