Forum for Health Economics and Policy最新文献

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.

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.

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.

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.