BackgroundGeneral surgery is an area with a major incidence of adverse evets and entails increased use of resources, in addition to the injury caused to the patient. The preparation of specific tools in the field of patient safety and specifically to detect adverse events is a priority of healthcare systems. Regarding the hypothesis that the trigger tool is effective to detect adverse events in general surgery we set out this study with the aim to validate this and propose optimization.MethodsObservational, descriptive, retrospective and multicenter national study where trigger tool (40 triggers) was applied in patients who underwent surgery in general surgery departments. A descriptive analysis was performed. The tool’s sensitivity and specificity was studied by means of looking at predictive capacity. A prediction model was used for the proposed optimization by means of binary logistic regressionResults A total of 31 hospitals took part. The prevalence of adverse events was 31.53%.The tool revealed sensitivity and specificity of 86.27% and 79.55%, respectively. A total of 12 triggers comprised the optimized model. An area under the curve of 79.29% was obtained. Conclusions Trigger Tool is extremely effective to detect adverse events during surgery. The optimized model significantly reduces the number of triggers used and upholds