A comparison of the methods used to support risk identification for patient safety in one UK NHS foundation trust. (March 2015)

• Record Type: Journal Article
• Authors: Simsekler, MC Emre; Card, Alan J; Ruggeri, Kai; Ward, James R; Clarkson, P John
• Is Part Of: Clinical risk. Volume 21:Number 2/3(2015)
• Page Start: 37
• Page End: 46
• Publication Date: 2015-03
• Subjects: Risk identification -- incident investigation -- risk registers -- safety walkabouts -- patient safety; Patients -- Safety measures -- Periodicals; Medical personnel -- Malpractice -- Periodicals; 610.289
• DOI: 10.1177/1356262215580224
• Languages: English
• ISSNs: 1356-2622

Abstract

In healthcare, various methods are available to support risk identification in risk management process. However, there is no clear evidence on their contribution to risk identification. In this study, different methods used to support risk identification were therefore analysed to compare their contribution to overall risk identification. The study was conducted at Cambridge University Hospitals Foundation Trust, UK. Three main methods were selected to compare their support in risk identification: incident reports through their Risk Management Information System, risk registers through their Risk Registers system, and safety walkabouts through their internal patient safety assessment process. Where possible, simple comparison tests were run between the different methods of identifying risks as well as by the type of risks identified. It was found that each method has contributed to the risk identification by adding different sets of risk sources despite some overlaps. However, they produced discrete assessments from different aspects and none of them, on its own, could produce adequate results for effective risk identification. In any healthcare setting, having a system to put all risk information in one picture would help maximise the contribution of each method within the scope risk management process. Future studies may benefit from broader use of multiple and system-based risk identification approaches, and coding methods for more powerful analytical test.