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OpenTrials
Completed

NCT Number: NCT04684836

Comparative Effectiveness of Telemedicine in Primary Care

Leveraging a natural experiment approach, the investigators will examine rapidly changing telemedicine and in-person models of care during and after the COVID-19 crisis to determine whether certain patients could safely choose to continue telemedicine or telemedicine-supplemented care, rather than return to in-person care.

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Key information

Conditions

Asthma Bronchial Diseases Cardiovascular Diseases Chronic Disease Chronic Obstructive Pulmonary Disease (COPD) Congestive Heart Failure Diabetes Diabetes Mellitus Disease Attributes Endocrine System Diseases Glucose Metabolism Disorders Heart Diseases Heart Failure Hypersensitivity Hypersensitivity, Immediate Hypertension Immune System Diseases Lung Diseases Lung Diseases, Obstructive Metabolic Diseases Nutritional and Metabolic Diseases Pathologic Processes Pathological Conditions, Signs and Symptoms Pulmonary Disease, Chronic Obstructive Respiratory Hypersensitivity Respiratory Tract Diseases Vascular Diseases

Age range

19 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

University of Florida, Gainesville, New York, United States

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About this study

During the COVID-19 pandemic, telemedicine has quickly emerged as the primary method of providing outpatient care in many regions with shelter-in-place and social distancing policies. It is critical to understand the impact of this rapid and widespread transition from in-person to remote visits on disparities in access to primary care, especially in chronic disease where ongoing communication between providers and patients is essential. Also, these newly developed or expanded telemedicine programs vary widely, raising important questions about the effect of these differences on uptake of telemedicine among different patient populations and on patient-centered outcomes. Leveraging a natural experiment approach, the investigators will examine rapidly changing telemedicine and in-person models of care during and after the COVID-19 crisis to determine whether certain patients could safely choose to continue telemedicine or telemedicine-supplemented care, rather than return to in-person care. The overarching goals of this study are to describe the features of telemedicine programs in primary care during the COVID-19 pandemic and to use natural experiment methods to provide rigorous evidence on the effects of these programs.

PCORI has granted an extension for the final research report to October 1, 2023.

Who can participate

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • patients that are attributed to primary care clinics across four health systems in the INSIGHT (Mount Sinai Health System and Weill Cornell Medicine), OneFlorida (University of Florida Health), and STAR (University of North Carolina Health) CRNs.
  • Patients received two or more outpatient visits at a participating practice during a one-year period before the COVID-19 pandemic,
  • Patients had one or more of five chronic illnesses (asthma, chronic obstructive pulmonary disease (COPD), congestive heart failure (CHF), diabetes, hypertension) as defined by the Medicare Chronic Conditions Warehouse algorithm

Exclusion criteria

  • Patients who tested COVID-positive
  • Patients from hospice and palliative care practices
  • Patients from osteopathic medicine practices
  • Patients from pediatric practices
  • Patients that did not reside in states where the four health systems were located: the New York-Tri State Area (Connecticut, New York, and New Jersey), Florida, and North Carolina.
  • Patients that moved out of state (or out of the New York-Tri State Area) or who died during the study period were also excluded.
  • Patients who were not continuously enrolled over the entire study period (2019-2021).

Treatment and study plan

Exposure to telemedicine, after the onset of the pandemic

Other

The exposure of interest was the switch to primary care telemedicine prompted by the COVID-19 epidemic

Primary outcomes

  1. Preventable Emergency Department (ED) Admissions

    Time frame: Assessed per person per quarter for 3 years, data collected encompasses retrospective data from Q1 2019 to Q4 2021

    Avoidable emergency department (ED) admissions will be obtained from claims data. The Effect of telemedicine on preventable emergency department admissions will be calculated using difference-in-differences methodology. The estimate coefficient of the difference-in-difference model will be reported.

  2. Unplanned Hospital Admissions From the ED

    Time frame: Assessed at the quarter level for 3 years, data collected encompasses retrospective data from Q1 2019 to Q4 2021

    Unplanned hospital admissions from the ED will be obtained from claims data. The effect of telemedicine on unplanned hospital admissions will be calculated using difference-in-difference methodology. The estimate coefficient will be reported.

