Article Text

Prioritising recommendations following analyses of adverse events in healthcare: a systematic review
  1. Kelly Bos1,
  2. Maarten J van der Laan2,
  3. Dave A Dongelmans3
  1. 1Department of Surgery, Amsterdam UMC - location AMC, Amsterdam, the Netherlands
  2. 2Department of Surgery, University Medical Centre Groningen, Groningen, the Netherlands
  3. 3Department of Intensive Care Medicine, Amsterdam UMC - location AMC, Amsterdam, the Netherlands
  1. Correspondence to Dr Kelly Bos; k.bos{at}amsterdamumc.nl

Abstract

Purpose The purpose of this systematic review was to identify an appropriate method—a user-friendly and validated method—that prioritises recommendations following analyses of adverse events (AEs) based on objective features.

Data sources The electronic databases PubMed/MEDLINE, Embase (Ovid), Cochrane Library, PsycINFO (Ovid) and ERIC (Ovid) were searched.

Study selection Studies were considered eligible when reporting on methods to prioritise recommendations.

Data extraction Two teams of reviewers performed the data extraction which was defined prior to this phase.

Results of data synthesis Eleven methods were identified that are designed to prioritise recommendations. After completing the data extraction, none of the methods met all the predefined criteria. Nine methods were considered user-friendly. One study validated the developed method. Five methods prioritised recommendations based on objective features, not affected by personal opinion or knowledge and expected to be reproducible by different users.

Conclusion There are several methods available to prioritise recommendations following analyses of AEs. All these methods can be used to discuss and select recommendations for implementation. None of the methods is a user-friendly and validated method that prioritises recommendations based on objective features. Although there are possibilities to further improve their features, the ‘Typology of safety functions’ by de Dianous and Fiévez, and the ‘Hierarchy of hazard controls’ by McCaughan have the most potential to select high-quality recommendations as they have only a few clearly defined categories in a well-arranged ordinal sequence.

  • adverse events
  • epidemiology and detection
  • incident reporting
  • patient safety
  • quality improvement
  • root cause analysis
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Footnotes

  • Contributors Study conception and design: KB, MJvdL and DAD. Acquisition of data: KB, MJvdL and DAD. Analysis and interpretation of data: KB, MJvdL and DAD. Drafting manuscript: KB. Revising it critically for important intellectual content: KB, MJvdL and DAD. All authors approved the final version of the manuscript.

  • Funding This work was supported by the Quality-based Governance programme and is funded by the Citrien foundation. This foundation supports the development of sustainable and broadly applicable solutions in healthcare and is made possible by ZonMw.

  • Competing interests None declared.

  • Patient consent for publication Not required.

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

  • Data availability statement All data relevant to the study are included in the article or uploaded as supplementary information.

  • 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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