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Patient Characteristics Associated With Telemedicine Access for Primary and Specialty Ambulatory Care During the COVID-19 Pandemic.
JAMA Netw Open. 2020 12 01; 3(12):e2031640.JN

Abstract

Importance

The coronavirus disease 2019 (COVID-19) pandemic has required a shift in health care delivery platforms, necessitating a new reliance on telemedicine.

Objective

To evaluate whether inequities are present in telemedicine use and video visit use for telemedicine visits during the COVID-19 pandemic.

Design, Setting, and Participants

In this cohort study, a retrospective medical record review was conducted from March 16 to May 11, 2020, of all patients scheduled for telemedicine visits in primary care and specialty ambulatory clinics at a large academic health system. Age, race/ethnicity, sex, language, median household income, and insurance type were all identified from the electronic medical record.

Main Outcomes and Measures

A successfully completed telemedicine visit and video (vs telephone) visit for a telemedicine encounter. Multivariable models were used to assess the association between sociodemographic factors, including sex, race/ethnicity, socioeconomic status, and language, and the use of telemedicine visits, as well as video use specifically.

Results

A total of 148 402 unique patients (86 055 women [58.0%]; mean [SD] age, 56.5 [17.7] years) had scheduled telemedicine visits during the study period; 80 780 patients (54.4%) completed visits. Of 78 539 patients with completed visits in which visit modality was specified, 35 824 (45.6%) were conducted via video, whereas 24 025 (56.9%) had a telephone visit. In multivariable models, older age (adjusted odds ratio [aOR], 0.85 [95% CI, 0.83-0.88] for those aged 55-64 years; aOR, 0.75 [95% CI, 0.72-0.78] for those aged 65-74 years; aOR, 0.67 [95% CI, 0.64-0.70] for those aged ≥75 years), Asian race (aOR, 0.69 [95% CI, 0.66-0.73]), non-English language as the patient's preferred language (aOR, 0.84 [95% CI, 0.78-0.90]), and Medicaid insurance (aOR, 0.93 [95% CI, 0.89-0.97]) were independently associated with fewer completed telemedicine visits. Older age (aOR, 0.79 [95% CI, 0.76-0.82] for those aged 55-64 years; aOR, 0.78 [95% CI, 0.74-0.83] for those aged 65-74 years; aOR, 0.49 [95% CI, 0.46-0.53] for those aged ≥75 years), female sex (aOR, 0.92 [95% CI, 0.90-0.95]), Black race (aOR, 0.65 [95% CI, 0.62-0.68]), Latinx ethnicity (aOR, 0.90 [95% CI, 0.83-0.97]), and lower household income (aOR, 0.57 [95% CI, 0.54-0.60] for income <$50 000; aOR, 0.89 [95% CI, 0.85-0.92], for $50 000-$100 000) were associated with less video use for telemedicine visits. These results were similar across medical specialties.

Conclusions and Relevance

In this cohort study of patients scheduled for primary care and medical specialty ambulatory telemedicine visits at a large academic health system during the early phase of the COVID-19 pandemic, older patients, Asian patients, and non-English-speaking patients had lower rates of telemedicine use, while older patients, female patients, Black, Latinx, and poorer patients had less video use. Inequities in accessing telemedicine care are present, which warrant further attention.

