Showing papers by "José J. Escarce published in 2011"

Medicare’s Bundled Payment Pilot For Acute And Postacute Care: Analysis And Recommendations On Where To Begin

Abstract: In the National Pilot Program on Payment Bundling, a subset of Medicare providers will receive a single payment for an episode of acute care in a hospital, followed by postacute care in a skilled nursing or rehabilitation facility, the patient’s home, or other appropriate setting. This article examines the promises and pitfalls of bundled payments and addresses two important design decisions for the pilot: which conditions to include, and how long an episode should be. Our analysis of Medicare data found that hip fracture and joint replacement are good conditions to include in the pilot because they exhibit strong potential for cost savings. In addition, these conditions pose less financial risk for providers than other common ones do, so including them would make participation in the program more appealing to providers. We also found that longer episode lengths captured a higher percentage of costs and hospital readmissions while adding little financial risk. We recommend that the Medicare pilot program ...

Neighborhood Disadvantage and Ischemic Stroke The Cardiovascular Health Study (CHS)

Abstract: Background and Purpose—Neighborhood characteristics may influence the risk of stroke and contribute to socioeconomic disparities in stroke incidence. The objectives of this study were to examine the relationship between neighborhood socioeconomic status and incident ischemic stroke and examine potential mediators of these associations. Methods—We analyzed data from 3834 whites and 785 blacks enrolled in the Cardiovascular Health Study, a multicenter, population-based, longitudinal study of adults ages ≥65 years from 4 US counties. The primary outcome was adjudicated incident ischemic stroke. Neighborhood socioeconomic status was measured using a composite of 6 census tract variables. Race-stratified multilevel Cox proportional hazard models were constructed adjusted for sociodemographic, behavioral, and biological risk factors. Results—Among whites, in models adjusted for sociodemographic characteristics, stroke hazard was significantly higher among residents of neighborhoods in the lowest compared with t...

English Language Proficiency and Geographical Proximity to a Safety Net Clinic as a Predictor of Health Care Access

Abstract: Studies suggest that proximity to a safety net clinic (SNC) promotes access to care among the uninsured. Distance-based barriers to care may be greater for people with limited English proficiency (LEP), compared to those who are English proficient (EP), but this has not been explored. We assessed the relationship between distance to the nearest SNC and access in non-rural uninsured adults in California, and examined whether this relationship differs by language proficiency. Using the 2005 California Health Interview Survey and a list we compiled of California's SNCs, we calculated distance between uninsured interviewee residence and the exact address of the nearest SNC. Using multivariate regression to adjust for other relevant characteristics, we examined associations between this distance and interviewee's probability of having a usual source of health care (USOC) and having visited a physician in the prior 12 months. To examine differences by language proficiency, we included interactions between distance and language proficiency. Uninsured LEP adults living within 2 miles of a SNC were 9.3% less likely than their EP counterparts to have a USOC (P = 0.046). Further, distance to the nearest SNC was inversely associated with the probability of having a USOC among LEP, but not among EP; consequently, the difference between LEP and EP in the probability of having a USOC widened with increasing distance to the nearest SNC. There was no difference between LEP and EP adults living within 2 miles of a SNC in likelihood of having a physician visit; however, as with USOC, distance to the nearest SNC was inversely associated with the probability of having a physician visit among LEP but not EP. The effect sizes diminished, but remained significant, when we included county fixed effects in the models. Having LEP is a barrier to health care access, which compounds when combined with increased distance to the nearest SNC, among uninsured adults. Future studies should explore potential mechanisms so that appropriate interventions can be implemented.

Racial/ethnic differences in US health behaviors: a decomposition analysis.

Abstract: Objective—To quantify contributions of individual sociodemographic factors, neighborhood socioeconomic status (NSES) and unmeasured factors to racial/ethnic differences in health behaviors for Non-Hispanic (NH) Whites, NH Blacks, and Mexican-Americans. Methods—We used linear regression and Oaxaca decomposition analyses. Results—Although individual characteristics and NSES contributed to racial/ethnic differences in health behaviors, differences in responses individual characteristics and NSES also played a significant role. Conclusions—There are racial/ethnic differences in the way that individual-level determinants and NSES affect health behaviors. Understanding the mechanisms for differential responses could inform community interventions and public health campaigns that targeted to particular groups.

