Related Experiment Video
Updated: Mar 14, 2026

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
Published on: May 15, 2020
Identifying Undiagnosed High-Risk Suicidality Cases by Matching Patients With a Similar Comorbidity Burden:
Louisa Bode1,2, Rena Xu2,3, Matthew Garber2
1Peter L. Reichertz Institute for Medical Informatics, TU Braunschweig and Hannover Medical School, Hannover, Germany.
Background:
Suicide is the second leading cause of death for children and adolescents aged 6 to 18 years. Pediatric suicidality is underreported, which poses significant challenges for effective intervention and prevention strategies. Identifying populations at risk of suicidality can provide critical benefits in terms of study cohort selection, prevalence estimation, and clinical resource allocation.
Objective:
This study sought to (1) measure the prevalence of mental health comorbidities in pediatric suicidality and (2) identify undiagnosed high-risk suicidality cases by matching them with patients with a similar mental health comorbidity burden.
Methods:
Electronic health record data from a large academic pediatric hospital in Boston, Massachusetts, were analyzed for patients aged 6 to 18 years presenting to the emergency department between June 1, 2016, and June 1, 2022. Suicidality cases were defined using International Classification of Diseases, 10th Revision (ICD-10) codes for 3 suicidality subtypes: suicidal ideation, self-harm, and suicide attempt. Comorbidities of suicidality were calculated as the conditional probability of ICD-10 code pairs. After multiple hypothesis corrections, statistically significant comorbidities and patient encounter demographics were input as covariates into a propensity score matching (PSM) model. The accuracy of the PSM model was validated against chart review by 2 independent subject matter experts.
Results:
In total, 2.9% (2638/90,980) of emergency department encounters met an ICD-10-based case definition of suicidality during the study period. The prevalence of suicidality by subtype was 2.5% (2275/90,980) for ideation, 1.1% (1030/90,980) for self-harm, and 0.2% (177/90,980) for suicide attempt. Suicidality prevalence was more common for the female sex (1825/43,929, 4.2%) than for the male sex (813/47,045, 1.7%). Comorbidities of suicidality were statistically significant for 55 frequently co-occurring ICD-10 codes. Nearly half of these comorbidities (26/55, 47.3%) were not present in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, and nearly a quarter (12/55, 21.8%) consisted of ICD-10 codes for accidental rather than intentional self-harm. Increased probability of suicidality was observed for patients with personality disorder (84/190, 44.2%), gender dysphoria (143/333, 42.9%), bipolar disorder (162/448, 36.2%), depression (1791/5426, 33%), and schizophrenia spectrum disorders (133/411, 32.4%). On the basis of gold-standard chart review, 53.4% of propensity-matched noncases were unrecognized cases of suicidality.
Conclusions:
PSM using comorbidity profiles is an effective approach for identifying suicidality cases that lack ICD-10 codes for suicidality.
More Related Videos
06:55Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
Published on: January 8, 2020
10:46A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
Published on: December 9, 2015
Related Concept Videos
Diagnostic and Statistical Manual of Mental Disorders (DSM)
Depressive Disorders: Etiology
Biological Factors in Depression
Biological predispositions significantly influence the risk of developing depressive disorders. Genetic studies highlight the role of variations in the serotonin transporter...
Comparing the Survival Analysis of Two or More Groups