David L Veenstra, Jeanne Mandelblatt, Peter Neumann, Anirban Basu, Josh F Peterson, Scott D Ramsey
Precision medicine - individualizing care for patients and addressing variations in treatment response - is likely to be important in improving the nation's health in a cost-effective manner. Despite this promise, widespread use of precision medicine, specifically genomic markers, in clinical care has been limited in practice to date. Lack of evidence, clear evidence thresholds, and reimbursement have been cited as major barriers. Health economics frameworks and tools can elucidate the effects of legal, regulatory, and reimbursement policies on the use of precision medicine while guiding research investments to enhance the appropriate use of precision medicine. Despite the capacity of economics to enhance the clinical and human impact of precision medicine, application of health economics to precision medicine has been limited - in part because precision medicine is a relatively new field - but also because precision medicine is complex, both in terms of its applications and implications throughout medicine and the healthcare system. The goals of this review are several-fold: (1) provide an overview of precision medicine and key policy challenges for the field; (2) explain the potential utility of economics methods in addressing these challenges; (3) describe recent research activities; and (4) summarize opportunities for cross-disciplinary research.
{"title":"Health Economics Tools and Precision Medicine: Opportunities and Challenges.","authors":"David L Veenstra, Jeanne Mandelblatt, Peter Neumann, Anirban Basu, Josh F Peterson, Scott D Ramsey","doi":"10.1515/fhep-2019-0013","DOIUrl":"https://doi.org/10.1515/fhep-2019-0013","url":null,"abstract":"<p><p>Precision medicine - individualizing care for patients and addressing variations in treatment response - is likely to be important in improving the nation's health in a cost-effective manner. Despite this promise, widespread use of precision medicine, specifically genomic markers, in clinical care has been limited in practice to date. Lack of evidence, clear evidence thresholds, and reimbursement have been cited as major barriers. Health economics frameworks and tools can elucidate the effects of legal, regulatory, and reimbursement policies on the use of precision medicine while guiding research investments to enhance the appropriate use of precision medicine. Despite the capacity of economics to enhance the clinical and human impact of precision medicine, application of health economics to precision medicine has been limited - in part because precision medicine is a relatively new field - but also because precision medicine is complex, both in terms of its applications and implications throughout medicine and the healthcare system. The goals of this review are several-fold: (1) provide an overview of precision medicine and key policy challenges for the field; (2) explain the potential utility of economics methods in addressing these challenges; (3) describe recent research activities; and (4) summarize opportunities for cross-disciplinary research.</p>","PeriodicalId":38039,"journal":{"name":"Forum for Health Economics and Policy","volume":"23 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/fhep-2019-0013","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10839806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sophie Snyder, Christopher S Hollenbeak, Kamyar Kalantar-Zadeh, Matthew Gitlin, Akhtar Ashfaq
Background The optimal timing of treatment with vitamin D therapy for patients with chronic kidney disease (CKD), vitamin D insufficiency, and secondary hyperparathyroidism (SHPT) is a pressing question in nephrology with economic and patient outcome implications. Objective The objective of this study was to estimate the cost-effectiveness of earlier vitamin D treatment in CKD patients not on dialysis with vitamin D insufficiency and SHPT. Design A cost-effectiveness analysis based on a Markov model of CKD progression was developed from the Medicare perspective. The model follows a hypothetical cohort of 1000 Stage 3 or 4 CKD patients over a 5-year time horizon. The intervention was vitamin D therapy initiated in CKD stages 3 or 4 through CKD stage 5/end-stage renal disease (ESRD) versus initiation in CKD stage 5/ESRD only. The outcomes of interest were cardiovascular (CV) events averted, fractures averted, time in CKD stage 5/ESRD, mortality, quality-adjusted life years (QALYs), and costs associated with clinical events and CKD stage. Results Vitamin D treatment in CKD stages 3 and 4 was a dominant strategy when compared to waiting to treat until CKD stage 5/ESRD. Total cost savings associated with treatment during CKD stages 3 and 4, compared to waiting until CKD stage 5/ESRD, was estimated to be $19.9 million. The model estimated that early treatment results in 159 averted CV events, 5 averted fractures, 269 fewer patient-years in CKD stage 5, 41 fewer deaths, and 191 additional QALYs. Conclusions Initiating vitamin D therapy in CKD stages 3 or 4 appears to be cost-effective, largely driven by the annual costs of care by CKD stage, CV event costs, and risks of hypercalcemia. Further research demonstrating causal relationships between vitamin D therapy and patient outcomes is needed to inform decision making regarding vitamin D therapy timing.
