Doing Justice: Ethical Considerations Identifying and Researching Transgender and Gender Diverse People in Insurance Claims Data.
Data on the health of transgender and gender diverse (TGD) people are scarce. Researchers are increasingly turning to insurance claims data to investigate disease burden among TGD people. Since claims do not include gender self-identification or modality (i.e., TGD or not), researchers have develope...
| Publicado en: | Journal of Medical Systems Vol. 48; no. 1; pp. 1 - 8 |
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| Autores principales: | , , , , , , |
| Formato: | tables/charts Journal Article |
| Publicado: |
Springer Nature
10/12/2024
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=180519002&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 180519002 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01485598 4N0 jtl: Journal of Medical Systems issn: 01485598 maglogo: N pubinfo: dt: 10/12/2024 vid: 48 iid: 1 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 180519002 180519002 180519002 10.1007/s10916-024-02111-w 180519002 ppf: 1 ppct: 7 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Doing Justice: Ethical Considerations Identifying and Researching Transgender and Gender Diverse People in Insurance Claims Data. aug: au: Alpert, Ash B. Babbs, Gray Sanaeikia, Rebecca Ellison, Jacqueline Hughes, Landon Herington, Jonathan Dembroff, Robin affil: https://ror.org/03j7sze86 Yale Cancer Center, 333 Cedar Street, WWW 205, 06511, New Haven, CT, USA sug: subj: Transgender Persons Gender-Nonconforming Persons Insurance, Health Social Justice Ethical Issues Health Services Research Ethical Issues Research Personnel Algorithms Coding Gender Assigned at Birth Epistemology Harm Reduction Communities Resource Databases Reinforcement (Psychology) Respect Ethical Issues Beneficence Ethical Issues ab: Data on the health of transgender and gender diverse (TGD) people are scarce. Researchers are increasingly turning to insurance claims data to investigate disease burden among TGD people. Since claims do not include gender self-identification or modality (i.e., TGD or not), researchers have developed algorithms to attempt to identify TGD individuals using diagnosis, procedure, and prescription codes, sometimes also inferring sex assigned at birth and gender. Claims-based algorithms introduce epistemological and ethical complexities that have yet to be addressed in data informatics, epidemiology, or health services research. We discuss the implications of claims-based algorithms to identify and categorize TGD populations, including perpetuating cisnormative biases and dismissing TGD individuals' self-identification. Using the framework of epistemic injustice, we outline ethical considerations when undertaking claims-based TGD health research and provide suggestions to minimize harms and maximize benefits to TGD individuals and communities. pubtype: Academic Journal doctype: tables/charts Journal Article ougenre: Unknown language: English refInfo: holdings: @attributes: islocal: N |
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