Automation in nursing decision support systems: a systematic review of effects on decision making, care delivery, and patient outcomes

Saba Akbar*, David Lyell, Farah Magrabi

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

Abstract

Objective: The study sought to summarize research literature on nursing decision support systems (DSSs ); understand which steps of the nursing care process (NCP) are supported by DSSs, and analyze effects of automated information processing on decision making, care delivery, and patient outcomes.

Materials and Methods: We conducted a systematic review in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement. PubMed, CINAHL, Cochrane, Embase, Scopus, and Web of Science were searched from January 2014 to April 2020 for studies focusing on DSSs used exclusively by nurses and their effects. Information about the stages of automation (information acquisition, information analysis, decision and action selection, and action implementation), NCP, and effects was assessed.

Results: Of 1019 articles retrieved, 28 met the inclusion criteria, each studying a unique DSS. Most DSSs were concerned with two NCP steps: assessment (82%) and intervention (86%). In terms of automation, all included DSSs automated information analysis and decision selection. Five DSSs automated information acquisition and only one automated action implementation. Effects on decision making, care delivery, and patient outcome were mixed. DSSs improved compliance with recommendations and reduced decision time, but impacts were not always sustainable. There were improvements in evidence-based practice, but impact on patient outcomes was mixed.

Conclusions: Current nursing DSSs do not adequately support the NCP and have limited automation. There remain many opportunities to enhance automation, especially at the stage of information acquisition. Further research is needed to understand how automation within the NCP can improve nurses’ decision making, care delivery, and patient outcomes.
Original languageEnglish
Pages (from-to)2502-2513
Number of pages12
JournalJournal of the American Medical Informatics Association : JAMIA
Volume28
Issue number11
Early online date8 Sep 2021
DOIs
Publication statusPublished - Nov 2021

Keywords

  • clinical decision support systems
  • nursing informatics
  • automation
  • patient safety

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