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Research ArticleOriginal Research

Telemedicine versus in-Person Primary Care: Impact on Visit Completion Rate in a Rural Appalachian Population

Treah Haggerty, Heather M. Stephens, Shaylee A. Peckens, Erika Bodkins, Michael Cary, Geri A. Dino and Cara L. Sedney
The Journal of the American Board of Family Medicine May 2022, 35 (3) 475-484; DOI: https://doi.org/10.3122/jabfm.2022.03.210518
Treah Haggerty
the West Virginia University School of Medicine, Department of Family Medicine, Morgantown, WV (TH, SAP, EB); Davis College of Agriculture, Natural Resources and Design, Resource Economics and Management, Morgantown, WV (HMS, MC); West Virginia University, School of Public Health, WV Prevention Research Center, Department of Social and Behavioral Sciences (GAD); West Virginia University School of Medicine, Department of Neurosurgery (CLS).
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Heather M. Stephens
the West Virginia University School of Medicine, Department of Family Medicine, Morgantown, WV (TH, SAP, EB); Davis College of Agriculture, Natural Resources and Design, Resource Economics and Management, Morgantown, WV (HMS, MC); West Virginia University, School of Public Health, WV Prevention Research Center, Department of Social and Behavioral Sciences (GAD); West Virginia University School of Medicine, Department of Neurosurgery (CLS).
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Shaylee A. Peckens
the West Virginia University School of Medicine, Department of Family Medicine, Morgantown, WV (TH, SAP, EB); Davis College of Agriculture, Natural Resources and Design, Resource Economics and Management, Morgantown, WV (HMS, MC); West Virginia University, School of Public Health, WV Prevention Research Center, Department of Social and Behavioral Sciences (GAD); West Virginia University School of Medicine, Department of Neurosurgery (CLS).
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Erika Bodkins
the West Virginia University School of Medicine, Department of Family Medicine, Morgantown, WV (TH, SAP, EB); Davis College of Agriculture, Natural Resources and Design, Resource Economics and Management, Morgantown, WV (HMS, MC); West Virginia University, School of Public Health, WV Prevention Research Center, Department of Social and Behavioral Sciences (GAD); West Virginia University School of Medicine, Department of Neurosurgery (CLS).
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Michael Cary
the West Virginia University School of Medicine, Department of Family Medicine, Morgantown, WV (TH, SAP, EB); Davis College of Agriculture, Natural Resources and Design, Resource Economics and Management, Morgantown, WV (HMS, MC); West Virginia University, School of Public Health, WV Prevention Research Center, Department of Social and Behavioral Sciences (GAD); West Virginia University School of Medicine, Department of Neurosurgery (CLS).
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Geri A. Dino
the West Virginia University School of Medicine, Department of Family Medicine, Morgantown, WV (TH, SAP, EB); Davis College of Agriculture, Natural Resources and Design, Resource Economics and Management, Morgantown, WV (HMS, MC); West Virginia University, School of Public Health, WV Prevention Research Center, Department of Social and Behavioral Sciences (GAD); West Virginia University School of Medicine, Department of Neurosurgery (CLS).
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Cara L. Sedney
the West Virginia University School of Medicine, Department of Family Medicine, Morgantown, WV (TH, SAP, EB); Davis College of Agriculture, Natural Resources and Design, Resource Economics and Management, Morgantown, WV (HMS, MC); West Virginia University, School of Public Health, WV Prevention Research Center, Department of Social and Behavioral Sciences (GAD); West Virginia University School of Medicine, Department of Neurosurgery (CLS).
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Article Figures & Data

Tables

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    Table 1.

    Data

    Individual Data from EPIC
    Gender
    Age at visit
    Race/Ethnicity
    Marital Status
    Education Level
    Zip Code
    Date of Appointment
    Department
    Provider
    Primary Care Provider (PCP)
    LACE score (a readmission risk score based on hospital admission information, the Charlson Comorbidity index, and emergency department visits within the last 6 to 12 months)
    Hospital or emergency department admission risk
    Zip-Code Level Regional Data (2019)
    Poverty Rate, American Community Survey (ACS)
    Median Household Income, ACS
    Unemployment Rate, ACS
    Percent of population 25 + with various education levels, ACS
    Broadband Speed, the Federal Communications Commission (FCC)
    • Note: the full patient dataset from EPIC also includes information on the following, however, some of the data points were missing for many of our patients or the information was redacted for confidentiality reasons: medical record number (MRN), patient name, full address, phone, date of birth, date the appointment was made, the location of the appointment, type of appointment, appointment cancellation reason, no show count, payor/insurance type, financial class, bad debt, reason for the visit/chief complaint, last PCP visit, next PCP visit, next appointment and provider in the department, health maintenance topics due, problem list, primary encounter diagnosis, all encounter diagnoses, patient employer, employer state/zip, urgent care visits/year and in the past 90 days days, emergency department visits in the last year and past 6 months, number of emergency department visits, and number of inpatient admissions.

