Thursday, April 25, 2024
4/25/2024
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, this study was funded to derive a clinical decision rule to support universal risk detection and optimize patient care workflow in adults. 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 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 developed a pool of empirically supported clinician-acceptable candidate suicide risk indicators. Data on these candidate indicators are being collected by trained research staff on adult medical and psychiatric patients from a large ED. Participants are undergoing a comprehensive suicide risk assessment by a research clinician, blinded to the indicators, who assigns the participant to a criterion reference risk group: Negligible, Mild-Moderate, or High risk. Participants are being 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.”
HHS’ Tracking Accountability in Government Grants System (TAGGS) website provides access to detailed descriptions of grants, loans, aggregated direct payments and other types of financial assistance awarded by the HHS Operating Divisions (OPDIVs) and the Office of the Secretary Staff Divisions (STAFFDIVs).
