Extreme Risk Protection Orders (ERPO) are state laws intended to prevent gun violence by preemptively and temporarily removing firearms from individuals determined to be at risk of self-harm or violence against others. Here, we propose a framework for tackling questions about how well ERPOs have been targeted to those at highest risk of suicide and how effective ERPOs are at preventing suicide among those who were targeted. This framework makes use of novel causal inference approaches using data on ERPOs issued and suicide deaths that could be reasonably obtained in many states with ERPO policies. More specifically, we formalize estimands related to effectiveness and risk-targeting and describe the conditions under which these estimands can be identified or bounded with available data. We provide adaptable R code for implementing these approaches and highlight key considerations for using these methods in practice.
Swanson et al. (Sat,) studied this question.