Reformulating human reliability in healthcare systems

In complex and high-risk systems such as healthcare, human error and human reliability are critical issues due to the devastating patient health and financial consequences. Proactive risk assessments can be implemented to predict human performance and inform human error risk mitigation strategies. Existing human reliability tools do not adequately incorporate data-driven methodologies to predict performance for operators on a specific task. Given these current limitations, the proposed Human Reliability Assessment (HRA) methodology provides health care professionals with an integrated three stage process to develop operator- And context-specific tools that can be used to identify, evaluate and mitigate human error risk. In the initial stage, human response is identified through the development of human error causal factors (Performance Shaping Factors - PSFs) and manifestations (unsafe acts, tasks). In the second stage, response probabilities (Human Error Probabilities - HEPs) are estimated through empirical data collection to build and validate the error prediction algorithm. The third and final stage involves the identification of significant contributors to human error to support the development of risk mitigation strategies. Potential benefits of utilizing the proposed methodology in healthcare decisions include a significant reduction in human errors which will ultimately lead to a reduction in patient deaths and health care system resources.