Title:
Health Analytics for Decision Making in Healthcare Spatial Access
Health Analytics for Decision Making in Healthcare Spatial Access
Author(s)
Harati, Pravara
Advisor(s)
Serban, Nicoleta
Editor(s)
Collections
Supplementary to
Permanent Link
Abstract
Appropriate access to healthcare services is important for preventing the spread of disease, reducing hospitalizations and emergency department use, and increasing quality of life. However, within the United States healthcare system, there exist many disparities in access to care. In this dissertation, we aim to quantify and assess disparities in healthcare access, for informed decision making towards improving access. Compared to existing methods, our approach allows for local-level estimates, is data-rich, and is statistically rigorous.
In Chapter 2 of this dissertation, we focus on access to pediatric primary care services in seven states. We design an optimization model to match primary care need with supply while taking into consideration system constraints such as health insurance acceptance and maximum travel distance. We perform statistical inference, both between and within states, to determine whether there are significant disparities in travel distance and congestion. In Chapter 3, we focus on primary care for non-elderly adults in Georgia and how it may be impacted by the Affordable Care Act. We additionally evaluate the impact of two other policies intended to improve access: increasing the number of residency positions in Georgia and implementing a parity program so that more providers accept Medicaid insurance.
In Chapter 4, we begin analysis of psychosocial services for Medicaid-insured children. Using Medicaid claims data for 34 states, we identify which providers are likely to treat Medicaid-insured children and their practice settings, comparing across states, urbanicity, and provider specialties. Finally, in Chapter 5, we develop a modeling framework for one potential intervention to increase access to psychosocial services: collaboration between mental health providers and primary care providers. We create this framework by extending congestion games into a setting in which players have their own private cost function for each resource and resources have their own capacities and preferences over the players. We construct a polynomial-time algorithm to find a Nash equilibrium for singleton games with non-decreasing cost functions under this setting and demonstrate our model for services to Medicaid-insured children in New York.
Sponsor
Date Issued
2021-01-14
Extent
Resource Type
Text
Resource Subtype
Dissertation