GOALI: Improving Access to Primary Care through E-Visits: Theory and Applications
University Of Wisconsin-Madison, Madison WI
Investigators
Abstract
E-visits, an alternative to the traditional office visit for medical services made possible by secure patient-physician communication, has the potential to improve access to care, and increase provider efficiency and patient satisfaction. For clinics that adopt e-visit strategy, several operational challenges arise. For example, how to determine the optimal staffing levels, how to allocate providers' time across different types of visits, how to schedule both office and e-visit requests, and how to identify system bottlenecks. An understanding of these operational dynamics can help in the identification of implementable mitigation strategies. This Grant Opportunity for Academic Liaison with Industry (GOALI) research project will be informed by collaboration with the Dean Health System and validated by utilizing Dean Health as a test case. The successful completion of this work will provide rigorous quantitative tools for primary care practitioners and administrators to improve patient access and quality of care. If successful, the results of this research will provide mathematical model to study the complex primary care delivery process with e-visits as part of a mix of services offered by comprehensive health systems such as Dean Health. Based on analytical investigation of the stochastic processes underlying primary care operations, network analyses will be used to model the patient flow and clinic operations. The research team will begin with analyses of patient flow at the clinic level and then analyze work flow within an office visit. By addressing their interactions and considering the limited availability and multiple tasks of providers through recursive algorithms, researchers will investigate optimal staffing, resource allocation, and workflow scheduling problems. Bottleneck analysis will be performed to identify significant constraints and to develop strategies to mitigate them.
View original record on NSF Award Search →