Article2018

Positive predictive value of a register‐based algorithm using the Danish National Registries to identify suicidal events

Christiane Gasse · Andreas Aalkjær Danielsen · Marianne Giørtz Pedersen · Carsten Bøcker Pedersen · Ole N Mors · Jakob Christensen

53 citations0/0 files storedPharmacoepidemiology and Drug Safety

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Suicide and Self-Harm Studies Medical Coding and Health Information Homicide, Infanticide, and Child Abuse

Abstract

PURPOSE: It is not possible to fully assess intention of self-harm and suicidal events using information from administrative databases. We conducted a validation study of intention of suicide attempts/self-harm contacts identified by a commonly applied Danish register-based algorithm (DK-algorithm) based on hospital discharge diagnosis and emergency room contacts. METHODS: Of all 101 530 people identified with an incident suicide attempt/self-harm contact at Danish hospitals between 1995 and 2012 using the DK-algorithm, we selected a random sample of 475 people. We validated the DK-algorithm against medical records applying the definitions and terminology of the Columbia Classification Algorithm of Suicide Assessment of suicidal events, nonsuicidal events, and indeterminate or potentially suicidal events. We calculated positive predictive values (PPVs) of the DK-algorithm to identify suicidal events overall, by gender, age groups, and calendar time. RESULTS: We retrieved medical records for 357 (75%) people. The PPV of the DK-algorithm to identify suicidal events was 51.5% (95% CI: 46.4-56.7) overall, 42.7% (95% CI: 35.2-50.5) in males, and 58.5% (95% CI: 51.6-65.1) in females. The PPV varied further across age groups and calendar time. After excluding cases identified via the DK-algorithm by unspecific codes of intoxications and injury, the PPV improved slightly (56.8% [95% CI: 50.0-63.4]). CONCLUSIONS: The DK-algorithm can reliably identify self-harm with suicidal intention in 52% of the identified cases of suicide attempts/self-harm. The PPVs could be used for quantitative bias analysis and implemented as weights in future studies to estimate the proportion of suicidal events among cases identified via the DK-algorithm.

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References

2011The Danish Psychiatric Central Research Register 2007Columbia Classification Algorithm of Suicide Assessment (C-CASA): Classification of Suicidal Events in the FDA’s Pediatric Suicidal Risk Analysis of Antidepressants 2009Risk of suicidality in clinical trials of antidepressants in adults: analysis of proprietary data submitted to US Food and Drug Administration 2013Non-suicidal self-injury v. attempted suicide: new diagnosis or false dichotomy?2007Risk of Repetition of Suicide Attempt, Suicide or all Deaths after an Episode of Attempted Suicide: A Register-Based Survival Analysis 2007Prevention of suicide and attempted suicide in Denmark. Epidemiological studies of suicide and intervention studies in selected risk groups.2006Definitions of Suicidal Behavior 2015Suicide Risk After Nonfatal Self-Harm

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