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Beyond Gender Identity Disorder Diagnoses Codes: An Examination of Additional Methods to Identify Transgender Individuals in Administrative Databases.
Jasuja, Guneet K; de Groot, Alexander; Quinn, Emily K; Ameli, Omid; Hughto, Jaclyn M W; Dunbar, Michael; Deutsch, Madeline; Streed, Carl G; Paasche-Orlow, Michael K; Wolfe, Hill L; Rose, Adam J.
Afiliação
  • Jasuja GK; Center for Healthcare Organization and Implementation Research (CHOIR), ENRM VAMC, Bedford.
  • de Groot A; Department of Health Law, Policy and Management, Boston University School of Public Health, Boston, MA.
  • Quinn EK; OptumLabs, Eden Prairie, MN.
  • Ameli O; Biostatistics and Epidemiology Data Analytics Center, Boston University School of Public Health, Boston, MA.
  • Hughto JMW; Biostatistics and Epidemiology Data Analytics Center, Boston University School of Public Health, Boston, MA.
  • Dunbar M; OptumLabs, Eden Prairie, MN.
  • Deutsch M; Departments of Behavioral and Social Sciences and Epidemiology, Brown School of Public Health.
  • Streed CG; Center for Health Promotion and Health Equity, Brown University, Providence, RI.
  • Paasche-Orlow MK; The Fenway Institute, Fenway Health, Boston, MA.
  • Wolfe HL; RAND Corporation, Health Care Division, Pittsburgh, PA.
  • Rose AJ; UCSF Transgender Care, Department of Family and Community Medicine, University of California, San Francisco, CA.
Med Care ; 58(10): 903-911, 2020 10.
Article em En | MEDLINE | ID: mdl-32925416
ABSTRACT

BACKGROUND:

Large administrative databases often do not capture gender identity data, limiting researchers' ability to identify transgender people and complicating the study of this population.

OBJECTIVE:

The objective of this study was to develop methods for identifying transgender people in a large, national dataset for insured adults. RESEARCH

DESIGN:

This was a retrospective analysis of administrative claims data. After using gender identity disorder (GID) diagnoses codes, the current method for identifying transgender people in administrative data, we used the following 2 strategies to improve the accuracy of identifying transgender people that involved (1) Endocrine Disorder Not Otherwise Specified (Endo NOS) codes and a transgender-related procedure code; or (2) Receipt of sex hormones not associated with the sex recorded in the patient's chart (sex-discordant hormone therapy) and an Endo NOS code or transgender-related procedure code.

SUBJECTS:

Seventy-four million adults 18 years and above enrolled at some point in commercial or Medicare Advantage plans from 2006 through 2017.

RESULTS:

We identified 27,227 unique transgender people overall; 18,785 (69%) were identified using GID codes alone. Using Endo NOS with a transgender-related procedure code, and sex-discordant hormone therapy with either Endo NOS or transgender-related procedure code, we added 4391 (16%) and 4051 (15%) transgender people, respectively. Of the 27,227 transgender people in our cohort, 8694 (32%) were transmasculine, 3959 (15%) were transfeminine, and 14,574 (54%) could not be classified.

CONCLUSION:

In the absence of gender identity data, additional data elements beyond GID codes improves the identification of transgender people in large, administrative claims databases.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Bases de Dados Factuais / Pessoas Transgênero / Análise de Dados Tipo de estudo: Diagnostic_studies / Observational_studies / Prognostic_studies Limite: Adult / Aged / Female / Humans / Male / Middle aged País/Região como assunto: America do norte Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Bases de Dados Factuais / Pessoas Transgênero / Análise de Dados Tipo de estudo: Diagnostic_studies / Observational_studies / Prognostic_studies Limite: Adult / Aged / Female / Humans / Male / Middle aged País/Região como assunto: America do norte Idioma: En Ano de publicação: 2020 Tipo de documento: Article