Community health insurance schemes in rural Ghana tie enrollment to annual deadlines, creating sharp discontinuities in coverage that may shape whether patients present for diagnostic testing. Because no field data were collected for this protocol, the paper also reports a replication-based evaluation of the ordinary least squares estimator used in the proposed analysis: 600 data sets of N = 500 were drawn from a declared data-generating process with intercept 12.0, exposure 0.42, group -3.1, severity 1.35, and error SD 4.2. Across replications, the estimator recovered the exposure coefficient with negligible bias (-0.00023) and empirical coverage of the nominal 95% intervals of 1.0 for both intercept and exposure, while the intercept showed modest bias (0.01707) and RMSE of 0.86225. The protocol contributes a design that treats enrollment deadlines as a source of exogenous variation in coverage, linking medical-sociological theories of access, uncertainty, and institutional trust to a credible identification strategy for diagnostic deferral in low-resource clinic settings.
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Sana Ben Moussa (2026) studied this question.
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