<clinical_study>
  <!-- This xml conforms to an XML Schema at:
    https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
  <required_header>
    <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
    <link_text>Link to the current ClinicalTrials.gov record.</link_text>
    <url>https://clinicaltrials.gov/ct2/show/NCT04441944</url>
  </required_header>
  <id_info>
    <org_study_id>201901748</org_study_id>
    <nct_id>NCT04441944</nct_id>
  </id_info>
  <brief_title>TELEmedicine as an Intervention for Sepsis in Emergency Departments</brief_title>
  <acronym>TELEvISED</acronym>
  <official_title>TELEmedicine as an Intervention for Sepsis in Emergency Departments</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>University of Iowa</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
    <collaborator>
      <agency>Agency for Healthcare Research and Quality (AHRQ)</agency>
      <agency_class>U.S. Fed</agency_class>
    </collaborator>
  </sponsors>
  <source>University of Iowa</source>
  <oversight_info>
    <has_dmc>No</has_dmc>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>No</is_fda_regulated_device>
  </oversight_info>
  <brief_summary>
    <textblock>
      Sepsis is a life-threatening condition that has doubled in incidence over the past decade,&#xD;
      and timely aggressive medical intervention has been shown to save lives. Rural sepsis&#xD;
      patients have a 38% higher mortality rate, possibly attributable to delays in early sepsis&#xD;
      care. Rural emergency department (ED)-based provider-to-provider telemedicine has been&#xD;
      proposed to standardize care and support local clinicians in rural hospitals. The goal of&#xD;
      this multicenter observational comparative effectiveness study is to measure the association&#xD;
      between tele-ED use and clinical outcomes in a cohort of rural sepsis patients.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      Sepsis is a life-threatening condition that has doubled in incidence over the past decade,&#xD;
      and timely aggressive medical intervention has been shown to save lives. Rural sepsis&#xD;
      patients have a 38% higher mortality rate, possibly attributable to delays in early sepsis&#xD;
      care. This effect persists even among patients who are transferred between hospitals and who&#xD;
      bypass rural hospitals. With 17% of all hospital deaths attributable to sepsis and 19% of&#xD;
      Americans living in rural areas, there is a critical need to identify strategies to reduce&#xD;
      the disparities in outcomes between rural and urban sepsis care.&#xD;
&#xD;
      Rural ED-based telemedicine has been proposed to standardize care and support local&#xD;
      clinicians in rural hospitals. Telemedicine networks provide a real-time, high-definition&#xD;
      on-demand video connection between a rural hospital and a tertiary hub 24 h daily. Based in&#xD;
      Sioux Falls, South Dakota, Avera eCare is a tele-emergency network that serves as a hub for a&#xD;
      140-hospital network that spans 12 rural Midwestern states. It is the largest rural ED-based&#xD;
      telehealth network in North America, and a network the investigators have studied previously.&#xD;
&#xD;
      Our central hypothesis is that telemedicine will improve clinical outcomes through improved&#xD;
      adherence with Surviving Sepsis Campaign (SSC) guidelines. Using comparative effectiveness&#xD;
      methods and a patient-centered outcomes research (PCOR) approach, this study will test the&#xD;
      hypotheses with the following specific aims:&#xD;
&#xD;
        1. To measure the association between rural ED-based telemedicine use, guideline adherence,&#xD;
           and clinical outcomes using an observational cohort comparative effectiveness research&#xD;
           study. Rural clinicians choose whether individual sepsis patients will be treated with&#xD;
           telemedicine-supplemented care. Medical records will be analyzed from patients with&#xD;
           severe sepsis who present to 25 rural hospital EDs that are part of a telemedicine&#xD;
           network to estimate the effect of telemedicine on changing early SSC guideline&#xD;
           adherence. Guideline adherence has been studied extensively as an outcome of sepsis&#xD;
           implementation studies. The study will also analyze the impact of telemedicine on&#xD;
           clinical outcomes, such as mechanical ventilation, hospital length-of-stay, and&#xD;
           survival, using mediation analysis in a propensity-matched cohort design. Our working&#xD;
           hypothesis is that telemedicine consultation will improve SSC guideline adherence and&#xD;
           will reduce delays in care, leading to improved clinical outcomes.&#xD;
&#xD;
        2. To measure the effect of ED-based telemedicine on guideline adherence among patients who&#xD;
           have telemedicine available but not used. In addition to the effect of use for&#xD;
           individual patient care, telemedicine interactions may provide ongoing training for&#xD;
