Top four types of sentinel events in Saudi Arabia during the period 2016–19

Abstract

Abstract Background This study discusses the summary, investigation and root causes of the top four sentinel events (SEs) in Saudi Arabia (SA) that occurred between January 2016 and December 2019, as reported by the Ministry of Health (MOH) and private hospitals through the MOH SE reporting system (SERS). It is intended for use by legislators, health-care facilities and the public to shed light on areas that still need improvement to preserve patient safety. Objectives The purpose of this study is to review the most common SEs reported by the MOH and private hospitals between the years 2016 and 2019 to assess the patterns and identify risk areas and the common root causes of these events in order to promote country-wide learning and support services that can improve patient safety. Methods In this retrospective descriptive study, the data were retrieved from the SERS, which routinely collects records from both MOH and private hospitals in SA. SEs were analyzed by type of event, location, time, patient demographics, outcome and root causes. Results There were 727 SEs during this period, 38.4% of which were under the category of unexpected patient death, 19.4% under maternal death, 11.7% under unexpected loss of limb or function and 9.9% under retained instruments or sponge. Common root causes were related to policies and procedures, guidelines, miscommunication between health-care facilities, shortage of staff and lack of competencies. Conclusion Given these results, efforts should focus on improving the care of deteriorating patients in general wards, ICU (Intensive Care Units) admission/discharge criteria and maternal, child and surgical safety. The results also highlighted the problem of underreporting of SEs, which needs to be addressed and improved. Linking data sources such as claims and patient complaints databases and electronic medical records to the national reporting system must also be considered to ensure an optimal estimation of the number of events.