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Seminar_20231129

A Joint Economic Analysis of Disproportionate Share Hospital (DSH) Funding for Emergency Care and  Global Payment Program (GPP) for Preventative Care

10/11/29 | 3:00pm | Zoom

Dr. Ujjal Mukherjee, Associate Professor

University of Illinois at Urbana Champaign

Abstract: In this paper, we perform an economic analysis of the Global Payment Program (GPP) instituted in 2014 by the Department of Health Services in the state of California, USA to enable healthcare providers to extend primary and preventative care to uninsured patients. The GPP is a fraction of the regular Disproportionate Share Hospital (DSH) federal fund (which is provided for emergency healthcare services to uninsured patients) that is set aside to provide a fixed and assured payment against set targets and subject to meeting the targets to participating healthcare organizations in the state of California. First, we derive equilibrium conditions for healthcare organizations to invest in emergency outpatient capacity above the mandated minimum levels in the absence of GPP, i.e., with only DSH payments. Second, we derive the equilibrium conditions for hospitals to participate in the GPP program, and invest in emergency outpatient capacity under combined GPP and DSH payments. We show that in general GPP increases the social surplus of healthcare services. Finally, we analyze conditions under which social planners can maximize the social surplus from the GPP program. Particularly, we derive optimal set-aside the amount for GPP from DSH and derive optimal allocation policies for GPP funds by comparing demand-driven allocation policies, and supply-driven allocation policies. We use data from the US healthcare system to validate the findings using numerical examples and provide counterfactual effects. This paper contributes by demonstrating that social support for primary and preventative care in addition to emergency care has the potential to improve social surplus from healthcare services.

Bio: Ujjal Kumar Mukherjee is an Associate Professor at the Gies College of Business at the University of Illinois at Urbana-Champaign, IL. He has a joint appointment at the Carle Illinois Medical School (CI-MED) as a Health Innovation Professor with a 33% time commitment. His research interests are focused on using analytical and empirical methods to understand product recalls in medical devices, pharmaceuticals, and other industries. Additionally, his research focuses on social healthcare delivery and healthcare analytics, particularly in the use of machine learning and statistical methods in healthcare problems, including precision medicine applications in the area of cancer treatment. Apart from clinical research, he works in the area of healthcare process and technology management. He has conducted in-depth field studies at a large multi-specialty hospital in the Mid-western United States to study operational issues related to the effective use of surgical robots for delivering critical surgical care to OB/GYN and Urological patients. Using data analysis, he has helped the partner hospital in selecting the right surgical procedures and patients to optimize cost and quality of surgical care delivery. Apart from clinical research, he conducts methodological research in the area of statistics and machine learning. Also, he has worked with several healthcare organizations to model and improve healthcare delivery processes such as rural and social healthcare delivery processes. I have conducted several research projects in developing countries such as India and China to address social healthcare delivery in partnerships with non-profit organizations. Recently he has been actively associated with COVID-19 research and mitigation activities. He had been an active team member of the team of researchers from UIUC supporting the state of Illinois’s COVID-19 response, and the UIUC’s SHIELD testing program. For his research, Ujjal has received grants from NSF (Mathematical Sciences Division) and C3.ai for developing mathematical models for social conflict and epidemic diffusion. Additionally, he has been involved in theoretical research in analytical modeling of healthcare operational issues using econometric and economic theories. He worked on a multi-year, multi-university grant ($1.8 Million) under a Federal Contract with the Food and Drug Administration (FDA) for developing mathematical and statistical models for drug quality evaluation. He has developed models for predicting and detecting drug quality failures by integrating data from different sources and different formats such as used feedback, social media text data, and facility inspection data.

Event Time and Venue: November 29, 2023, 3:00pm, Online

Zoom Access: Click here