Identifying a list of healthcare 'never events' to effect system change: a systematic review and narrative synthesis

Abstract

Background: Never events (NEs) are patient safety incidents that are preventable and so serious they should never happen. To reduce NEs, several frameworks have been introduced over the past two decades; however, NEs and their harms continue to occur. These frameworks have varying events, terminology and preventability, which hinders collaboration. This systematic review aims to identify the most serious and preventable events for targeted improvement efforts by answering the following questions: Which patient safety events are most frequently classified as never events? Which ones are most commonly described as entirely preventable?

Methods: For this narrative synthesis systematic review we searched Medline, Embase, PsycINFO, Cochrane Central and CINAHL for articles published from 1 January 2001 to 27 October 2021. We included papers of any study design or article type (excluding press releases/announcements) that listed NEs or an existing NE framework.

Results: Our analyses included 367 reports identifying 125 unique NEs. Those most frequently reported were surgery on the wrong body part, wrong surgical procedure, unintentionally retained foreign objects and surgery on the wrong patient. Researchers classified 19.4% of NEs as 'wholly preventable'. Those most included in this category were surgery on the wrong body part or patient, wrong surgical procedure, improper administration of a potassium-containing solution and wrong-route administration of medication (excluding chemotherapy).

Conclusions: To improve collaboration and facilitate learning from errors, we need a single list that focuses on the most preventable and serious NEs. Our review shows that surgery on the wrong body part or patient, or the wrong surgical procedure best meet these criteria.

Keywords: Health services research; Never events; Patient safety.

Figure 1

Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow chart.