Risk of Cardiovascular Disease in First and Second Generation Mexican-Americans

Abstract: This study examines the cardiovascular disease (CVD) risk profiles of first generation (FG) and second generation (SG) Mexican-Americans (MA) in two large national studies––the Hispanic Health and Nutrition Examination Study (HHANES) (1982–1984) and the National Health and Examination Study (NHANES) (1999–2004). The main outcome measures were five individual risk indicators of CVD (total cholesterol, HDL cholesterol, hypertension, diabetes, and smoking) and a composite measure (the Framingham Risk Score [FRS]). The analyses included cross-survey (pseudocohort) and within-survey (cross-sectional) comparisons. In multivariate analyses, SG men had higher rates of hypertension and lower rates of smoking than FG men; and SG women had lower total cholesterol levels, higher rates of hypertension, and lower rates of smoking than FG women. There was no generational difference in the FRS in men or women. The cross-survey comparisons detected generational differences in CVD risk factors not detected in within-survey comparisons, particularly among MA women. Future studies of generational differences in risk should consider using pseudocohort comparisons when possible.

Collection Of Race And Ethnicity Data By Health Plans Has Grown Substantially, But Opportunities Remain To Expand Efforts

Abstract: In 2003 the Institute of Medicine called on health plans to collect data on their members’ race and ethnicity as a foundation for improving the quality of care and reducing disparities. We describe the progress made toward collecting these data, the most commonly used data collection methods, and the challenges plans have encountered. We found that from 2003 through 2008, the proportion of plans that collected members’ data on race and ethnicity doubled in the commercial market to 60 percent. It increased even more sharply to 94 percent and 83 percent, respectively, for plans covering Medicaid and Medicare Advantage enrollees. However, the scope of data collection varied greatly across plans, and data collection was an organizationwide initiative in a minority of plans. To fulfill the goals of recent legislation, including the Affordable Care Act, health plans will need to expand their efforts. Among other steps, plans and other key stakeholders should agree on uniform race and ethnicity categories, modif...

Neighborhood Environment and Health Status and Mortality Among Veterans

Abstract: BACKGROUND The VHA is the largest integrated US health system and is increasingly moving care into the communities where veterans reside. Veterans who utilize the VA for their care have worse health status than the general population. However, there is limited evidence about the association of neighborhood environment and health outcomes among veterans.

The Effect of Prospective Payment on Admission and Treatment Policy: Evidence from Inpatient Rehabilitation Facilities

Abstract: We examine provider responses to the Medicare inpatient rehabilitation facility (IRF) prospective payment system (PPS), which simultaneously reduced marginal reimbursement and increased average reimbursement. IRFs could respond to the PPS by changing the total number of patients admitted, admitting different types of patients, or changing the intensity of care for admitted patients. We use Medicare claims data to separately estimate each type of provider response to the PPS. We also examine changes in patient outcomes and spillover effects on other post acute care providers. We find that costs of care initially fell following the PPS implementation, which we attribute to changes in treatment decisions rather than the types of patients admitted to IRFs. However, the probability of admission to IRFs increased after the PPS due to the expanded admission policies of providers. We find modest spillover effects on skilled nursing home costs and no substantive impact on patient health outcomes.

Spillover effects of community uninsurance on working-age adults and seniors: an instrumental variables analysis.

Abstract: Background:Previous research suggests, but does not definitively establish, that a high level of uninsurance in a community may negatively affect access to and quality of health care for insured persons.Objective:To assess the effect of the level of uninsurance in a community on access to and satisf

Relative Affordability of Health Insurance Premiums under CHIP Expansion Programs and the ACA

Abstract: Affordability is integral to the success of health care reforms aimed at ensuring universal access to health insurance coverage, and affordability determina- tions have major policy and practical consequences. This article describes factors that influenced the determination of affordability benchmarks and premium- contribution requirements for Children's Health Insurance Program (CHIP) expansions in three states that sought to universalize access to coverage for youth. It also compares subsidy levels developed in these states to the premium subsidy schedule under the Afford- able Care Act (ACA) for health insurance plans purchased through an exchange. We find sizeable variability in premium- contribution requirements as a percentage of family income across the three states and in the progressivity and regressivity of the premium- contribution schedules developed. These findings underscore the ambi - guity and subjectivity of affordability standards. Further, our analyses suggest that the future of CHIP beyond 2015 is likely to have significant implications for health insurance coverage costs incurred by families who currently rely at least in part on CHIP for coverage.

Collection of language data and services provided by health plans.

