Cost-effective Intervention - Innovative Strategies for Public Health Care

Open Access
Yan, Renfei
Graduate Program:
Industrial Engineering
Doctor of Philosophy
Document Type:
Date of Defense:
March 21, 2014
Committee Members:
  • Paul Griffin, Dissertation Advisor
  • Paul Griffin, Committee Chair
  • Harriet Black Nembhard, Committee Chair
  • Vittaldas V Prabhu, Committee Member
  • Douglas J Thomas, Committee Member
  • Cost-Effective Modeling
  • Public Health Intervention
  • Dental Care
  • Tuberculosis Transimission
  • Food Environment
Limits on health care resources mandate that decision makers design intervention strategies that are cost-effective. In this dissertation, three cost-effective models are developed and applied to address three different health care problems. The first problem is concerned with the evaluation of children’s dental care practices using longitudinal claims data. By linking service mix to the stage of care and applying a Markov chain approach, we examine the feasibility of using recurring patterns of care to evaluate how well patients are integrated into the dental system. The results suggest that privately-insured children are better integrated into dental care than Medicaid-insured children. In addition, transition probabilities estimated from longitudinal claims data provide insight on the quality of a dental program. The model enables practitioners to institute changes in the pattern of delivery, to identify problem areas, and to determine if proposed changes should take place. It also provides a mechanism to estimate the level of government funding needed to support a service goal. We illustrate this by applying the model to estimate the financial cost of implementing a component of the Affordable Care Act for the oral health of children. The second problem deals with the development of appropriate intervention strategies for Tuberculosis transmission in health care settings. The risk of occupational infection by Mycobacterium Tuberculosis among patients and health care workers has received increased attention. An infection risk model based on biological and physical principles was developed by taking into consideration primary intervention measures. The simulation results show that HIV+ patients should be isolated during admission into the hospital, and that a higher screening frequency for health care workers will significantly reduce the infection cases among patients and health care workers. A distributive model with space segmentation was also studied which suggests that susceptible patients sitting closer to the infectious sources will have a greater risk of being infected. The study will help hospitals in designing their personalized cost-effective intervention strategy based on their specific situation. The third problem examines the impact of food deserts on obesity as well as interventions to reduce their significance. We focused on finding the association of food retailers and obesity in US adults. A nonlinear parametric regression was developed using publicly available data at the county level. The model suggests that, in metropolitan areas, obesity rate is positively associated with supercenters and convenience stores and negatively associated with grocery stores and specialty food stores. In non-metropolitan areas, obesity rate is positively associated with supercenters and negatively associated with specialty food stores. We estimated the marginal effect on obesity from the addition of a new food retailer type in a geographic region. This will be useful in identifying regions where interventions based on food retailer type would be most effective. We illustrate several possible applications of the model including: an incentive contract that will elicit a desired level of operator's effort while maximizing the foundation's utility, a proper division of the total subsidies into loans and grants, and a strategic design of food store establishment plan by local government.