journal article·2021-12-16Open access

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

Shuo-Chen Chien, Yen-Po Chin, Chang-Ho Yoon, Chun-You Chen, Chun-Kung Hsu, Chia-Hui Chien, Yu-Chuan Li

Applied Sciences· Volume 11· Issue 24

Abstract

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.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Electronic Health Records Systems · Healthcare Technology and Patient Monitoring · Healthcare Operations and Scheduling Optimization

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei 110, Taiwan

International Center for Health Information and Technology, College of Medical Science and Technology, Taipei Medical University, Taipei 110, Taiwan

Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA

Big Data Institute, University of Oxford, Oxford OX3 7LF, UK

St. John’s College, University of Oxford, Oxford OX1 3JP, UK

Information Technology Office in Taipei Municipal Wan Fang Hospital, Taipei Medical University, Taipei 110, Taiwan

Department of Radiation Oncology, Taipei Municipal Wan Fang Hospital, Taipei Medical University, Taipei 110, Taiwan

Office of Public Affairs, Taipei Medical University, Taipei 110, Taiwan

Department of Dermatology, Taipei Municipal Wan Fang Hospital, Taipei Medical University, Taipei 110, Taiwan

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