Abstract: Objectives Key stakeholders agree better data on patients' language are needed to effectively address language-related barriers to timely, highquality healthcare. Our objective was to describe health plan efforts to collect language data from its members, provide language services, and improve the provision of culturally and linguistically appropriate services (CLAS). Study design National surveys in 2003, 2006, and 2008. Methods Surveys were administered to health plans offering commercial, Medicaid, and/or Medicare Advantage products. Results 123 health plans responded to the 2008 survey (50% response rate), including 65 commercial (50%), 46 Medicaid (53%), and 12 Medicare plans (44%), representing a total enrollment of 133.8 million Americans. In 2008, 74.0% of health plans collected language data (commercial 60.0%, Medicaid 89.1%, Medicare 91.7%), which is an increase for each plan type since 2003. Health plans used direct and indirect collection methods. Nearly all health plans reported offering language services, the most common being telephonic interpreting, multilingual member materials, and access to bilingual providers. A variety of strategies for improving CLAS were cited by health plans, including improving health plan communication materials, health literacy initiatives for members, and targeted training for providers and staff. Conclusions Health plans have made substantial progress in the collection of language data and many are offering options for language services. With the rapid growth in Medicaid participation and newly insured individuals anticipated under the Affordable Care Act, health plans may be uniquely positioned to implement and test interventions that aim to improve appropriate utilization of language services by providers and patients.

Preventing Obesity and Its Consequences: Highlights of RAND Health Research

Abstract: Summarizes key RAND studies on the causes of obesity, its economic and health consequences, and potential strategies for prevention, including work on health care costs, junk food, food deserts, school meals, and proximity of parks.

Take-Up of Public Insurance and Crowd-out of Private Insurance Under Recent CHIP Expansions to Higher Income Children

Abstract: We analyze the effects of states' expansions of CHIP eligibility to children in higher income families during 2002-2009 on take-up of public coverage, crowd-out of private coverage, and rates of uninsurance Our results indicate these expansions were associated with limited uptake of public coverage and only a two percentage point reduction in the uninsurance rate among these children Because not all of the take-up of public insurance among eligible children is accounted for by children who transfer from being uninsured to having public insurance, our results suggest that there may be some crowd-out of private insurance coverage; the upper bound crowd-out rate we calculate is 46 percent

Introduction to Special Section: Causality in Health Services Research

Abstract: In 2002, the Agency for Healthcare Research and Quality (AHRQ) defined health services research as “research [that] examines how people get access to health care, how much care costs, and what happens to patients as a result of this care. The main goals of health services research are to identify the most effective ways to organize, manage, finance, and deliver high quality care; reduce medical errors; and improve patient safety” (http://www.academyhealth.org). AcademyHealth's (AH) definition is parallel but focuses more explicitly on the factors studied. Thus AH defines health services research as “the multidisciplinary field of scientific investigation that studies how social factors, financing systems, organizational structures and processes, health technologies, and personal behaviors affect access to health care, the quality and cost of health care, and ultimately our health and well-being. Its research domains are individuals, families, organizations, institutions, communities, and populations” (http://www.academyhealth.org). Explicit in both definitions is the notion that health services researchers should strive to identify and estimate the causal effects on outcomes of interest of alternative organizational structures, management approaches, financing systems, provider practices, and personal choices regarding lifestyle and behavior. Without a focus on causal effects, it would be impossible to identify the most effective ways to achieve the outcomes we seek through clinical, management, or policy interventions. Yet most health services researchers know from first-hand experience that identifying and estimating causal effects using observational data is extremely difficult, and that convincing others and even ourselves that we have successfully done so can be challenging. Most health services researchers—and certainly any who have worked in multidisciplinary teams—also know that even having conversations with research colleagues about causality can be trying, and that different disciplines have different perspectives on these questions. In general, social scientists—and especially economists and sociologists—are more open than statisticians and physician health services researchers to the possibility that causal effects can be identified and estimated using observational data. These attitudinal differences arise early, as they are based on the training that students and fellows in different disciplines receive. In this issue of Health Services Research (HSR), we are pleased to publish a special section that includes an original article and two commentaries addressing why approaches to questions of causality in health services research are discipline-specific, often with little overlap or agreement. The article, written by Bryan Dowd, Ph.D., and titled “Separated at Birth: Statisticians, Social Scientists and Causality in Health Services Research,” traces the historical roots of these discipline-based differences and some recent attempts to remedy the situation. In tracing the history, the article also highlights and underscores the assumptions that underlie efforts to estimate causal effects using observational data. The two excellent commentaries, by Judea Pearl, Ph.D., and James O'Malley, Ph.D., provide additional insights into both the history of the separation between social scientists and statisticians and the challenges inherent in causal inference. This special section of HSR, with its thoughtful discussion of the meaning of causality in the context of health services research and its implications for high-quality empirical work, is the first of an occasional series in HSR that will address cutting-edge methods in health services research and aim to help researchers improve the way they apply these methods in their research. We will describe and explain the intent and focus of this series in more detail in a future editorial, but for now we are pleased to present this inaugural special section on causality by three distinguished investigators: Bryan Dowd, Ph.D., is Mayo Professor in the Division of Health Policy and Management, School of Public Health, at the University of Minnesota. Dr. Dowd's research interests include Medicare policy, markets for health insurance and health care services, analysis of nonexperimental data, and application of econometric methods to health service research problems. He is the principal investigator for the Division's CMS Master Research and Demonstration contract and cochairs the Program in Human Rights and Health at the University of Minnesota. He currently serves as chair of the Methods Council of AH. His Ph.D. in public policy analysis is from the University of Pennsylvania. Judea Pearl, Ph.D., is professor of computer science and statistics at the University of California, Los Angeles (UCLA). Dr. Pearl directs the Cognitive Systems Laboratory at UCLA and conducts research in artificial intelligence, causal inference, and philosophy of science. He has authored three books: Heuristics (1984), Probabilistic Reasoning (1988), and Causality (2000). A member of the National Academy of Engineering, and a Founding Fellow the American Association for Artificial Intelligence, he received the London School of Economics Lakatos Award for 2001, the ACM Alan Newell Award for 2004, the Benjamin Franklin Medal for Computer and Cognitive Science from the Franklin Institute in 2008, and the David Rumelhart Prize from the Cognitive Science Society last year. He is a graduate of the Technion, Israel. James O'Malley, Ph.D., is associate professor of statistics in the Department of Health Care Policy, Harvard Medical School. Dr. O'Malley's methodological interests encompass Bayesian statistics, statistical inference for social networks, multivariate hierarchical models, and causal inference for both randomized and observational studies. His applied research interests include the relationship between health and social networks and the evaluation and estimation of quality of care. He was chair of the Health Policy Statistics Section of the American Statistical Association in 2008, and is cochair of the 2011 International Conference on Health Policy Statistics. He received his Ph.D. in statistics from the University of Canterbury, New Zealand.

