RESUMEN
BACKGROUND: To characterize the regional and national variation in prescribing patterns in the Medicare Part D program using dimensional reduction visualization methods. METHODS: Using publicly available Medicare Part D claims data, we identified and visualized regional and national provider prescribing profile variation with unsupervised clustering and t-distributed stochastic neighbor embedding (t-SNE) dimensional reduction techniques. Additionally, we examined differences between regionally representative prescribing patterns for major metropolitan areas. RESULTS: Distributions of prescribing volume and medication diversity were highly skewed among over 800,000 Medicare Part D providers. Medical specialties had characteristic prescribing patterns. Although the number of Medicare providers in each state was highly correlated with the number of Medicare Part D enrollees, some states were enriched for providers with > 10,000 prescription claims annually. Dimension-reduction, hierarchical clustering and t-SNE visualization of drug- or drug-class prescribing patterns revealed that providers cluster strongly based on specialty and sub-specialty, with large regional variations in prescribing patterns. Major metropolitan areas had distinct prescribing patterns that tended to group by major geographical divisions. CONCLUSIONS: This work demonstrates that unsupervised clustering, dimension-reduction and t-SNE visualization can be used to analyze and visualize variation in provider prescribing patterns on a national level across thousands of medications, revealing substantial prescribing variation both between and within specialties, regionally, and between major metropolitan areas. These methods offer an alternative system-wide and pattern-centric view of such data for hypothesis generation, visualization, and pattern identification.
Asunto(s)
Prescripciones de Medicamentos/estadística & datos numéricos , Medicare Part D/estadística & datos numéricos , Pautas de la Práctica en Medicina/estadística & datos numéricos , Análisis por Conglomerados , Visualización de Datos , Humanos , Estados UnidosRESUMEN
Background: Transgender (TG) clients experience provider bias, erasure, refusal to treat, and violence. Objective: The purpose of this article is to identify barriers to healthcare for TG individuals and discuss recommendations for providers treating this population. Methods: Literature review of prime research was conducted using the Whittemore and Knafl methodology (2005). Results: Evidence suggests that barriers to TG healthcare include lack of provider TG knowledge and trans sensitivity, lack of provider communication, and lack of emotional and physical safe healthcare environments. Conclusions: TG clients face barriers to accessing healthcare, and specific recommendations to improve provider practice will decrease these barriers. Implications for Practice: Lack of provider education affects TG individuals accessing quality healthcare. Recommendations to improve provider practice are essential to improve care.