Operationalising FRAM in Healthcare: A critical reflection on practice. (February 2023)

• Record Type: Journal Article
• Authors: Sujan, M.; Pickup, L.; de Vos, M.S.; Patriarca, R.; Konwinski, L.; Ross, A.; McCulloch, P.
• Is Part Of: Safety science. Volume 158(2023)
• Publication Date: 2023-02
• Subjects: Patient Safety -- FRAM -- Resilience Engineering -- System Safety; Industrial accidents -- Periodicals; Accident Prevention -- Periodicals; Safety -- Periodicals; Travail -- Accidents -- Périodiques; 363.11
• DOI: 10.1016/j.ssci.2022.105994
• Languages: English
• ISSNs: 0925-7535

Abstract

Highlights: Reflective study of FRAM use in healthcare. 5 FRAM use cases are analysed. Core characteristics of a FRAM study described. FRAM is not a singular method, but family of approaches. Distinguished between computational FRAM and reflexive FRAM. Abstract: Resilience Engineering principles are becoming increasingly popular in healthcare to improve patient safety. FRAM is the best-known Resilience Engineering method with several examples of its application in healthcare available. However, the guidance on how to apply FRAM leaves gaps, and this can be a potential barrier to its adoption and potentially lead to misuse and disappointing results. The article provides a self-reflective analysis of FRAM use cases to provide further methodological guidance for successful application of FRAM to improve patient safety. Five FRAM use cases in a range of healthcare settings are described in a structured way including critical reflection by the original authors of those studies. Individual reflections are synthesised through group discussion to identify lessons for the operationalisation of FRAM in healthcare. Four themes are developed: (1) core characteristics of a FRAM study, (2) flexibility regarding the underlying epistemological paradigm, (3) diversity with respect to the development of interventions, and (4) model complexity. FRAM is a systems analysis method that offers considerable flexibility to accommodate different epistemological positions, ranging from realism to phenomenology. We refer to these as computational FRAM and reflexive FRAM, respectively. Practitioners need to be clear about their analysis aims and their analysis position. Further guidance is needed to support practitioners to tell a convincing and meaningful "system story" through the lens of FRAM.