The Community Safety Net and Prescription Drug Access for Low-Income, Uninsured People

Examines strategies adopted by hospitals and community health centers to maintain access to affordable brand name and generic prescription drugs. Based on site visits to twelve nationally representative communities

Moving research into practice: lessons from the US Agency for Healthcare Research and Quality's IDSRN program

BACKGROUND: The U.S. Agency for Healthcare Research and Quality's (AHRQ) Integrated Delivery Systems Research Network (IDSRN) program was established to foster public-private collaboration between health services researchers and health care delivery systems. Its broad goal was to link researchers and delivery systems to encourage implementation of research into practice. We evaluated the program to address two primary questions: 1) How successful was IDSRN in generating research findings that could be applied in practice? and 2) What factors facilitate or impede such success? METHODS: We conducted in-person and telephone interviews with AHRQ staff and nine IDSRN partner organizations and their collaborators, reviewed program documents, analyzed projects funded through the program, and developed case studies of four IDSRN projects judged promising in supporting research implementation. RESULTS: Participants reported that the IDSRN structure was valuable in creating closer ties between researchers and participating health systems. Of the 50 completed projects studied, 30 had an operational effect or use. Some kinds of projects were more successful than others in influencing operations. If certain conditions were met, a variety of partnership models successfully supported implementation. An internal champion was necessary for partnerships involving researchers based outside the delivery system. Case studies identified several factors important to success: responsiveness of project work to delivery system needs, ongoing funding to support multiple project phases, and development of applied products or tools that helped users see their operational relevance. Factors limiting success included limited project funding, competing demands on potential research users, and failure to reach the appropriate audience. CONCLUSION: Forging stronger partnerships between researchers and delivery systems has the potential to make research more relevant to users, but these benefits require clear goals and appropriate targeting of resources. Trade-offs are inevitable. The health services research community can best consider such trade-offs and set priorities if there is more dialogue to identify areas and approaches where such partnerships may have the most promise. Though it has unique features, the IDSRN experience is relevant to research implementation in diverse settings

Awareness in Practice: Tensions in Access to Sensitive Attribute Data for Antidiscrimination

Organizations cannot address demographic disparities that they cannot see. Recent research on machine learning and fairness has emphasized that awareness of sensitive attributes, such as race and sex, is critical to the development of interventions. However, on the ground, the existence of these data cannot be taken for granted. This paper uses the domains of employment, credit, and healthcare in the United States to surface conditions that have shaped the availability of sensitive attribute data. For each domain, we describe how and when private companies collect or infer sensitive attribute data for antidiscrimination purposes. An inconsistent story emerges: Some companies are required by law to collect sensitive attribute data, while others are prohibited from doing so. Still others, in the absence of legal mandates, have determined that collection and imputation of these data are appropriate to address disparities. This story has important implications for fairness research and its future applications. If companies that mediate access to life opportunities are unable or hesitant to collect or infer sensitive attribute data, then proposed techniques to detect and mitigate bias in machine learning models might never be implemented outside the lab. We conclude that today's legal requirements and corporate practices, while highly inconsistent across domains, offer lessons for how to approach the collection and inference of sensitive data in appropriate circumstances. We urge stakeholders, including machine learning practitioners, to actively help chart a path forward that takes both policy goals and technical needs into account

Consumer behavior and health insurance among two populations: Elderly Medicare beneficiaries and low -income parents.

The first study of this dissertation examines the determinants of Medicare supplemental coverage choice, focusing on the relationship between Medigap premiums and supplemental coverage decisions of elderly Medicare beneficiaries across geographic markets. Using data from the Community Tracking Study (1998--99) combined with Medigap premium data, multinomial logit results suggest that Medigap premiums have a positive and highly statistically significant effect on Medicare HMO participation. Medigap premiums also have a marginally significant and positive effect on Medicaid participation, but do not drive individuals from supplemental coverage altogether. Implied elasticity estimates indicate that Medigap premiums have a much larger effect on the likelihood of Medicare HMO participation (cross-price elasticity around 1) than do Medicare HMO premiums. The results reveal how Medigap premiums influence coverage decisions and highlight important connections between Medicare supplemental alternatives. The second study develops a conceptual framework for and describes existing literature on pent-up demand for medical care. If previously uninsured individuals exhibit pent-up demand after obtaining coverage, program expansions and reform efforts could face large start-up costs. I present a conceptual framework that identifies several types of pent-up demand and suggests how they might be measured empirically. Although much research has documented utilization differences between insured and uninsured persons, fewer studies have examined utilization patterns of newly enrolled individuals across time. Existing evidence for pent-up demand is mixed and few studies have tried to disentangle it from moral hazard and adverse selection. The third study presents an empirical analysis of pent-up demand, modeling utilization patterns of low-income parents who obtain coverage from a Medicaid HMO. Although the program represents a local initiative, it resembles efforts in some states to cover parents of publicly-insured children. Using self-reported utilization data from a telephone survey, results provide some evidence for pent-up demand for overall health care utilization in the first six months of enrollment, relative to the second six. However, intensity of use (i.e., number of visits) does not differ over this time. I also examine utilization before and after enrollment and find strong evidence for higher utilization after enrollment, both in terms of its likelihood as well as its intensity.Ph.D.Health and Environmental SciencesHealth care managementPublic healthUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/123720/2/3096216.pd