Take-Up of Public Insurance and Crowd-out of Private Insurance Under Recent CHIP Expansions to Higher Income Children

Abstract: We analyze the effects of states' expansions of CHIP eligibility to children in higher income families during 2002-2009 on take-up of public coverage, crowd-out of private coverage, and rates of uninsurance. Our results indicate these expansions were associated with limited uptake of public coverage and only a two percentage point reduction in the uninsurance rate among these children. Because not all of the take-up of public insurance among eligible children is accounted for by children who transfer from being uninsured to having public insurance, our results suggest that there may be some crowd-out of private insurance coverage; the upper bound crowd-out rate we calculate is 46 percent.

The Effect of Prospective Payment on Admission and Treatment Policy: Evidence from Inpatient Rehabilitation Facilities

Abstract: We examine provider responses to the Medicare inpatient rehabilitation facility (IRF) prospective payment system (PPS), which simultaneously reduced marginal reimbursement and increased average reimbursement. IRFs could respond to the PPS by changing the total number of patients admitted, admitting different types of patients, or changing the intensity of care for admitted patients. We use Medicare claims data to separately estimate each type of provider response to the PPS. We also examine changes in patient outcomes and spillover effects on other post acute care providers. We find that costs of care initially fell following the PPS implementation, which we attribute to changes in treatment decisions rather than the types of patients admitted to IRFs. However, the probability of admission to IRFs increased after the PPS due to the expanded admission policies of providers. We find modest spillover effects on skilled nursing home costs and no substantive impact on patient health outcomes.

Take-Up of Public Insurance and Crowd-Out of Private Insurance Under Recent Chip Expansions to Higher Income Children

Abstract: We analyze the effects of states' expansions of CHIP eligibility to children in higher income families during 2002-2009 on take-up of public coverage, crowd-out of private coverage, and rates of uninsurance. Our results indicate these expansions were associated with limited uptake of public coverage and only a two percentage point reduction in the uninsurance rate among these children. Because not all of the take-up of public insurance among eligible children is accounted for by children who transfer from being uninsured to having public insurance, our results suggest that there may be some crowd-out of private insurance coverage; the upper bound crowd-out rate we calculate is 46 percent.