Authors+Show Affiliations

Division of Cardiovascular Medicine, Department of Medicine, Hospital of the University of Pennsylvania, Philadelphia. Penn Cardiovascular Outcomes, Quality, and Evaluative Research Center, Cardiovascular Institute, University of Pennsylvania, Philadelphia. Penn Cardiovascular Center for Health Equity and Social Justice, University of Pennsylvania, Philadelphia. Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia.Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia.Division of Cardiovascular Medicine, Department of Medicine, Hospital of the University of Pennsylvania, Philadelphia. Penn Cardiovascular Center for Health Equity and Social Justice, University of Pennsylvania, Philadelphia.Division of Cardiovascular Medicine, Department of Medicine, Hospital of the University of Pennsylvania, Philadelphia. Penn Cardiovascular Center for Health Equity and Social Justice, University of Pennsylvania, Philadelphia.Division of Cardiovascular Medicine, Department of Medicine, Hospital of the University of Pennsylvania, Philadelphia. Penn Cardiovascular Outcomes, Quality, and Evaluative Research Center, Cardiovascular Institute, University of Pennsylvania, Philadelphia. Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia.Division of Cardiovascular Medicine, Department of Medicine, Hospital of the University of Pennsylvania, Philadelphia. Penn Cardiovascular Outcomes, Quality, and Evaluative Research Center, Cardiovascular Institute, University of Pennsylvania, Philadelphia. Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia.Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia.Division of Cardiovascular Medicine, Department of Medicine, Hospital of the University of Pennsylvania, Philadelphia. Penn Center for Digital Cardiology, University of Pennsylvania, Philadelphia.Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia. Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia. Renal-Electrolyte and Hypertension, Department of Medicine, Hospital of the University of Pennsylvania, Philadelphia.Hematology and Oncology Division, Department of Medicine, Hospital of the University of Pennsylvania, Philadelphia.Department of Internal Medicine, Hospital of the University of Pennsylvania, Philadelphia.Department of Internal Medicine, Hospital of the University of Pennsylvania, Philadelphia. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia.Division of Cardiovascular Medicine, Department of Medicine, Hospital of the University of Pennsylvania, Philadelphia. Penn Cardiovascular Center for Health Equity and Social Justice, University of Pennsylvania, Philadelphia.Division of Cardiovascular Medicine, Department of Medicine, Hospital of the University of Pennsylvania, Philadelphia.Division of Cardiovascular Medicine, Department of Medicine, Hospital of the University of Pennsylvania, Philadelphia.Division of Cardiovascular Medicine, Department of Medicine, Hospital of the University of Pennsylvania, Philadelphia.Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia.Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia.Department of Internal Medicine, Hospital of the University of Pennsylvania, Philadelphia. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia.Division of Cardiovascular Medicine, Department of Medicine, Hospital of the University of Pennsylvania, Philadelphia.Division of Cardiovascular Medicine, Department of Medicine, Hospital of the University of Pennsylvania, Philadelphia. Penn Cardiovascular Center for Health Equity and Social Justice, University of Pennsylvania, Philadelphia.Division of Cardiovascular Medicine, Department of Medicine, Hospital of the University of Pennsylvania, Philadelphia.Office of the Chief Medical Information Officer, University of Pennsylvania Health System, Philadelphia.Office of the Chief Medical Information Officer, University of Pennsylvania Health System, Philadelphia.Division of Cardiovascular Medicine, Department of Medicine, Hospital of the University of Pennsylvania, Philadelphia. Penn Cardiovascular Outcomes, Quality, and Evaluative Research Center, Cardiovascular Institute, University of Pennsylvania, Philadelphia. Penn Cardiovascular Center for Health Equity and Social Justice, University of Pennsylvania, Philadelphia. Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia. Office of the Chief Medical Information Officer, University of Pennsylvania Health System, Philadelphia.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

