Automated, Component-Level Assessment of a National Inpatient Diabetes Guideline: Adherence and Its Association with Hospitalization Complications Across Six Hospitals
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Objective
To measure adherence to a national inpatient hyperglycemia guideline at the level of its individual recommendations across a hospital network, to determine whether it changed after the guideline was issued, and to identify which recommendations track subsequent outcomes.
Materials and Methods
Retrospective multicenter study of 48,354 admissions among 29,577 adults with diabetes or inpatient hyperglycemia at six Israeli general hospitals, Au-gust 2022 to December 2025. Each of 14 recommendations was formalized as a quality-assessment temporal pattern over knowledge-based temporal abstractions of the record, scored wherever it applied. Pre-post adherence was compared by Welch t -test with false discovery rate correction. Associations with 10 complications were estimated by bias-reduced logistic regression over 24-, 48-, and 72-hour windows, and by inverse probability of treat-ment weighting contrasting abovewith at-or-below-median adherence.
Results
Adherence ranged from near-universal admission and medication-management ac-tions to substantial gaps in insulin management (means, 0.15-0.28). Overall adherence rose modestly after issue (0.682 to 0.703, P < .001), with marked inter-hospital heterogeneity. After weighting, above-median adherence carried 44% lower odds of 30-day mortality (odds ratio [OR], 0.557; 95% CI, 0.514-0.603), 82% lower odds of hyperglycemia (OR, 0.175) and 52% lower odds of severe hyperglycemia (OR, 0.485), against 20% higher odds of hypo-glycemia (OR, 1.204).
Discussion
The least-implemented recommendations were largely those whose adherence tracked outcomes: repeated insulin decisions spread across a stay, rather than discrete ac-tions on admission.
Conclusion
Guideline adherence can be assessed automatically and per-recommendation at national scale, identifying where fuller implementation would most plausibly matter.
