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Background: 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., Objectives: This study aims to measure the correlation of socioeconomic determinants with the use of telemedicine services in Milwaukee metropolitan area., Methods: 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., Results: 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., Conclusion: 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., Competing Interests: None declared., (Thieme. All rights reserved.)

Background: Excitement around the adoption of electronic communication between physicians and patients is tempered by the possibility of increased clinical and legal risk. If patients do not read messages in a timely fashion, duplicative communication efforts may be required and patient safety may be jeopardized., Objective: We sought to assess the prevalence and risk profile of unread messages in a mature patient portal., Methods: We analyzed six years of messages (2005-2010) from physicians to patients to determine the prevalence and associated characteristics of unread messages in a patient portal. We focused on clinical messages, and excluded announcements. Because some physicians sent clinical messages to groups of patients, we labeled messages sent to more than 5 patients as "outreach" messages and excluded them from general analyses. We performed a chart review of 75 clinical messages to assess for harm., Results: We found that 3% of clinical messages were unread after 21 days. Messages arriving outside of business hours were slightly more likely to go unread (RR 1.15 95% CI 1.11-1.19). Patients who were male (OR 1.14 CI 1.04-1.26) African American (OR 1.69 CI 1.29-2.22) or Hispanic (OR 1.74 CI 1.17-2.59), or in the lowest income group (OR 1.72 CI 1.19-2.49) were more likely to have unread messages. Chart review showed no evidence of harm, but 13% of sampled unread messages were associated with potential delays in care. Incidentally, we found 50% of the physician-initiated outreach messages were unread., Conclusions: Overall, secure messaging appears a safe form of communication, but systems to notify senders when messages are unread may have value. While most clinical messages were read, many outreach messages were not, providing caution for relying on such systems for information dissemination. Similar to other studies, differences by race and income were observed and require further study.