BACKGROUND: Severe hypoglycemia (SH), defined as a blood glucose (BG) <40 mg/dL, is associated with an increased risk of adverse clinical outcomes in inpatients. OBJECTIVE: To determine whether a predictive informatics hypoglycemia risk-alert supported by trained nurse responders would reduce the incidence of SH in our hospital. DESIGN: A 5-month prospective cohort intervention study. SETTING: Acute care medical floors in a tertiary care academic hospital in St. Louis, Missouri. PATIENTS: From 655 inpatients on designated medical floors with a BG of <90 mg/dL, 390 were identified as high risk for hypoglycemia by the alert system. MEASUREMENTS: The primary outcome was the incidence of SH occurring in high-risk intervention versus high-risk control patients. Secondary outcomes included: number of episodes of SH in all study patients, incidence of BG < 60 mg/dL and severe hyperglycemia with a BG >299 mg/dL, length of stay, transfer to a higher level of care, the frequency that high-risk patient's orders were changed in response to the alert-intervention process, and mortality. RESULTS: The alert process, when augmented by nurse-physician collaboration, resulted in a significant decrease by 68% in the rate of SH in alerted high-risk patients versus nonalerted high-risk patients (3.1% vs 9.7%, P = 0.012). Rates of hyperglycemia were similar on intervention and control floors at 28% each. There was no difference in mortality, length of stay, or patients requiring transfer to a higher level of care. CONCLUSION: A real-time predictive informatics-generated alert, when supported by trained nurse responders, significantly reduced inpatient SH.
BACKGROUND: Severe hypoglycemia (SH), defined as a blood glucose (BG) <40 mg/dL, is associated with an increased risk of adverse clinical outcomes in inpatients. OBJECTIVE: To determine whether a predictive informatics hypoglycemia risk-alert supported by trained nurse responders would reduce the incidence of SH in our hospital. DESIGN: A 5-month prospective cohort intervention study. SETTING: Acute care medical floors in a tertiary care academic hospital in St. Louis, Missouri. PATIENTS: From 655 inpatients on designated medical floors with a BG of <90 mg/dL, 390 were identified as high risk for hypoglycemia by the alert system. MEASUREMENTS: The primary outcome was the incidence of SH occurring in high-risk intervention versus high-risk control patients. Secondary outcomes included: number of episodes of SH in all study patients, incidence of BG < 60 mg/dL and severe hyperglycemia with a BG >299 mg/dL, length of stay, transfer to a higher level of care, the frequency that high-risk patient's orders were changed in response to the alert-intervention process, and mortality. RESULTS: The alert process, when augmented by nurse-physician collaboration, resulted in a significant decrease by 68% in the rate of SH in alerted high-risk patients versus nonalerted high-risk patients (3.1% vs 9.7%, P = 0.012). Rates of hyperglycemia were similar on intervention and control floors at 28% each. There was no difference in mortality, length of stay, or patients requiring transfer to a higher level of care. CONCLUSION: A real-time predictive informatics-generated alert, when supported by trained nurse responders, significantly reduced inpatient SH.
Authors: Sreekar Mantena; Aldo Robles Arévalo; Jason H Maley; Susana M da Silva Vieira; Roselyn Mateo-Collado; João M da Costa Sousa; Leo Anthony Celi Journal: J Clin Monit Comput Date: 2021-10-04 Impact factor: 1.977
Authors: Colleen M Culley; Subashan Perera; Zachary A Marcum; Sandra L Kane-Gill; Steven M Handler Journal: J Am Geriatr Soc Date: 2015-10-12 Impact factor: 5.562
Authors: Nestoras Nicolas Mathioudakis; Estelle Everett; Shuvodra Routh; Peter J Pronovost; Hsin-Chieh Yeh; Sherita Hill Golden; Suchi Saria Journal: BMJ Open Diabetes Res Care Date: 2018-03-02
Authors: Nestoras Mathioudakis; Moeen Aboabdo; Mohammed S Abusamaan; Christina Yuan; LaPricia Lewis Boyer; Scott J Pilla; Erica Johnson; Sanjay Desai; Amy Knight; Peter Greene; Sherita H Golden Journal: JMIR Hum Factors Date: 2021-11-26