Appl Clin Inform 2021; 12(03): 528-538
DOI: 10.1055/s-0041-1730031
Research Article

Quantifying the Impact of Infusion Alerts and Alarms on Nursing Workflows: A Retrospective Analysis

Denny Yu
1  School of Industrial Engineering, Purdue University, West Lafayette, Indiana, United States
2  Regenstrief Center for Healthcare Engineering, Purdue University, West Lafayette, Indiana, United States
,
Marian Obuseh
1  School of Industrial Engineering, Purdue University, West Lafayette, Indiana, United States
2  Regenstrief Center for Healthcare Engineering, Purdue University, West Lafayette, Indiana, United States
,
Poching DeLaurentis
2  Regenstrief Center for Healthcare Engineering, Purdue University, West Lafayette, Indiana, United States
› Author Affiliations
Funding This study was partly supported by the Regenstrief Foundation.

Abstract

Background Smart infusion pumps affect workflows as they add alerts and alarms in an information-rich clinical environment where alarm fatigue is already a major concern. An analytic approach is needed to quantify the impact of these alerts and alarms on nursing workflows and patient safety.

Objectives To analyze a detailed infusion dataset from a smart infusion pump system and identify contributing factors for infusion programming alerts, operational alarms, and alarm resolution times.

Methods We analyzed detailed infusion pump data across four hospitals in a health system for up to 1 year. The prevalence of alerts and alarms was grouped by infusion type and a selected list of 32 high-alert medications (HAMs). Logistic regression was used to explore the relationship between a set of risk factors and the occurrence of alerts and alarms. We used nonparametric tests to explore the relationship between alarm resolution times and a subset of predictor variables.

Results The study dataset included 745,641 unique infusions with a total of 3,231,300 infusion events. Overall, 28.7% of all unique infusions had at least one operational alarm, and 2.1% of all unique infusions had at least one programming alert. Alarms averaged two per infusion, whereas at least one alert happened in every 48 unique infusions. Eight percent of alarms took over 4 minutes to resolve. Intravenous fluid infusions had the highest rate of error-state occurrence. HAMs had 1.64 more odds for alerts than the rest of the infusions. On average, HAMs had a higher alert rate than maintenance fluids.

Conclusion Infusion pump alerts and alarms impact clinical care, as alerts and alarms by design interrupt clinical workflow. Our study showcases how hospital system leadership teams can leverage infusion pump informatics to prioritize quality improvement and patient safety initiatives pertaining to infusion practices.

Protection of Human and Animal Subjects

There was no direct patient involvement in this study. The infusion pump data used in this study contained no patient identifier.


Supplementary Material



Publication History

Received: 14 December 2020

Accepted: 01 April 2021

Publication Date:
30 June 2021 (online)

© 2021. Thieme. All rights reserved.

Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany