Workflow interruption and nurses' mental workload in electronic health record tasks: An observational study

Yawei Shan; Jing Shang; Yan Yan; Xuchun Ye

doi:10.1186/s12912-023-01209-9

Workflow interruption and nurses' mental workload in electronic health record tasks: An observational study

BMC Nurs. 2023 Mar 9;22(1):63. doi: 10.1186/s12912-023-01209-9.

Authors

Yawei Shan^#^{1

2}, Jing Shang^#¹, Yan Yan¹, Xuchun Ye³

Affiliations

¹ School of Nursing, Naval Medical University, No. 800 Xiangyin Road, Shanghai, 200433, China.
² School of Nursing, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
³ School of Nursing, Naval Medical University, No. 800 Xiangyin Road, Shanghai, 200433, China. ye_xch8639@163.com.

^# Contributed equally.

Abstract

Background: Workflow interruptions are common in modern work systems. Electronic health record (EHR) tasks are typical tasks involving human-machine interactions in nursing care, but few studies have examined interruptions and nurses' mental workload in the tasks. Therefore, this study aims to investigate how frequent interruptions and multilevel factors affect nurses' mental workload and performance in EHR tasks.

Methods: A prospective observational study was conducted in a tertiary hospital providing specialist and sub-specialist care from June 1^st to October 31^st, 2021. An observer documented nurses' EHR task interruptions, reactions and performance (errors and near errors) during one-shift observation sessions. Questionnaires were administered at the end of the electronic health record task observation to measure nurses' mental workload for the electronic health record tasks, task difficulty, system usability, professional experience, professional competency, and self-efficacy. Path analysis was used to test a hypothetical model.

Results: In 145 shift observations, 2871 interruptions occurred, and the mean task duration was 84.69 (SD 56.68) minutes per shift. The incidence of error or near error was 158, while 68.35% of errors were self-corrected. The total mean mental workload level was 44.57 (SD 14.08). A path analysis model with adequate fit indices is presented. There was a relationship among concurrent multitasking, task switching and task time. Task time, task difficulty and system usability had direct effects on mental workload. Task performance was influenced by mental workload and professional title. Negative affect mediated the path from task performance to mental workload.

Conclusions: Nursing interruptions occur frequently in EHR tasks, come from different sources and may lead to elevated mental workload and negative outcomes. By exploring the variables related to mental workload and performance, we offer a new perspective on quality improvement strategies. Reducing harmful interruptions to decrease task time can avoid negative outcomes. Training nurses to cope with interruptions and improve competency in EHR implementation and task operation has the potential to decrease nurses' mental workload and improve task performance. Moreover, improving system usability is beneficial to nurses to mitigate mental workload.

Keywords: Electronic nursing record; Mental workload; Nursing interruption; Observational study; Task performance.