HARRISBURG, PA — Harrisburg University of Science and Technology (HU) Professors Teray Johnson, Ph.D., MS, MBA, and Sameh Shamroukh, Ph.D., have published an original, peer-reviewed research article in the journal Artificial Intelligence in Health. The paper is entitled, “Assessing the predictive influence of organizational culture on employee burnout within health systems: Insights and strategic implications.”
It is widely recognized that organizational culture (OC) plays a key role in employee well-being, but its link to burnout has rarely been explored using machine learning. This exploratory study used a random forest algorithm to analyze survey data from 67 health system employees in the US, examining whether elements of OC could predict burnout.
The results suggest that specific aspects of OC – such as work interfering with personal life – are strong predictors of burnout. These findings highlight the importance of fostering a supportive workplace culture (implementing flexible scheduling, ensuring employees have adequate resources to succeed, etc.) and emphasize the potential of machine learning to reveal how organizational culture influences burnout and employee morale.
Dr. Johnson, an HU alumna, noted: “Because burnout is prevalent among non-patient-facing health system employees, Dr. Shamroukh and I used my existing survey data from my dissertation at HU to create a predictive model with a random forest algorithm. The model uses several aspects of organizational culture, which has been demonstrated in previous publications to be associated with burnout rates, to predict burnout. The model is useful for healthcare leaders to reduce burnout among these unique employees.”
She continued: “Burnout must be addressed among non-patient-facing employees because of its downstream effects on patient care. I hope leaders take away practical ways to address their organizational culture and, therefore, the lingering problem of burnout in our healthcare system.”
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