Telemedicine Use across Medical Specialties and Diagnoses

Author:

Hsiao Vivian12,Chandereng Thevaa34,Huebner Jeffrey A.15,Kunstman David T.15,Flood Grace E.1,Tevaarwerk Amye J.6,Schneider David F.12

Affiliation:

1. School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, United States

2. Department of Surgery, University of Wisconsin, Madison, Wisconsin, United States

3. UW Carbone Cancer Center, University of Wisconsin-Madison, Madison, Wisconsin, United States

4. Department of Biostatistics, Columbia University, New York, New York, United States

5. Department of Family Medicine, University of Wisconsin, Madison, Wisconsin, United States

6. Department of Oncology, Mayo Clinic, Rochester, Minnesota, United States

Abstract

Abstract Background The COVID-19 (coronavirus disease 2019) pandemic rapidly expanded telemedicine scale and scope. As telemedicine becomes routine, understanding how specialty and diagnosis combine with demographics to impact telemedicine use will aid in addressing its current limitations. Objectives To analyze the relationship between medical specialty, diagnosis, and telemedicine use, and their interplay with patient demographics in determining telemedicine usage patterns. Methods We extracted encounter and patient data of all adults who scheduled outpatient visits from June 1, 2020 to June 30, 2021 from the electronic health record of an integrated academic health system encompassing a broad range of subspecialties. Extracted variables included medical specialty, primary visit diagnosis, visit modality (video, audio, or in-person), and patient age, sex, self-reported race/ethnicity and 2013 rural–urban continuum code. Six specialties (General Surgery, Family Medicine, Gastroenterology, Oncology, General Internal Medicine, and Psychiatry) ranging from the lowest to the highest quartile of telemedicine use (video and audio) were chosen for analysis. Relative proportions of video, audio, and in-person modalities were compared. We examined diagnoses associated with the most and least frequent telemedicine use within each specialty. Finally, we analyzed associations between patient characteristics and telemedicine modality (video vs. audio/in-person, and video/audio vs. in-person) using a mixed-effects logistic regression model. Results A total of 2,494,296 encounters occurred during the study period, representing 420,876 unique patients (mean age: 44 years, standard deviation: 24 years, 54% female). Medical diagnoses requiring physical examination or minor procedures were more likely to be conducted in-person. Rural patients were more likely than urban patients to use video telemedicine in General Surgery and Gastroenterology and less likely to use video for all other specialties. Within most specialties, male patients and patients of nonwhite race were overall less likely to use video modality and video/audio telemedicine. In Psychiatry, members of several demographic groups used video telemedicine more commonly than expected, while in other specialties, members of these groups tended to use less telemedicine overall. Conclusion Medical diagnoses requiring physical examination or minor procedures are more likely to be conducted in-person. Patient characteristics (age, sex, rural vs. urban, race/ethnicity) affect video and video/audio telemedicine use differently depending on medical specialty. These factors contribute to a unique clinical scenario which impacts perceived usefulness and accessibility of telemedicine to providers and patients, and are likely to impact rates of telemedicine adoption.

Publisher

Georg Thieme Verlag KG

Subject

Health Information Management,Computer Science Applications,Health Informatics

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