Technologies for Studying Healthcare Worker Fatigue and Burnout
Work-related fatigue and burnout are problems that occupational and environmental health and safety professionals may not address on a regular basis. However, these health effects can have a profound impact on not only the well-being of workers but also their ability to perform their jobs safely. Burnout, which is the condition of emotional exhaustion, maladaptive detachment, and reduced effectiveness at work that occurs in response to long-term occupational stress, has been linked to poor health, substance abuse, depression, and suicide. According to NIOSH, “High levels of fatigue can affect any worker in any occupation or industry with serious consequences for worker safety and health.”
Over the past year and a half, healthcare workers have endured an enormous burden in responding to the COVID-19 pandemic. While these pandemic-related challenges have been particularly visible in media reports and in stories from family and friends, healthcare workers faced occupation-related burnout and fatigue long before the pandemic. Industrial hygienists and OEHS professionals often turn to traditional techniques like the tried-and-true sampling pump and more recent direct-reading instruments to monitor for hazardous exposures in the workplace. However, monitoring and evaluating for worker fatigue and burnout may require harnessing new technologies that we are not as familiar with.
Exploring the use of these new technologies is exactly what one doctor at Columbia University Medical Center is doing now. Dr. Alexander Thomas, a postdoctoral research fellow, and others at the medical center were concerned about the effect of fatigue and burnout on their surgical residents. Surgical trainees are known to be at particularly high risk for burnout, which seems, in part, to be related to the requisite long and strenuous shifts and weeks of back-to-back workdays. In an ongoing study, Dr. Thomas and his colleagues are using biometric data captured by wearable devices (for example, Garmin or FitBit trackers) to give their surgical residents insights about their stress and fatigue levels. Researchers will compare the collected biometric data—including heart rate, heart rate variation, blood oxygen levels, and sleep patterns—to subjective data from survey responses to evaluate whether biometrics can accurately identify periods of increased stress and associated risk factors.
Additionally, software incorporating artificial intelligence (AI) algorithms will be utilized to analyze the biometric data. It is hypothesized that these biometric data will exhibit patterns indicative of impending risk for high levels of stress and fatigue that the AI can recognize, providing predictive value in the days prior to a worker subjectively reporting stress and fatigue. While the wearable technologies are not intended to diagnose or treat disease, this study is intended to validate the use of wearable devices in identifying stress points, which may serve as important tools to track the effect of implemented worker interventions. “I am proud of the work we do in surgery and passionate about improving the circumstances for surgical trainees,” Dr. Thomas said when asked about the study. “By limiting the impact of stress, fatigue, and burnout, I believe that we can protect high-risk people from potentially devastating mental and physical health outcomes, maximize resident productivity, and improve patient care.”
This example demonstrates the power of new technologies such as wearable devices and AI to assist in addressing worker safety and health issues. It also highlights the challenges of new technologies, including complex issues related to workers’ acceptance of wearing such devices (particularly during non-work activities), data privacy concerns, and analysis of “Big Data” sets to allow for predictive and preventive actions rather than reactive ones. Despite these challenges, OEHS professionals owe it to themselves and the workers they help protect to become more familiar with these technologies as they find increasingly new applications in the OEHS realm.
For further information on fatigue monitoring and detection technology, see the following NIOSH Science Blog posts:
- “Choosing the ‘Right’ Fatigue Monitoring and Detection Technology”
- “The Who, What, How and When of Implementing Fatigue Monitoring and Detection Technologies”
Do you have an interesting case study in the use of new technologies to address worker health and safety issues? Share your thoughts and experiences in the comments.
Related: Read “COVID-19 and Worker Fatigue: Lessons Learned and Mitigation Strategies” in the November 2020 issue of The Synergist.