The Experts below are selected from a list of 50736 Experts worldwide ranked by ideXlab platform
William B Vogt - One of the best experts on this subject based on the ideXlab platform.
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are invisible hands good hands moral hazard competition and the second best in Health Care Markets
Journal of Political Economy, 2000Co-Authors: Martin Gaynor, Deborah Haaswilson, William B VogtAbstract:The nature and normative properties of competition in Health Care Markets have long been the subject of much debate. In this paper we consider what the optimal benchmark is in the presence of moral hazard effects on consumption due to Health insurance. Intuitively, it seems that imperfect competition in the Health Care Market may constrain this moral hazard by increasing prices. We show that this intuition cannot be correct if insurance Markets are competitive. A competitive insurance Market will always produce a contract that leaves consumers at least as well off under lower prices as under higher prices.
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are invisible hands good hands moral hazard competition and the second best in Health Care Markets
Research Papers in Economics, 1998Co-Authors: Martin Gaynor, Deborah Haaswilson, William B VogtAbstract:The nature, and normative properties, of competition in Health Care Markets has long been the subject of much debate. In particular, policymakers have exhibited a great deal of reservation toward competition in Health Care Markets, as demonstrated by the plethora of regulations governing the Health Care sector. Currently, as consolidation rapidly occurs in Health Care Markets, concern about reduced competition has arisen. This concern, however, cannot be properly evaluated without a normative standard. In this paper we consider what the optimal benchmark is in the presence of moral hazard effects on consumption due to Health insurance. Moral hazard is widely recognized as one of the most important distortions in Health Care Markets. Moral hazard due to Health insurance leads to excess consumption, therefore it is not obvious that competition is second best optimal given this distortion. Intuitively, it seems that imperfect competition in the Health Care Market may constrain this moral hazard by increasing prices. We show that this intuition cannot be correct if insurance Markets are competitive. A competitive insurance Market will always produce a contract that leaves consumers at least as well off under lower prices as under higher prices. Thus, imperfect competition in Health Care Markets can not have efficiency enhancing effects if the only distortion is due to moral hazard.
Martin Gaynor - One of the best experts on this subject based on the ideXlab platform.
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are invisible hands good hands moral hazard competition and the second best in Health Care Markets
Journal of Political Economy, 2000Co-Authors: Martin Gaynor, Deborah Haaswilson, William B VogtAbstract:The nature and normative properties of competition in Health Care Markets have long been the subject of much debate. In this paper we consider what the optimal benchmark is in the presence of moral hazard effects on consumption due to Health insurance. Intuitively, it seems that imperfect competition in the Health Care Market may constrain this moral hazard by increasing prices. We show that this intuition cannot be correct if insurance Markets are competitive. A competitive insurance Market will always produce a contract that leaves consumers at least as well off under lower prices as under higher prices.
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are invisible hands good hands moral hazard competition and the second best in Health Care Markets
Research Papers in Economics, 1998Co-Authors: Martin Gaynor, Deborah Haaswilson, William B VogtAbstract:The nature, and normative properties, of competition in Health Care Markets has long been the subject of much debate. In particular, policymakers have exhibited a great deal of reservation toward competition in Health Care Markets, as demonstrated by the plethora of regulations governing the Health Care sector. Currently, as consolidation rapidly occurs in Health Care Markets, concern about reduced competition has arisen. This concern, however, cannot be properly evaluated without a normative standard. In this paper we consider what the optimal benchmark is in the presence of moral hazard effects on consumption due to Health insurance. Moral hazard is widely recognized as one of the most important distortions in Health Care Markets. Moral hazard due to Health insurance leads to excess consumption, therefore it is not obvious that competition is second best optimal given this distortion. Intuitively, it seems that imperfect competition in the Health Care Market may constrain this moral hazard by increasing prices. We show that this intuition cannot be correct if insurance Markets are competitive. A competitive insurance Market will always produce a contract that leaves consumers at least as well off under lower prices as under higher prices. Thus, imperfect competition in Health Care Markets can not have efficiency enhancing effects if the only distortion is due to moral hazard.
Deborah Haaswilson - One of the best experts on this subject based on the ideXlab platform.
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are invisible hands good hands moral hazard competition and the second best in Health Care Markets
Journal of Political Economy, 2000Co-Authors: Martin Gaynor, Deborah Haaswilson, William B VogtAbstract:The nature and normative properties of competition in Health Care Markets have long been the subject of much debate. In this paper we consider what the optimal benchmark is in the presence of moral hazard effects on consumption due to Health insurance. Intuitively, it seems that imperfect competition in the Health Care Market may constrain this moral hazard by increasing prices. We show that this intuition cannot be correct if insurance Markets are competitive. A competitive insurance Market will always produce a contract that leaves consumers at least as well off under lower prices as under higher prices.
