Differences in Rates of Suicidal Ideation and Potential Suicide Attempt Among Disabled and Gender Minority Medicare Beneficiaries from 2009--2014

• Activity Number: 647 - Current Federal Research on Improving Measurement of LGBT Populations
• Type: Invited
• Date/Time: Thursday, August 2, 2018 : 10:30 AM to 12:20 PM
• Sponsor: ASA LGBT Concerns Committee
• Author(s): Ana M. Progovac* and Brian Mullin and Alex McDowell and Maria Jose Sanchez and Sari L. Reisner and Emilia Dunham and Cynthia Telingator and Benjamin Le Cook
• Companies: Harvard Medical School / Cambridge Health Alliance and Cambridge Health Alliance and Harvard Medical School / Cambridge Health Alliance and Cambridge Health Alliance and Harvard T.H. Chan School of Public Health and Massachusetts Department of Public Health and Cambridge Health Alliance and Harvard Medical School / Cambridge Health Alliance
• Keywords: transgender; gender minority; suicide; LGBTQ; mental health; disparities

Abstract

We identified gender minority beneficiaries in Medicare claims data using a diagnosis code algorithm, and compared them to a 5% random sample of beneficiaries from 2009-2014 within each eligibility cohort (disabled or aged ?65, based on original entitlement reason). We used logistic regression models to model any suicidal ideation, attempt, or potential suicide (y/n), adjusting for (1) age only and (2) age and mental health conditions as captured in Medicare's Chronic Conditions Warehouse. Adjusting for age only, disabled gender minority beneficiaries had higher rates of potential suicide attempt or ideation (9.2%) compared to non-gender minority disabled beneficiaries (2.5%). Predicted means fell to 2.7% vs. 1.4% respectively after adjusting for mental health conditions (both p< 0.0001). Aged gender minority beneficiaries had higher rates of potential suicide (2.5%) than non-gender minority aged beneficiaries (0.9%) after adjusting for age only; the difference was not attenuated after adjusting for mental health conditions (1.5% vs. 0.8%, respectively, both p< 0.0001). We will present additional sub-group analysis by Medicaid eligibility status and race.