Attitudes Regarding Automatic Sharing of Race, Ethnicity, and Language Data Between Healthcare Settings (Preprint)
Le résumé fourni par la source
BACKGROUND Little is known regarding patient attitudes toward automatic sharing of race, ethnicity, and language (REL) data in healthcare settings despite the universal practice of data sharing across healthcare institutions and providers. OBJECTIVE Assess public comfort with disclosing and automatically sharing REL data in healthcare settings. METHODS Using the 2022 DataHaven Community Wellbeing Survey from 1,034 adult Connecticut residents, we examined factors associated with public comfort with disclosing and automatically sharing REL data across healthcare settings. We generated unadjusted and adjusted logistic models to examine associations between factors and responses to the data-sharing questions. RESULTS Hispanic/Latino respondents were less willing to disclose REL data compared to White respondents (p<0.001). Individuals who sometimes trust healthcare providers (p=0.019) or rarely/never (p=0.040) were less willing to disclose REL data than those who almost always. African American/Black (p=0.004) and American Indian/Alaska Native (p<0.001) individuals were less likely to share REL data automatically than White individuals. Those with poor/fair self-rated health (SRH) versus very good/excellent were less likely to automatically share REL data (p=0.010). Individuals with less trust in their healthcare providers were less likely to automatically share REL data. CONCLUSIONS Racial and ethnic identity, SRH, and trust in healthcare providers affect willingness to share REL information with providers and other health systems.
Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.
Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Attitudes Regarding Automatic Sharing of Race, Ethnicity, and Language Data Between Healthcare Settings (Preprint)
- Date Crossref
- 07/10/2024
- Éditeur
- JMIR Publications Inc.
- Type
- posted-content
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.