Skip to main content

Main menu

  • HOME
  • ARTICLES
    • Current Issue
    • Ahead of Print
    • Archives
    • Abstracts In Press
    • Special Issue Archive
    • Subject Collections
  • INFO FOR
    • Authors
    • Reviewers
    • Call For Papers
    • Subscribers
    • Advertisers
  • SUBMIT
    • Manuscript
    • Peer Review
  • ABOUT
    • The JABFM
    • The Editing Fellowship
    • Editorial Board
    • Indexing
    • Editors' Blog
  • CLASSIFIEDS
  • Other Publications
    • abfm

User menu

Search

  • Advanced search
American Board of Family Medicine
  • Other Publications
    • abfm
American Board of Family Medicine

American Board of Family Medicine

Advanced Search

  • HOME
  • ARTICLES
    • Current Issue
    • Ahead of Print
    • Archives
    • Abstracts In Press
    • Special Issue Archive
    • Subject Collections
  • INFO FOR
    • Authors
    • Reviewers
    • Call For Papers
    • Subscribers
    • Advertisers
  • SUBMIT
    • Manuscript
    • Peer Review
  • ABOUT
    • The JABFM
    • The Editing Fellowship
    • Editorial Board
    • Indexing
    • Editors' Blog
  • CLASSIFIEDS
  • JABFM on Bluesky
  • JABFM On Facebook
  • JABFM On Twitter
  • JABFM On YouTube
Research ArticleOriginal Research

Prevalence and Factors Associated with Family Physicians Providing E-Visits

Michael R. Peabody, Mingliang Dai, Kea Turner, Lars E. Peterson and Arch G. Mainous
The Journal of the American Board of Family Medicine November 2019, 32 (6) 868-875; DOI: https://doi.org/10.3122/jabfm.2019.06.190081
Michael R. Peabody
From the American Board of Family Medicine, Lexington, KY (MRP, MD, LEP); Department of Health Services Research, Management and Policy, University of Florida, Gainesville, FL (KT, ARM); Department of Family and Community Medicine, University of Kentucky, Lexington, KY (LEP); Department of Family Medicine and Community Health, University of Florida, Gainesville, FL (AGM).
PhD
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Mingliang Dai
From the American Board of Family Medicine, Lexington, KY (MRP, MD, LEP); Department of Health Services Research, Management and Policy, University of Florida, Gainesville, FL (KT, ARM); Department of Family and Community Medicine, University of Kentucky, Lexington, KY (LEP); Department of Family Medicine and Community Health, University of Florida, Gainesville, FL (AGM).
PhD
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Kea Turner
From the American Board of Family Medicine, Lexington, KY (MRP, MD, LEP); Department of Health Services Research, Management and Policy, University of Florida, Gainesville, FL (KT, ARM); Department of Family and Community Medicine, University of Kentucky, Lexington, KY (LEP); Department of Family Medicine and Community Health, University of Florida, Gainesville, FL (AGM).
PhD, MPH, MA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Lars E. Peterson
From the American Board of Family Medicine, Lexington, KY (MRP, MD, LEP); Department of Health Services Research, Management and Policy, University of Florida, Gainesville, FL (KT, ARM); Department of Family and Community Medicine, University of Kentucky, Lexington, KY (LEP); Department of Family Medicine and Community Health, University of Florida, Gainesville, FL (AGM).
MD, PhD
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Arch G. Mainous III
From the American Board of Family Medicine, Lexington, KY (MRP, MD, LEP); Department of Health Services Research, Management and Policy, University of Florida, Gainesville, FL (KT, ARM); Department of Family and Community Medicine, University of Kentucky, Lexington, KY (LEP); Department of Family Medicine and Community Health, University of Florida, Gainesville, FL (AGM).
PhD
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Article
  • Figures & Data
  • References
  • Info & Metrics
  • PDF
Loading

Article Figures & Data

Tables

    • View popup
    Table 1.

    Individual and Practice Characteristics of Practicing Physicians Who Registered for the 2017 American Board of Family Medicine Certification Examination by Whether They Provided e-Visits or Not

