FAMILY CHARACTERISTICS, STATE PROGRAM EFFECTIVENESS, AND REPORT OF INADEQUATE CARE AMONG FAMILIES OF YOUNG CHILDREN WITH HEARING LOSS

Approximately 1.6 per 1,000 newborns in the U.S. are born with hearing loss. Congenital hearing loss poses a risk to their speech, language, cognitive, and social-emotional development. Early detection and intervention can improve outcomes. Every state has an Early Hearing Detection and Intervention program (EHDI) to promote and track screening, audiological assessments and linkage to early intervention. However, a large percentage of children are “lost to system (LTS),” meaning that they did not receive recommended care or that it was not reported. This study used data from the 2009-2010 National Survey of Children with Special Health Care Needs and data from the 2011 EHDI Hearing Screening and Follow-Up Survey to examine how 1) family characteristics; 2) EHDI program effectiveness, as determined by LTS percentages; and 3) the family conditions of education and poverty are related to parental report of inadequate care. The sample comprised 684 children between the ages of 0 and 5 years with hearing loss. The results indicated that living in states with less effective EHDI programs was associated with an increased likelihood of not receiving early intervention services (EIS) and of reporting poor family-centered communication. Sibling classification was associated with both receipt of EIS and report of unmet need. Single mothers were less likely to report increased difficulties accessing care. Poor and less educated families, assessed separately, who lived in states with less effective EHDI programs, were more likely to report non-receipt of EIS and less likely to report unmet need as compared to similar families living in states with more effective programs. Poor families living in states with less effective programs were more likely to report less coordinated care than were poor families living in states with more effective programs. This study supports the conclusion that both family characteristics and the effectiveness of state programs affect quality of care outcomes. It appears that less effective state programs affect disadvantaged families’ service receipt report more than that of advantaged families. These findings are important because they may provide insights into the development of targeted efforts to improve the system of care for children with hearing loss.

Multi-level, Multi-stage and Stochastic Optimization Models for Energy Conservation in Buildings for Federal, State and Local Agencies

Energy Conservation Measure (ECM) project selection is made difficult given real-world constraints, limited resources to implement savings retrofits, various suppliers in the market and project financing alternatives. Many of these energy efficient retrofit projects should be viewed as a series of investments with annual returns for these traditionally risk-averse agencies. Given a list of ECMs available, federal, state and local agencies must determine how to implement projects at lowest costs. The most common methods of implementation planning are suboptimal relative to cost. Federal, state and local agencies can obtain greater returns on their energy conservation investment over traditional methods, regardless of the implementing organization. This dissertation outlines several approaches to improve the traditional energy conservations models. Any public buildings in regions with similar energy conservation goals in the United States or internationally can also benefit greatly from this research. Additionally, many private owners of buildings are under mandates to conserve energy e.g., Local Law 85 of the New York City Energy Conservation Code requires any building, public or private, to meet the most current energy code for any alteration or renovation. Thus, both public and private stakeholders can benefit from this research. The research in this dissertation advances and presents models that decision-makers can use to optimize the selection of ECM projects with respect to the total cost of implementation. A practical application of a two-level mathematical program with equilibrium constraints (MPEC) improves the current best practice for agencies concerned with making the most cost-effective selection leveraging energy services companies or utilities. The two-level model maximizes savings to the agency and profit to the energy services companies (Chapter 2). An additional model presented leverages a single congressional appropriation to implement ECM projects (Chapter 3). Returns from implemented ECM projects are used to fund additional ECM projects. In these cases, fluctuations in energy costs and uncertainty in the estimated savings severely influence ECM project selection and the amount of the appropriation requested. A risk aversion method proposed imposes a minimum on the number of “of projects completed in each stage. A comparative method using Conditional Value at Risk is analyzed. Time consistency was addressed in this chapter. This work demonstrates how a risk-based, stochastic, multi-stage model with binary decision variables at each stage provides a much more accurate estimate for planning than the agency’s traditional approach and deterministic models. Finally, in Chapter 4, a rolling-horizon model allows for subadditivity and superadditivity of the energy savings to simulate interactive effects between ECM projects. The approach makes use of inequalities (McCormick, 1976) to re-express constraints that involve the product of binary variables with an exact linearization (related to the convex hull of those constraints). This model additionally shows the benefits of learning between stages while remaining consistent with the single congressional appropriations framework.