Our first review: An evaluation of effectiveness of root cause analysis recommendations in Hong Kong public hospitals

Background: To evaluate the effectiveness of root cause analysis (RCA) recommendations and propose possible ways to enhance its quality in Hong Kong public hospitals. Methods: A retrospective cross-sectional study was performed across 43 public hospitals and institutes in Hong Kong, reviewing RCA reports of all Sentinel Events and Serious Untoward Events within a two-year period. The incident nature, types of root causes and strengths of recommendations were analysed. The RCA recommendations were categorised as \u27strong\u27, \u27medium\u27 or \u27weak\u27 strengths utilizing the US\u27s Veteran Affairs National Center for Patient Safety action hierarchy. Results: A total of 214 reports from October 2016 to September 2018 were reviewed. These reports generated 504 root causes, averaging 2.4 per RCA report, and comprising 249 (49%) system, 233 (46%) staff behavioural and 22 (4%) patient factors. There were 760 recommendations identified in the RCA reports with an average of 3.6 per RCA. Of these, 18 (2%) recommendations were rated strong, 116 (15%) medium and 626 (82%) weak. Most recommendations were related to \u27training and education\u27 (466, 61%), \u27additional study/review\u27 (104, 14%) and \u27review/enhancement of policy/guideline\u27 (39, 5%). Conclusions: This study provided insights about the effectiveness of RCA recommendations across all public hospitals in Hong Kong. The results showed a high proportion of root causes were attributed to staff behavioural factors and most of the recommendations were weak. The reasons include the lack of training, tools and expertise, appropriateness of panel composition, and complicated processes in carrying out large scale improvements. The Review Team suggested conducting regular RCA training, adopting easy-to-use tools, enhancing panel composition with human factors expertise, promoting an organization-wide safety culture to staff and aggregating analysis of incidents as possible improvement actions