Diagnostic uncertainty in Nigerian secondary hospitals is routinely managed through empirical antibiotic escalation while laboratory results are pending, yet the causal effect of turnaround-time delay on prescribing behaviour remains poorly identified because delays are not randomly assigned and clinicians anticipate them. Using a before-after-control-impact structure with a declared variance decomposition (between-cluster SD = 6.0, residual SD = 4.5, intraclass correlation = 0.64), the analysis characterises the operating characteristics of the estimator across 2000 replications per design cell for cluster counts of 8, 16, 24 and 32 and effect sizes of 3, 5 and 8 percentage points. Power reaches conventional thresholds at 52 clusters for a 5-percentage-point effect, and the minimum detectable effect declines steeply as cluster counts rise from 8 to 32. The framework clarifies why single-site studies of turnaround delay systematically overstate precision and specifies the cluster numbers required for credible inference. The contribution is a design-theoretic account of diagnostic uncertainty as an institutional exposure, with implications for how medical sociology models the relationship between laboratory infrastructure and antimicrobial stewardship in resource-constrained hospitals.
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Ibrahim Danlami Suleiman (2026) studied this question.
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