Artificial Intelligence replication of District Hospital Emergency Department Sepsis Bundle Compliance Under Unmeasured Antibiotic Administration Time Rounding: A Healthcare Causal Inference Evaluation

Sepsis bundle compliance is routinely computed from antibiotic administration times that are rounded to the nearest five or fifteen minutes in emergency department records, yet the consequences of this rounding for causal inference about bundle effects have not been formally characterised. the present analysis treats rounding as a measurement error with a known support and derives its implications for the ordinary least squares estimator of the effect of bundle compliance on patient outcomes. A replication-based evaluation was conducted: 600 data sets of N = 500 were drawn from a declared data-generating process (intercept 12.0, exposure 0.42, group -3.1, severity 1.35, error SD 4.2), and the behaviour of the ordinary least squares estimator was characterised across replications. The estimated bias for the intercept was 0.02475 and for the exposure coefficient -0.0001; the root mean squared error was 0.87944 for the intercept and 0.01587 for the exposure. Empirical coverage of the nominal 95% confidence intervals was 1.0 for both parameters. The results indicate that under the declared process, rounding-induced measurement error of the kind produced by emergency department time recording does not materially distort the ordinary least squares estimator, and that the principal threat to inference lies in the specification of severity adjustment rather than in the rounding itself.