The telemedicine industry has been experiencing fast growth in recent years. The outbreak of coronavirus disease 2019 (COVID-19) further accelerated the deployment and utilization of telemedicine services. An analysis of the socioeconomic characteristics of telemedicine users to understand potential socioeconomic gaps and disparities is critical for improving the adoption of telemedicine services among patients.This study aims to measure the correlation of socioeconomic determinants with the use of telemedicine services in Milwaukee metropolitan area.Electronic health record review of patients using telemedicine services compared with those not using telemedicine services within an academic-community health system: patient demographics (e.g., age, gender, race, and ethnicity), insurance status, and socioeconomic determinants obtained through block-level census data in Milwaukee area. The telemedicine users were compared with all other patients using regression analysis. The telemedicine adoption rates were calculated across regional ZIP codes to analyze the geographic patterns of telemedicine adoption.A total of 104,139 patients used telemedicine services during the study period. Patients who used video visits were younger (median age 48.12), more likely to be White (odds ratio [OR] 1.34; 95% confidence interval [CI], 1.31-1.37), and have private insurance (OR 1.43; CI, 1.41-1.46); patients who used telephone visits were older (median age 57.58), more likely to be Black (OR 1.31; CI 1.28-1.35), and have public insurance (OR 1.30; CI 1.27-1.32). In general, Latino and Asian populations were less likely to use telemedicine; women used more telemedicine services in general than men. In the multiple regression analysis of social determinant factors across 126 ZIP codes, college education (coefficient 1.41, p = 0.01) had a strong correlation to video telemedicine adoption rate.Adoption of telemedicine services was significantly impacted by the social determinant factors of health, such as income, education level, race, and insurance type. The study reveals the potential inequities and disparities in telemedicine adoption.

Jake Luo

Ling Tong

Bradley H. Crotty

Melek Somai

Bradley Taylor

Kristen Osinski

Ben George

Applied Clinical Informatics

ACI 是第三本涉及生物医学和健康信息学的 SCHATTAUER 期刊。它完美地补充了我们的其他期刊 ÖFFNET INTERNEN LINK IM AKTUELLEN FENSTERMETHODS OF INFORMATION IN MEDICINE 和 ÖFFNET INTERNEN LINK IM AKTUELLEN FENSTERYEARBOOK OF MEDICAL INFORMATICS。 THE YEARBOOK OF MEDICAL INFORMATICS 是 IMIA 的“里程碑”或最先进的期刊，METHOD OF INFORMATION IN MEDICINE 是 IMIA 的“SCIENCE AND RESEARCH”期刊，ACI 打算成为 IMIA 的“PRACTICAL”期刊。

Applied Clinical Informatics is the third journal published by SCHATTAUER that focuses on biomedical and health informatics. It complements our other journals, Methods of Information in Medicine and Yearbook of Medical Informatics. The Yearbook of Medical Informatics is considered IMIA's 'milestone' or leading journal, while Methods of Information in Medicine serves as IMIA's 'science and research' journal. Applied Clinical Informatics aims to be IMIA's 'practical' journal.

《Applied Clinical Informatics》是第三本涉及生物医学和健康信息学的SCHATTAUER期刊。它完美地补充了我们的其他期刊《Methods of Information in Medicine》和《Yearbook of Medical Informatics》。其中，《Yearbook of Medical Informatics》是IMIA的“里程碑”或最先进的期刊，而《Methods of Information in Medicine》则是IMIA的“科学与研究”期刊。《Applied Clinical Informatics》旨在成为IMIA的“实用”期刊。

Telemedicine Adoption during the COVID-19 Pandemic: Gaps and Inequalities

Adoption of telemedicine services was significantly impacted by the social determinant factors of health, such as income, education level, race, and insurance type, and the study reveals the potential inequities and disparities in teleMedicine adoption.

Category	Quartile
医学	2
医学, 医学信息	3

Telemedicine Adoption during the COVID-19 Pandemic: Gaps and Inequalities

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