Background: 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.

This is the abstract only. Read the full article on the JMIR site. JMIR is the leading open access journal for eHealth and healthcare in the Internet age.

中文翻译：

---

《 2017-2019年健康信息国家趋势调查》（HINTS）中的医疗补助和非医疗补助人群中采用eHealth工具的方式和影响因素

背景：有证据表明，采用eHealth工具与各个人群中更好的健康结果有关。影响美国医疗补助人群中采用eHealth的模式和因素仍然晦涩。目的：本研究的目的是探讨医疗补助人群中采用eHealth工具的方式，并研究与采用eHealth相关的因素。方法：使用2017年至2019年《健康信息国家趋势调查》中的数据估算医疗补助和非医疗补助人群中采用eHealth工具的方式。使用Logistic回归模型评估了医疗补助保险状况和其他影响因素的影响。结果：与非医疗补助人群相比，医疗补助受益人的电子卫生保健工具采用率显着降低（用于健康信息管理）（降低11.2％至17.5％）和用于自我监管的移动医疗（降低0.8％至9.7％）。相反，医疗补助人群使用社交媒体获取健康信息的采用率明显高于相应人群（2018年增加8％，P = .01; 2019年增加10.1％，P = .01）。互联网访问的多样性，教育和心血管疾病与医疗信息管理和移动医疗密切相关，以促进医疗补助人群的自我调节。互联网访问多样性是与社交媒体采用健康信息的获取显着相关的唯一因素（OR 1.98，95％CI 1.26-3.11）。结论：我们的结果表明，医疗补助和非医疗补助人群之间在电子卫生保健工具采用方面存在数字差异。未来的研究应调查行为相关性并制定干预措施，以改善服务不足的社区中对eHealth的采用和使用。

这仅仅是抽象的。阅读JMIR网站上的全文。JMIR是互联网时代电子健康和医疗保健领域领先的开放获取期刊。