Pasupathy, Kalyan S.

Workload experienced by health care workers continues to be a challenge to define and quantify. The purpose of the current study is to present descriptive data on the application of sociometers in an emergency care environment during simulated hand-off scenarios and discuss their potential and limitations for quantifying individual’s workload in health care settings. Sociometer devices, worn by nine actors, collected body movement, interactions, and speech data during four simulated hand-off scenarios in the emergency department wards. Results found that sociometers distinguished body movement differences between sitting, standing, lying, and walking individuals. Interactions quantified by the devices were limited by obstructions, distance, and angles between the sociometer devices. The data collected by these devices show promise in providing human factors researchers a tool for quantifying the dynamic exposures experienced by health care workers over time.

Fatigue and recovery have been associated with health, safety, and performance outcomes in hospital nurses. There is a growing emphasis on fatigue risk management and health promotion programs to support nurses and promote quality in hospitals. However, little is known about the relationships between fatigue and wellness measures in nurses. This study used a tree-based classification method to identify associations between self-reported fatigue, recovery and wellness measures in a survey study of hospital nurses. Significant relationships between multiple wellness measures and acute fatigue, chronic fatigue, and intershift recovery levels were identified. Specifically, the findings include critical levels of wellness measures where fatigue and recovery change. These findings have implications for ongoing efforts to develop effective fatigue management programs in this population.

Healthcare processes have variability embedded within care delivery systems. Process mapping has been traditionally used to study processes, and is based on human perceptions of how the process is structured and how care is delivered. Process mapping can be biased based on individual perceptions and not comprehensive to capture variability. Radio frequency identification (RFID) provides a more objective means for collecting process-related data. This paper discusses process mapping, its benefits and drawbacks, and how RFID can complement process mapping. Qualitative information (process mapping) and quantitative information (data collected using RFID and from other sources) can potentially be combined to develop process models. Such models can inform process improvement and increase safety and efficiency.

Healthcare processes have variability embedded within care delivery systems. Healthcare providers and managers need visibility of the process to understand variability, and make process design changes, to improve safety and efficiency. Process mapping has been traditionally used to study processes, and is based on perceptions. However, to better understand and manage variability, there is an urgent need for process mining techniques. Process mining requires data for validation, to increase understanding and/or change perceptions and improve visibility. Radio frequency identification (RFID) can be used for collecting process-related data and can eliminate data quality issues. This paper discusses process mining and its application in healthcare, summarizes process mapping and RFID, and proposes an integration framework and method to improve visibility.