Min Kyung Lee, PhD Student
1. Monte Carlo Markov Chain (MCMC) Approaches to Building the Evidence for Cross-Sector Payment Models
Although the behavioral health of pregnant women has profound implications for the later development of both the mother and her child, most pregnant women do not receive the needed health services and supports. Prenatal supports have received unprecedented attention following the opioid crisis. To finance the necessary innovation, a special kind of value-based payment contract can be initiated with a Medicaid payer based on the Net Present Value of Care (NPVoC). While previous attempts at value based payment looked at sharing past-year savings, NPVoC builds on this by sharing future year savings predicted by past-year outcomes. Using Markov chain Monte Carlo simulation techniques, we demonstrate how such a contract can be specified.
Collaborators: Dr. Paul Griffin, Nathaniel Z. Counts, J.D.
2. Simulation Modeling of a Stroke System of Care: Improving Patient Outcomes in Rural Communities
Following a landmark paper by the Joint Commission in 2015, several states including California and Illinois, implemented new protocols that reflect the ‘stroke system of care,’ putting EMS agencies with the responsibility of diagnosing stroke patients and bypassing hospitals that are not accredited as stroke centers. However, there is an increasing concern among decision-makers about dealing with stroke care in rural areas under the current healthcare infrastructure. Albeit the efforts to reduce delays to treatments and to provide the optimal care for stroke patients, stroke system of care is premature in rural areas, where access to neurological expertise and coordinated stroke care are inadequate. The project evaluates the impact of a stroke system of care in varying urbanicity, in the presence or absence of novel technology.
Collaborators: Dr. Yuehwern Yih, Dr. Paul Griffin, and Dr. David Johnson