{"title":"Cost-Effectiveness and Estimated Health Benefits of Treating Patients with Vitamin D in Pre-Dialysis.","authors":"Sophie Snyder, Christopher S Hollenbeak, Kamyar Kalantar-Zadeh, Matthew Gitlin, Akhtar Ashfaq","doi":"10.1515/fhep-2019-0020","DOIUrl":"https://doi.org/10.1515/fhep-2019-0020","url":null,"abstract":"<p><p>Background The optimal timing of treatment with vitamin D therapy for patients with chronic kidney disease (CKD), vitamin D insufficiency, and secondary hyperparathyroidism (SHPT) is a pressing question in nephrology with economic and patient outcome implications. Objective The objective of this study was to estimate the cost-effectiveness of earlier vitamin D treatment in CKD patients not on dialysis with vitamin D insufficiency and SHPT. Design A cost-effectiveness analysis based on a Markov model of CKD progression was developed from the Medicare perspective. The model follows a hypothetical cohort of 1000 Stage 3 or 4 CKD patients over a 5-year time horizon. The intervention was vitamin D therapy initiated in CKD stages 3 or 4 through CKD stage 5/end-stage renal disease (ESRD) versus initiation in CKD stage 5/ESRD only. The outcomes of interest were cardiovascular (CV) events averted, fractures averted, time in CKD stage 5/ESRD, mortality, quality-adjusted life years (QALYs), and costs associated with clinical events and CKD stage. Results Vitamin D treatment in CKD stages 3 and 4 was a dominant strategy when compared to waiting to treat until CKD stage 5/ESRD. Total cost savings associated with treatment during CKD stages 3 and 4, compared to waiting until CKD stage 5/ESRD, was estimated to be $19.9 million. The model estimated that early treatment results in 159 averted CV events, 5 averted fractures, 269 fewer patient-years in CKD stage 5, 41 fewer deaths, and 191 additional QALYs. Conclusions Initiating vitamin D therapy in CKD stages 3 or 4 appears to be cost-effective, largely driven by the annual costs of care by CKD stage, CV event costs, and risks of hypercalcemia. Further research demonstrating causal relationships between vitamin D therapy and patient outcomes is needed to inform decision making regarding vitamin D therapy timing.</p>","PeriodicalId":38039,"journal":{"name":"Forum for Health Economics and Policy","volume":"23 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/fhep-2019-0020","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10839809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The income gap between specialists and primary care physicians and among specialists is well established, but the drivers of this difference are not well delineated. Using the Community Tracking Study (CTS) Physician Survey, we sought to isolate and compare premiums paid to physicians for specialization and the proportion of time spent on offices visit rather than procedures. We divided medical subspecialties according the proportion of Medicare billing for Evaluation and Management (E&M) codes for the specialty as a whole. We report substantial differences in income across physician specialty, and over 70 percent of the difference in income remained controlling for factors that may confound the relationship between income and specialty including gender, location and type of practice, and hours. We note a large variation in premiums for specialization: 11.3-46.8 percent above family medicine after controlling for confounders. Classifying medical subspecialties by E&M billing as procedural versus non-procedural specialties revealed clear income differences. Controlling for confounders, procedural medical specialties earned 37.5 percent more than family medicine, as compared with 15.3 percent for non-procedural medical specialties. This analysis suggests that differences in physician income and resulting incentives are a direct consequence of the payment structure itself, rather than compensation for additional years of training or a reflection of different underlying demographics.