  3. Continuity of Care as Assessed by the Breslau Usual Provider of Care Measure

    Time frame: Assessed at the quarter level for 3 years, data collected encompasses retrospective data from Q1 2019 to Q4 2021

    Continuity of care as assessed by the Breslau Usual Provider of Care measure. The Breslau Usual Provider of Care index is also an indicator of continuity of care, ranging from 0 to 1, where 1 represents continuity of care. The effect of telemedicine on continuity of care using the Breslau Usual Provider of Care measure will be calculated using difference-in-difference methodology. The estimate coefficient will be reported.

  4. Number of Unplanned Hospital Admissions From the ED

    Time frame: 60 days after the exposure to one of the comparator arms of clinic-level telemedicine used

    Unplanned hospital admissions from the ED will be obtained from claims data

  5. Continuity of Care as Assessed by the Bice-Boxerman Continuity of Care Index

    Time frame: Assessed at the quarter level for 3 years, data collected encompasses retrospective data from Q1 2019 to Q4 2021

    Continuity of Care as Assessed by the Bice-Boxerman Continuity of Care Index. The Bice-Boxerman Continuity of Care Index is also an indicator of continuity of care, ranging from 0 to 1, where 1 represents continuity of care. The effect of telemedicine on continuity of care using the Bice-Boxerman Continuity of care index will be calculated using difference-in-difference methodology. The estimate coefficient will be reported.

  6. Number of Unplanned Hospital Admissions From the ED

    Time frame: 6 months after the exposure to one of the comparator arms of clinic-level telemedicine used

    Unplanned hospital admissions from the ED will be obtained from claims data

  7. Number of Unplanned Hospital Admissions From the ED

    Time frame: 12 months after the exposure to one of the comparator arms of clinic-level telemedicine used

    Unplanned hospital admissions from the ED will be obtained from claims data

  8. Number of Avoidable Emergency Department (ED) Admissions

    Time frame: 60 days after the exposure to one of the comparator arms of clinic-level telemedicine used

    Avoidable emergency department (ED) admissions will be obtained from claims data

  9. Number of Avoidable Emergency Department (ED) Admissions

    Time frame: 6 months after the exposure to one of the comparator arms of clinic-level telemedicine used

    Avoidable emergency department (ED) admissions will be obtained from claims data

  10. Number of Avoidable Emergency Department (ED) Admissions

    Time frame: 12 months after the exposure to one of the comparator arms of clinic-level telemedicine used

    Avoidable emergency department (ED) admissions will be obtained from claims data

  11. Continuity of Care as Assessed by the Bice-Boxerman Continuity of Care Index

    Time frame: 60 days after the exposure to one of the comparator arms of clinic-level telemedicine used

    Continuity of care will be measured using the Bice-Boxerman Continuity of Care Index. The Bice-Boxerman continuity of care (COC) index reflects the relative share of all of a patient's visits during the year that are billed by distinct providers and/or practices. The index ranges from 0 to 1, where 0 indicates that each visit involved a different provider than all other visits, and 1 that all visits were billed by a single provider, representing continuity of care.

  12. Continuity of Care as Assessed by the Bice-Boxerman Continuity of Care Index

    Time frame: 6 months after the exposure to one of the comparator arms of clinic-level telemedicine used

    Continuity of care will be measured using the Bice-Boxerman Continuity of Care Index. The Bice-Boxerman continuity of care (COC) index reflects the relative share of all of a patient's visits during the year that are billed by distinct providers and/or practices. The index ranges from 0 to 1, where 0 indicates that each visit involved a different provider than all other visits, and 1 that all visits were billed by a single provider, representing continuity of care.

  13. Continuity of Care as Assessed by the Bice-Boxerman Continuity of Care Index

    Time frame: 12 months after the exposure to one of the comparator arms of clinic-level telemedicine used

    Continuity of care will be measured using the Bice-Boxerman Continuity of Care Index. The Bice-Boxerman continuity of care (COC) index reflects the relative share of all of a patient's visits during the year that are billed by distinct providers and/or practices. The index ranges from 0 to 1, where 0 indicates that each visit involved a different provider than all other visits, and 1 that all visits were billed by a single provider, representing continuity of care.

