Comparison of different methods for work accidents investigation in hospitals: A Portuguese case study

BACKGROUND: The hospital environment has many occupational health risks that predispose healthcare workers to various kinds of work accidents. OBJECTIVE: This study aims to compare different methods for work accidents investigation and to verify their suitability in hospital environment. METHODS: For this purpose, we selected three types of accidents that were related with needle stick, worker fall and inadequate effort/movement during the mobilization of patients. A total of thirty accidents were analysed with six different work accidents investigation methods. RESULTS: The results showed that organizational factors were the group of causes which had the greatest impact in the three types of work accidents. CONCLUSIONS: The methods selected to be compared in this paper are applicable and appropriate for the work accidents investigation in hospitals. However, the Registration, Research and Analysis of Work Accidents method (RIAAT) showed to be an optimal technique to use in this context.

Power Law Behavior and Self-similarity in Modern Industrial Accidents

Advances in technology have produced more and more intricate industrial systems, such as nuclear power plants, chemical centers and petroleum platforms. Such complex plants exhibit multiple interactions among smaller units and human operators, rising potentially disastrous failure, which can propagate across subsystem boundaries. This paper analyzes industrial accident data-series in the perspective of statistical physics and dynamical systems. Global data is collected from the Emergency Events Database (EM-DAT) during the time period from year 1903 up to 2012. The statistical distributions of the number of fatalities caused by industrial accidents reveal Power Law (PL) behavior. We analyze the evolution of the PL parameters over time and observe a remarkable increment in the PL exponent during the last years. PL behavior allows prediction by extrapolation over a wide range of scales. In a complementary line of thought, we compare the data using appropriate indices and use different visualization techniques to correlate and to extract relationships among industrial accident events. This study contributes to better understand the complexity of modern industrial accidents and their ruling principles.