           providers and nurses and influence care even for patients for whom telemedicine is not&#xD;
           used. This effect may result from a learning effect in which local providers adopt&#xD;
           practices they observe in telemedicine-consulted patients. The investigators will use&#xD;
           hospital fixed-effects models to measure this association. The working hypothesis is&#xD;
           that guideline adherence will increase after telemedicine adoption even in&#xD;
           non-telemedicine patients, and adherence will be associated with the number of prior&#xD;
           telemedicine sepsis encounters (dose-response).&#xD;
&#xD;
      The rationale for this research is that dissemination and implementation of best practices&#xD;
      through rural networks remains difficult, but telemedicine offers one potential solution.&#xD;
      Sepsis is an ideal model to study the effect of telemedicine because it differs from other&#xD;
      acute care conditions treated in rural hospitals (e.g., trauma, myocardial infarction) in&#xD;
      that early treatment provided in rural hospitals may be more important than rapid transfer to&#xD;
      tertiary centers. Focusing on telemedicine in rural sepsis care will serve as a powerful&#xD;
      model for examining strategies for disseminating innovations across rural networks.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Completed</overall_status>
  <start_date type="Actual">August 1, 2016</start_date>
  <completion_date type="Actual">October 30, 2022</completion_date>
  <primary_completion_date type="Actual">October 30, 2022</primary_completion_date>
  <study_type>Observational</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <observational_model>Cohort</observational_model>
    <time_perspective>Retrospective</time_perspective>
  </study_design_info>
  <primary_outcome>
    <measure>28-day Hospital-Free Days</measure>
    <time_frame>Within 28 days of emergency department presentation</time_frame>
    <description>The total number of days in the 28 days after emergency department presentation that a patient is alive and outside the hospital.</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>Surviving Sepsis Campaign Guideline Adherence</measure>
    <time_frame>6 hours after emergency department arrival</time_frame>
    <description>Adherence with all elements of the Surviving Sepsis Campaign 3-hour and 6-hour bundles (dichotomous)</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Mortality</measure>
    <time_frame>Through hospital discharge, an average of 8 days</time_frame>
    <description>Did patient die in the hospital?</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Mechanical Ventilation</measure>
    <time_frame>Through hospital discharge, an average of 8 days</time_frame>
    <description>Was mechanical ventilation required during admission?</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Vasopressors</measure>
    <time_frame>Through hospital discharge, an average of 8 days</time_frame>
    <description>Was vasopressor therapy required during admission?</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>New Hemodialysis</measure>
    <time_frame>Through hospital discharge, an average of 8 days</time_frame>
    <description>Was dialysis required during this admission (if not on chronic dialysis)?</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Inter-hospital Transfer</measure>
    <time_frame>Through hospital discharge, an average of 8 days</time_frame>
    <description>Was inter-hospital transfer required from the index hospital?</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>28-Day Ventilator-Free Days</measure>
    <time_frame>28 days</time_frame>
    <description>The total number of days in the 28 days after emergency department presentation that a patient is alive and not requiring a ventilator.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>28-Day Vasopressor-Free Days</measure>
    <time_frame>28 days</time_frame>
    <description>The total number of days in the 28 days after emergency department presentation that a patient is alive and not requiring a vasopressor.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>28-Day ICU-Free Days</measure>
    <time_frame>28 days</time_frame>
    <description>The total number of days in the 28 days after emergency department presentation that a patient is alive and not requiring an ICU bed.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Emergency Department Length-of-Stay</measure>
    <time_frame>Index emergency department duration (1 day)</time_frame>
    <description>The total duration of stay in the index emergency department.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Time-to-inpatient unit arrival</measure>
    <time_frame>24 hours</time_frame>
    <description>The time from index emergency department registration to arrival in the inpatient unit</description>
  </secondary_outcome>
  <number_of_groups>2</number_of_groups>
  <enrollment type="Actual">1191</enrollment>
