Healthcare systems (HSs) are complex socio-technical systems that rely on seamless collaboration between healthcare providers (i.e., doctors and nurses) with distinct expertise and engineered systems (e.g., electronic health records) to provide safety-critical services for communities. While provider performance plays a crucial role in the overall functionality and effectiveness of the broader HS; provider wellbeing has been consistently overlooked in the U.S. and this trend led to systemic issues such as burnout as documented by the National Academies. Burnout is detrimental to both the HSs and the providers suffering from it. On the HS-level, it leads to decreased quality of care and patient satisfaction, along with increased safety incidents, patient mortality, and operational costs. On a provider-level, it leads to a deterioration in mental health, increased likelihood of substance abuse and occupational injuries; thus, perpetuating a vicious cycle that negatively impact provider wellbeing. To that end, this research leverages the advancing digital twin (DT) technologies, particularly their real-time monitoring and intervention capabilities, to address the provider burnout issue at its core by developing a prototype DT of an existing microsystem in healthcare, a family medicine clinic operated by Carilion. This project will utilize systems engineering techniques to model the provider-technology-patient interplay and then use data-driven methods to quantify provider workload. Formulated workload models will be empirically verified through an array of mixed-methods approaches, and the resulting DT will be implemented into practice. By doing so, this project concurrently addresses the knowledge gaps (i) in the DT literature regarding representation of human decision-makers in the loop, (ii) the virtual-to-physical mapping challenges that have been documented in DTs for HSs, (iii) agile measurement and mitigation of burnout in HSs research through rigorous analytical techniques that are transferable to other representative HSs.
