@article{ref1,
title="Predictors of intentional self -harm among Medicaid mental health clinic clients in New York",
journal="Journal of affective disorders",
year="2021",
author="Rahman, Mahfuza and Leckman-Westin, Emily and Stanley, Barbara and Kammer, Jamie and Layman, Deborah and Labouliere, Christa D. and Cummings, Anni and Vasan, Prabu and Vega, Katrina and Green, Kelly L. and Brown, Gregory K. and Finnerty, Molly and Galfalvy, Hanga",
volume="ePub",
number="ePub",
pages="ePub-ePub",
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. <br><br>METHODS: The study population (N=248,491) included New York State Medicaid-enrolled individuals aged 10 to 64 with mental health specialty clinic visits 11/1/15-11/1/16. 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). <br><br>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 age17-25, 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. <br><br>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.<p /> <p>Language: en</p>",
language="en",
issn="0165-0327",
doi="10.1016/j.jad.2021.11.035",
url="http://dx.doi.org/10.1016/j.jad.2021.11.035"
}