    VariableTotal (N = 7580)Do Not Offer E-Visits (N = 6878)Offer E-Visits (N = 702)P Value
    Race, n (%).559
        American Indian or Alaska Native69 (0.9)62 (0.9)7 (1.0)
        Asian1115 (14.7)1011 (14.7)104 (14.8)
        Black or African American459 (6.1)406 (5.9)53 (7.6)
        Native Hawaiian or Other Pacific Islander36 (0.5)32 (0.5)4 (0.6)
        Other431 (5.7)395 (5.7)36 (5.1)
        White5470 (72.2)4972 (72.3)498 (70.9)
    Ethnicity, n (%).606
        Hispanic or Latino527 (7.0)482 (7.0)45 (6.4)
        Non-Hispanic7053 (93.0)6396 (93.0)657 (93.6)
    Gender, n (%).041
        Female3292 (43.4)2961 (43.1)331 (47.2)
        Male4288 (56.6)3917 (56.9)371 (52.8)
    Medical school training*, n (%).018
        IMG1667 (22.0)1538 (22.4)129 (18.4)
        USMG5896 (78.0)5325 (77.6)571 (81.6)
    Practice site ownership status, n (%)<.001
        No official ownership stake (100% employed)4770 (62.9)4352 (63.3)418 (59.5)
        Partial owner or shareholder1427 (18.8)1247 (18.1)180 (25.6)
        Self-employed as a contractor (including locums)240 (3.2)219 (3.2)21 (3.0)
        Sole owner1051 (13.9)976 (14.2)75 (10.7)
        Other92 (1.21)84 (1.22)8 (1.14)
    Practice site size, n (%)<.001
        Solo practice953 (12.6)887 (12.9)66 (9.4)
        2 to 5 providers2624 (34.6)2449 (35.6)175 (24.9)
        6 to 20 providers2323 (30.6)2102 (30.6)221 (31.5)
        >20 providers1680 (22.2)1440 (20.9)240 (34.2)
    Practice site specialty mix, n (%)<.001
        Family medicine only3940 (52.0)3627 (52.7)313 (44.6)
        Multiple specialties (not only primary care)1594 (21.0)1393 (20.3)201 (28.6)
        Primary care specialty mix (Family Medicine, Internal Medicine and/or Pediatrics)2046 (27.0)1858 (27.0)188 (26.8)
    Faculty status, n (%).001
        No5130 (67.7)4695 (68.3)435 (62.0)
        Yes, core/salaried faculty744 (9.8)672 (9.8)72 (10.3)
        Yes, volunteer/clinical faculty1706 (22.5)1511 (22.0)195 (27.8)
    Hours per week worked, n (%)<.001
        0 to 8277 (3.7)260 (3.8)17 (2.4)
        9 to 16469 (6.2)418 (6.1)51 (7.3)
        17 to 24803 (10.6)717 (10.4)86 (12.3)
        25 to 321712 (22.6)1501 (21.8)211 (30.1)
        33 to 391360 (17.9)1242 (18.1)118 (16.8)
        40 or more2959 (39.0)2740 (39.8)219 (31.2)
    Years in Practice, n (%).180
        0 to 101991 (26.3)1811 (26.3)180 (25.6)
        11 to 202555 (33.7)2316 (33.7)239 (34.0)
        21 to 292135 (28.2)1920 (27.9)215 (30.6)
        30 or more899 (11.9)831 (12.1)68 (9.7)
    Primary practice type, n (%)<.001
        Private practice2645 (34.9)2480 (36.1)165 (23.5)
        Academic health center517 (6.8)472 (6.9)45 (6.4)
        Federal (military, Veterans Administration/Department of Defense)400 (5.3)348 (5.1)52 (7.4)
        Managed care/HMO practice407 (5.4)268 (4.0)139 (19.8)
        Hospital-/health system-owned2513 (33.2)2277 (33.1)236 (33.6)
        Safety Net726 (9.6)690 (10.0)36 (5.1)
        Other372 (4.9)343 (5.0)29 (4.1)
    Scope of practice, mean (SD)13.2 (3.7)13.1 (3.7)13.6 (3.6).002
    Age in years, mean (SD)51.7 (9.00)51.7 (9.0)51.4 (8.6).295
    • HMO, health maintenance organization; IMG, international medical graduate; USMG, United States medical graduate, SD, standard deviation.

    • ↵* 17 omitted for missing data.

    • View popup
    Table 2.

