CHSU Discovery

Abstract:

Human trafficking (HT) is a growing concern throughout the United States, with a large and increasing population of victims lacking primary health care and reporting to emergency departments for treatment. Regionally, Central California is a major hub for human trafficking but has limited social service resources. The current problem being addressed is how to better identify likely human trafficking victims for the limited social service consults. Our hypothesis is that certain electronic medical record indicators can selectively identify victims with reduced false negatives compared to the status quo. The methods for this research project are to obtain data from a small cohort of known human trafficking victims (less than 20 patients) and control patients (between 100-500) that were admitted. We will quantify the false positive, false negative, and other statistical information for each variable both alone and in combination. The data will be provided as de-identified. There is no harm to the patient greater than normal daily activity. Moving forward, we want to conduct a retrospective chart review at Kaweah Health to test if the curated identifiable factors accurately predict if a patient is an HT victim in a clinical setting. We plan to go through randomized patient files, note which patients are positive for the identifiable factors listed below, and note whether the patient was an identified HT victim.