Identifying clinical diagnostic trajectories associated with suicide death using temporal sequence mining of linked claims and mortality data

Most approaches to suicide risk assessment consider clinical conditions as independent risk factors, potentially overlooking prognostic information in the order in which conditions accumulate. We applied temporal sequence mining to linked claims and mortality data to identify ordered clinical diagnostic trajectories associated with suicide death. The cohort included 3 647 059 insured Maryland residents aged 10 years or older with available claims records in the Maryland Suicide Data Warehouse from January 1, 2016, to December 31, 2020, among whom 768 suicide deaths were ascertained through medical examiner linkage. Sequential pattern mining of ICD-10-CM diagnoses grouped into Clinical Classifications Software Refined categories identified 89 221 candidate sequences, of which 1 816 remained significantly associated with suicide death in time-varying Cox models. Adjusted hazard ratios (AHRs) ranged from 2.4 to 134.1. Half of significant trajectories ended in physical conditions, and 93.7% of these began with a psychiatric diagnosis. Among suicide decedents, 62% were exposed to at least 1 significant sequence (median, 16 per case); median sequence duration was 18.7 months, and median time from completion to death was 13.1 months. In landmark analyses, among patients with depression who later developed suicidal ideation ( n = 26 356), the path through anxiety, then anemia, was associated with a higher hazard of subsequent suicide death than other paths from depression to suicidal ideation (AHR, 4.6; 95% CI, 2.2–9.5), whereas the anxiety-only path was not (AHR, 1.3; 95% CI, 0.8–2.1). Among patients with anxiety who later developed hypertension ( n = 149 215), the path through history of self-harm was associated with a higher hazard of subsequent suicide death than other paths from anxiety to hypertension (AHR, 32.0; 95% CI, 16.6–61.6). Temporal ordering of clinical conditions may carry prognostic information for suicide death. Clinical trajectories incorporating physical illness within psychiatric sequences identified higher-risk groups. These findings suggest that opportunities for risk detection may extend beyond psychiatric settings and that suicide risk signals may be fragmented across care settings and not apparent within isolated encounters.

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Journal
BioData Mining
Published
2026-10-06
DOI
https://doi.org/10.1186/s13040-026-00608-3
Primary Topic
Suicide and Self-Harm Studies
Type
article
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article

Identifying clinical diagnostic trajectories associated with suicide death using temporal sequence mining of linked claims and mortality data

Holly C. Wilcox, Paul Sasha Nestadt, Christopher Kitchen, Anas Belouali et al.
BioData Mining
Suicide and Self-Harm Studies
article

Identifying clinical diagnostic trajectories associated with suicide death using temporal sequence mining of linked claims and mortality data

Holly C. Wilcox, Paul Sasha Nestadt, Christopher Kitchen, Anas Belouali, Hadi H.K. Kharrazi, Emily Haroz, Harold Lehmann
article en

Abstract

Most approaches to suicide risk assessment consider clinical conditions as independent risk factors, potentially overlooking prognostic information in the order in which conditions accumulate. We applied temporal sequence mining to linked claims and mortality data to identify ordered clinical diagnostic trajectories associated with suicide death. The cohort included 3 647 059 insured Maryland residents aged 10 years or older with available claims records in the Maryland Suicide Data Warehouse from January 1, 2016, to December 31, 2020, among whom 768 suicide deaths were ascertained through medical examiner linkage. Sequential pattern mining of ICD-10-CM diagnoses grouped into Clinical Classifications Software Refined categories identified 89 221 candidate sequences, of which 1 816 remained significantly associated with suicide death in time-varying Cox models. Adjusted hazard ratios (AHRs) ranged from 2.4 to 134.1. Half of significant trajectories ended in physical conditions, and 93.7% of these began with a psychiatric diagnosis. Among suicide decedents, 62% were exposed to at least 1 significant sequence (median, 16 per case); median sequence duration was 18.7 months, and median time from completion to death was 13.1 months. In landmark analyses, among patients with depression who later developed suicidal ideation ( n = 26 356), the path through anxiety, then anemia, was associated with a higher hazard of subsequent suicide death than other paths from depression to suicidal ideation (AHR, 4.6; 95% CI, 2.2–9.5), whereas the anxiety-only path was not (AHR, 1.3; 95% CI, 0.8–2.1). Among patients with anxiety who later developed hypertension ( n = 149 215), the path through history of self-harm was associated with a higher hazard of subsequent suicide death than other paths from anxiety to hypertension (AHR, 32.0; 95% CI, 16.6–61.6). Temporal ordering of clinical conditions may carry prognostic information for suicide death. Clinical trajectories incorporating physical illness within psychiatric sequences identified higher-risk groups. These findings suggest that opportunities for risk detection may extend beyond psychiatric settings and that suicide risk signals may be fragmented across care settings and not apparent within isolated encounters.

BioData Mining
Johns Hopkins University (US), Johns Hopkins Medicine (US)
Good health and well-being
Openalex Percentile: Top 8%
Suicide and Self-Harm Studies
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