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DETROIT – A group of researchers led by an industrial engineer have been awarded a National Science Foundation grant to find efficiency models for patient-centered medical homes by studying the U.S. Department of Veterans Affairs, the largest health system in the country.
Kai Yang, a professor of industrial and systems engineering at Wayne State University in Detroit, is leading the research team, with an NSF grant of $552,000. The group will study the VA’s patient-centered medical homes, a model emerging as a way to improve health outcomes by focusing services around primary care.
Yang said they’ll study VA health services nationwide, working with the VA’s office of informatics and analytics. “We’re going to use the data they have to analyze the workload for each patient, and we’re going to model how to divide workload across team members,” Yang said.
[See also: 5 ways case management puts care coordination on steroids]
The project’s aim is create adaptive statistical models that can predict workloads based on patient factors, and to create optimization models that help manage a doctors’ patient panels and staff levels.
Yang and his team plan to develop algorithms for how the facility allocates work under varying factors and then create an app for administrators and doctors to track and manage their workloads and progress. Looking at the needs throughout a health system, Yang said, “You can bump up or lower down the patients each team will see.”
With about 150 medical centers and more than 650 outpatient clinics, the VA is an enormous health system, and has struggled to coordinate and improve patient-centered care. The VA is implementing the patient-centered medical home model in all of its primary care sites, as part of its efforts to redesign its healthcare delivery by increasing access, coordination, communication and continuity of care.
Yang thinks the models his team creates could lead to much more streamlined care plans taking root in VA and other health systems. The project is called "An Allocation Model with Dynamic Updates for Balanced Workload Distribution on Patient-Centered Medical Homes."
