Clinician Prediction of Future Suicide Attempts

Objective: Established risk assessment tools are often inaccurate at predicting future suicide risk. We therefore investigated whether clinicians are able to predict individuals’ suicide risk with greater accuracy. Method: We used the SAFE Database, which included consecutive adult (age ≥18 years) presentations ( N = 3818) over a 22-month period to the 2 tertiary care hospitals in Manitoba, Canada. Medical professionals assessed each individual and recorded his or her predicted risk for future suicide attempt (SA) on a 0-10 scale—the clinician prediction scale. The SAD PERSONS scale was completed as a comparison. SAs within 6 months, assessed using the Columbia Classification Algorithm for Suicide Assessment, were the primary outcome measure. Receiver operating characteristic curve and logistic regression analyses were conducted to determine the accuracy of both scales to predict SAs, and the scales were compared with z scores. Clinician prediction scale performance was stratified based on level of training. Results: Clinicians were able to predict future SAs with significantly greater accuracy (area under the curve [AUC] = 0.73; 95% CI, 0.68 to 0.77; P Conclusions: Clinicians are able to predict future attempts with fewer false positives than a conventional risk assessment scale, and this skill appears related to training level. Predicting future suicidal behaviour remains very challenging.