TY - JOUR
T1 - Prevention of inpatient hypoglycemia with a real-time informatics alert
AU - Kilpatrick, C. Rachel
AU - Elliott, Michael B.
AU - Pratt, Elizabeth
AU - Schafers, Stephen J.
AU - Blackburn, Mary Clare
AU - Heard, Kevin
AU - Mcgill, Janet B.
AU - Thoelke, Mark
AU - Tobin, Garry S.
N1 - Publisher Copyright:
© 2014 Society of Hospital Medicine.
PY - 2014/10/1
Y1 - 2014/10/1
N2 - 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. Journal of Hospital Medicine 2014;9:621-626.
AB - 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. Journal of Hospital Medicine 2014;9:621-626.
UR - http://www.scopus.com/inward/record.url?scp=84908231043&partnerID=8YFLogxK
U2 - 10.1002/jhm.2221
DO - 10.1002/jhm.2221
M3 - Article
C2 - 24898687
AN - SCOPUS:84908231043
SN - 1553-5592
VL - 9
SP - 621
EP - 626
JO - Journal of hospital medicine
JF - Journal of hospital medicine
IS - 10
ER -