33372974

Citation

Eberly, Lauren A., et al. "Patient Characteristics Associated With Telemedicine Access for Primary and Specialty Ambulatory Care During the COVID-19 Pandemic." JAMA Network Open, vol. 3, no. 12, 2020, pp. e2031640.
Eberly LA, Kallan MJ, Julien HM, et al. Patient Characteristics Associated With Telemedicine Access for Primary and Specialty Ambulatory Care During the COVID-19 Pandemic. JAMA Netw Open. 2020;3(12):e2031640.
Eberly, L. A., Kallan, M. J., Julien, H. M., Haynes, N., Khatana, S. A. M., Nathan, A. S., Snider, C., Chokshi, N. P., Eneanya, N. D., Takvorian, S. U., Anastos-Wallen, R., Chaiyachati, K., Ambrose, M., O'Quinn, R., Seigerman, M., Goldberg, L. R., Leri, D., Choi, K., Gitelman, Y., ... Adusumalli, S. (2020). Patient Characteristics Associated With Telemedicine Access for Primary and Specialty Ambulatory Care During the COVID-19 Pandemic. JAMA Network Open, 3(12), e2031640. https://doi.org/10.1001/jamanetworkopen.2020.31640
Eberly LA, et al. Patient Characteristics Associated With Telemedicine Access for Primary and Specialty Ambulatory Care During the COVID-19 Pandemic. JAMA Netw Open. 2020 12 1;3(12):e2031640. PubMed PMID: 33372974.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Patient Characteristics Associated With Telemedicine Access for Primary and Specialty Ambulatory Care During the COVID-19 Pandemic. AU - Eberly,Lauren A, AU - Kallan,Michael J, AU - Julien,Howard M, AU - Haynes,Norrisa, AU - Khatana,Sameed Ahmed M, AU - Nathan,Ashwin S, AU - Snider,Christopher, AU - Chokshi,Neel P, AU - Eneanya,Nwamaka D, AU - Takvorian,Samuel U, AU - Anastos-Wallen,Rebecca, AU - Chaiyachati,Krisda, AU - Ambrose,Marietta, AU - O'Quinn,Rupal, AU - Seigerman,Matthew, AU - Goldberg,Lee R, AU - Leri,Damien, AU - Choi,Katherine, AU - Gitelman,Yevginiy, AU - Kolansky,Daniel M, AU - Cappola,Thomas P, AU - Ferrari,Victor A, AU - Hanson,C William, AU - Deleener,Mary Elizabeth, AU - Adusumalli,Srinath, Y1 - 2020/12/01/ PY - 2020/12/29/entrez PY - 2020/12/30/pubmed PY - 2021/1/15/medline SP - e2031640 EP - e2031640 JF - JAMA network open JO - JAMA Netw Open VL - 3 IS - 12 N2 - Importance: The coronavirus disease 2019 (COVID-19) pandemic has required a shift in health care delivery platforms, necessitating a new reliance on telemedicine. Objective: To evaluate whether inequities are present in telemedicine use and video visit use for telemedicine visits during the COVID-19 pandemic. Design, Setting, and Participants: In this cohort study, a retrospective medical record review was conducted from March 16 to May 11, 2020, of all patients scheduled for telemedicine visits in primary care and specialty ambulatory clinics at a large academic health system. Age, race/ethnicity, sex, language, median household income, and insurance type were all identified from the electronic medical record. Main Outcomes and Measures: A successfully completed telemedicine visit and video (vs telephone) visit for a telemedicine encounter. Multivariable models were used to assess the association between sociodemographic factors, including sex, race/ethnicity, socioeconomic status, and language, and the use of telemedicine visits, as well as video use specifically. Results: A total of 148 402 unique patients (86 055 women [58.0%]; mean [SD] age, 56.5 [17.7] years) had scheduled telemedicine visits during the study period; 80 780 patients (54.4%) completed visits. Of 78 539 patients with completed visits in which visit modality was specified, 35 824 (45.6%) were conducted via video, whereas 24 025 (56.9%) had a telephone visit. In multivariable models, older age (adjusted odds ratio [aOR], 0.85 [95% CI, 0.83-0.88] for those aged 55-64 years; aOR, 0.75 [95% CI, 0.72-0.78] for those aged 65-74 years; aOR, 0.67 [95% CI, 0.64-0.70] for those aged ≥75 years), Asian race (aOR, 0.69 [95% CI, 0.66-0.73]), non-English language as the patient's preferred language (aOR, 0.84 [95% CI, 0.78-0.90]), and Medicaid insurance (aOR, 0.93 [95% CI, 0.89-0.97]) were independently associated with fewer completed telemedicine visits. Older age (aOR, 0.79 [95% CI, 0.76-0.82] for those aged 55-64 years; aOR, 0.78 [95% CI, 0.74-0.83] for those aged 65-74 years; aOR, 0.49 [95% CI, 0.46-0.53] for those aged ≥75 years), female sex (aOR, 0.92 [95% CI, 0.90-0.95]), Black race (aOR, 0.65 [95% CI, 0.62-0.68]), Latinx ethnicity (aOR, 0.90 [95% CI, 0.83-0.97]), and lower household income (aOR, 0.57 [95% CI, 0.54-0.60] for income <$50 000; aOR, 0.89 [95% CI, 0.85-0.92], for $50 000-$100 000) were associated with less video use for telemedicine visits. These results were similar across medical specialties. Conclusions and Relevance: In this cohort study of patients scheduled for primary care and medical specialty ambulatory telemedicine visits at a large academic health system during the early phase of the COVID-19 pandemic, older patients, Asian patients, and non-English-speaking patients had lower rates of telemedicine use, while older patients, female patients, Black, Latinx, and poorer patients had less video use. Inequities in accessing telemedicine care are present, which warrant further attention. SN - 2574-3805 UR - https://www.unboundmedicine.com/medline/citation/33372974/Patient_Characteristics_Associated_With_Telemedicine_Access_for_Primary_and_Specialty_Ambulatory_Care_During_the_COVID_19_Pandemic_ L2 - https://jamanetwork.com/journals/jamanetworkopen/fullarticle/10.1001/jamanetworkopen.2020.31640 DB - PRIME DP - Unbound Medicine ER -