Mahfuza Rahman1, Emily Leckman-Westin2, Barbara Stanley3, Jamie Kammer4, Deborah Layman4, Christa D Labouliere3, Anni Cummings4, Prabu Vasan4, Katrina Vega4, Kelly L Green5, Gregory K Brown5, Molly Finnerty6, Hanga Galfalvy7. 1. New York State Office of Mental Health, NY. Electronic address: mahfuza.rahman@omh.ny.gov. 2. New York State Office of Mental Health, NY; Department of Epidemiology and Biostatistics, University at Albany-SUNY, School of Public Health. 3. New York State Psychiatric Institute, NY; Department of Psychiatry, Columbia University Vagelos College of Physicians and Surgeons, NY. 4. New York State Office of Mental Health, NY. 5. Department of Psychiatry Perelman School of Medicine University of Pennsylvania, PA. 6. New York State Office of Mental Health, NY; Department of Child and Adolescent Psychiatry, New York University Langone Health, NY. 7. Department of Psychiatry, Columbia University Vagelos College of Physicians and Surgeons, NY; Department of Biostatistics Columbia University Mailman School of Public Health, NY.
Abstract
BACKGROUND: Behavioral health outpatients are at risk for self-harm. Identifying individuals or combination of risk factors could discriminate those at elevated risk for self-harm. METHODS: The study population (N = 248,491) included New York State Medicaid-enrolled individuals aged 10 to 64 with mental health clinic services between November 1, 2015 to November 1, 2016. Self-harm episodes were defined using ICD-10 codes from emergency department and inpatient visits. Multi-predictor logistic regression models were fit on a subsample of the data and compared to a testing sample based on discrimination performance (Area Under the Curve or AUC). RESULTS: Of N = 248,491 patients, 4,224 (1.70%) had an episode of intentional self-harm. Factors associated with increased self-harm risk were age 17-25, being female and having recent diagnoses of depression (AOR=4.3, 95%CI: 3.6-5.0), personality disorder (AOR=4.2, 95%CI: 2.9-6.1), or substance use disorder (AOR=3.4, 95%CI: 2.7-4.3) within the last month. A multi-predictor logistic regression model including demographics and new psychiatric diagnoses within 90 days prior to index date had good discrimination and outperformed competitor models on a testing sample (AUC=0.86, 95%CI:0.85-0.87). LIMITATIONS: New York State Medicaid data may not be generalizable to the entire U.S population. ICD-10 codes do not allow distinction between self-harm with and without intent to die. CONCLUSIONS: Our results highlight the usefulness of recency of new psychiatric diagnoses, in predicting the magnitude and timing of intentional self-harm risk. An algorithm based on this finding could enhance clinical assessments support screening, intervention and outreach programs that are at the heart of a Zero Suicide prevention model.
BACKGROUND: Behavioral health outpatients are at risk for self-harm. Identifying individuals or combination of risk factors could discriminate those at elevated risk for self-harm. METHODS: The study population (N = 248,491) included New York State Medicaid-enrolled individuals aged 10 to 64 with mental health clinic services between November 1, 2015 to November 1, 2016. Self-harm episodes were defined using ICD-10 codes from emergency department and inpatient visits. Multi-predictor logistic regression models were fit on a subsample of the data and compared to a testing sample based on discrimination performance (Area Under the Curve or AUC). RESULTS: Of N = 248,491 patients, 4,224 (1.70%) had an episode of intentional self-harm. Factors associated with increased self-harm risk were age 17-25, being female and having recent diagnoses of depression (AOR=4.3, 95%CI: 3.6-5.0), personality disorder (AOR=4.2, 95%CI: 2.9-6.1), or substance use disorder (AOR=3.4, 95%CI: 2.7-4.3) within the last month. A multi-predictor logistic regression model including demographics and new psychiatric diagnoses within 90 days prior to index date had good discrimination and outperformed competitor models on a testing sample (AUC=0.86, 95%CI:0.85-0.87). LIMITATIONS: New York State Medicaid data may not be generalizable to the entire U.S population. ICD-10 codes do not allow distinction between self-harm with and without intent to die. CONCLUSIONS: Our results highlight the usefulness of recency of new psychiatric diagnoses, in predicting the magnitude and timing of intentional self-harm risk. An algorithm based on this finding could enhance clinical assessments support screening, intervention and outreach programs that are at the heart of a Zero Suicide prevention model.
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