  <condition>Sepsis</condition>
  <arm_group>
    <arm_group_label>Telemedicine Cases</arm_group_label>
    <description>Patients presenting to rural emergency departments who had real-time provider-to-provider telemedicine used to supplement their emergency department care.</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Non-Telemedicine Cases</arm_group_label>
    <description>Patients presenting to rural emergency departments who did not have real-time provider-to-provider telemedicine used to supplement their emergency department care.</description>
  </arm_group>
  <intervention>
    <intervention_type>Other</intervention_type>
    <intervention_name>Telemedicine</intervention_name>
    <description>Use of provider-to-provider telemedicine</description>
    <arm_group_label>Telemedicine Cases</arm_group_label>
  </intervention>
  <eligibility>
    <study_pop>
      <textblock>
        This study will include all adult (age≥18 years) sepsis patients who presented to a&#xD;
        participating rural ED between August 1, 2016 and June 30, 2019. Because of poor&#xD;
        sensitivity in diagnosis code-based definitions of sepsis, we elected to use a multi-step&#xD;
        definition requiring (1) hospital diagnosis of both infection and organ failure, (2)&#xD;
        identification of infection in the ED, (3) presence of organ failure in the ED, and (4)&#xD;
        presence of systemic inflammatory response syndrome (SIRS) criteria in the ED. To identify&#xD;
        hospital diagnosis of infection and organ failure, we used the Fleischmann-Struzek&#xD;
        approximation of sepsis using International Classification of Diseases, 10th edition,&#xD;
        Clinical Modification (ICD-10-CM) or an explicit sepsis code (R65.20 or R65.21).&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  Adults (age 18 years or older)&#xD;
&#xD;
          -  Arrive at participating emergency department between August 1, 2016 and June 30, 2019&#xD;
&#xD;
          -  Hospital diagnosis of infection and organ failure&#xD;
&#xD;
          -  Identification of infection in the emergency department&#xD;
&#xD;
          -  Presence of organ failure in the emergency department (SOFA score of at least 2)&#xD;
&#xD;
          -  Presence of systemic inflammatory response syndrome (SIRS) in the emergency department&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  None&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>18 Years</minimum_age>
    <maximum_age>N/A</maximum_age>
  </eligibility>
  <overall_official>
    <last_name>Nicholas Mohr, MD, MS</last_name>
    <role>Principal Investigator</role>
    <affiliation>University of Iowa</affiliation>
  </overall_official>
  <location>
    <facility>
      <name>University of Iowa Hospitals and Clinics</name>
      <address>
        <city>Iowa City</city>
        <state>Iowa</state>
        <zip>52242</zip>
        <country>United States</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>United States</country>
  </location_countries>
  <verification_date>November 2022</verification_date>
  <study_first_submitted>June 17, 2020</study_first_submitted>
  <study_first_submitted_qc>June 18, 2020</study_first_submitted_qc>
  <study_first_posted type="Actual">June 22, 2020</study_first_posted>
  <last_update_submitted>November 8, 2022</last_update_submitted>
  <last_update_submitted_qc>November 8, 2022</last_update_submitted_qc>
  <last_update_posted type="Actual">November 9, 2022</last_update_posted>
  <responsible_party>
    <responsible_party_type>Principal Investigator</responsible_party_type>
    <investigator_affiliation>University of Iowa</investigator_affiliation>
    <investigator_full_name>Nicholas M Mohr</investigator_full_name>
    <investigator_title>Professor</investigator_title>
  </responsible_party>
  <keyword>Telemedicine</keyword>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Sepsis</mesh_term>
    <mesh_term>Toxemia</mesh_term>
    <mesh_term>Emergencies</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>No</sharing_ipd>
    <ipd_description>Aggregate data will be shared with investigators who make a written request to the study team. These data will include aggregate effect sizes, but will not be patient-level data. Because of the sparsely populated region where this study is being conducted, hospital-identifiable data would be sufficient to identify individuals in this region, so fully de-identifying this data set would make it unusable for subsequent independent analyses (e.g., would require removing age, sex, hospital, transfer distance, transport times, comorbidities). The study team will, however, collaborate with other investigators to conduct additional analysis, maintaining the security of the data set.</ipd_description>
  </patient_data>
  <!-- Results have not yet been posted for this study                                          -->
</clinical_study>


download date: ClinicalTrials.gov processed this data on September 20, 2023
link text: Link to the current ClinicalTrials.gov record.
