<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/NCT04435041</url>
  </required_header>
  <id_info>
    <org_study_id>283196</org_study_id>
    <nct_id>NCT04435041</nct_id>
  </id_info>
  <brief_title>Remote-by-Default Care in the COVID-19 Pandemic</brief_title>
  <official_title>Remote-by-Default Care in the COVID-19 Pandemic: Addressing the Micro-, Meso-, and Macro-level Challenges of a Radical New Service Model</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>University of Oxford</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
    <collaborator>
      <agency>University of Plymouth</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>Nuffield Trust</agency>
      <agency_class>Other</agency_class>
    </collaborator>
  </sponsors>
  <source>University of Oxford</source>
  <oversight_info>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>No</is_fda_regulated_device>
  </oversight_info>
  <brief_summary>
    <textblock>
      18 month study, funded by ESRC COVID-19 research fund. The aim is to explore and support the&#xD;
      rapid shift from face-to-face to remote (telephone and video) conversations in primary care.&#xD;
      There are three components: a study of clinical interactions and decision making (micro);&#xD;
      four locality-based organisational case studies of new models of care (meso); abd a a study&#xD;
      of how digital innovation can support NHS infrastructure and vice versa (macro).&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      18 month study, funded by ESRC COVID-19 research fund. The aim is to explore and support the&#xD;
      rapid shift from face-to-face to remote (telephone and video) conversations in primary care.&#xD;
      There are three components: a study of clinical interactions and decision making (micro);&#xD;
      four locality-based organisational case studies of new models of care (meso); abd a a study&#xD;
      of how digital innovation can support NHS infrastructure and vice versa (macro). The methods&#xD;
      are mainly qualitative (interviews, virtual ethnography, analysis of documents,&#xD;
      micro-analysis of conversations) and are designed to inform action research.&#xD;
&#xD;
      Key deliverables:&#xD;
&#xD;
      At least two evidence-based assessment tools: qualitative (questions for remote assessment of&#xD;
      breathlessness) and quantitative (a COVID-19-specific early warning score)&#xD;
&#xD;
      Transferable lessons about how to achieve rapid spread and scale-up, spread in real time&#xD;
      through our extensive intersectoral networks&#xD;
&#xD;
      Strengthened infrastructure for supporting digital innovation in the NHS&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Completed</overall_status>
  <start_date type="Actual">May 13, 2020</start_date>
  <completion_date type="Actual">February 28, 2022</completion_date>
  <primary_completion_date type="Actual">July 27, 2021</primary_completion_date>
  <study_type>Observational [Patient Registry]</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <observational_model>Other</observational_model>
    <time_perspective>Other</time_perspective>
  </study_design_info>
  <target_duration>1 Day</target_duration>
  <primary_outcome>
    <measure>Remote COVID-19 Assessment in Primary Care (RECAP) Early warning score</measure>
    <time_frame>18 months</time_frame>
    <description>A set of questions and a predictive tool built into electronic records, designed to distinguish people with suspected covid-19 who need to go to hospital from those who can safely be monitored at home. The final Remote COVID-19 Assessment in Primary Care (RECAP) Early warning score score divides people into 'green' (stay at home, self-monitor), amber (professional monitoring e.g., via virtual wards with home oximetry), or red (assess in person promptly).</description>
  </primary_outcome>
  <number_of_groups>4</number_of_groups>
  <enrollment type="Actual">103</enrollment>
  <condition>COVID-19</condition>
  <arm_group>
    <arm_group_label>Remote assessment tools</arm_group_label>
    <description>Qualitative methods: semi-structured interviews for approx 40 front line clinical practitioners</description>
  </arm_group>
  <arm_group>
    <arm_group_label>RECAP early warning score</arm_group_label>
    <description>Development of disease specific early warning score, building on earlier work through literature review and NEWS2 score</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Implementation/Scale up case studies</arm_group_label>
    <description>Study of implementation and scale up of remote-by-default at four different UK sites</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Infrastructure strengthening</arm_group_label>
    <description>Theory and data driven change effort involving policymakers, regulators, professional bodies, industry, patients and citizens with a view to overcoming interacting issues impacting success of digital projects.</description>
  </arm_group>
  <eligibility>
    <study_pop>
      <textblock>
        Mixed methods study&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Non-Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  Inclusion criteria for interviews&#xD;
&#xD;
        Willing and able to give informed consent for participation&#xD;
&#xD;
        Aged 18 years or above&#xD;
&#xD;
        Staff involved in delivering remote-by-default services in the frontline or 'back offices'&#xD;
&#xD;
        Patients/carers who have crossed paths with primary care services during the Covid&#xD;
        pandemic.&#xD;
&#xD;
        Pharmacy case studies:&#xD;
&#xD;
        Staff involved in delivering remote pharmacist consultation services in the frontline or&#xD;
        'back offices'&#xD;
&#xD;
        Patients/carers who have crossed paths with community pharmacy primary care services during&#xD;
        the COVID-19 pandemic.&#xD;
&#xD;
        Inclusion criteria for video and telephone consultations&#xD;
&#xD;
        Patients who have remote primary care consultation regarding symptoms associated with&#xD;
        COVID-19 and their clinicians (based in Oxford/Thames Valley) who have agreed to&#xD;
        participate in the study&#xD;
&#xD;
        Inclusion criteria for focus groups&#xD;
&#xD;
        Patients that have experienced self-reported 'long Covid' symptoms (for patient only focus&#xD;
        groups)&#xD;
&#xD;
        Clinicians that have experienced self-reported 'long Covid' symptoms (for clinician only&#xD;
        focus groups)&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
        Patients or clinicians who are too ill to be interviewed&#xD;
&#xD;
        -&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>18 Years</minimum_age>
    <maximum_age>N/A</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <location>
    <facility>
      <name>University of Oxford</name>
      <address>
        <city>Oxford</city>
        <country>United Kingdom</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>United Kingdom</country>
  </location_countries>
  <verification_date>May 2020</verification_date>
  <study_first_submitted>June 16, 2020</study_first_submitted>
  <study_first_submitted_qc>June 16, 2020</study_first_submitted_qc>
  <study_first_posted type="Actual">June 17, 2020</study_first_posted>
  <last_update_submitted>March 31, 2022</last_update_submitted>
  <last_update_submitted_qc>March 31, 2022</last_update_submitted_qc>
  <last_update_posted type="Actual">April 11, 2022</last_update_posted>
  <responsible_party>
    <responsible_party_type>Sponsor</responsible_party_type>
  </responsible_party>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>COVID-19</mesh_term>
  </condition_browse>
  <provided_document_section>
    <provided_document>
      <document_type>Study Protocol</document_type>
      <document_has_protocol>Yes</document_has_protocol>
      <document_has_icf>No</document_has_icf>
      <document_has_sap>No</document_has_sap>
      <document_date>March 22, 2021</document_date>
      <document_url>https://ClinicalTrials.gov/ProvidedDocs/41/NCT04435041/Prot_000.pdf</document_url>
    </provided_document>
  </provided_document_section>
  <!-- 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/NCT04435041
org study id: 283196
nct id: NCT04435041
lead sponsor: 
collaborator: 
collaborator: 
is fda regulated drug: No
is fda regulated device: No
18 month study, funded by ESRC COVID-19 research fund. The aim is to explore and support the
      rapid shift from face-to-face to remote (telephone and video) conversations in primary care.
      There are three components: a study of clinical interactions and decision making (micro);
      four locality-based organisational case studies of new models of care (meso); abd a a study
      of how digital innovation can support NHS infrastructure and vice versa (macro).
18 month study, funded by ESRC COVID-19 research fund. The aim is to explore and support the
      rapid shift from face-to-face to remote (telephone and video) conversations in primary care.
      There are three components: a study of clinical interactions and decision making (micro);
      four locality-based organisational case studies of new models of care (meso); abd a a study
      of how digital innovation can support NHS infrastructure and vice versa (macro). The methods
      are mainly qualitative (interviews, virtual ethnography, analysis of documents,
      micro-analysis of conversations) and are designed to inform action research.

