Patterns and Influencing Factors of eHealth Tools Adoption Among Medicaid and Non-Medicaid Populations From the Health Information National Trends Survey (HINTS) 2017-2019: Questionnaire Study

dc.contributor.authorYang, Xin
dc.contributor.authorYang, Ning
dc.contributor.authorLewis, Dwight
dc.contributor.authorParton, Jason
dc.contributor.authorHudnall, Matthew
dc.contributor.otherUniversity of Alabama Tuscaloosa
dc.date.accessioned2023-09-28T19:08:47Z
dc.date.available2023-09-28T19:08:47Z
dc.date.issued2021
dc.description.abstractBackground: Evidence suggests that eHealth tools adoption is associated with better health outcomes among various populations. The patterns and factors influencing eHealth adoption among the US Medicaid population remain obscure. Objective: The objective of this study is to explore patterns of eHealth tools adoption among the Medicaid population and examine factors associated with eHealth adoption. Methods: Data from the Health Information National Trends Survey from 2017 to 2019 were used to estimate the patterns of eHealth tools adoption among Medicaid and non-Medicaid populations. The effects of Medicaid insurance status and other influencing factors were assessed with logistic regression models. Results: Compared with the non-Medicaid population, the Medicaid beneficiaries had significantly lower eHealth tools adoption rates for health information management (11.2% to 17.5% less) and mobile health for self-regulation (0.8% to 9.7% less). Conversely, the Medicaid population had significantly higher adoption rates for using social media for health information than their counterpart (8% higher in 2018, P=.01; 10.1% higher in 2019, P=.01). Internet access diversity, education, and cardiovascular diseases were positively associated with health information management and mobile health for self-regulation among the Medicaid population. Internet access diversity is the only factor significantly associated with social media adoption for acquisition of health information (OR 1.98, 95% CI 1.26-3.11). Conclusions: Our results suggest digital disparities in eHealth tools adoption between the Medicaid and non-Medicaid populations. Future research should investigate behavioral correlates and develop interventions to improve eHealth adoption and use among underserved communities.en_US
dc.format.mediumelectronic
dc.format.mimetypeapplication/pdf
dc.identifier.citationYang, X., Yang, N., Lewis, D., Parton, J., & Hudnall, M. (2021). Patterns and Influencing Factors of eHealth Tools Adoption Among Medicaid and Non-Medicaid Populations From the Health Information National Trends Survey (HINTS) 2017-2019: Questionnaire Study. In Journal of Medical Internet Research (Vol. 23, Issue 2, p. e25809). JMIR Publications Inc. https://doi.org/10.2196/25809
dc.identifier.doi10.2196/25809
dc.identifier.orcidhttps://orcid.org/0000-0003-3063-2458
dc.identifier.orcidhttps://orcid.org/0000-0003-2018-6693
dc.identifier.urihttps://ir.ua.edu/handle/123456789/10935
dc.languageEnglish
dc.language.isoen_US
dc.publisherJMIR Publications
dc.rights.licenseAttribution 4.0 International (CC BY 4.0)
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectMedicaid program
dc.subjecteHealth
dc.subjectinternet access
dc.subjectdigital divide
dc.subjecthealth information technology
dc.subjectCOMMUNICATION
dc.subjectENGAGEMENT
dc.subjectADHERENCE
dc.subjectACCESS
dc.subjectINCOME
dc.subjectHealth Care Sciences & Services
dc.subjectMedical Informatics
dc.titlePatterns and Influencing Factors of eHealth Tools Adoption Among Medicaid and Non-Medicaid Populations From the Health Information National Trends Survey (HINTS) 2017-2019: Questionnaire Studyen_US
dc.typeArticle
dc.typetext
Files
Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
10.219625809.pdf
Size:
268.94 KB
Format:
Adobe Portable Document Format