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are invisible hands good hands moral hazard competition and the second best in Health Care Markets
Research Papers in Economics, 1998Co-Authors: Martin Gaynor, Deborah Haaswilson, William B VogtAbstract:The nature, and normative properties, of competition in Health Care Markets has long been the subject of much debate. In particular, policymakers have exhibited a great deal of reservation toward competition in Health Care Markets, as demonstrated by the plethora of regulations governing the Health Care sector. Currently, as consolidation rapidly occurs in Health Care Markets, concern about reduced competition has arisen. This concern, however, cannot be properly evaluated without a normative standard. In this paper we consider what the optimal benchmark is in the presence of moral hazard effects on consumption due to Health insurance. Moral hazard is widely recognized as one of the most important distortions in Health Care Markets. Moral hazard due to Health insurance leads to excess consumption, therefore it is not obvious that competition is second best optimal given this distortion. Intuitively, it seems that imperfect competition in the Health Care Market may constrain this moral hazard by increasing prices. We show that this intuition cannot be correct if insurance Markets are competitive. A competitive insurance Market will always produce a contract that leaves consumers at least as well off under lower prices as under higher prices. Thus, imperfect competition in Health Care Markets can not have efficiency enhancing effects if the only distortion is due to moral hazard.
Carole Roan Gresenz - One of the best experts on this subject based on the ideXlab platform.
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opportunities and challenges in supply side simulation physician based models
Health Services Research, 2013Co-Authors: Carole Roan Gresenz, David I Auerbach, Fabian DuarteAbstract:Microsimulation modeling is one tool in the arsenal available to policy makers for understanding the effects of potential policy changes. Such models have been used for decades in a variety of contexts, such as understanding the effects of tax rate changes (e.g., the TAXSIM model) and income support programs (e.g., the TRIM2 model). A distinguishing feature of microsimulation models is that the objects of the simulation are individual units—as opposed to aggregations of units—and their advantages include that they allow for examination of distributional effects of a policy change or other exogenous event and for understanding the effects of multiple, interacting policy changes (Chollet 1990; Giannarelli 1992; Mitton 2000). Recent years have witnessed the development and increased use of a number of microsimulation models designed to understand the effect of Health Care reform efforts, including the RAND COMPARE (Comprehensive Assessment of Reform Efforts) model, CBO's Health Insurance Simulation Model (HISim), and the Urban Institute's Health Insurance Reform Simulation Model (HIRSM), among others. These modeling efforts have largely been focused on understanding consumer demand for Health insurance coverage and Health Care under a range of policy scenarios, along with the associated costs of policies in terms of government and societal spending. But simulation modeling efforts aimed at understanding the supply-side effects of Health policies have been few and ad hoc—despite the fact that the Patient Protection and Affordable Care Act (ACA) includes a wide range of supply-oriented policy changes, and supply-side effects of major Health reforms have the potential to dwarf demand-side effects under some circumstances (Stewart and Enterline 1961; Enterline, McDonald, and McDonald 1973; Finkelstein 2007). One factor underlying the relative paucity of supply side models is a lack of good data. As Citro (1991)emphasize: Good data are a critical ingredient for models and other analysis tools to produce good estimates. Data that are of poor quality, scope and relevance will increase the uncertainty and decrease the validity of model outputs. Poor data also make it harder for models to respond to changing policy analysis needs in a timely and cost-effective manner. Chollet (1990) notes further that: Much of the effort involved in building and maintaining microsimulation models relates to enhancing and imputing the input data necessary to support even relatively simple analysis. There are many supply-side entities in Health Care that may be useful to analyze in the context of a microsimulation model—including insurance companies, Health plans, hospitals, urgent Care centers, retail clinics, community Health centers, physicians, nurse practitioners, psychologists, social workers, and others— to gauge the potential effects of the ACA. In this article, we focus for tractability on one key such entity in the Health Care Market: physicians. The adequacy of the current supply of physicians to accommodate what is expected to be an increase in the number of insured individuals of nearly 30 million after full ACA implementation (Eibner and Price 2012) has been of particular concern (AcademyHealth 2012). We provide a framework for understanding the types of data required for supply-side microsimulation modeling, identify key data sources available to fulfill these needs in the context of a physician model, and assess and compare the strengths and limitations of data from various sources.