    Predictors of Offering E-Visits from Logistic Regression Model

    VariableOR (95% CI)
    Race
        American Indian or Alaska Native1.28 (0.57 to 2.89)
        Asian0.95 (0.73 to 1.24)
        Black or African American1.46 (1.05 to 2.02)
        Native Hawaiian or Other Pacific Islander0.94 (0.31 to 2.86)
        Other1.00 (0.68 to 1.48)
        WhiteReference
    Ethnicity
        Hispanic or LatinoReference
        Non-Hispanic1.07 (0.75 to 1.52)
    Gender
        FemaleReference
        Male0.91 (0.76 to 1.08)
    Medical school training
        IMGReference
        USMG1.10 (0.87 to 1.40)
    Practice site ownership status
        No official ownership stake (100% employed)0.44 (0.28 to 0.68)
        Partial owner or shareholder0.79 (0.52 to 1.19)
        Self-employed as a contractor (including locums)0.57 (0.31 to 1.05)
        Sole ownerReference
        Other0.29 (0.12 to 0.71)
    Practice site size
        Solo practiceReference
        2 to 5 providers0.96 (0.65 to 1.41)
        6 to 20 providers1.26 (0.83 to 1.91)
        >20 providers1.45 (0.93 to 2.26)
    Practice site specialty mix
        Family medicine onlyReference
        Multiple specialties (not only primary care)1.06 (0.84 to 1.34)
        Primary care specialty mix (Family Medicine, Internal Medicine and/or Pediatrics)1.01 (0.82 to 1.25)
    Faculty status
        NoReference
        Yes, core/salaried faculty1.02 (0.71 to 1.48)
        Yes, volunteer/clinical faculty1.41 (1.16 to 1.71)
    Hours per week worked
        0 to 80.84 (0.49 to 1.43)
        9 to 161.63 (1.13 to 2.34)
        17 to 241.28 (0.96 to 1.71)
        25 to 321.62 (1.31 to 2.00)
        33 to 391.14 (0.89 to 1.45)
        40 or moreReference
    Years in practice
        0 to 10Reference
        11 to 201.10 (0.86 to 1.42)
        21 to 291.31 (0.91 to 1.87)
        30 or more1.05 (0.62 to 1.77)
    Primary practice type
        Private practiceReference
        Academic health center1.73 (1.03 to 2.91)
        Federal (military, Veterans Administration/Department of Defense)4.49 (2.93 to 6.89)
        Managed care/HMO practice9.79 (7.05 to 13.58)
        Hospital-/health system-owned2.50 (1.83 to 3.41)
        Other2.28 (1.43 to 3.63)
        Safety Net1.06 (0.68 to 1.66)
    Scope of Practice1.05 (1.03 to 1.08)
    Age in years1.00 (0.98 to 1.02)
    • CI, confidence interval HMO, health maintenance organization; IMG, international medical graduate; OR, odds ratio; USMG, United States medical graduate.

PreviousNext
Back to top

In this issue

The Journal of the American Board of Family     Medicine: 32 (6)
The Journal of the American Board of Family Medicine
Vol. 32, Issue 6
November-December 2019
  • Table of Contents
  • Table of Contents (PDF)
  • Cover (PDF)
  • Index by author
  • Back Matter (PDF)
  • Front Matter (PDF)
Print
Download PDF
Article Alerts
Sign In to Email Alerts with your Email Address
Email Article

Thank you for your interest in spreading the word on American Board of Family Medicine.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
Prevalence and Factors Associated with Family Physicians Providing E-Visits
(Your Name) has sent you a message from American Board of Family Medicine
(Your Name) thought you would like to see the American Board of Family Medicine web site.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
3 + 3 =
Solve this simple math problem and enter the result. E.g. for 1+3, enter 4.
Citation Tools
Prevalence and Factors Associated with Family Physicians Providing E-Visits
Michael R. Peabody, Mingliang Dai, Kea Turner, Lars E. Peterson, Arch G. Mainous
The Journal of the American Board of Family Medicine Nov 2019, 32 (6) 868-875; DOI: 10.3122/jabfm.2019.06.190081

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Share
Prevalence and Factors Associated with Family Physicians Providing E-Visits
Michael R. Peabody, Mingliang Dai, Kea Turner, Lars E. Peterson, Arch G. Mainous
The Journal of the American Board of Family Medicine Nov 2019, 32 (6) 868-875; DOI: 10.3122/jabfm.2019.06.190081
Twitter logo Facebook logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Jump to section

  • Article
    • Abstract
    • Methods
    • Results
    • Conclusions
    • Notes
    • References
  • Figures & Data
  • References
  • Info & Metrics
  • PDF

Related Articles

  • No related articles found.
  • PubMed
  • Google Scholar

Cited By...

  • A Stepwise Transition to Telemedicine in Response to COVID-19
  • New Research on Back Pain, Diet and Diabetes, Advanced Care Planning, and Other Issues Frequently Seen in Family Medicine
  • Google Scholar

More in this TOC Section

  • Integrating Adverse Childhood Experiences and Social Risks Screening in Adult Primary Care
  • A Pilot Comparison of Clinical Data Collection Methods Using Paper, Electronic Health Record Prompt, and a Smartphone Application
  • Associations Between Modifiable Preconception Care Indicators and Pregnancy Outcomes
Show more Original Research

Similar Articles

Keywords

  • Cross-Sectional Studies
  • Delivery of Health Care
  • Family Physicians
  • Logistic Models
  • Primary Care Physicians
  • Surveys and Questionnaires
  • Telemedicine

Navigate

  • Home
  • Current Issue
  • Past Issues

Authors & Reviewers

  • Info For Authors
  • Info For Reviewers
  • Submit A Manuscript/Review

Other Services

  • Get Email Alerts
  • Classifieds
  • Reprints and Permissions

Other Resources

  • Forms
  • Contact Us
  • ABFM News

© 2025 American Board of Family Medicine

Powered by HighWire