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Journal Article

Citation

Boggs JM, Quintana LM, Powers JD, Hochberg S, Beck A. Arch. Suicide Res. 2020; ePub(ePub): ePub.

Copyright

(Copyright © 2020, International Academy of Suicide Research, Publisher Informa - Taylor and Francis Group)

DOI

10.1080/13811118.2020.1761917

PMID

32379012

Abstract

Objective: We measured the frequency of clinicians' assessments for access to lethal means, including firearms and medications in patients at risk of suicide from electronic medical and mental health records in outpatient and emergency settings.Methods: We included adult patients who reported suicide ideation on the PHQ-9 depression screener in behavioral health and primary care outpatient settings of a large integrated health system in the U.S. and those with suicidal behavior treated in the emergency department. Two separate natural language processing queries were developed on medical record text documentation: (1) assessment for access to firearms (8,994 patients), (2) assessment for access to medications (4,939 patients).Results: Only 35% of patients had documentation of firearm or medication assessment in the month following treatment for suicidal behavior in the emergency setting. Among those reporting suicidal ideation in outpatient setting, 31% had documentation of firearm assessment and 23% for medication assessment. The accuracy of the estimates was very good for firearm assessment (F1 = 89%) and medication assessment in the outpatient setting (F1 = 91%) and fair for medication assessment in the emergency setting (F1 = 70%) due to more varied documentation styles.Conclusions: Lethal means assessment following report of suicidal ideation or behavior is low in a nonacademic health care setting. Until health systems implement more structured documentation to measure lethal means assessment, such as discrete data field, NLP methods may be used to conduct research and surveillance of this important prevention practice in real-world settings.


Language: en

Keywords

Electronic health records; firearms; lethal means; natural language processing; suicide

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