{"title":"Billing Codes Determine Lower Physician Income for Primary Care and Non-Procedural Specialties.","authors":"Arielle L Langer, Miriam Laugesen","doi":"10.1515/fhep-2019-0009","DOIUrl":"https://doi.org/10.1515/fhep-2019-0009","url":null,"abstract":"<p><p>The income gap between specialists and primary care physicians and among specialists is well established, but the drivers of this difference are not well delineated. Using the Community Tracking Study (CTS) Physician Survey, we sought to isolate and compare premiums paid to physicians for specialization and the proportion of time spent on offices visit rather than procedures. We divided medical subspecialties according the proportion of Medicare billing for Evaluation and Management (E&M) codes for the specialty as a whole. We report substantial differences in income across physician specialty, and over 70 percent of the difference in income remained controlling for factors that may confound the relationship between income and specialty including gender, location and type of practice, and hours. We note a large variation in premiums for specialization: 11.3-46.8 percent above family medicine after controlling for confounders. Classifying medical subspecialties by E&M billing as procedural versus non-procedural specialties revealed clear income differences. Controlling for confounders, procedural medical specialties earned 37.5 percent more than family medicine, as compared with 15.3 percent for non-procedural medical specialties. This analysis suggests that differences in physician income and resulting incentives are a direct consequence of the payment structure itself, rather than compensation for additional years of training or a reflection of different underlying demographics.</p>","PeriodicalId":38039,"journal":{"name":"Forum for Health Economics and Policy","volume":"22 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/fhep-2019-0009","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37457357","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Growing evidence suggests that medical marijuana laws have harm reduction effects across a variety of outcomes related to risky health behaviors. This study investigates the impact of medical marijuana laws on self-reported health using data from the Behavioral Risk Factor Surveillance System from 1993 to 2013. In our analyses we separately identify the effect of a medical marijuana law and the impact of subsequent active and legally protected dispensaries. Our main results show surprisingly limited improvements in self-reported health after the legalization of medical marijuana and legally protected dispensaries. Subsample analyses reveal strong improvements in health among non-white individuals, those reporting chronic pain, and those with a high school degree, driven predominately by whether or not the state had active and legally protected dispensaries. We also complement the analysis by evaluating the impact on risky health behaviors and find that the aforementioned demographic groups experience large reductions in alcohol consumption after the implementation of a medical marijuana law.
{"title":"The Impact of Medical Marijuana Laws and Dispensaries on Self-Reported Health","authors":"E. Andreyeva, Benjamin Ukert","doi":"10.1515/fhep-2019-0002","DOIUrl":"https://doi.org/10.1515/fhep-2019-0002","url":null,"abstract":"Abstract Growing evidence suggests that medical marijuana laws have harm reduction effects across a variety of outcomes related to risky health behaviors. This study investigates the impact of medical marijuana laws on self-reported health using data from the Behavioral Risk Factor Surveillance System from 1993 to 2013. In our analyses we separately identify the effect of a medical marijuana law and the impact of subsequent active and legally protected dispensaries. Our main results show surprisingly limited improvements in self-reported health after the legalization of medical marijuana and legally protected dispensaries. Subsample analyses reveal strong improvements in health among non-white individuals, those reporting chronic pain, and those with a high school degree, driven predominately by whether or not the state had active and legally protected dispensaries. We also complement the analysis by evaluating the impact on risky health behaviors and find that the aforementioned demographic groups experience large reductions in alcohol consumption after the implementation of a medical marijuana law.","PeriodicalId":38039,"journal":{"name":"Forum for Health Economics and Policy","volume":"40 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90708268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract It is widely believed that Medicaid reimbursement for primary care is too low and that these low fees adversely affect access to healthcare for Medicaid recipients. In this article, we exploit changes in Medicaid physician fees for primary care to study the response of primary care visits and services that are complements/substitutes with primary care, including emergency department, hospitalization, prescription drugs, and imaging. Results from our study indicate that higher Medicaid fees for primary care have modest effects. Among non-blind and non-disabled adults, we find that a 25% (or $10) increase in Medicaid fees for primary care is associated with approximately a 5% of a standard deviation increase in the number of primary care visits. For the same group, we also find that the fee increase is associated with an increase in the probability of having any primary care visits of approximately 3 percentage points. For children, changes in Medicaid fees are not significantly related to the number of primary care visits. In terms of other types of care, we find some evidence that Medicaid fees for primary care are associated with prescription drug use, and no evidence that primary care fees are associated with the use of emergency department, inpatient services, or imaging. Overall, our evidence provides, at best, limited support for the large effects of Medicaid fees on service provision sometimes asserted in policy discussions.
