Treatments for health conditions are not always cost saving (reducing future costs below that of treatment), though many are cost effective (yielding high value, e.g., in added life-years, for the cost). I would not suggest that cost saving should be the criterion by which we judge the virtue of treatments. However, for the subset of treatments that are cost saving, it’s hard to justify not providing them.
It’s a puzzle, then, that treatment for substance use disorders (SUDs) is underfunded and underprovided.* In 2010, less than 20% of the estimated 23 million individuals over age 11 with SUDs received treatment. Funding for SUD treatment is modest, accounting for just 1.2% of all health spending in 2005 and growing more slowly than spending for other types of health services.
Yet, SUD treatment has been shown to be both effective for patients and cost saving for payers and wider society. The annual economic cost of excessive alcohol use alone has been estimated to be in the hundreds of billions of dollars. Researchers have found that SUD treatment is associated with a substantial offset effect, a subsequent reduction in emergency department and inpatient hospital use and costs. In a review of eleven studies, seven of which included sufficient information to calculate benefit-to-cost ratios, McCollister and French (2003) found the range to be 1.33 to 23.33, attributing the majority of benefit to reductions in crime, a large minority to increases in income, and a smaller minority to avoided health spending.
A recent paper in Medical Care Research and Review provides new evidence that SUD treatment more than pays for itself. Thomas Wickizer, David Mancuso, and Alice Huber study the expansion of SUD treatment financed by the Washington State Medicaid program in the mid-2000s. Originally funded at $30 million, the actual expansion was scaled back to about $18 million and targeted three groups: (1) disabled adults between the ages 18 and 64, (2) disabled adults receiving welfare support through the state’s General Assistance — Unemployable program, and (3) adults on Medicaid with support from the Temporary Assistance for Needy Families (TANF) program.
Due to data limitations, the authors could only analyze costs associated with the first two groups. Compared to individuals in these groups that were in need of, but did not receive SUD treatment, and controlling for baseline health, the health care costs for those that were treated fell dramatically. For an $18 million investment by the state, treatment-related savings to the Medicaid program alone totaled $17 million. This is a conservative estimate for several reasons: The authors could not analyze one of the groups targeted for treatment (the TANF group). Moreover, this is savings to Medicaid alone, not to other health care payers, to the justice system, and it doesn’t account for increased ability to work, higher earnings, or other benefits to society. In light of the ample literature that suggests SUD treatment is associated with savings in all those areas, it is very likely that the Washington State program more than paid for itself.
This story is more than a health system success. It’s also an evidence-informed policy triumph. The authors write,
The central question [for state policymakers] was, should the state reallocate funds from Medicaid and other state agency budgets to expand [SUD] treatment on the assumption that expanded treatment capacity would generate cost savings? Although this question could not be answered with certainty, the degree of uncertainty was reduced by the extensive data analysis that was conducted—analysis made possible by Washington State’s willingness to make a major investment in developing and sustaining an analytical capacity and by the state’s insistence on data-based decision making for policy.
State agencies and legislatures often consider data analysis and evaluation to represent an added cost they “cannot afford.” [...] The experience of Washington State suggests that such an investment [in research] pays important dividends in improving health policy making and conducting program evaluation. Policy makers rarely ask the question on the flip side of the coin: What is the opportunity cost of failing to invest resources in data analysis and evaluation? That cost can be much greater than the cost of investing resources in building a data analysis and evaluation capacity if ineffective programs are allowed to continue and if health policies are developed without evidence.
In the current, budget-constrained environment, it is no doubt hard for policymakers to advocate for additional research funding. However, budgets are constrained in large part due to health care costs. Consequently, investing in research that points toward more efficient — and sometimes cost-saving — health care system organization and interventions is not just money we should spend. It’s money we must spend.
* I will explore why SUD treatment is underfunded and underprovided in a future post.
Austin Frakt is a health economist at the Department of Veterans Affairs and Boston University’s Schools of Medicine and Public Health. He blogs on health economics and policy at The Incidental Economist.
As part of our ongoing effort to raise awareness of health services research and increase its application in policy and practice, AcademyHealth has partnered with Austin Frakt, Ph.D., and Aaron Carroll, M.D., M.S., to contribute posts on the subjects of health care costs, delivery system transformation, and public and population health – areas AcademyHealth has identified as a priority in the current policy environment. As regular contributors, they’ll be discussing current events with an eye toward how new and existing research informs the issues.