Forum for Health Economics and Policy最新文献

A recent report from the National Academies of Sciences, Engineering, and Medicine (NASEM) highlights rising rates of working-age mortality in the United States, portending troubling population health trends for this group as they age. The Health and Retirement Study (HRS) is an invaluable resource for researchers studying health and aging dynamics among Americans ages 50 and above and has strong potential to be used by researchers to provide insights about the drivers of rising U.S. mortality rates. This paper assesses the strengths and limitations of HRS data for identifying drivers of rising mortality rates in the U.S. and provides recommendations to enhance the utility of the HRS in this regard. Among our many recommendations, we encourage the HRS to prioritize the following: link cause of death information to respondents; reduce the age of eligibility for inclusion in the sample; increase the rural sample size; enhance the existing HRS Contextual Data Resource by incorporating longitudinal measures of structural determinants of health; develop additional data linkages to capture residential settings and characteristics across the life course; and add measures that capture drug use, gun ownership, and social media use.

Selection bias is an ongoing concern in large-scale panel surveys where the cumulative effects of unit nonresponse increase at each subsequent wave of data collection. A second source of selection bias in panel studies is the inability to link respondents to supplementary administrative records, either because respondents do not consent to link or the matching algorithm fails to locate their administrative records. Both sources of selection bias can affect the validity of conclusions drawn from these data sources. In this article, I discuss recently proposed methods of reducing both sources of selection bias in panel studies, with a special emphasis on reducing selection bias in the US Health and Retirement Study.

In this paper we revisit the relationship between health outcomes, income, and income inequality by applying alternative panel methodologies to a dataset of high-income countries spanning the time period 1980-2017. In this direction, we adopt alternative methodological frameworks in order to provide a) meaningful results by taking into account standard errors that alleviate problems of cross-sectional (spatial) and temporal dependence, and b) insights into the underlying relationships at several points of the conditional distribution of the health outcomes dependent variables. The evidence strongly supports the significant role that income plays in determining health outcomes. The findings relating to income inequality and nonlinear terms are more fragmented in that their significance and sign-direction depend on the functional form and the respective quantiles of the distribution the relationships are evaluated.

This study aims to investigate the association between gross domestic product (GDP), mortality rate (MR) and current healthcare expenditure (CHE) in 31 high-income countries. We used panel data from 2000 to 2017 collected from WHO and OECD databases. The association between CHE, GDP and MR was investigated through a random-effects model. To control for reverse causality, we adopted a test of Granger causality. The model shows that the MR has a statistically significant and negative effect on CHE and that an increase in GDP is associated with an increase of CHE (p < 0.001). The Granger causality analysis shows that all the variables exhibit a bidirectional causality. We found a two-way relationship between GDP and CHE. Our analysis highlights the economic multiplier effect of CHE. In the debate on the optimal allocation of resources, this evidence should be taken into due consideration.

This study seeks to analyze the overall impact that biopharmaceutical innovation had on disability, Social Security recipiency, and the use of medical services of U.S. community residents during the period 1998-2015. We test the hypothesis that the probability of disability, Social Security recipiency, and medical care utilization associated with a medical condition is inversely related to the number of drug classes previously approved for that condition. We use data from the 1998-2015 waves of the Medical Expenditure Panel Survey and other sources to estimate probit models of an individual's probability of disability, Social Security recipiency, and medical care utilization. The effect of biopharmaceutical innovation is identified by differences across over 200 medical conditions in the growth in the lagged number of drug classes ever approved. 18 years of previous biopharmaceutical innovation is estimated to have reduced: the number of people who were completely unable to work at a job, do housework, or go to school in 2015 by 4.5%; the number of people with cognitive limitations by 3.2%; the number of people receiving SSI in 2015 by 247 thousand (3.1%); and the number of people receiving Social Security by 984 thousand (2.0%). Previous innovation is also estimated to have caused reductions in home health visits (9.2%), inpatient events (5.7%), missed school days (5.1%), and outpatient events (4.1%). The estimated value in 2015 of some of the reductions in disability, Social Security recipiency, and use of medical care attributable to previous biopharmaceutical innovation ($115 billion) is fairly close to 2015 expenditure on drug classes that were first approved by the FDA during 1989-2006 ($127 billion). However, for a number of reasons, the costs are likely to be lower, and the benefits are likely to be larger, than these figures.