url: https://clinicaltrials.gov/ct2/show/NCT04441944
org study id: 201901748
nct id: NCT04441944
lead sponsor: 
collaborator: 
has dmc: No
is fda regulated drug: No
is fda regulated device: No
Sepsis is a life-threatening condition that has doubled in incidence over the past decade,
      and timely aggressive medical intervention has been shown to save lives. Rural sepsis
      patients have a 38% higher mortality rate, possibly attributable to delays in early sepsis
      care. Rural emergency department (ED)-based provider-to-provider telemedicine has been
      proposed to standardize care and support local clinicians in rural hospitals. The goal of
      this multicenter observational comparative effectiveness study is to measure the association
      between tele-ED use and clinical outcomes in a cohort of rural sepsis patients.
Sepsis is a life-threatening condition that has doubled in incidence over the past decade,
      and timely aggressive medical intervention has been shown to save lives. Rural sepsis
      patients have a 38% higher mortality rate, possibly attributable to delays in early sepsis
      care. This effect persists even among patients who are transferred between hospitals and who
      bypass rural hospitals. With 17% of all hospital deaths attributable to sepsis and 19% of
      Americans living in rural areas, there is a critical need to identify strategies to reduce
      the disparities in outcomes between rural and urban sepsis care.

      Rural ED-based telemedicine has been proposed to standardize care and support local
      clinicians in rural hospitals. Telemedicine networks provide a real-time, high-definition
      on-demand video connection between a rural hospital and a tertiary hub 24 h daily. Based in
      Sioux Falls, South Dakota, Avera eCare is a tele-emergency network that serves as a hub for a
      140-hospital network that spans 12 rural Midwestern states. It is the largest rural ED-based
      telehealth network in North America, and a network the investigators have studied previously.

      Our central hypothesis is that telemedicine will improve clinical outcomes through improved
      adherence with Surviving Sepsis Campaign (SSC) guidelines. Using comparative effectiveness
      methods and a patient-centered outcomes research (PCOR) approach, this study will test the
      hypotheses with the following specific aims:

        1. To measure the association between rural ED-based telemedicine use, guideline adherence,
           and clinical outcomes using an observational cohort comparative effectiveness research
           study. Rural clinicians choose whether individual sepsis patients will be treated with
           telemedicine-supplemented care. Medical records will be analyzed from patients with
           severe sepsis who present to 25 rural hospital EDs that are part of a telemedicine
           network to estimate the effect of telemedicine on changing early SSC guideline
           adherence. Guideline adherence has been studied extensively as an outcome of sepsis
           implementation studies. The study will also analyze the impact of telemedicine on
           clinical outcomes, such as mechanical ventilation, hospital length-of-stay, and
           survival, using mediation analysis in a propensity-matched cohort design. Our working
           hypothesis is that telemedicine consultation will improve SSC guideline adherence and
           will reduce delays in care, leading to improved clinical outcomes.

        2. To measure the effect of ED-based telemedicine on guideline adherence among patients who
           have telemedicine available but not used. In addition to the effect of use for
           individual patient care, telemedicine interactions may provide ongoing training for
           providers and nurses and influence care even for patients for whom telemedicine is not
           used. This effect may result from a learning effect in which local providers adopt
           practices they observe in telemedicine-consulted patients. The investigators will use
           hospital fixed-effects models to measure this association. The working hypothesis is
           that guideline adherence will increase after telemedicine adoption even in
           non-telemedicine patients, and adherence will be associated with the number of prior
           telemedicine sepsis encounters (dose-response).

