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AIMS: The influence of human factors on safety in healthcare settings is well established, with targeted interventions reducing risk and enhancing team performance. In experimental and early phase clinical research participant safety is paramount and safeguarded by guidelines, protocolized care and staff training; however, the real-world interaction and implementation of these risk-mitigating measures has never been subjected to formal system-based assessment. METHODS: Independent structured observations, systematic review of study documents, and interviews and focus groups were used to collate data on three key tasks undertaken in a clinical research facility (CRF) during a SARS CoV-2 controlled human infection model (CHIM) study. The Systems Engineering Initiative for Patient Safety (SEIPS) was employed to analyse and categorize findings, and develop recommendations for safety interventions. RESULTS: High levels of team functioning and a clear focus on participant safety were evident throughout the study. Despite this, latent risks in both study-specific and CRF work systems were identified in all four SEIPS domains (people, environment, tasks and tools). Fourteen actionable recommendations were generated collaboratively. These included inter-organization and inter-study standardization, optimized checklists for safety critical tasks, and use of simulation for team training and exploration of work systems. CONCLUSIONS: This pioneering application of human factors techniques to analyse work systems during the conduct of research in a CRF revealed risks unidentified by routine review and appraisal, and despite international guideline adherence. SEIPS may aid categorization of system problems and the formulation of recommendations that reduce risk and mitigate potential harm applicable across a trials portfolio.

Original publication

DOI

10.1111/bcp.15949

Type

Journal article

Journal

Br j clin pharmacol

Publication Date

30/10/2023

Keywords

clinical trials, human factors, methodology, patient safety, translational research