Management of Suicide Risk: Data-Driven Clinical Decision Support using Transnational Electronic Registry Data

Purpose and goal

Two limitations hamper effective suicide risk management. First, unassisted clinical judgement is not sufficient to accurately assess suicide risk, leading to ineffective clinical decision-making and poor patient experience; and second, the need for adequate mental health treatment is often unmet among patients with suicide risk. The PERMANENS project aims to improve suicide prevention by developing a prototype of a Clinical Decision Support System (CDSS), i.e., a medical software programme that assists in the personalized clinical evaluation and management of suicide risk.

Expected effects and result

The CDSS will innovate current clinical practice by (1) increasing the prediction accuracy of suicide risk assessment and enabling (2) accurate assessment of risk for inadequate treatment delivery among those with suicide risk; (3) fine-grained clinical risk stratification; and (4) the personalized matching of the identified risk profiles with effective treatment options in order to improve indicated and tailored treatment trajectories among those with suicide risk.

Planned approach and implementation

Data for the project will be obtained via population-representative electronic registries from Ireland, Norway, Spain, and Sweden. Machine-learning techniques will be used to develop accurate and clinically useful prediction algorithms for suicide and inadequate or unmet treatment, including the identification of most important risk factors. Through co-creation and user-oriented qualitative implementation research with patients and clinicians, an effective and user-friendly CDSS prototype will be developed.