RIS (Refugee Identification System)
Automated and accurate identification of refugees in healthcare databases is a critical first step to investigate healthcare needs of this vulnerable population and improve health disparities. RIS is the first machine-learning method that classifies refugees and non-refugees based on an individual's age, residential address, and primary language.
The current RIS was trained and evaluated using Arizona state data. It achieved a high classification accuracy of 0.97, specificity of 0.98, sensitivity of 0.88, positive predictive value of 0.83, and negative predictive value of 0.99. The receiver operating characteristic curve (ROC) had an area under the curve (AUC) value of 0.96.
Here, we provide codes to re-train RIS with data from other US states.
The RIS Manuscript is under review in the Journal of the American Medical Informatics Association. Its preprint version is available at MedRixv.