Oliver T Nguyen, Amelia K Watson, Kartik Motwani, Chloe Warpinski, Katelin McDilda, Carlos Leon, Neel Khanna, Ryan W Nall, Kea Turner
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Logistic regression analyses were conducted. <b>Results:</b> Across 198 adult patients, 56.6% received telemedicine care. Of these, 99.1% elected for audio-only telemedicine instead of video telemedicine. Telemedicine use was more likely among those living within 15 miles of their clinic (adjusted odds ratio [aOR] = 4.43, 95% confidence interval [CI] 1.70-11.53). It was less likely to be used by older patients (aOR = 0.97, 95% CI 0.94-1.00), patients of male sex (aOR = 0.85, 95% CI 0.18-0.92), and those establishing care as a new patient (aOR = 0.01, 95% CI 0.00-0.07). <b>Conclusion:</b> The moderate usage of telemedicine suggests that its implementation in free clinics may be feasible. Solutions specific to patients with smartphone-only internet access are needed to improve the use of video telemedicine as smartphone-specific factors (e.g., data use limits) may influence the ability for underserved patients to receive video telemedicine.</p>","PeriodicalId":520784,"journal":{"name":"Telemedicine journal and e-health : the official journal of the American Telemedicine Association","volume":" ","pages":"526-534"},"PeriodicalIF":0.0000,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"Patient-Level Factors Associated with Utilization of Telemedicine Services from a Free Clinic During COVID-19.\",\"authors\":\"Oliver T Nguyen, Amelia K Watson, Kartik Motwani, Chloe Warpinski, Katelin McDilda, Carlos Leon, Neel Khanna, Ryan W Nall, Kea Turner\",\"doi\":\"10.1089/tmj.2021.0102\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p><b>Background:</b> Disparities in telemedicine use by race, age, and income have been consistently documented. To date, research has focused on telemedicine use among patients with adequate insurance coverage. To address this gap, this study identifies patient-level factors associated with telemedicine use during the coronavirus (COVID-19) pandemic among one free clinic network's patients who are underinsured or uninsured. <b>Methods:</b> Electronic health record data were reviewed for patient-level data on patients seen from March 2020 to September 2020. Patients were grouped by telemedicine use history. We controlled for sociodemographic factors (e.g., age, race/ethnicity) and comorbidities. Logistic regression analyses were conducted. <b>Results:</b> Across 198 adult patients, 56.6% received telemedicine care. Of these, 99.1% elected for audio-only telemedicine instead of video telemedicine. Telemedicine use was more likely among those living within 15 miles of their clinic (adjusted odds ratio [aOR] = 4.43, 95% confidence interval [CI] 1.70-11.53). It was less likely to be used by older patients (aOR = 0.97, 95% CI 0.94-1.00), patients of male sex (aOR = 0.85, 95% CI 0.18-0.92), and those establishing care as a new patient (aOR = 0.01, 95% CI 0.00-0.07). <b>Conclusion:</b> The moderate usage of telemedicine suggests that its implementation in free clinics may be feasible. Solutions specific to patients with smartphone-only internet access are needed to improve the use of video telemedicine as smartphone-specific factors (e.g., data use limits) may influence the ability for underserved patients to receive video telemedicine.</p>\",\"PeriodicalId\":520784,\"journal\":{\"name\":\"Telemedicine journal and e-health : the official journal of the American Telemedicine Association\",\"volume\":\" \",\"pages\":\"526-534\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Telemedicine journal and e-health : the official journal of the American Telemedicine Association\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1089/tmj.2021.0102\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2021/7/13 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Telemedicine journal and e-health : the official journal of the American Telemedicine Association","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1089/tmj.2021.0102","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2021/7/13 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14
摘要
背景:远程医疗使用的种族、年龄和收入差异一直被记录在案。迄今为止,研究主要集中在有足够保险覆盖的患者中远程医疗的使用。为了解决这一差距,本研究在一个免费诊所网络的保险不足或未保险的患者中确定了冠状病毒(COVID-19)大流行期间与远程医疗使用相关的患者层面因素。方法:回顾2020年3月至2020年9月期间患者的电子健康记录数据。患者按远程医疗使用史分组。我们控制了社会人口因素(如年龄、种族/民族)和合并症。进行Logistic回归分析。结果:198例成人患者中,56.6%接受了远程医疗护理。其中,99.1%的人选择纯音频远程医疗,而不是视频远程医疗。居住在诊所15英里以内的人更有可能使用远程医疗(调整后的优势比[aOR] = 4.43, 95%可信区间[CI] 1.70-11.53)。老年患者(aOR = 0.97, 95% CI 0.94-1.00)、男性患者(aOR = 0.85, 95% CI 0.18-0.92)和作为新患者开始护理的患者(aOR = 0.01, 95% CI 0.00-0.07)使用该方法的可能性较小。结论:远程医疗的适度使用表明在义诊实施远程医疗是可行的。需要针对只能使用智能手机上网的患者的特定解决方案来改善视频远程医疗的使用,因为智能手机特定因素(例如,数据使用限制)可能会影响服务不足的患者接受视频远程医疗的能力。
Patient-Level Factors Associated with Utilization of Telemedicine Services from a Free Clinic During COVID-19.
Background: Disparities in telemedicine use by race, age, and income have been consistently documented. To date, research has focused on telemedicine use among patients with adequate insurance coverage. To address this gap, this study identifies patient-level factors associated with telemedicine use during the coronavirus (COVID-19) pandemic among one free clinic network's patients who are underinsured or uninsured. Methods: Electronic health record data were reviewed for patient-level data on patients seen from March 2020 to September 2020. Patients were grouped by telemedicine use history. We controlled for sociodemographic factors (e.g., age, race/ethnicity) and comorbidities. Logistic regression analyses were conducted. Results: Across 198 adult patients, 56.6% received telemedicine care. Of these, 99.1% elected for audio-only telemedicine instead of video telemedicine. Telemedicine use was more likely among those living within 15 miles of their clinic (adjusted odds ratio [aOR] = 4.43, 95% confidence interval [CI] 1.70-11.53). It was less likely to be used by older patients (aOR = 0.97, 95% CI 0.94-1.00), patients of male sex (aOR = 0.85, 95% CI 0.18-0.92), and those establishing care as a new patient (aOR = 0.01, 95% CI 0.00-0.07). Conclusion: The moderate usage of telemedicine suggests that its implementation in free clinics may be feasible. Solutions specific to patients with smartphone-only internet access are needed to improve the use of video telemedicine as smartphone-specific factors (e.g., data use limits) may influence the ability for underserved patients to receive video telemedicine.