Using a learning curve approach to reduce laboratory errors

Abstract

Hospital laboratories have error rates that are too high and in some cases may be responsible for adverse patient treatment. This paper introduces reliability growth management (RGM), which is based on learning curve theory, as a method to improve laboratory error rates. RGM is widely used in the defense and automotive industry to solve problems when resources are limited and knowledge about the product and/or process is incomplete. An example of RGM, which was used to improve the reliability of instrument assay systems in the medical diagnostics industry is presented. RGM is a closed-loop process that entails creating a goal and event model, classifying events with failure review and corrective action system (FRACAS), tracking progress and predicting completion with Duane analysis. Results achieved by RGM were far better than those obtained by previously used methods. RGM techniques can be transferred to hospital laboratories to reduce laboratory error rates. The advantages of RGM compared to other quality initiatives such as ISO 9000 and Six Sigma are discussed.