A risk management method for enhancing patient safety based on interval- valued fuzzy numbers

Abstract

As the importance of patient safety increases for hospital management, improvements in patient safety are needed to reduce the high incidence of medical errors. Research on patient safety and medical errors shows that errors and the resulting adverse events are mainly the result of health-care providers, equipment and the quality management system. Most studies focused their research on the risk of the individual patient in health care. However, when facing patient safety problems, a hospital manager must consider the risk to the organization while making decisions about improvements. The risks will be relative to the cost-effectiveness of a health-care organization. Here we used a TOPSIS (technique for order preference by similarity to ideal solution) approach to manage the risk of a health-care organization in linguistic terms in the environment of interval-valued fuzzy numbers (IVFNs). Rather than calculating the distance between the alternatives and the positive/negative ideal solution in a TOPSIS approach, we use the similarity measure between IVFNs of the alternatives’ risk and the risk of the positive/negative ideal solution to help hospital managers analyze risks in an uncertain and complex situation and more easily determine the best alternative. Key words: Risk management, decision making, patient safety, interval-valued fuzzy numbers, TOPSIS, similarity measure.