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A scoping review of real-time automated clinical deterioration alerts and evidence of impacts on hospitalised patient outcomes
  1. Robin Blythe1,
  2. Rex Parsons1,
  3. Nicole M White1,
  4. David Cook2,
  5. Steven McPhail1,3
  1. 1 Australian Centre for Health Services Innovation, Centre for Healthcare Transformation, School of Public Health and Social Work, Faculty of Health, Queensland University of Technology, Kelvin Grove, Queensland, Australia
  2. 2 Intensive Care Unit, Princess Alexandra Hospital, Metro South Health, Brisbane, Queensland, Australia
  3. 3 Digital Health and Informatics, Metro South Health, Brisbane, Queensland, Australia
  1. Correspondence to Robin Blythe, Queensland University of Technology, Brisbane, QLD 4000, Australia; robin.blythe{at}


Background Hospital patients experiencing clinical deterioration are at greater risk of adverse events. Monitoring patients through early warning systems is widespread, despite limited published evidence that they improve patient outcomes. Current limitations including infrequent or incorrect risk calculations may be mitigated by integration into electronic medical records. Our objective was to examine the impact on patient outcomes of systems for detecting and responding to real-time, automated alerts for clinical deterioration.

Methods This review was conducted according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews checklist. We searched Medline, CINAHL and Embase for articles implementing real-time, automated deterioration alerts in hospitalised adults evaluating one or more patient outcomes including intensive care unit admission, length of stay, in-hospital cardiopulmonary arrest and in-hospital death.

Results Of 639 studies identified, 18 were included in this review. Most studies did not report statistically significant associations between alert implementation and better patient outcomes. Four studies reported statistically significant improvements in two or more patient outcomes, and were the only studies to directly involve the patient’s clinician. However, only one of these four studies was robust to existing trends in patient outcomes. Of the six studies using robust study designs, one reported a statistically significant improvement in patient outcomes; the rest did not detect differences.

Conclusions Most studies in this review did not detect improvements in patient outcomes following the implementation of real-time deterioration alerts. Future implementation studies should consider: directly involving the patient’s physician or a dedicated surveillance nurse in structured response protocols for deteriorating patients; the workflow of alert recipients; and incorporating model features into the decision process to improve clinical utility.

  • Information technology
  • Decision support, clinical
  • Quality improvement
  • Healthcare quality improvement
  • Decision support, computerized

Data availability statement

Data sharing is not applicable as no data sets were generated and/or analysed for this study.

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Data availability statement

Data sharing is not applicable as no data sets were generated and/or analysed for this study.

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  • Contributors All authors have fulfilled the following criteria: Substantial contributions to the conception or design of the work; or the acquisition, analysis, or interpretation of data for the work; and drafting the work or revising it critically for important intellectual content; and final approval of the version to be published; and agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Guarantor: RB.

  • Funding This study was funded by NHMRC (1181138); Cooperative Research Centre (DHCRC-0058).

  • Competing interests None declared.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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