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dimensions of the local Health Care environment and use of Care by uninsured children in rural and urban areas
Pediatrics, 2006Co-Authors: Carole Roan Gresenz, Jeannette Rogowski, Jose J EscarceAbstract:OBJECTIVE.Despite concerted policy efforts, a sizeable percentage of children lack Health insurance coverage. This article examines the impact of the Health Care safety net and Health Care Market structure on the use of Health Care by uninsured children. METHODS.We used the Medical Expenditure Panel Survey linked with data from multiple sources to analyze Health Care utilization among uninsured children. We ran analyses separately for children who lived in rural and urban areas and assessed the effects on utilization of the availability of safety net providers, safety net funding, supply of primary Care physicians, Health maintenance organization penetration, and the percentage of people who are uninsured, controlling for other factors that influence use. RESULTS.Fewer than half of uninsured children had office-based visits to Health Care providers during the year, 8% of rural and 10% of urban children visited the emergency department at least once, and just over half of children had medical expenditures or charges during the year. Among uninsured children in rural areas, living closer to a safety net provider and living in an area with a higher supply of primary Care physicians were positively associated with higher use and medical expenditures. In urban areas, the supply of primary Care physicians and the level of safety net funding were positively associated with uninsured children’s medical expenditures, whereas the percentage of the population that was uninsured was negatively associated with use of the emergency department. CONCLUSIONS.Uninsured children had low levels of utilization over a range of different Health Care provider types and settings. The availability of safety net providers in the local area and the safety net’s capacity to serve the uninsured influence access to Care among children. Possible measures for ensuring access to Health Care among uninsured children include increasing the density of safety net providers in rural areas, enhancing funding for the safety net, and policies to increase primary Care physician supply.
David C Grabowski - One of the best experts on this subject based on the ideXlab platform.
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secret shopper data on private prices in the nursing home industry from 2008 to 2010
Medical Care Research and Review, 2021Co-Authors: Lacey Loomer, Fangli Geng, Ashvin Gandhi, David C GrabowskiAbstract:Nationwide nursing home private-pay prices at the facility-level have not been available for researchers interested in studying this unique Health Care Market. This study presents a new data source, Caregiverlist, for private-pay prices for private and semiprivate rooms for 12,000 nursing homes nationwide collected between 2008 and 2010. We link these data to publicly available national nursing home-level data sets to examine the relationship between price and nursing home characteristics. We also compare private-pay prices with average private-pay revenues per day for California nursing homes obtained from facilities' financial filings. On average, private-pay prices were $224 per day for private rooms compared with $197 per day for semiprivate rooms. We find that nursing homes that are nonprofit, urban, hospital-based, have a special Care unit, chain-owned, and have higher quality ratings have higher prices. We find average revenues per day in California to be moderately correlated with prices reported by Caregiverlist.
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evolution of the home Health Care Market the expansion and quality performance of multi agency chains
Health Services Research, 2020Co-Authors: Fangli Geng, Sarah Mansouri, David G Stevenson, David C GrabowskiAbstract:OBJECTIVE To examine the growth and evolution of the home Health agency (HHA) Market and to compare quality performance across HHA ownership categories. DATA SOURCE Agency characteristics were extracted from MediCare cost reports and Provider of Services file. Quality of Care and patient characteristics were extracted from Quality of Patient Care Star Ratings and HHA Public Use File. STUDY DESIGN Agency- and state-level analyses were conducted to describe HHA Market trends. Patient characteristics and quality measures were compared across ownership categories of interest. DATA COLLECTION/EXTRACTION METHODS All MediCare-certified HHAs in operation, 2005-2018. PRINCIPAL FINDINGS Over the study period, the HHA sector grew substantially, increasing from 7899 to 10 818 agencies, and chain-owned HHAs doubled in number from 903 (11.4% of all agencies) to 1841 (17.0%). In 2018, across agency types, for-profit nonchain agencies were the largest category both in the number of agencies (67.8%) and the number of MediCare enrollees served (40.7%). Additionally, for-profit nonchain agencies grew most in total number, from 4293 (54.3%) to 7337 (67.8%), while for-profit chain agencies grew most in the number of MediCare enrollees served, from 439 998 (12.9%) to 1 082 385 (28.3%). Regarding patient composition, for-profit nonchain agencies served the highest proportion of dual eligible beneficiaries (42.2%) and African-Americans (27.9%) among all agency types. Regarding quality performance, a higher star rating is significantly (P < .01) associated with chain agency status. Moreover, chain HHAs performed better on self-reported process measures, and risk-adjusted self-reported outcome measures; however, they performed worse on risk-adjusted claims-based outcome measures. These results were similar across for-profit and nonprofit chain agencies. CONCLUSION Chains play a growing role in the home Health sector. Substantial differences in geographic distribution, patient composition, and quality performance were observed between chain- and nonchain HHAs. Examining the growth and performance of multi-agency chains can help inform quality reporting and monitoring, assess payment adequacy, and facilitate greater transparency and accountability within the HHA Marketplace.
