Prioritising recommendations following analyses of adverse events in healthcare: a systematic review. Issue 4 (9th October 2020)

• Record Type: Journal Article
• Authors: Bos, Kelly; van der Laan, Maarten J; Dongelmans, Dave A
• Is Part Of: BMJ open quality. Volume 9:Issue 4(2020)
• Publication Date: 2020-10-09
• Subjects: adverse events -- epidemiology and detection -- incident reporting -- patient safety -- quality improvement -- root cause analysis; Medical care -- Quality control -- Periodicals; 362.106805
• DOI: 10.1136/bmjoq-2019-000843
• Languages: English
• ISSNs: 2399-6641

Abstract

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.