Methodologic Approaches for Using Electronic Medical Records to Identify Experiences of Violence in Transgender and Cisgender People: Closing the Gap Between Diagnostic Coding and Lived Experiences.

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 χ 2 test of independence. RESULTS: Of the transgender cohort, 47% had experienced some type of violence versus 14% of the cisgender cohort (χ 2P 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.

From months to minutes: Creating Hyperion, a novel data management system expediting data insights for oncology research and patient care.

Here we describe the design and implementation of a novel data management platform for an academic cancer center which meets the needs of multiple stakeholders. A small, cross-functional technical team identified key challenges to creating a broad data management and access software solution: lowering the technical skill floor, reducing cost, enhancing user autonomy, optimizing data governance, and reimagining technical team structures in academia. The Hyperion data management platform was designed to meet these challenges in addition to usual considerations of data quality, security, access, stability, and scalability. Implemented between May 2019 and December 2020 at the Wilmot Cancer Institute, Hyperion includes a sophisticated custom validation and interface engine to process data from multiple sources, storing it in a database. Graphical user interfaces and custom wizards permit users to directly interact with data across operational, clinical, research, and administrative contexts. The use of multi-threaded processing, open-source programming languages, and automated system tasks (normally requiring technical expertise) minimizes costs. An integrated ticketing system and active stakeholder committee support data governance and project management. A co-directed, cross-functional team with flattened hierarchy and integration of industry software management practices enhances problem solving and responsiveness to user needs. Access to validated, organized, and current data is critical to the functioning of multiple domains in medicine. Although there are downsides to developing in-house customized software, we describe a successful implementation of custom data management software in an academic cancer center.