  14. Continuity of Care as Assessed by the Breslau Usual Provider of Care Measure

    Time frame: 60 days after the exposure to one of the comparator arms of clinic-level telemedicine used

    Continuity of care as assessed by the Breslau Usual Provider of Care measure. The Breslau Usual Provider of Care index is also an indicator of continuity of care, ranging from 0 to 1, where 1 represents continuity of care.

  15. Continuity of Care as Assessed by the Breslau Usual Provider of Care Measure

    Time frame: 6 months after the exposure to one of the comparator arms of clinic-level telemedicine used

    Continuity of care as assessed by the Breslau Usual Provider of Care measure. The Breslau Usual Provider of Care index is also an indicator of continuity of care, ranging from 0 to 1, where 1 represents continuity of care.

  16. Continuity of Care as Assessed by the Breslau Usual Provider of Care Measure

    Time frame: 12 months after the exposure to one of the comparator arms of clinic-level telemedicine used

    Continuity of care as assessed by the Breslau Usual Provider of Care measure. The Breslau Usual Provider of Care index is also an indicator of continuity of care, ranging from 0 to 1, where 1 represents continuity of care.

  17. Continuity of Care as Assessed by Attendance at Follow-up Appointment

    Time frame: 30 days after the exposure to one of the comparator arms of clinic-level telemedicine used

    Continuity of care as assessed by attendance at follow-up appointment.

  18. Continuity of Care as Assessed by Attendance at Follow-up Appointment

    Time frame: 60 days after the exposure to one of the comparator arms of clinic-level telemedicine used

    Continuity of care as assessed by attendance at follow-up appointment.

  19. Continuity of Care as Assessed by Attendance at Follow-up Appointment

    Time frame: 6 months after the exposure to one of the comparator arms of clinic-level telemedicine used

    Continuity of care as assessed by attendance at follow-up appointment.

  20. Continuity of Care as Assessed by Attendance at Follow-up Appointment

    Time frame: 12 months after the exposure to one of the comparator arms of clinic-level telemedicine used

    Continuity of care as assessed by attendance at follow-up appointment.

Secondary outcomes

  1. Evidence of Controlled Disease as Indicated by as Indicated by the National Quality Forum (NQF 0059): Diabetes: Hemoglobin A1c (HbA1c) Poor Control (>9%)

    Time frame: 30 days after the exposure to one of the comparator arms of clinic-level telemedicine used

    Evidence of controlled disease as indicated by as indicated by the National Quality Forum (NQF 0059): Diabetes: Hemoglobin A1c (HbA1c) Poor Control (>9%), which is the percentage of patients 18 - 75 years of age with diabetes who had hemoglobin A1c > 9.0% during the measurement period

  2. Evidence of Controlled Disease as Indicated by as Indicated by the National Quality Forum (NQF 0059): Diabetes: Hemoglobin A1c (HbA1c) Poor Control (>9%)

    Time frame: 60 days after the exposure to one of the comparator arms of clinic-level telemedicine used

    Evidence of controlled disease as indicated by as indicated by the National Quality Forum (NQF 0059): Diabetes: Hemoglobin A1c (HbA1c) Poor Control (>9%), which is the percentage of patients 18 - 75 years of age with diabetes who had hemoglobin A1c > 9.0% during the measurement period

  3. Evidence of Controlled Disease as Indicated by as Indicated by the National Quality Forum (NQF 0059): Diabetes: Hemoglobin A1c (HbA1c) Poor Control (>9%)

    Time frame: 6 months after the exposure to one of the comparator arms of clinic-level telemedicine used

    Evidence of controlled disease as indicated by as indicated by the National Quality Forum (NQF 0059): Diabetes: Hemoglobin A1c (HbA1c) Poor Control (>9%), which is the percentage of patients 18 - 75 years of age with diabetes who had hemoglobin A1c > 9.0% during the measurement period

  4. Evidence of Controlled Disease as Indicated by as Indicated by the National Quality Forum (NQF 0059): Diabetes: Hemoglobin A1c (HbA1c) Poor Control (>9%)

