OBJECTIVE Dysglycemia influences hospital outcomes and resource utilization. Clinical decision support (CDS) holds promise for optimizing care by overcoming management barriers. This study assessed the impact on hospital length of stay (LOS) of an alert-based CDS tool in the electronic medical record that detected dysglycemia or inappropriate insulin use, coined as gaps in care (GIC). RESEARCH DESIGN AND METHODS Using a 12-month interrupted time series among hospitalized persons aged ‡18 years, our CDS tool identified GIC and, when active, provided recommendations. We compared LOS during 6-month-long active and inactive periods using linear models for repeated measures, multiple comparison adjustment, and mediation analysis. RESULTS Among 4,788 admissions with GIC, average LOS was shorter during the tool’s active periods. LOS reductions occurred for all admissions with GIC (25.7 h, P = 0.057), diabetes and hyperglycemia (26.4 h, P = 0.054), stress hyperglycemia (231.0 h, P = 0.054), patients admitted to medical services (28.4 h, P = 0.039), and recurrent hypoglycemia (229.1 h, P = 0.074). Subgroup analysis showed sig-nificantly shorter LOS in recurrent hypoglycemia with three events (282.3 h, P = 0.006) and nonsignificant in two (25.2 h, P = 0.655) and four or more (214.8 h, P = 0.746). Among 22,395 admissions with GIC (4,788, 21%) and without GIC (17,607, 79%), LOS reduction during the active period was 1.8 h (P = 0.053). When recommendations were provided, the active tool indirectly and signifi-cantly contributed to shortening LOS through its influence on GIC events during admissions with at least one GIC (P = 0.027), diabetes and hyperglycemia (P = 0.028), and medical services (P = 0.019). CONCLUSIONS Use of the alert-based CDS tool to address inpatient management of dysglycemia contributed to reducing LOS, which may reduce costs and improve patient well-being.

Original languageEnglish (US)
Pages (from-to)2526-2534
Number of pages9
JournalDiabetes care
Issue number11
StatePublished - Nov 2022

All Science Journal Classification (ASJC) codes

  • Internal Medicine
  • Endocrinology, Diabetes and Metabolism
  • Advanced and Specialized Nursing


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