Validating a predictive algorithm for suicide risk with Alaska Native populations.
Suicide Life Threat Behav
; 52(4): 696-704, 2022 08.
Article
em En
| MEDLINE
| ID: mdl-35293010
ABSTRACT
INTRODUCTION:
The American Indian/Alaska Native (AI/AN) suicide rate in Alaska is twice the state rate and four times the U.S. rate. Healthcare systems need innovative methods of suicide risk detection. The Mental Health Research Network (MHRN) developed suicide risk prediction algorithms in a general U.S.METHODS:
We applied MHRN predictors and regression coefficients to electronic health records of AI/AN patients aged ≥13 years with behavioral health diagnoses and primary care visits between October 1, 2016, and March 30, 2018. Logistic regression assessed model accuracy for predicting and stratifying risk for suicide attempt within 90 days after a visit. We compared expected to observed risk and assessed model performance characteristics.RESULTS:
10,864 patients made 47,413 primary care visits. Suicide attempt occurred after 589 (1.2%) visits. Visits in the top 5% of predicted risk accounted for 40% of actual attempts. Among visits in the top 0.5% of predicted risk, 25.1% were followed by suicide attempt. The best fitting model had an AUC of 0.826 (95% CI 0.809-0.843).CONCLUSIONS:
The MHRN model accurately predicted suicide attempts among AI/AN patients. Future work should develop clinical and operational guidance for effective implementation of the model with this population.Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Indígenas Norte-Americanos
Tipo de estudo:
Etiology_studies
/
Guideline
/
Prognostic_studies
/
Risk_factors_studies
Limite:
Humans
País/Região como assunto:
America do norte
Idioma:
En
Revista:
Suicide Life Threat Behav
Ano de publicação:
2022
Tipo de documento:
Article
País de afiliação:
Estados Unidos