Wakeman Michael, Buckman Dennis W, El-Toukhy Sherine
Division of Intramural Research, National Institute on Minority Health and Health Disparities, National Institutes of Health, Rockville, Maryland.
Information Management Services, Calverton, Maryland.
JAMA Netw Open. 2025 Apr 1;8(4):e255359. doi: 10.1001/jamanetworkopen.2025.5359.
Digital health care services expanded with the COVID-19 pandemic. Disparities in telehealth, telemedicine, and telemonitoring use remain understudied.
To examine associations between individual-level characteristics and digital health care use and if these associations differ by county-level social vulnerability.
DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study was an online survey that included a nonprobability sample of US adults aged 18 years or older who resided in 871 counties in the least or most vulnerable quartiles of the Minority Health Social Vulnerability Index (MHSVI), an indicator of county-level social vulnerability. The study was conducted between February and August 2022, and data were analyzed from August 2023 to August 2024.
Participant characteristics and MHSVI county-level social vulnerability.
Self-reported use of telehealth, telemedicine, and telemonitoring. Multivariable logistic regression models were fit to examine associations between sociodemographic, health, and technology factors and each service use, overall and stratified by MHSVI.
Of the 5444 participants who were included in this study, 2927 were female (53.77%), 798 were non-Hispanic Black or African American (14.66%), 838 were Hispanic or Latino (15.39%), 3542 were non-Hispanic White (65.06%); the mean (SE) age was 45.4 (0.2) years. Overall, 2754 participants used telehealth (50.59%), 1609 used telemedicine (29.56%), and 854 used telemonitoring (15.69%). Being English nonproficient (adjusted odds ratio [aOR], 1.54; 95% CI, 1.23-1.92) and having had in-person health care visits (aOR, 4.71; 95% CI, 3.93-5.63) were associated with higher odds of using telehealth, whereas not having a primary care clinician was associated with lower odds (aOR, 0.68; 95% CI, 0.59-0.78). Similar findings were documented for telemedicine and telemonitoring use. Education was associated with higher odds of digital health care use in MHSVI most vulnerable counties (telehealth: aOR, 1.18; 95% CI, 1.06-1.32; telemedicine: aOR, 1.18; 95% CI, 1.05-1.33), whereas individuals who did not self-identify as heterosexual (telehealth: aOR, 1.47; 95% CI, 1.10-1.97; telemedicine: aOR, 1.57; 95% CI, 1.16-2.11; telemonitoring: aOR, 1.54; 95% CI, 1.02-2.31) and those who self-reported fair or poor mental health (telehealth: aOR, 1.29; 95% CI, 1.03-1.61) had higher odds of digital service use in the least vulnerable counties. Self-identifying as Black or African American or Hispanic was associated with high odds of telehealth (Black or African American: aOR, 1.41; 95% CI, 1.17-1.70; Hispanic or Latino: aOR, 1.41; 95% CI, 1.17-1.70), telemedicine (Black or African American: aOR, 1.44; 95% CI, 1.18-1.76; Hispanic or Latino: aOR, 1.27; 95% CI, 1.04-1.54), and telemonitoring (Black or African American: aOR, 1.40; 95% CI, 1.11-1.78; Hispanic or Latino: aOR, 1.46; 95%CI, 1.16-1.84) use overall, but these associations varied across MHSVI strata.
In this cross-sectional study of US adults from MHSVI most and least vulnerable counties, digital health care use varied by participant characteristics. Some traditionally underserved groups self-reported higher use of digital health care. Differing associations between individual-level characteristics and digital health care use by county-level social vulnerability reflect the importance of place-based disadvantage indicators. Eliminating digital health care use disparities is important as it represents a complementary avenue to access health care for underserved populations.
随着新冠疫情的爆发，数字医疗服务得到了扩展。远程医疗、远程医学和远程监测使用方面的差异仍未得到充分研究。
研究个体层面特征与数字医疗使用之间的关联，以及这些关联在县级社会脆弱性方面是否存在差异。
设计、设置和参与者：这项横断面研究是一项在线调查，纳入了居住在少数族裔健康社会脆弱性指数（MHSVI）最脆弱或最不脆弱四分位数的871个县中的18岁及以上美国成年人的非概率样本，MHSVI是县级社会脆弱性的一个指标。该研究于2022年2月至8月进行，数据于2023年8月至2024年8月进行分析。
参与者特征和MHSVI县级社会脆弱性。
自我报告的远程医疗、远程医学和远程监测使用情况。采用多变量逻辑回归模型来研究社会人口学、健康和技术因素与每种服务使用之间的关联，总体分析以及按MHSVI分层分析。
本研究纳入的5444名参与者中，2927名是女性（53.77%），798名是非西班牙裔黑人或非裔美国人（14.66%），838名是西班牙裔或拉丁裔（15.39%），3542名是非西班牙裔白人（65.06%）；平均（SE）年龄为45.4（0.2）岁。总体而言，2754名参与者使用过远程医疗（50.59%），1609名使用过远程医学（29.56%），854名使用过远程监测（15.69%）。英语不熟练（调整后的优势比[aOR]，1.54；95%置信区间[CI]，1.23 - 1.92）以及有过面对面医疗就诊经历（aOR，4.71；95% CI，3.93 - 5.63）与使用远程医疗的较高几率相关，而没有初级保健医生则与较低几率相关（aOR，0.68；95% CI，0.59 - 0.78）。远程医学和远程监测使用也有类似发现。在MHSVI最脆弱的县，教育程度与使用数字医疗的较高几率相关（远程医疗：aOR，1.18；95% CI，1.06 - 1.32；远程医学：aOR，1.18；95% CI，1.05 - 1.33），而在最不脆弱的县，不自我认定为异性恋者（远程医疗：aOR，1.47；95% CI，1.10 - 1.97；远程医学：aOR，1.57；95% CI，1.16 - 2.11；远程监测：aOR，1.54；95% CI，1.02 - 2.31）以及自我报告心理健康状况为一般或较差者（远程医疗：aOR，1.29；95% CI，1.03 - 1.61）使用数字服务的几率较高。总体而言，自我认定为黑人或非裔美国人或西班牙裔与使用远程医疗（黑人或非裔美国人：aOR，1.41；95% CI，1.17 - 1.70；西班牙裔或拉丁裔：aOR，1.41；95% CI，1.17 - 1.70）、远程医学（黑人或非裔美国人：aOR，1.44；95% CI，1.18 - 1.76；西班牙裔或拉丁裔：aOR，1.27；95% CI，1.04 - 1.54）和远程监测（黑人或非裔美国人：aOR，1.40；95% CI，1.11 - 1.78；西班牙裔或拉丁裔：aOR，1.46；95% CI，1.16 - 1.84）的较高几率相关，但这些关联在MHSVI各层中有所不同。
在这项对MHSVI最脆弱和最不脆弱县的美国成年人进行的横断面研究中，数字医疗的使用因参与者特征而异。一些传统上服务不足的群体自我报告使用数字医疗的比例较高。个体层面特征与数字医疗使用之间的关联在县级社会脆弱性方面存在差异，这反映了基于地点的劣势指标的重要性。消除数字医疗使用方面的差异很重要，因为这是为服务不足人群提供医疗服务的一条补充途径。
