The Social Value of Improvement in Activities of Daily Living among the Advanced Parkinson’s Disease Population

ObjectivesQuantify 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.MethodsThe 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.ResultsTotal 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.ConclusionsFS improvements, consistent with improvements due to LCIG treatment, in the APD population created health benefits and reduced healthcare costs in the US.

Health Economics Tools and Precision Medicine: Opportunities and Challenges

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.

Cost-Effectiveness and Estimated Health Benefits of Treating Patients with Vitamin D in Pre-Dialysis

BackgroundThe 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.ObjectiveThe 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.DesignA 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.ResultsVitamin 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.ConclusionsInitiating 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.

Switching Costs in Medicare Advantage

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.

Billing Codes Determine Lower Physician Income for Primary Care and Non-Procedural Specialties

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.

Is Primary Care A Substitute or Complement for Other Medical Care? Evidence from Medicaid

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.

The Impact of Medical Marijuana Laws and Dispensaries on Self-Reported Health

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.

Modeling Product Choices in a Peer Network

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.

The Impact of New Drug Launches on Hospitalization in 2015 for 67 Medical Conditions in 15 OECD Countries: A Two-Way Fixed-Effects Analysis

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.