Volume 17, Issue 1

This paper sets out a model of technical change and health care cost growth for a representative Medicare beneficiary facing a budget constraint. Derivation of an explicit expression for health care cost growth shows how technological change and preferences, including income effects, affect cost growth. The analysis highlights the role of the 76% subsidy from current taxpayers to Medicare beneficiaries for purchase of health insurance. This subsidy insulates beneficiaries from the income effects of cost growth by shifting the costs and income effects to taxpayers. Simulations show that over the next 10–20 years, income effects will have little effect on cost growth in Medicare.

Barriers and delays to medical device innovation are often solely attributable to the regulatory environment instead of both the current state of innovation practices and product development processes in the industry. Increasing the pace of innovation while reducing costs requires the creation of a new approach that fits both established medical device corporations as well as entrepreneurial start-ups. In this commentary we advance the concept of innovation platforms to facilitate ideation in the medical device space. Such platforms could also allow the full health benefits from individual medical devices to be reaped, by overcoming interoperability concerns through simulation and credentialing. Given the dramatic benefits of medical device success, such non-traditional business models for development may be potential solutions for industry, users and regulators.

Payers increasingly require evidence of a statistically significant difference in overall survival (OS) for reimbursement of new cancer therapies. At the same time, it becomes increasingly costly to design clinical trials that measure OS endpoints instead of progression-free survival (PFS) endpoints. While PFS is often an imperfect proxy for OS effects, it is also faster and cheaper to measure accurately. This study develops a general cost-benefit framework that quantifies the competing trade-offs of the use of PFS versus that of OS in oncology reimbursement. We then apply this general framework to the illustrative case of metastatic renal cell carcinoma (mRCC). In the particular case of mRCC, the framework demonstrates that the net benefit to society from basing reimbursement decisions on PFS endpoints could be between $271 and $1271 million in the United States, or between €171 and €1128 million in Europe. In longevity terms, waiting for OS data in this case would result in a net loss of 3549–14,557 life-years among US patients, or 6785–27,993 life-years for European patients. While more stringent standards for medical evidence improve accuracy, they also impose countervailing costs on patients in terms of foregone health gains. These costs must be weighed against the benefits of greater accuracy. The magnitudes of the costs and benefits may vary across tumor types and need to be quantified systematically.

The relation between the quantity of many healthcare services delivered and health outcomes is uncertain. In January 2004, the Centers for Medicare and Medicaid Services introduced a tiered fee-for-service system for patients on hemodialysis, creating an incentive for providers to see patients more frequently. We analyzed the effect of this change on patient mortality, transplant wait-listing, and costs. While mortality rates for Medicare beneficiaries on hemodialysis declined after reimbursement reform, mortality declined more – or was no different – among patients whose providers were not affected by the economic incentive. Similarly, improved placement of patients on the kidney transplant waitlist was no different among patients whose providers were not affected by the economic incentive; payments for dialysis visits increased 13.7% in the year following reform. The payment system designed to increase provider visits to hemodialysis patients increased Medicare costs with no evidence of a benefit on survival or kidney transplant listing.

We construct and test a new model of employer-provided health insurance provision in the presence of adverse selection in the health insurance market. In our model, employers cannot observe the health of their employees, but can decide whether to offer insurance. Employees sort themselves among employers who do and do not offer insurance on the basis of their current health status and the probability distribution over future health status changes. We show that there a pooling equilibrium is more likely when the costs of switching jobs are high or when health status is not persistent. We test and verify some of the key implications of our model using data from the Current Population Survey, linked to information provided by the US Department of Labor about the job-specific human capital requirements of jobs.