1 Risk Analysis on the Planning of Surgery: A Case Study in a Brazilian Public Hospital of Oncology Ana Maria Saut University of São Paulo ana.saut@usp.br Anne Caroline de Oliveira Ramos University of São Paulo Fernando Tobal Berssaneti University of São Paulo Marília Piccinini da Carvalhinha University of São Paulo Abstract This study aimed to demonstrate the applicability of the Health Care Failure Mode and Effect Analysis tool (HFMEA) by reporting the experience in the planning of surgery. There was a reduction of errors, with reports of only three near miss in one year, indicating that the tool was highly effective. Keywords: Risk management, Health care, Patient Safety. INTRODUCTION In recent years, there was a change in the focus on thinking about adverse events from an individual approach (blame a person by mistake) to a systems approach. The systems approach assumes that people make mistakes, and that the system around them should provide a safety net for these errors (De Vries et al. 2008). This change in approach is strongly based on the theory developed by Reason seeing that adverse events are rarely determined by a single mistake, be it human or technological; but more often they are the result of a sequence of errors and events in which the person responsible for the final error is just the latest causal link (Reason 1995). After the report published by the Institute of Medicine of the United States, "To Err Is Human: Building a Safer Health System", some significant studies have been conducted on adverse events, some of them nationwide. In a review of the main studies on the occurrence of adverse events, that the general average incidence of adverse events in hospitals was found to be 9.2%, and the average of these possible events to be prevented was 43.5 %. Another important finding is that most of these events are related to surgery (52.9%) and drugs (15.7%) (Brennan et al. 1991; Baker et al. 2004; De Vries et al. 2008). Some retrospective methods have been used to analyze the errors in healthcare services and to prevent them from happening again, such as the Root Cause Analysis (RCA) technique (Teixeira and Cassiani, 2010). However, to reduce harm to patients, the need to identify the risks prospectively and to predict possible errors was emphasized (Kessels-Habraken et al. 2009).