Forum for Health Economics and Policy最新文献

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.

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.

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.

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.

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.

Background Treatment options in oncology have increased in recent years due to the quick pace of innovation. In the cancer care landscape, therapies that enable patients to live to the next innovation have additional value, "option value," from the benefit of surviving to the next innovation. In such disease areas, providers and payers should consider this value when gauging the value of new therapies. The purpose of this study is to develop a model to estimate the additional survival patients attain from a therapy that allows them to live to benefit from further advances in care, and to apply the model to immunotherapy for metastatic melanoma. Methods The benefit of a therapy extends beyond immediate tumor control; it can also allow patients to live to benefit from further advances in care. This is a therapy's option value. Using data from the SEER cancer registry and clinical trial publications, we developed a model to estimate option value and applied it to ipilimumab, the first immune checkpoint modulator used to treat metastatic melanoma. Because ipilimumab extends survival, select patients benefited from survival extension to live to benefit from the introduction of PD-1 inhibitors (i.e. pembrolizumab and nivolumab). We calculated the option value of ipilimumab in terms of additional life-months patients gained by living to become potential candidates for PD-1 inhibitors, discounting at 3% per year. Results Patients taking ipilimumab as a second-line therapy for metastatic melanoma gained 10.5 months compared to patients taking the prior standard of care. Patients diagnosed in 2011, 2012, and 2013 gained an additional 1.6, 2.8, and 5.1 months of life expectancy, respectively, by living to see the introduction of PD-1 inhibitors. This equates to an option value of 15%, 27%, and 49%, respectively, of the conventionally calculated survival gain from ipilimumab. Ipilimumab had greater option value for patients diagnosed in later years who were more likely to live to the introduction of PD-1 inhibitors. Conclusions Therapies that enable patients to see further advances in care have option value. Option value is particularly important to patients with disease areas undergoing rapid innovation.

Specialty drugs can bring substantial benefits to patients with debilitating conditions, such as cancer, but their costs are very high. Insurers/payers have increased patient cost-sharing for specialty drugs to manage specialty drug spending. We utilized Medicare Part D plan formulary data to create the initial price (cost-sharing in the initial coverage phase in Part D), and estimated the total demand (both on- and off-label uses) for specialty cancer drugs among elderly Medicare Part D enrollees with no low-income subsidies (non-LIS) as a function of the initial price. We corrected for potential endogeneity associated with plan choice by instrumenting the initial price of specialty cancer drugs with the initial prices of specialty drugs in unrelated classes. We report three findings. First, we found that elderly non-LIS beneficiaries with cancer were less likely to use a Part D specialty cancer drug when the initial price was high: the overall price elasticity of specialty cancer drug spending ranged between -0.72 and -0.75. Second, the price effect in Part D specialty cancer drug use was not significant among newly diagnosed patients. Finally, we found that use of Part B-covered cancer drugs was not responsive to the Part D specialty cancer drug price. As the demand for costly specialty drugs grows, it will be important to identify clinical circumstances where specialty drugs can be valuable and ensure access to high-value treatments.