Medicare Part D has significantly enhanced access to prescription drugs among Medicare beneficiaries. However, the recent rapid rise of utilization management policies in the Medicare Part D program may have adversely affected access to prescription drugs. I study the effects of expected and observed exposure to utilization management in prescription drug utilization using Medicare Part D claims data from 2009 to 2016 and an instrumental variables strategy based on the interaction of lagged health status and the set of plans available to each beneficiary. I find that the expected share of spending subject to utilization management increases the observed share, with the smallest effect for prior authorization. Increases in the expected share of drug spending subject to prior authorization increases Part D spending by $122.27 per percentage point, with almost three-quarters of this increase being paid by the Medicare program, rather than beneficiaries or plans. Comparable increases in step therapy and quantity limit exposure increase spending by $46 and decrease spending by $31, respectively. Interestingly, increased exposure to prior authorization and quantity limits increases the average price per 30-day prescription.

Objectives: Quantify the value of functional status (FS) improvements consistent in magnitude with improvements due to levodopa-carbidopa intestinal gel (LCIG) treatment, among the advanced Parkinson's disease (APD) population.

Methods: The Health Economic Medical Innovation Simulation (THEMIS), a microsimulation that estimates future health conditions and medical spending, was used to quantify the health and cost burden of disability among the APD population, and the value of quality-adjusted life-years gained from FS improvement due to LCIG treatment compared to standard of care (SoC). A US-representative Parkinson's disease (PD)-comparable cohort was constructed in THEMIS based on observed PD patient characteristics in a nationally representative dataset. APD was defined from the literature and clinical expert input. The PD and APD cohorts were followed from 2010 over their remaining lifetimes. All individuals were ages 65 and over at the start of the simulation. To estimate the value of FS improvement due to LCIG treatment, decreases in activities of daily living (ADL) limitations caused by LCIG treatment were calculated using data from a randomized, controlled, double-blind, double-dummy clinical trial and applied to the APD population in THEMIS.

Results: Total burden of disability associated with APD was $17.7 billion (B). From clinical trial data, LCIG treatment versus SoC lowers the odds of difficulties in walking, dressing, and bathing by 76%, 42% and 39%, respectively. Among the APD population, these reductions generated $2.6B in value to patients and cost savings to payers. The added value was 15% of the burden of disability associated with APD and offsets 15% of the cost of LCIG treatment.

Conclusions: FS improvements, consistent with improvements due to LCIG treatment, in the APD population created health benefits and reduced healthcare costs in the US.

This paper estimates the magnitude of switching costs in the Medicare Advantage program. Consumers are generally assumed to pick plans that provide the combination of benefits and premiums that maximize their individual utility. However, the plan choice literature has generally omitted prior choices from choice models. The analysis is based on five years of the Medicare Current Beneficiary Survey, a nationally representative longitudinal dataset. The MCBS data were combined with data on Medicare Advantage Part C plan benefits and premiums. Individual choices are modeled as a function of individual characteristics, plan characteristics and prior year plan choices using a mixed logit model. We found relatively high rates of switching between plans within insurer (20%), although less switching between insurers. Prior year plan choices were highly significant at both the contract and plan level. Premium was negative and significant. Loyalty (contract and plan), premium and plan structure were found to be heterogeneous in preferences. We found a statistically significant willingness to pay for a lower prescription drug deductible and lower copays. Switching costs were higher for sicker individuals. Switching costs between plans offered by the same insurer are far lower than switching costs between insurers; beneficiaries will switch plans if an alternative is perceived as $233 a month better than the current choice and switch insurers if the alternative is perceived as $944 better than the current plan/contract, on average. Premium elasticities would be 34% greater in magnitude if prior choices were irrelevant. We provide evidence that the state dependence is structural rather than spurious.