      The rationale for this research is that dissemination and implementation of best practices
      through rural networks remains difficult, but telemedicine offers one potential solution.
      Sepsis is an ideal model to study the effect of telemedicine because it differs from other
      acute care conditions treated in rural hospitals (e.g., trauma, myocardial infarction) in
      that early treatment provided in rural hospitals may be more important than rapid transfer to
      tertiary centers. Focusing on telemedicine in rural sepsis care will serve as a powerful
      model for examining strategies for disseminating innovations across rural networks.
observational model: Cohort
time perspective: Retrospective
measure: 28-day Hospital-Free Days
time frame: Within 28 days of emergency department presentation
description: The total number of days in the 28 days after emergency department presentation that a patient is alive and outside the hospital.
measure: Surviving Sepsis Campaign Guideline Adherence
time frame: 6 hours after emergency department arrival
description: Adherence with all elements of the Surviving Sepsis Campaign 3-hour and 6-hour bundles (dichotomous)
measure: Mortality
time frame: Through hospital discharge, an average of 8 days
description: Did patient die in the hospital?
measure: Mechanical Ventilation
time frame: Through hospital discharge, an average of 8 days
description: Was mechanical ventilation required during admission?
measure: Vasopressors
time frame: Through hospital discharge, an average of 8 days
description: Was vasopressor therapy required during admission?
measure: New Hemodialysis
time frame: Through hospital discharge, an average of 8 days
description: Was dialysis required during this admission (if not on chronic dialysis)?
measure: Inter-hospital Transfer
time frame: Through hospital discharge, an average of 8 days
description: Was inter-hospital transfer required from the index hospital?
measure: 28-Day Ventilator-Free Days
time frame: 28 days
description: The total number of days in the 28 days after emergency department presentation that a patient is alive and not requiring a ventilator.
measure: 28-Day Vasopressor-Free Days
time frame: 28 days
description: The total number of days in the 28 days after emergency department presentation that a patient is alive and not requiring a vasopressor.
measure: 28-Day ICU-Free Days
time frame: 28 days
description: The total number of days in the 28 days after emergency department presentation that a patient is alive and not requiring an ICU bed.
measure: Emergency Department Length-of-Stay
time frame: Index emergency department duration (1 day)
description: The total duration of stay in the index emergency department.
measure: Time-to-inpatient unit arrival
time frame: 24 hours
description: The time from index emergency department registration to arrival in the inpatient unit
arm group label: Telemedicine Cases
description: Patients presenting to rural emergency departments who had real-time provider-to-provider telemedicine used to supplement their emergency department care.
arm group label: Non-Telemedicine Cases
description: Patients presenting to rural emergency departments who did not have real-time provider-to-provider telemedicine used to supplement their emergency department care.
intervention type: Other
intervention name: Telemedicine
description: Use of provider-to-provider telemedicine
arm group label: Telemedicine Cases
study pop: 
sampling method: Probability Sample
criteria: 
gender: All
minimum age: 18 Years
maximum age: N/A
last name: Nicholas Mohr, MD, MS
role: Principal Investigator
affiliation: University of Iowa
facility: 
country: United States
responsible party type: Principal Investigator
investigator affiliation: University of Iowa
investigator full name: Nicholas M Mohr
investigator title: Professor
mesh term: Sepsis
mesh term: Toxemia
mesh term: Emergencies
sharing ipd: No
ipd description: Aggregate data will be shared with investigators who make a written request to the study team. These data will include aggregate effect sizes, but will not be patient-level data. Because of the sparsely populated region where this study is being conducted, hospital-identifiable data would be sufficient to identify individuals in this region, so fully de-identifying this data set would make it unusable for subsequent independent analyses (e.g., would require removing age, sex, hospital, transfer distance, transport times, comorbidities). The study team will, however, collaborate with other investigators to conduct additional analysis, maintaining the security of the data set.