Abstract
Background and objective: Probabilistic risk assessment methods are well suited for exploring hazards and threats in patient care due to their ability to analyse complex systems and include human factors. Adopting an event (A) – consequence (C) – uncertainty (U) perspective (referred to as the (A, C, U) perspective) the focus of the risk assessment is on predictions and uncertainty assessment of observable quantities. Uncertainty is the main component of risk, and probability is a tool for expressing this uncertainty. To demonstrate the feasibility of this perspective in risk assessment to improve patient safety, we have applied it to the high-risk activity of percutaneous dilatational tracheostomy in an intensive care unit. Methods: Using a Bayesian belief network, we modelled and analysed fault trees of two relevant adverse events: “Perioperative bleeding” and “loss of airway”. The analysis was based on a broad knowledge basis and incorporated risk influencing factors. Results: In the risk assessment we assigned the probability of “perioperative bleeding” at 8.0% and “loss of airway” at 0.05%. The uncertainty assessment identified operator and team performance to affect risk the most. Conclusion: Risk assessment according to the (A, C, U) perspective is a valuable tool to support decision-making in patient safety matters and explore risk influencing factors.
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