{"title":"Is Primary Care A Substitute or Complement for Other Medical Care? Evidence from Medicaid","authors":"Jiajia Chen, Eunkyung van den Berghe, R. Kaestner","doi":"10.1515/fhep-2018-0032","DOIUrl":"https://doi.org/10.1515/fhep-2018-0032","url":null,"abstract":"Abstract It is widely believed that Medicaid reimbursement for primary care is too low and that these low fees adversely affect access to healthcare for Medicaid recipients. In this article, we exploit changes in Medicaid physician fees for primary care to study the response of primary care visits and services that are complements/substitutes with primary care, including emergency department, hospitalization, prescription drugs, and imaging. Results from our study indicate that higher Medicaid fees for primary care have modest effects. Among non-blind and non-disabled adults, we find that a 25% (or $10) increase in Medicaid fees for primary care is associated with approximately a 5% of a standard deviation increase in the number of primary care visits. For the same group, we also find that the fee increase is associated with an increase in the probability of having any primary care visits of approximately 3 percentage points. For children, changes in Medicaid fees are not significantly related to the number of primary care visits. In terms of other types of care, we find some evidence that Medicaid fees for primary care are associated with prescription drug use, and no evidence that primary care fees are associated with the use of emergency department, inpatient services, or imaging. Overall, our evidence provides, at best, limited support for the large effects of Medicaid fees on service provision sometimes asserted in policy discussions.","PeriodicalId":38039,"journal":{"name":"Forum for Health Economics and Policy","volume":"19 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84859321","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Consumers are uncertain about their preferences for innovative product attributes until the first trial. They search for information as a means of reducing uncertainty and improving the likelihood that they will be satisfied with their purchase. One way to receive information is through peer networks. As a peer network is often a priori unknown, we conduct an experiment to solicit self-reported peer nominations. We compare two mechanisms through which peer networks operate: Strength of social ties and perceived peer expertise, to draw inferences regarding consumers’ preference reversal after exposure to peer recommendations. Our results indicate that perceived source expertise influences preferences while the closeness of social relationships has no statistically significant impact.
{"title":"Modeling Product Choices in a Peer Network","authors":"D. Fang, T. Richards, Carola Grebitus","doi":"10.1515/fhep-2018-0007","DOIUrl":"https://doi.org/10.1515/fhep-2018-0007","url":null,"abstract":"Abstract Consumers are uncertain about their preferences for innovative product attributes until the first trial. They search for information as a means of reducing uncertainty and improving the likelihood that they will be satisfied with their purchase. One way to receive information is through peer networks. As a peer network is often a priori unknown, we conduct an experiment to solicit self-reported peer nominations. We compare two mechanisms through which peer networks operate: Strength of social ties and perceived peer expertise, to draw inferences regarding consumers’ preference reversal after exposure to peer recommendations. Our results indicate that perceived source expertise influences preferences while the closeness of social relationships has no statistically significant impact.","PeriodicalId":38039,"journal":{"name":"Forum for Health Economics and Policy","volume":"8 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85372006","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
There are two types of prescription drug cost offsets. The first type of cost offset - from prescription drug use - is primarily about the effect of changes in drug quantity (e.g. due to changes in out-of-pocket drug costs) on other medical costs. Previous studies indicate that the cost offsets from prescription drug use may slightly exceed the cost of the drugs themselves. The second type of cost offset - the cost offset from prescription drug innovation - is primarily about the effect of prescription drug quality on other medical costs. Two previous studies (of a single disease or a single country) found that pharmaceutical innovation reduced hospitalization, and that the reduction in hospital cost from the use of newer drugs was considerably greater than the innovation-induced increase in pharmaceutical expenditure. In this study, we reexamine the impact that pharmaceutical innovation has had on hospitalization, employing a different type of 2-way fixed effects research design. In lieu of analyzing different countries over time for a single disease, or different diseases over time for a single country, we estimate the impact that new drug launches that occurred during the period 1982-2015 had on hospitalization in 2015 for 67 diseases in 15 OECD countries. Our models include both country fixed effects and disease fixed effects, which control for the average propensity of people to be hospitalized in each country and from each disease. The number of hospital discharges and days of care in 2015 is significantly inversely related to the number of drugs launched during 1982-2005, but not significantly related to the number of drugs launched after 2005. (Utilization of drugs during the first few years after they are launched is relatively low, and drugs for chronic conditions may have to be consumed for several years to achieve full effectiveness.) The estimates imply that, if no new drugs had been launched after 1981, total days of care in 2015 would have been 163% higher than it actually was. The estimated reduction in 2015 hospital expenditure that may be attributable to post-1981 drug launches was 5.3 times as large as 2015 expenditure on those drugs.
