Events / Biomedical Data Science Seminar Series: “Evaluating an existing suicide risk prediction tool in Transgender patients” (Robert “Alex” Becker)

Biomedical Data Science Seminar Series: “Evaluating an existing suicide risk prediction tool in Transgender patients” (Robert “Alex” Becker)

December 13, 2023
4:00 pm - 5:00 pm

John Morgan Building, Reunion Auditorium

Abstract: Validated in a general hospital population, the Vanderbilt Suicide Attempt and Ideation Likelihood (VSAIL) model predicts risk of suicide 30 days post-visit. VSAIL performance differed between clinical settings, noting worse performance in behavioral health. Creating “site- aware” VSAIL models may improve performance in clinics but does not guarantee equitable performance for historically underrepresented groups, like the transgender and gender diverse (TGD) community. We first performed a systematic review of methods used to identify TGD patients in electronic health record (EHR) data, finding that combining structured and unstructured data offered the most consistent results. We then developed a method to ascertain the status of TGD patients using novel identifiers (pronouns and ICD-10 codes alone) and verified TGD status via manual review of clinical notes; successfully identifying 2523 patients and achieving a positive predictive value (PPV) of 99.49%. We leveraged the confirmed and verified TGD cohort to evaluate the performance of VSAIL in TGD patients. We found that VSAIL was not well calibrated for the TGD cohort with a Spiegelhalter’s p-value <0.001. VSAIL had high false negative rates (between 27.5% and 77.2%, depending on the selected score threshold), and PPV values (between 6.1% and 19.3%). This indicates that visits with high VSAIL scores are likely followed by a suicide event but between 27.5% and 77.2% of visits that are followed by a suicide event do not generate a sufficiently high VSAIL score.


Bio: Robert (Alex) Becker is a PhD candidate in Biomedical Informatics at Vanderbilt University. He earned a BS in biomedical engineering from the University of Cincinnati and an MS in biomedical informatics from Vanderbilt. His thesis focused on health equity, electronic health record phenotyping, and risk prediction. For his dissertation, he hopes to draw on these experiences and expand into mixed methods informatics approaches to foster shared decision making. Academically, Alex is very passionate about STEM education and undergraduate research opportunities. He’s recently earned a certificate in college teaching; served as a graduate teaching assistant for his department’s summer internship program for the last three years; will launch a biomedical informatics-focused, semester-long virtual course for 11th and 12th grade students early next year; and recently advocated to house and senate representatives of Tennessee on the importance of federal funding for undergraduate research experiences through an event hosted by the Council on Undergraduate Research. Outside of work, Alex enjoys spending time outdoors (especially hiking) and attempting new recipes in his air fryer.