Can Affordability of Health Care Be Measured?
Affordability may be the most ubiquitous buzzword in health reform. In repeated surveys, Americans cite the affordability of health care as their top financial concern. Despite their handwringing, politicians often avoid defining what constitutes “affordable” health care, and both non-experts and seasoned policymakers seem to lack robust measures of affordability. How can the most important crisis in health care lack reliable metrics?
Americans do share some common intuitions: $500,000 cancer drugs, $50,000 insurance premiums, and $10,000 deductibles represent “unaffordable” health care. But beyond these extremes, there are few points of consensus. This is no accident. Affordability is not a synonym for low prices. It describes a qualitative ability to pay—an interaction of price, disposable income, and judgments about the necessity of a particular good. Prudent health economists avoid measuring feelings, and affordability, unlike prices and wages, is essentially a sentiment. Can it be quantified and measured?
A new issue of JAMA takes the question head on with three viewpoints that weigh the prospects—and challenges—of measuring the amorphous idea of affordable health care.
Typical measures of health care spending—total spending, medical waste, and health care as percentage of GDP—are meaningless to most Americans, who don’t think in terms of gross domestic product and can’t imagine spending trillions of dollars. To personalize the cost of health care, Zeke Emanuel, David Johnson, and Aaron Glickman propose the development of an “Affordability Index,” which describes the average cost of health care as a percentage of median household income.
The structure of health care financing and delivery obscures the typical cost of health care from consumers. Third-party payment is the norm in the United States, so families experience health care costs through the purchase of health insurance—typically employer-sponsored insurance (ESI). Two important challenges arise from this arrangement. First, employers’ pay the lion’s share of the premium cost as pretax fringe benefits, which ultimately are counted as total compensation and depress take-home cash wages. Secondly, insurance companies pay the majority of health care costs, so individuals and families rarely see the itemized price of services. Simply put, because most health insurance costs are paid as a pre-tax fringe benefit and nearly all health care costs are paid by insurers, it is difficult to grasp the link between health care costs, insurance premiums, and income.
To make this connection easier to understand, Emanuel and colleagues propose an index created by dividing the mean total cost of employer-sponsored family health insurance (both the employer and employee contribution, because both are ultimately paid by workers) by median household income. They assert that the index presents a streamlined measure of the downward pressure health care costs exert on wages, both in any particular year and over time. The index would have grown from 14.2% in 1999 to 30.7% in 2016. Put another way, in 1999 one sixth of workers’ compensation came in the form of health care, while in 2016 nearly a third of compensation was spent on health care.
This simplified measure of affordability supplies an easy to read topline figure. But there are reasons for skepticism. The simple index doesn’t overcome other hurdles to measuring affordability.
There is tremendous regional variation in health care spending, and the cost of insurance is unevenly spread nationally. James Capretta and Joseph Antos note that an average, national figure cannot account for uneven distribution of spending driven by federal subsidies that help many Americans pay for health insurance. The largest subsidy is the $250 billion per year federal tax exclusion for health insurance, which, according to the Joint Committee on Taxation, provides an average tax break of $3,106 for households earning between $50,000 and $75,000. Additionally, the Affordable Care Act (ACA) provides income-linked subsidies for families earning between 100-400% of the federal poverty level to buy health insurance on the non-group market. Under the ACA, a family of four just above the poverty level is expected to pay no more than 2% of its income for health insurance, while a similar sized family making about $100,000 is expected to pay no more than 9% of its income for health insurance.
Furthermore, adults over 65 of age receive federally subsided insurance through Medicare, and households below 138% of the federal poverty level are eligible for free insurance through Medicaid in most states. Thus, most households at or below median income typically receive generous federal subsidies—either implicitly through the tax code or explicitly through federal programs. These federal subsidies shift costs from families at or near the median income level to federal taxpayers, who are disproportionately higher-income earners.
Additionally, the possibility of double counting employer contributions to premiums and making microeconomic assertions from macroeconomic data may disturb many economists. As the late Uwe Reinhardt noted, measuring affordability as total premium divided by median income does not reflect the economic principle that median income already has the employer contribution to premiums deducted from it (as part of total compensation). Thus, the index may overestimate the burden of health insurance on households. Furthermore, affordability is essentially a microeconomic indicator—i.e., a household-level estimate. In contrast, median household income and average premium costs are macroeconomic data. Even if average premiums account for nearly 30% of median income, it does not follow that a particular worker’s wage would rise by 30% if health care costs dropped to zero.
Despite concerns over methodology, economists and non-experts have much to agree on: no matter how it is measured, health care costs depress wages and threaten family budgets. The lack of appropriate measures of affordability—adjusted for region, income, or industry—hampers policymaking and demands sustained attention.
Precise and clear data are essential tools for researchers, policy experts, and lawmakers. As health systems and consumers become increasingly cost conscious, researchers will need to consider ways to measure the impact of health care spending on families. Ultimately, what constitutes an affordable and equitable distribution of health care spending is a societal question, but generating the right data is a necessary first step towards open debate.
Aaron Glickman is a policy analyst at LDI.