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The association between electronic health information usage and patient-centered communication: a cross sectional analysis from the Health Information National Trends Survey (HINTS).
Knowles, Heidi; Swoboda, Thomas K; Sandlin, Devin; Huggins, Charles; Takami, Trevor; Johnson, Garrett; Wang, Hao.
Afiliación
  • Knowles H; Department of Emergency Medicine, JPS Health Network, 1500 S. Main St, Fort Worth, TX, 76104, USA.
  • Swoboda TK; Department of Emergency Medicine, The Valley Health System, Touro University Nevada School of Osteopathic Medicine, 657 N. Town Center Drive, Las Vegas, NV, 89144, USA.
  • Sandlin D; Department of Emergency Medicine, JPS Health Network, 1500 S. Main St, Fort Worth, TX, 76104, USA.
  • Huggins C; Department of Emergency Medicine, JPS Health Network, 1500 S. Main St, Fort Worth, TX, 76104, USA.
  • Takami T; Department of Emergency Medicine, JPS Health Network, 1500 S. Main St, Fort Worth, TX, 76104, USA.
  • Johnson G; Department of Emergency Medicine, JPS Health Network, 1500 S. Main St, Fort Worth, TX, 76104, USA.
  • Wang H; Department of Emergency Medicine, JPS Health Network, 1500 S. Main St, Fort Worth, TX, 76104, USA. hwang@ies.healthcare.
BMC Health Serv Res ; 23(1): 1398, 2023 Dec 12.
Article en En | MEDLINE | ID: mdl-38087311
ABSTRACT

BACKGROUND:

Patient-provider communication can be assessed by the patient-centered communication (PCC) score. With rapid development of electronic health (eHealth) information usage, we are uncertain of their role in PCC. Our study aims to determine the association between PCC and eHealth usage with the analysis of national representative survey data.

METHODS:

This is a cross sectional analysis using the Health Information National Trends Survey 5 (HINTS 5) cycle 1 to cycle 4 data (2017-2020). Seven specific questions were used for PCC assessment, and eHealth usage was divided into two types (private-eHealth and public-eHealth usage). A multivariate logistic regression was performed to determine the association between PCC and eHealth usage after the adjustment of other social, demographic, and clinical variables.

RESULTS:

Our study analyzed a total of 13,055 unweighted participants representing a weighted population of 791,877,728. Approximately 43% of individuals used private eHealth and 19% used public eHealth. The adjusted odds ratio (AOR) of private-eHealth usage associated with positive PCC was 1.17 (95% CI 1.02-1.35, p = 0.027). The AOR of public-eHealth usage associated with positive PCC was 0.84 (95% CI 0.71-0.99, p = 0.043).

CONCLUSION:

Our study found that eHealth usage association with PCC varies. Private-eHealth usage was positively associated with PCC, whereas public-eHealth usage was negatively associated with PCC.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Telemedicina Límite: Humans Idioma: En Revista: BMC Health Serv Res Asunto de la revista: PESQUISA EM SERVICOS DE SAUDE Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Telemedicina Límite: Humans Idioma: En Revista: BMC Health Serv Res Asunto de la revista: PESQUISA EM SERVICOS DE SAUDE Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos