Patient safety: latent risk factors

• Published in: British journal of anaesthesia : BJA Vol. 105; no. 1; pp. 52 - 59
• Main Authors: van Beuzekom, M, Boer, F, Akerboom, S, Hudson, P
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.07.2010; Oxford University Press
• Subjects: Anesthesia; Anesthesia. Intensive care medicine. Transfusions. Cell therapy and gene therapy; Anesthesiology - organization & administration; Anesthesiology - standards; Biological and medical sciences; health care; Humans; medical errors; Medical Errors - prevention & control; Medical sciences; quality assurance; Quality Assurance, Health Care; Risk Factors; risk management; Risk Management - methods; safety; medical errors; risk management; quality assurance, health care; safety; Human; Latent; Quality assurance; Clinical management; Risk factor; Anesthesia; health care
• ISSN: 0007-0912; 1471-6771
• DOI: 10.1093/bja/aeq135

The person-centred analysis and prevention approach has long dominated proposals to improve patient safety in healthcare. In this approach, the focus is on the individual responsible for making an error. An alternative is the systems-centred approach, in which attention is paid to the organizational factors that create precursors for individual errors. This approach assumes that since humans are fallible, systems must be designed to prevent humans from making errors or to be tolerant to those errors. The questions raised by this approach might, for example, include asking why an individual had specific gaps in their knowledge, experience, or ability. The systems approach focuses on working conditions rather than on errors of individuals, as the likelihood of specific errors increases with unfavourable conditions. Since the factors that promote errors are not directly visible in the working environment, they are described as latent risk factors (LRFs). Safety failures in anaesthesia, in particular, and medicine, in general, result from multiple unfavourable LRFs, so we propose that effective interventions require that attention is paid to interactions between multiple factors and actors. Understanding how LRFs affect safety can enable us to design more effective control measures that will impact significantly on both individual performance and patient outcomes.