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    Table 2.

    Factors Affecting Use of Telemedicine

    All AgesAged 18 Years and Older Only
    (1)(2)(3)(4)(5)
    New patient−0.041***−0.047***−0.046***−0.046***−0.047***
    (0.003)(0.003)(0.003)(0.003)(0.003)
    Primary care visit0.0030.0030.0020.002−0.000
    (0.002)(0.002)(0.002)(0.002)(0.002)
    LACE/Risk score−0.000***−0.000−0.000*−0.000***−0.000**
    (0.000)(0.000)(0.000)(0.000)(0.000)
    Hospital admission risk0.000***
    (0.000)
    Sex = Male0.020***0.019***0.019***0.019***0.016***
    (0.002)(0.002)(0.002)(0.002)(0.002)
    Race = White0.012***0.011***0.011***0.011***0.009**
    (0.003)(0.004)(0.004)(0.004)(0.004)
    Age, years0.002***−0.002***
    (0.000)(0.000)
    Married0.003−0.005***−0.007***−0.007***−0.004**
    (0.003)(0.002)(0.002)(0.002)(0.002)
    Persons aged 35 years and older but younger than 65 years = 1−0.024***−0.029***−0.021***
    (0.003)(0.004)(0.004)
    Persons aged 65 years or older = 1−0.024***−0.040***−0.029***
    (0.003)(0.007)(0.007)
    Persons aged older than 35 years but younger than 65 years interacted with LACE score0.000**0.000
    (0.000)(0.000)
    Persons aged 65 years or older interacted with LACE score0.001***0.001**
    (0.000)(0.000)
    Constant−0.118***−0.029−0.067**−0.065**−0.067**
    (0.029)(0.030)(0.028)(0.029)(0.028)
    Observations110,991105,988106,025106,025106,025
    R-squared0.0670.0680.0680.0680.083
    Adjusted R-squared0.06660.06800.06780.06790.0822
    • ↵*** P < .01,

    • ↵** P < .05,

    • ↵* P < .1.

    • Models also control for whether the visit was on a weekday, the month of the visit, distance of the patient from the clinics in Morgantown, and community-level factors at the zip code level including the poverty rate, median household income, the unemployment rate, the percentage of persons with a bachelor's degree or higher and with a high school diploma. Model 5 also include diagnosis codes.

    • Robust standard errors in parentheses.

    • Abbreviations: LACE score, a readmission risk score based on hospital admission information, the Charlson Comorbidity index, and emergency department visits within the last 6 to 12 months.

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    Table 3.

    Factors Affecting Completion of Primary Care Visits

    All AgesAged 18 Years and Older Only
    (1)(2)(3)(4)(5)
    Telemedicine = 10.243***0.245***0.243***0.231***0.171***
    (0.004)(0.004)(0.004)(0.007)(0.007)
    New patient−0.033***−0.027***−0.029***−0.030***−0.028***
    (0.005)(0.005)(0.005)(0.005)(0.004)
    Primary care visit0.010***0.011***0.014***0.014***−0.067***
    (0.003)(0.003)(0.003)(0.003)(0.003)
    LACE/Risk score0.001***0.000***0.000−0.000−0.001***
    (0.000)(0.000)(0.000)(0.000)(0.000)
    Hospital admission risk−0.001***−0.001***
    (0.000)(0.000)
    Sex = Male−0.020***−0.020***−0.023***−0.023***−0.016***
    (0.003)(0.003)(0.003)(0.003)(0.003)
    Race = White0.014**0.012**0.010*0.010*0.006
    (0.005)(0.006)(0.006)(0.006)(0.005)
    Age, years−0.003***−0.001***
    (0.000)(0.000)
    Married0.0040.0050.035***0.035***0.037***
    (0.004)(0.004)(0.003)(0.003)(0.003)
    Distance in miles to the facility−0.001***−0.001***
    (0.000)(0.000)
    Persons aged older than 35 years but younger than 65 years = 10.0040.004−0.052***
    (0.004)(0.004)(0.004)
    Persons aged 65 years or older = 10.056***0.056***−0.040***
    (0.005)(0.005)(0.005)
    LACE score interacted with use of telemedicine0.001**
    (0.000)
    Persons aged older than 35 years but younger than 65 years interacted with use of telemedicine0.052***
    (0.009)
    Persons aged 65 years or older interacted with use of telemedicine0.013
    (0.010)
    Constant0.582***0.544***0.598***0.600***0.560***
    (0.045)(0.047)(0.045)(0.045)(0.038)
    Observations110,991105,988106,025106,025106,025
    R-squared0.0370.0380.0360.0360.317
    Adjusted R-squared0.03690.03810.03610.03620.316
    • ↵*** P < .01,

    • ↵** P < .05,

    • ↵* P < .1.