      Key deliverables:

      At least two evidence-based assessment tools: qualitative (questions for remote assessment of
      breathlessness) and quantitative (a COVID-19-specific early warning score)

      Transferable lessons about how to achieve rapid spread and scale-up, spread in real time
      through our extensive intersectoral networks

      Strengthened infrastructure for supporting digital innovation in the NHS
observational model: Other
time perspective: Other
measure: Remote COVID-19 Assessment in Primary Care (RECAP) Early warning score
time frame: 18 months
description: A set of questions and a predictive tool built into electronic records, designed to distinguish people with suspected covid-19 who need to go to hospital from those who can safely be monitored at home. The final Remote COVID-19 Assessment in Primary Care (RECAP) Early warning score score divides people into 'green' (stay at home, self-monitor), amber (professional monitoring e.g., via virtual wards with home oximetry), or red (assess in person promptly).
arm group label: Remote assessment tools
description: Qualitative methods: semi-structured interviews for approx 40 front line clinical practitioners
arm group label: RECAP early warning score
description: Development of disease specific early warning score, building on earlier work through literature review and NEWS2 score
arm group label: Implementation/Scale up case studies
description: Study of implementation and scale up of remote-by-default at four different UK sites
arm group label: Infrastructure strengthening
description: Theory and data driven change effort involving policymakers, regulators, professional bodies, industry, patients and citizens with a view to overcoming interacting issues impacting success of digital projects.
study pop: 
sampling method: Non-Probability Sample
criteria: 
gender: All
minimum age: 18 Years
maximum age: N/A
healthy volunteers: No
facility: 
country: United Kingdom
responsible party type: Sponsor
mesh term: COVID-19
provided document: 