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Comparative Effectiveness of Telemedicine in Primary Care

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ClinicalTrials.gov Identifier: NCT04684836
Recruitment Status : Not yet recruiting
First Posted : December 28, 2020
Last Update Posted : December 28, 2020
Sponsor:
Collaborator:
Patient-Centered Outcomes Research Institute
Information provided by (Responsible Party):
Weill Medical College of Cornell University

Brief Summary:
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.

Condition or disease Intervention/treatment
Asthma Chronic Obstructive Pulmonary Disease (COPD Congestive Heart Failure Diabetes Hypertension Other: Exposure to telemedicine, after the onset of the pandemic

Detailed Description:
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.

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Study Type : Observational
Estimated Enrollment : 216000 participants
Observational Model: Cohort
Time Perspective: Retrospective
Official Title: Evaluating the Comparative Effectiveness of Telemedicine in Primary Care: Learning From the COVID-19 Pandemic
Estimated Study Start Date : February 2021
Estimated Primary Completion Date : April 2022
Estimated Study Completion Date : December 2023

Group/Cohort Intervention/treatment
Synchronous telemedicine alone Other: Exposure to telemedicine, after the onset of the pandemic
Telemedicine exposure will be defined based on the proportion of all visits at a given clinic that are delivered via telemedicine in each month.

Telemedicine-supplemented in-person care Other: Exposure to telemedicine, after the onset of the pandemic
Telemedicine exposure will be defined based on the proportion of all visits at a given clinic that are delivered via telemedicine in each month.

In-person care alone Other: Exposure to telemedicine, after the onset of the pandemic
Telemedicine exposure will be defined based on the proportion of all visits at a given clinic that are delivered via telemedicine in each month.




Primary Outcome Measures :
  1. Number of avoidable emergency department (ED) admissions [ Time Frame: 30 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

  2. 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

  3. 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

  4. 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

  5. Number of unplanned hospital admissions from the ED [ Time Frame: 30 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

  6. 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

  7. 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

  8. Number of unplanned hospital admissions from the ED [ Time Frame: 12 months the comparator arms of clinic-level telemedicine used ]
    Unplanned hospital admissions from the ED will be obtained from claims data

  9. Continuity of care as assessed by the Bice-Boxerman Continuity of Care Index [ Time Frame: 30 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.

  10. 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.

  11. 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.

  12. 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.

  13. Continuity of care as assessed by the Breslau Usual Provider of Care measure [ Time Frame: 30 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.

  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 Outcome Measures :
  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



Information from the National Library of Medicine

Choosing to participate in a study is an important personal decision. Talk with your doctor and family members or friends about deciding to join a study. To learn more about this study, you or your doctor may contact the study research staff using the contacts provided below. For general information, Learn About Clinical Studies.


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Ages Eligible for Study:   19 Years and older   (Adult, Older Adult)
Sexes Eligible for Study:   All
Sampling Method:   Non-Probability Sample
Study Population
The study population encompasses patients that are attributed to primary care clinics in one of the four health systems defined above. Patients are included in the study if they are ages 19 or older and received two or more outpatient visits at a participating practice during a one-year period before the COVID-19 pandemic, and 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. For the claims analyses, it will be required that patients are continuously enrolled over the entire study time period.
Criteria

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

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT04684836


Contacts
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Contact: Jessica Ancker, MPH, PhD 646-248-9281 jsa7002@med.cornell.edu
Contact: Katerina Andreadis, MS kaa2055@med.cornell.edu

Locations
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United States, New York
University of Florida
Gainesville, New York, United States, 32610
Mount Sinai
New York, New York, United States, 10029
Contact: Carol Horowitz, MD, MPH       carol.horowitz@mountsinai.org   
Principal Investigator: Carol Horowitz, MD, MPH         
Weill Cornell Medicine
New York, New York, United States, 10065
Contact: Jessica Ancker, MPH, PhD         
Contact: Katerina Andreadis, MS         
Principal Investigator: Jessica Ancker, MPH, PhD         
Principal Investigator: Rainu Kaushal, MD, MPH         
United States, North Carolina
University of North Carolina
Chapel Hill, North Carolina, United States, 27599
Contact: Saif Khairat, PhD, MPH       saif@unc.edu   
Principal Investigator: Saif Khairat, PhD, MPH         
Sponsors and Collaborators
Weill Medical College of Cornell University
Patient-Centered Outcomes Research Institute
Investigators
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Principal Investigator: Jessica Ancker, MPH, PhD Weill Medical College of Cornell University
Principal Investigator: Rainu Kaushal, MD, MPH Weill Medical College of Cornell University
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Responsible Party: Weill Medical College of Cornell University
ClinicalTrials.gov Identifier: NCT04684836    
Other Study ID Numbers: 20-12023014
First Posted: December 28, 2020    Key Record Dates
Last Update Posted: December 28, 2020
Last Verified: December 2020
Individual Participant Data (IPD) Sharing Statement:
Plan to Share IPD: No

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Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: No
Keywords provided by Weill Medical College of Cornell University:
telemedicine
primary care
Additional relevant MeSH terms:
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Lung Diseases, Obstructive
Pulmonary Disease, Chronic Obstructive
Heart Failure
Cardiovascular Diseases
Heart Diseases
Lung Diseases
Respiratory Tract Diseases