    • Models also control for whether the visit was on a weekday, the month of the visit, and community-level factors at the zip code level including the poverty rate, median household income, the unemployment rate, the percentage of persons with a bachelor's degree or higher and with a high school diploma. Model 5 also include diagnosis codes.

    • Robust standard errors in parentheses.

    • Abbreviations: LACE score, a readmission risk score based on hospital admission information, the Charlson Comorbidity index, and emergency department visits within the last 6 to 12 months.

    • View popup
    Table 4.

    Community Factors and the Completion of Telemedicine Visits

    Poverty rate in patient's zip code of residence, 20190.0010.000−0.0000.000
    (0.001)(0.001)(0.001)(0.001)
    Median household income in patient's zip code of residence, 2019−0.000−0.000−0.000−0.000
    (0.000)(0.000)(0.000)(0.000)
    Unemployment rate in patient's zip code of residence, 2019−0.002−0.002−0.001−0.003
    (0.002)(0.002)(0.002)(0.002)
    Percent of the population with a bachelor's degree or higher in patient's zip co0.0010.0010.0000.000
    (0.001)(0.001)(0.001)(0.001)
    Percent of the population with only a high school diploma in patient's zip code0.0020.0010.0010.001
    (0.001)(0.001)(0.001)(0.001)
    Broadband Speed in mbps in patient's zip code of residence, 20190.0000.0000.0000.000
    (0.000)(0.000)(0.000)(0.000)
    • ***P < .01, **P < .05, *P < .1.

    • Models also control for whether the patient was a new patient, whether the visit was on a weekday, to a primary care provider, the age, sex, race, marital status, and health risk of the individual, distance of the patient from the clinics in Morgantown, and the month of the visit. Model 4 also include diagnosis codes.

    • Robust standard errors in parentheses.

    • View popup
    Appendix Table 1:

    Diagnosis Code Results

    Anemia0.008
    (0.014)
    Angina0.026***
    (0.009)
    Anxiety0.132***
    (0.008)
    Arthritis0.002
    (0.007)
    Carcinoma0.047**
    (0.021)
    Cervix−0.085***
    (0.010)
    Cholesterol0.004
    (0.007)
    Congestive−0.015
    (0.020)
    Coronary−0.009
    (0.011)
    Degenerative0.054***
    (0.021)
    Depression0.075***
    (0.005)
    Diabetes Mellitus0.011***
    (0.004)
    Disability−0.019
    (0.023)
    Edema0.018
    (0.012)
    Exposure0.323***
    (0.033)
    Fibrillation0.007
    (0.010)
    Headache0.017
    (0.014)
    Hyperactivity0.084***
    (0.012)
    Hyperglycemia0.016
    (0.013)
    Hyperlipidemia−0.005
    (0.004)
    Hypertension−0.004
    (0.003)
    Hypothyroid0.040**
    (0.016)
    Impairment0.005
    (0.025)
    Incontinence0.000
    (0.017)
    Infection0.033***
    (0.008)
    Libido0.054
    (0.057)
    Myelopathy0.082**
    (0.033)
    Nicotine−0.027
    (0.022)
    Pacemaker−0.071
    (0.044)
    Pain−0.008**
    (0.003)
    Pneumonia−0.021
    (0.018)
    Polyneuropathy0.024
    (0.016)
    Posttraumatic0.127***
    (0.022)
    Radiculopathy0.048**
    (0.020)
    Restless−0.005
    (0.034)
    Retardation−0.102***
    (0.012)
    Stone0.020
    (0.026)
    Tendinitis−0.046**
    (0.023)
    Thyroid0.001
    (0.006)
    Ulcer−0.021
    (0.015)
    Weakness0.013
    (0.027)
    • ↵*** P < .01,

    • ↵** P < .05,

    • * P < .1.

    • Results are from Model 7 in Table 2.

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The Journal of the American Board of Family Medicine: 35 (3)
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Telemedicine versus in-Person Primary Care: Impact on Visit Completion Rate in a Rural Appalachian Population
Treah Haggerty, Heather M. Stephens, Shaylee A. Peckens, Erika Bodkins, Michael Cary, Geri A. Dino, Cara L. Sedney
The Journal of the American Board of Family Medicine May 2022, 35 (3) 475-484; DOI: 10.3122/jabfm.2022.03.210518

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Telemedicine versus in-Person Primary Care: Impact on Visit Completion Rate in a Rural Appalachian Population
Treah Haggerty, Heather M. Stephens, Shaylee A. Peckens, Erika Bodkins, Michael Cary, Geri A. Dino, Cara L. Sedney
The Journal of the American Board of Family Medicine May 2022, 35 (3) 475-484; DOI: 10.3122/jabfm.2022.03.210518
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