ABSTRACT Significance: As recent national controversy over Joint Commission mandates proves, universal suicide risk screening in emergency departments (ED) will not achieve widespread adoption because confusion remains around which specific risk indicators to assess, and clinicians fear that such screening will lead to massive surges in psychiatric evaluations. To address these two implementation barriers, the proposed study will derive a clinical decision rule to support universal risk detection and optimize patient care workflow in adult patients. Investigators: The Project Team has extensive expertise in ED-based suicide risk screening and assessment (Boudreaux, Larkin), clinical decision rule design (Boudreaux, Stiell), predictive analytics (Wang, Liu, Simon), machine learning and informatics (Liu, Simon), industrial engineering (Johnson), and healthcare economics (Clements). A Clinical Advisory Panel ensures that the proposal is grounded in the practical realities of the ED. Innovation: The proposed study will be the first to apply industry standards for deriving decision rules to suicide risk and will directly inform the controversy regarding the relative strengths and weaknesses of universal versus targeted screening. We will pioneer new statistical innovations for rule derivation and will integrate simulation of potential workflow impact using industrial engineering modeling and economic analyses. Approach: We have already developed a pool of empirically supported, clinician-acceptable candidate suicide risk indicators. Data on these candidate indicators will be collected by trained research staff on 500 adult medical patients and 500 adult psychiatric patients from a large ED. Participants will undergo a comprehensive suicide risk assessment by a research clinical psychologist blinded to the indicators who will assign the participant to a criterion reference risk group: Negligible, Mild-Moderate, or High risk. Participants will be followed for 24 weeks after the visit to assess suicidal behavior, our secondary outcome. In Aim 1, we will derive a universal screening decision rule for “all comers,” as well as a variant to be used with patients presenting with a psychiatric chief complaint (targeted). In Aim 2, we will test whether a previously validated risk stratification algorithm using data from the electronic health record improves the performance of the decision rules. In Aim 3, we will model the potential operational impact of the rules through dynamic modeling of clinical workflow and economic costs and assessing clinician and patient acceptability in a new sample of 100 ED clinician-patient dyads. Environment: UMass has demonstrated its capability to support this study through several key preliminary studies, including the ED-SAFE studies, System of Safety, and other suicide-related studies set in the ED. Impact: By providing clear, evidence-based recommendations on universal screening and optimized workflow using standards accepted by emergency clinicians, this study will address two pivotal barriers to universal suicide risk screening, transforming the “right thing” into the “easy thing” so it becomes the “usual thing.”

NARRATIVE Effective prevention of suicide among adult emergency department (ED) patients hinges on two indispensable components: effective identification of all patients who are at risk for suicidal behavior, and successful delivery of effective interventions to those with risk. Because many ED patients have hidden risk and do not present with psychiatric chief complaints, universal screening has been recommended by several prominent groups, such as the Joint Commission and the Action Alliance for Suicide Prevention; however, two trenchant barriers prevent such universal screening from being widely implemented, namely, (1) lack of clarity around the specific indicators to use for screening and (2) fear that screening all-comers will cause ED workflow to come to a grinding halt because of surges in psychiatric evaluations and boarding. The proposed study will address these two barriers by deriving the first clinical decision rule for use with all ED patients using rigorous standards and procedures and modelling its impact on workflow and costs, thereby revolutionizing the field's ability to actualize the first indispensable component of suicide prevention: effective, efficient identification and triaging of suicide risk, both hidden and obvious.