Romanelli M, et al. - Utilizing data from the 2015 U.S. Transgender Survey, researchers studied patterns of healthcare discrimination among transgender help-seekers, using latent class analysis. To recognize subpopulations carrying the highest risk for healthcare discrimination, they explored predictors of class membership. As latent class indicators, they considered 10 healthcare experiences. There were 23,541 respondents in total. A 3-class model fit best: Class 1 encountered overt bias and interfaced with providers with limited trans-competence; Class 2 did not endure healthcare discrimination or state problems associated with providers’ trans-competence; and Class 3 did not encounter discrimination but had providers with low trans-competence. Findings revealed that across transgender help-seekers, experiences of healthcare discrimination were not homogeneous. The risk for healthcare discrimination or care from providers with limited trans-competence may be higher among transgender help-seekers holding an additional marginalized identity, as suggested by predictors of the latent classes. Improvement in these transgender help-seekers’ access to and links with care might be achieved via targeted engagement and education interventions.