{"title":"The Impact of New Drug Launches on Hospitalization in 2015 for 67 Medical Conditions in 15 OECD Countries: A Two-Way Fixed-Effects Analysis.","authors":"Frank R Lichtenberg","doi":"10.1515/fhep-2018-0009","DOIUrl":"https://doi.org/10.1515/fhep-2018-0009","url":null,"abstract":"<p><p>There are two types of prescription drug cost offsets. The first type of cost offset - from prescription drug use - is primarily about the effect of changes in drug quantity (e.g. due to changes in out-of-pocket drug costs) on other medical costs. Previous studies indicate that the cost offsets from prescription drug use may slightly exceed the cost of the drugs themselves. The second type of cost offset - the cost offset from prescription drug innovation - is primarily about the effect of prescription drug quality on other medical costs. Two previous studies (of a single disease or a single country) found that pharmaceutical innovation reduced hospitalization, and that the reduction in hospital cost from the use of newer drugs was considerably greater than the innovation-induced increase in pharmaceutical expenditure. In this study, we reexamine the impact that pharmaceutical innovation has had on hospitalization, employing a different type of 2-way fixed effects research design. In lieu of analyzing different countries over time for a single disease, or different diseases over time for a single country, we estimate the impact that new drug launches that occurred during the period 1982-2015 had on hospitalization in 2015 for 67 diseases in 15 OECD countries. Our models include both country fixed effects and disease fixed effects, which control for the average propensity of people to be hospitalized in each country and from each disease. The number of hospital discharges and days of care in 2015 is significantly inversely related to the number of drugs launched during 1982-2005, but not significantly related to the number of drugs launched after 2005. (Utilization of drugs during the first few years after they are launched is relatively low, and drugs for chronic conditions may have to be consumed for several years to achieve full effectiveness.) The estimates imply that, if no new drugs had been launched after 1981, total days of care in 2015 would have been 163% higher than it actually was. The estimated reduction in 2015 hospital expenditure that may be attributable to post-1981 drug launches was 5.3 times as large as 2015 expenditure on those drugs.</p>","PeriodicalId":38039,"journal":{"name":"Forum for Health Economics and Policy","volume":"21 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/fhep-2018-0009","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37180345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper examines the impact of the New Rural Pension Scheme (NRPS) in China. Exploiting the staggered implementation of an NRPS policy expansion that began in 2009, we use a difference-in-difference approach to study the effects of the introduction of pension benefits on the health status, health behaviors, and healthcare utilization of rural Chinese adults age 60 and above. The results point to three main conclusions. First, in addition to improvements in self-reported health, older adults with access to the pension program experienced significant improvements in several important measures of health, including mobility, self-care, usual activities, and vision. Second, regarding the functional domains of mobility and self-care, we found that the females in the study group led in improvements over their male counterparts. Third, in our search for the mechanisms that drive positive retirement program results, we find evidence that changes in individual health behaviors, such as a reduction in drinking and smoking, and improved sleep habits, play an important role. Our findings point to the potential benefits of retirement programs resulting from social spillover effects. In addition, these programs may lessen the morbidity burden among the retired population.
{"title":"Short-Run Health Consequences of Retirement and Pension Benefits: Evidence from China.","authors":"Plamen Nikolov, Alan Adelman","doi":"10.1515/fhep-2017-0031","DOIUrl":"https://doi.org/10.1515/fhep-2017-0031","url":null,"abstract":"<p><p>This paper examines the impact of the New Rural Pension Scheme (NRPS) in China. Exploiting the staggered implementation of an NRPS policy expansion that began in 2009, we use a difference-in-difference approach to study the effects of the introduction of pension benefits on the health status, health behaviors, and healthcare utilization of rural Chinese adults age 60 and above. The results point to three main conclusions. First, in addition to improvements in self-reported health, older adults with access to the pension program experienced significant improvements in several important measures of health, including mobility, self-care, usual activities, and vision. Second, regarding the functional domains of mobility and self-care, we found that the females in the study group led in improvements over their male counterparts. Third, in our search for the mechanisms that drive positive retirement program results, we find evidence that changes in individual health behaviors, such as a reduction in drinking and smoking, and improved sleep habits, play an important role. Our findings point to the potential benefits of retirement programs resulting from social spillover effects. In addition, these programs may lessen the morbidity burden among the retired population.</p>","PeriodicalId":38039,"journal":{"name":"Forum for Health Economics and Policy","volume":"21 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/fhep-2017-0031","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37135471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper investigates the impact of the Affordable Care Act's (ACA's) dependent coverage mandate on health insurance coverage rates and health care utilization among young adults. Using data from the Medical Panel Expenditure Survey, I exploit the discontinuity in health insurance coverage rates at age 26, the new dependent coverage age cutoff enforced by the ACA. Under alternative regression discontinuity design models, I find that 2.5 to 5.3 percent of young adults lose their health insurance coverage once they turn 26. This effect is mainly driven by those who lose their private health insurance plan coverage and those who lose their health insurance plan coverage, whose main holder resides outside of the household. I also find that the discrete change in health insurance coverage rates at age 26 is associated with up to a 3.6 percentage point decrease in office-based physician and and up to a 2.1 percentage point decrease in dental visits, but does not have a significant impact on the utilization of outpatient or emergency department services. Furthermore, the effects of the ACA's dependent coverage mandate on health care spending and out-of-pocket costs are insignificant. These results are robust under alternative model specifications.
