A Tool to Retrieve Alert Dwell Time from a Homegrown Computerized Physician Order Entry (CPOE) System of an Academic Medical Center: An Exploratory Analysis

• Published in: Applied sciences Vol. 11; no. 24; p. 12004
• Main Authors: Chien, Shuo-Chen, Chin, Yen-Po, Yoon, Chang-Ho, Chen, Chun-You, Hsu, Chun-Kung, Chien, Chia-Hui, Li, Yu-Chuan
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.12.2021
• Subjects: alert dwell time; alert fatigue; Computerized physician order entry; Correlation analysis; Efficiency; Health care facilities; Impact analysis; interruptive alert; Physicians; Programming languages; Sensors; Statistics
• ISSN: 2076-3417; 2076-3417
• DOI: 10.3390/app112412004

Alert dwell time, defined as the time elapsed from the generation of an interruptive alert to its closure, has rarely been used to describe the time required by clinicians to respond to interruptive alerts. Our study aimed to develop a tool to retrieve alert dwell times from a homegrown CPOE (computerized physician order entry) system, and to conduct exploratory analysis on the impact of various alert characteristics on alert dwell time. Additionally, we compared this impact between various professional groups. With these aims, a dominant window detector was developed using the Golang programming language and was implemented to collect all alert dwell times from the homegrown CPOE system of a 726-bed, Taiwanese academic medical center from December 2019 to February 2021. Overall, 3,737,697 interruptive alerts were collected. Correlation analysis was performed for alerts corresponding to the 100 most frequent alert categories. Our results showed that there was a negative correlation (ρ = −0.244, p = 0.015) between the number of alerts and alert dwell times. Alert dwell times were strongly correlated between different professional groups (physician vs. nurse, ρ = 0.739, p < 0.001). A tool that retrieves alert dwell times can provide important insights to hospitals attempting to improve clinical workflows.