Data at Work

By Scott Burris, JD

The past few weeks saw two important studies published using legal mapping data to understand the role law plays in addressing health inequity and disparities. Both provide immediately actionable insights for health policy.

The first, published in the American Journal of Public Health, evaluates more than 200 changes in state minimum wage laws over 31 years (1980-2011) using LawAtlas data, and the impact of those changes on infant mortality and birth weight. Komro and her colleagues find that a $1 increase in the minimum wage above the federal level was associated with a 1 to 2 percent decrease in the number of low birth weight births and a four percent decrease in infant mortality in the United States. The research was built on data that identified every change in state and federal minimum wages over 31 years. The natural experiment represented by 206 state law changes—which can be compared by month both before and after within state and against states that did not change—can give us great confidence that the effect of the increases is causal.

The second, published in Health Affairs, assesses the effects of state prescription monitoring programs (PDMPs) on opioid-related deaths. The study, which also uses LawAtlas data, finds that a state’s implementation of a program was associated with an average reduction of 1.12 opioid-related overdose deaths per 100,000 population in the year after implementation.  Using the detailed LawAtlas data, originally compiled by Corey Davis, allowed the researchers to test the effects of specific program attributes that differ across states: how many drug schedules were monitored, how frequently the data were updated, and whether or not registration or use of the program was mandatory. More schedules and more frequent updating showed significant impact; program mandates, not common in the study period, was associated with fewer deaths but not significantly.

An interesting contrast is a second Health Affairs paper, which found that the implementation of a prescription drug monitoring program was associated with more than a 30 percent reduction in the rate of prescribing of Schedule II opioids. What’s interesting from the legal research standpoint is that the authors took their PDMP measures from a static source not designed to provide data for evaluation, and looked only at whether a PDMP was in operation or not.  As we move forward (and as the authors of this paper themselves note), the big research question is not whether PDMP’s can have an impact, but what specific elements of the PDMP drive its positive effects. The LawAtlas PDMP database has been revised and extended on NIDA’s Prescription Drug Abuse Policy System, and will enable that sort of more detailed assessment.

These findings are significant not only because they address questions about two currently “hot” topics, but also because they make excellent use of legal mapping data. We’re biased, of course, because the minimum wage data are ours (check out the maps at LawAtlas.org), but we’re excited to see this sort of study taking off.

The scientific method for legal mapping—policy surveillance—is essential to identifying and spreading legal interventions and reforms that promote public health because it creates reliable, replicable data researchers need.

Temple University Center for Public Health Law Research

Based at the Temple University Beasley School of Law, the Center for Public Health Law Research supports the widespread adoption of scientific tools and methods for mapping and evaluating the impact of law on health. It works by developing and teaching public health law research and legal epidemiology methods (including legal mapping and policy surveillance); researching laws and policies that improve health, increase access to care, and create or remove barriers to health (e.g., laws or policies that create or remove inequity); and communicating and disseminating evidence to facilitate innovation.

Leave a Reply

This site uses Akismet to reduce spam. Learn how your comment data is processed.