{"title":"Health insurance coverage and health care utilization: Evidence from the Affordable Care Act's dependent coverage mandate.","authors":"Barış K Yörük","doi":"10.1515/fhep-2017-0032","DOIUrl":"https://doi.org/10.1515/fhep-2017-0032","url":null,"abstract":"<p><p>This paper investigates the impact of the Affordable Care Act's (ACA's) dependent coverage mandate on health insurance coverage rates and health care utilization among young adults. Using data from the Medical Panel Expenditure Survey, I exploit the discontinuity in health insurance coverage rates at age 26, the new dependent coverage age cutoff enforced by the ACA. Under alternative regression discontinuity design models, I find that 2.5 to 5.3 percent of young adults lose their health insurance coverage once they turn 26. This effect is mainly driven by those who lose their private health insurance plan coverage and those who lose their health insurance plan coverage, whose main holder resides outside of the household. I also find that the discrete change in health insurance coverage rates at age 26 is associated with up to a 3.6 percentage point decrease in office-based physician and and up to a 2.1 percentage point decrease in dental visits, but does not have a significant impact on the utilization of outpatient or emergency department services. Furthermore, the effects of the ACA's dependent coverage mandate on health care spending and out-of-pocket costs are insignificant. These results are robust under alternative model specifications.</p>","PeriodicalId":38039,"journal":{"name":"Forum for Health Economics and Policy","volume":"21 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/fhep-2017-0032","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37120071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Priyanka Anand, Jody Schimmel Hyde, Maggie Colby, Paul O'Leary
In this paper, we estimate the impact of Medicaid expansions via the Patient Protection and Affordable Care Act (ACA) on applications to federal disability programs in 14 states that expanded Medicaid in January 2014. We use a difference-in-differences regression model to compare disability application rates in geographic areas within states that expanded Medicaid to rates in areas of non-expansion states that were carefully selected using a matching approach that accounts for state Medicaid policies pre-ACA as well as demographic and socioeconomic characteristics that might influence disability application rates. We find a slower decrease in Supplemental Security Income (SSI) application rates after Medicaid expansions in expansion states relative to non-expansion states, with application rates declining in both state groups from 2014 through 2016. Our analysis of the impact of the Medicaid expansions on Social Security Disability Insurance (SSDI) application rates was inconclusive for reasons we discuss in the paper.
{"title":"The Impact of Affordable Care Act Medicaid Expansions on Applications to Federal Disability Programs.","authors":"Priyanka Anand, Jody Schimmel Hyde, Maggie Colby, Paul O'Leary","doi":"10.1515/fhep-2018-0001","DOIUrl":"https://doi.org/10.1515/fhep-2018-0001","url":null,"abstract":"<p><p>In this paper, we estimate the impact of Medicaid expansions via the Patient Protection and Affordable Care Act (ACA) on applications to federal disability programs in 14 states that expanded Medicaid in January 2014. We use a difference-in-differences regression model to compare disability application rates in geographic areas within states that expanded Medicaid to rates in areas of non-expansion states that were carefully selected using a matching approach that accounts for state Medicaid policies pre-ACA as well as demographic and socioeconomic characteristics that might influence disability application rates. We find a slower decrease in Supplemental Security Income (SSI) application rates after Medicaid expansions in expansion states relative to non-expansion states, with application rates declining in both state groups from 2014 through 2016. Our analysis of the impact of the Medicaid expansions on Social Security Disability Insurance (SSDI) application rates was inconclusive for reasons we discuss in the paper.</p>","PeriodicalId":38039,"journal":{"name":"Forum for Health Economics and Policy","volume":"21 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/fhep-2018-0001","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37167070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}