Patient Safety, Present and Future

Health care tends to oversimplify patient safety concepts. We tend to think about patient safety as a linear dimension that is only associated with the progressive reduction in the number of errors and accidents, with the simple notion that fewer are always better. We consider figures in isolation from the underlying context and prerequisites that drive safety models and the reality of the clinical fields. There is no one ultimate reference model of safety, but many models that can be adapted to fit the various clinical fields requirements and constraints. It is therefore not necessarily a bad result to observe a lower safety figure in a medical domain compared to the figures obtained in nonmedical ultra-safe models. The poor figures may represent the best local safety optimization while coping with the special health care requirements such as a high frequency of unplanned and nonstandard challenges. The paper distinguishes three classes of safety models that fit different field demands: the resilient and adaptive model, the high reliability (HRO) model, and the ultra-safe model. The lecture benchmarks the traits of each model while highlighting the specific dimensions for optimization. The conclusion is that firstly, that since the task requirements dictate the relevance and choice of the model and not the other way around, it is counterproductive to impose a model that is inadequate for the task requirements. Either you move the requirements and change the model, or you keep the constraints, and try to locally optimize the model to the clinical and organizational needs. (author)