By Scott Burris, JD
There is a lot of interest in civil commitment these days, as a possible tool to fight two big health problems. As we continue to watch the rates of opioid-related deaths climb, and in the wake of an unfunded emergency declaration by President Trump, some policymakers are looking to involuntarily commit overdose survivors for drug treatment. On the gun violence side, experts like Jeffrey Swanson have argued for applying gun-access restrictions that now cover people subject to long-term civil commitment to those subjected to short-term civil commitment.
With those kinds of ideas in the air, it is important to recognize how little modern data we have on commitment and its effects. In a recent article in the Washington Post discussing commitment for opioid treatment, Michael Stein and Paul Christopher emphasize how little we know. I entirely agree on the need for more research, and offer a couple of things to help.
The first is the Policy Surveillance Program’s LawAtlas dataset that maps civil commitment laws across all 50 states and the District of Columbia. If we’re going to examine these laws and their impact, this is the place to start. We also put out the call to anyone interested in studying this to work with us not only to update this data through 2017, but also to make sure we’re mining these laws and their characteristics for the right information in these circumstances — Are we asking the right questions?
In May 2016, our team at the Center for Public Health Law Research and colleagues used the data we mention above to analyze these laws and their characteristics. Published Psychiatric Services, we find significant variability in state law for emergency holds for individuals with acute mental illness. But, as Stein and Christopher explain, we too conclude that how this variability affects the individual, the treatment system, and law enforcement behavior is unknown.
Neither gun violence nor opioid overdose are going away soon, so it’s more important than ever for us to apply the strategies that are proven to work, and to work diligently to find new ones that will in the future.
