M T DelMonte1, J R Bostwick, J D Bess, G W Dalack. 1. Carolina Advanced Health, UNC Health Care, Department of Pharmacy Services, Chapel Hill, NC, USA. mdelmonte@gmail.com
Abstract
WHAT IS KNOWN AND OBJECTIVE: Second-generation antipsychotics (SGAs) play an important role in the pharmacologic management of various psychiatric conditions. Use of these medications has been associated with metabolic complications. Adherence to guideline-recommended monitoring is suboptimal. We evaluated the effect of a computerized physician order entry (CPOE) pop-up alert designed to improve rates of laboratory metabolic monitoring of patients treated with SGAs on a University Hospital inpatient psychiatry unit. METHODS: A single-centre, retrospective chart review was performed in which patient demographics and SGA drug and laboratory data were extracted from the CPOE database. We assessed the number of orders for appropriate metabolic monitoring data for patients admitted within a 6-month period before or after the alert implementation. RESULTS AND DISCUSSION: Pre-alert (n = 171) and post-alert (n = 157) groups were similar with respect to age, length of stay, sex, race and comorbidities. Following alert implementation, significant increases in monitoring both random (92.4% vs. 100%) and fasting (46.8% vs. 70%) glucose levels as well as random (28.7% vs. 74.5%) and fasting (18.7% vs. 59.9%) lipid panels (all P ≤ 0.001) were observed. The number of patients with both a fasting glucose level and fasting lipid panel available for monitoring increased from 12.9% to 47.8% (P < 0.0001). Significantly more post-alert laboratory orders were submitted at the same time as the SGA drug order (P < 0.0001), suggesting that the alert itself had a direct influence on the ordering of metabolic monitoring labs. WHAT IS NEW AND CONCLUSIONS: Implementation and use of an electronic pop-up alert in an inpatient psychiatric unit significantly improved rates of ordering fasting blood glucose and lipid levels for inpatients treated with SGAs. Overall rates remain suboptimal, suggesting a need for additional strategies to further improve metabolic monitoring.
WHAT IS KNOWN AND OBJECTIVE: Second-generation antipsychotics (SGAs) play an important role in the pharmacologic management of various psychiatric conditions. Use of these medications has been associated with metabolic complications. Adherence to guideline-recommended monitoring is suboptimal. We evaluated the effect of a computerized physician order entry (CPOE) pop-up alert designed to improve rates of laboratory metabolic monitoring of patients treated with SGAs on a University Hospital inpatient psychiatry unit. METHODS: A single-centre, retrospective chart review was performed in which patient demographics and SGA drug and laboratory data were extracted from the CPOE database. We assessed the number of orders for appropriate metabolic monitoring data for patients admitted within a 6-month period before or after the alert implementation. RESULTS AND DISCUSSION: Pre-alert (n = 171) and post-alert (n = 157) groups were similar with respect to age, length of stay, sex, race and comorbidities. Following alert implementation, significant increases in monitoring both random (92.4% vs. 100%) and fasting (46.8% vs. 70%) glucose levels as well as random (28.7% vs. 74.5%) and fasting (18.7% vs. 59.9%) lipid panels (all P ≤ 0.001) were observed. The number of patients with both a fasting glucose level and fasting lipid panel available for monitoring increased from 12.9% to 47.8% (P < 0.0001). Significantly more post-alert laboratory orders were submitted at the same time as the SGA drug order (P < 0.0001), suggesting that the alert itself had a direct influence on the ordering of metabolic monitoring labs. WHAT IS NEW AND CONCLUSIONS: Implementation and use of an electronic pop-up alert in an inpatient psychiatric unit significantly improved rates of ordering fasting blood glucose and lipid levels for inpatients treated with SGAs. Overall rates remain suboptimal, suggesting a need for additional strategies to further improve metabolic monitoring.
Authors: Julie Kreyenbuhl; Lisa B Dixon; Clayton H Brown; Deborah R Medoff; Elizabeth A Klingaman; Li Juan Fang; Stephanie Tapscott; Mary Brighid Walsh Journal: Community Ment Health J Date: 2016-04-09
Authors: Christina Mangurian; Grace C Niu; Dean Schillinger; John W Newcomer; James Dilley; Margaret A Handley Journal: Implement Sci Date: 2017-11-14 Impact factor: 7.327