    Time frame: 12 months after the exposure to one of the comparator arms of clinic-level telemedicine used

    Evidence of controlled disease as indicated by as indicated by the National Quality Forum (NQF 0059): Diabetes: Hemoglobin A1c (HbA1c) Poor Control (>9%), which is the percentage of patients 18 - 75 years of age with diabetes who had hemoglobin A1c > 9.0% during the measurement period

  5. Evidence of Controlled Disease as Indicated by as Indicated by the National Quality Forum (NQF 0018): Controlling High Blood Pressure

    Time frame: 30 days after the exposure to one of the comparator arms of clinic-level telemedicine used

    Evidence of controlled disease as indicated by as indicated by the National Quality Forum (NQF 0018): Controlling High Blood Pressure, which is the percentage of patients 18 - 85 with hypertension diagnosis and adequate control (< 140/90 mmHg)

  6. Evidence of Controlled Disease as Indicated by as Indicated by the National Quality Forum (NQF 0018): Controlling High Blood Pressure

    Time frame: 60 days after the exposure to one of the comparator arms of clinic-level telemedicine used

    Evidence of controlled disease as indicated by as indicated by the National Quality Forum (NQF 0018): Controlling High Blood Pressure, which is the percentage of patients 18 - 85 with hypertension diagnosis and adequate control (< 140/90 mmHg)

  7. Evidence of Controlled Disease as Indicated by as Indicated by the National Quality Forum (NQF 0018): Controlling High Blood Pressure

    Time frame: 6 months after the exposure to one of the comparator arms of clinic-level telemedicine used

    Evidence of controlled disease as indicated by as indicated by the National Quality Forum (NQF 0018): Controlling High Blood Pressure, which is the percentage of patients 18 - 85 with hypertension diagnosis and adequate control (< 140/90 mmHg)

  8. Evidence of Controlled Disease as Indicated by as Indicated by the National Quality Forum (NQF 0018): Controlling High Blood Pressure

    Time frame: 12 months after the exposure to one of the comparator arms of clinic-level telemedicine used

    Evidence of controlled disease as indicated by as indicated by the National Quality Forum (NQF 0018): Controlling High Blood Pressure, which is the percentage of patients 18 - 85 with hypertension diagnosis and adequate control (< 140/90 mmHg)

  9. Days at Home

    Time frame: 30 days after the exposure to one of the comparator arms of clinic-level telemedicine used

    Days per month not in hospital or institutional setting

  10. Days at Home

    Time frame: 60 days after the exposure to one of the comparator arms of clinic-level telemedicine used

    Days per month not in hospital or institutional setting

  11. Days at Home

    Time frame: 6 months after the exposure to one of the comparator arms of clinic-level telemedicine used

    Days per month not in hospital or institutional setting

  12. Days at Home

    Time frame: 12 months after the exposure to one of the comparator arms of clinic-level telemedicine used

    Days per month not in hospital or institutional setting

  13. Patient Experiences Based on the Patient Satisfaction Questionnaire (PSQ-18)

    Time frame: 12 months after the exposure to one of the comparator arms of clinic-level telemedicine used

    Patient experiences based on the Patient Satisfaction Questionnaire (PSQ-18), which is a 5-scale questionnaire including questions on patient satisfaction, communication quality with providers and accessibility/convenience of care.

  14. Ease of Use and Access to Telemedicine Based on Telehealth Usability Questionnaire (TUQ)

    Time frame: 12 months after the exposure to one of the comparator arms of clinic-level telemedicine used

    For individuals who accessed a telemedicine visit, we will ask questions based on the validated Telehealth Usability Questionnaire (TUQ), including the ease of use and access to the telemedicine service, quality of the interaction with the provider, and satisfaction

Sponsors and collaborators

Lead sponsor

Weill Medical College of Cornell University

Other

Collaborators

  • Patient-Centered Outcomes Research Institute

Registry information

Official study title

Evaluating the Comparative Effectiveness of Telemedicine in Primary Care: Learning From the COVID-19 Pandemic

Important dates

Study start
2021
Primary completion
2022
Study completion
2022
First posted
Dec 28, 2020
Registry last updated
Sep 19, 2024

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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