Volume 19, Issue 2

We study how the optimal public provision of health care depends on whether or not individuals have an option to seek publicly financed treatment in other regions. We find that, relative to the first-best solution, the government has an incentive to over-provide health care to low-income individuals. When cross-border health care takes place, this incentive is solely explained by that over-provision facilitates redistribution. The reason why more health care facilitates redistribution is that high-ability individuals mimicking low-ability individuals benefit the least from health care when health and labor supply are complements. Without cross-border health care, higher demand for health care among high-income individuals also contributes to the over-provision given that high-income individuals do not work considerably less than low-income individuals and that the government cannot discriminate between the income groups by giving them different access to health care.

Prior research on treatment of low back pain has documented large increases in use of spinal surgery, MRIs and lumbosacral injections linked to physician self-referral arrangements. No recent research has examined whether physician ownership of physical therapy services results in greater use of physical therapy to treat low back pain. The objective of this study is to investigate whether physician ownership of physical therapy services affects frequency of use, visits and types of physical therapy services received by patients with low back pain. Using claims records from insured patients covered by Blue Cross Blue Shield of Texas (2008–2011) we compared several metrics of use of physical therapy services for low back pain episodes controlling for self-referral status. We identified 158,151 low back pain episodes, 27% met the criteria to be classified as “self-referral.” Only 10% of “non-self-referral” episodes received physical therapy compared to 26% of self-referral episodes ( p <0.001). The unadjusted and regression adjusted self-referral effect was identical – about 16 percentage point difference ( p <0.001). Among patients who received some physical therapy, self-referral episodes were comprised of 2.26 fewer visits and 11 fewer physical therapy service units ( p <0.001). Non-self-referring episodes included a significantly higher proportion of “active” (hands on or patient engaged) as opposed to “passive” treatments ( p <0.001). The regression-adjusted difference was 30 percentage points when measured as actual counts and 29 percentage points when measured in RVUs ( p <0.001). Total spending on back-related care was 35% higher for self-referred episodes compared to their non-self-referred counterparts ( p <0.001). Ownership of physical therapy services influence physicians’ referral to initiate a course of physical therapy to treat low back pain, but also affect the types of physical therapy services a patient receives.

On March 23, 2010, President Barack Obama signed the Patient Protection and Affordable Care Act (ACA) into law. This comprehensive health care reform legislation sought to expand health care coverage to millions of Americans, control health care costs, and improve the overall quality of the health care system. The ACA required that all US citizens and legal residents have qualifying health insurance by 2014. In this paper we give readers a brief overview of the effects of the ACA based on recent research. We then turn our attention to the possibility of using the ACA expansion to answer important underlying questions, such as: To what extent does the holding of insurance lead to improvements in access to care? To what extent does the holding of coverage lead to improvements in health? In mental health? Are there likely general equilibrium effects on labor force participation, hours worked, employment setting, and indeed even the probability of marrying? By necessity, researchers’ ability to answer these questions depends on the availability of data, so we discuss current and potential data sources relevant for answering these questions. We also look to what has been studied about the health reform in Massachusetts and early Medicaid expansions to speculate what we can expect to learn about the effects of the ACA on these outcomes in the future.

I construct a disease-based medical expenditure index for Medicare Advantage (private plan) enrollees using data from the Medicare Current Beneficiary Survey from 2001 to 2009. I create the indexes by modeling total health-care expenditure as a function of each respondent’s diagnoses. Total medical inflation for this population is found to be 5.7 percent annually. By comparison, medical inflation in the Medicare fee-for-service (FFS) population is 4.5 percent annually. The difference is partly due to differential reporting of drug and nondrug spending in the MCBS for FFS beneficiaries; once this is corrected for, inflation among FFS beneficiaries is 5.0 percent. The remaining difference results from drug spending increasingly more rapidly among Medicare Advantage enrollees. I show that the introduction of Part D accounts for much of, and possibly all the remaining gap in inflation.

Several studies have explored the causes and magnitude of geographic variation in Medicare spending and service use, but most of these studies have not taken into account that pharmaceuticals may substitute for medical service use. We address this issue using Medicare medical and pharmaceutical administrative claims data to explore the correlation between medical and pharmaceutical spending and utilization; we also examine medical and pharmaceutical use for subsets of the Medicare population with certain chronic conditions often treated with drugs. Beneficiary-level regressions with controls for health status and demographics were used to construct standardized medical spending and pharmaceutical spending and utilization measures for each region and patient cohort. Areas with higher medical spending tend to have higher pharmaceutical spending in general. However, areas with higher medical spending also tend to have lower pharmaceutical spending for conditions for which prescription drugs may substitute for additional medical care. Both of these patterns are consistent with less efficient medical practices in higher-spending areas. Likewise, more expensive drugs and more broad-spectrum antibiotics, which are often considered discretionary and overused, are more likely to be prescribed in higher-spending areas. Our results suggest that care may be provided more efficiently in some regions than in others. However, additional research is needed to investigate relationships between spending and health care outcomes, and what types of policies may create incentives for higher-spending regions to reduce spending without a loss in quality.

Background: The high cost of new hepatitis C (HCV) treatments has resulted in “watchful waiting” strategies being developed to safely delay treatment, which will in turn delay viral load suppression (VLS). Objective: To document if delayed VLS adversely impacted patient risk for adverse events and death. Methods: 187,860 patients were selected from the Veterans Administration’s (VA) clinical registry (CCR), a longitudinal compilation of electronic medical records (EMR) data for 1999–2010. Inclusion criteria required at least 6 months of CCR/EMR data prior to their HCV diagnosis and sufficient data post-diagnosis to calculate one or more FIB-4 scores. Primary outcome measures were time-to-death and time-to-a composite of liver-related clinical events. Cox proportional hazards models were estimated separately using three critical FIB-4 levels to define early and late viral response. Results: Achieving an undetectable viral load before the patient’s FIB-4 level exceed pre-specified critical values (1.00, 1.45 and 3.25) effectively reduced the risk of an adverse clinical events by 33–35% and death by 21–26%. However, achieving VLS after FIB-4 exceeds 3.25 significantly reduced the benefit of viral response. Conclusions: Delaying VLS until FIB-4 >3.25 reduces the benefits of VLS in reducing patient risk.