LAUSR

Background: Transgender people experience extreme rates of violence and the electronic medical record (EMR) remains a mostly untapped resource to study the medical sequelae of such experiences. Objectives: To develop and test a method for identifying experiences of violence using EMR data. Research Design: Cross-sectional study utilizing EMR data. People: Transgender and cisgender people seen at a regional referral center in Upstate New York. Measures: We tested the utility of keyword searches and structured data queries to identify specific types of violence at various ages and in various contexts among cohorts of transgender and cisgender people. We compared the effectiveness of keyword searches to diagnosis codes and a screening question, “Are you safe at home?” using McNemar’s test. We compared the prevalence of various types of violence between transgender and cisgender cohorts using the χ2 test of independence. Results: Of the transgender cohort, 47% had experienced some type of violence versus 14% of the cisgender cohort (χ2 P value <0.001). Keywords were significantly more effective than structured data at identifying violence among both cohorts (McNemar P values all <0.05). Conclusions: Transgender people experience extreme amounts of violence throughout their lives, which is better identified and studied using keyword searches than structured EMR data. Policies are urgently needed to stop violence against transgender people. Interventions are also needed to ensure safe documentation of violence in EMRs to improve care across settings and aid research to develop and implement effective interventions.