<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/NCT03000491</url>
  </required_header>
  <id_info>
    <org_study_id>AC16078</org_study_id>
    <nct_id>NCT03000491</nct_id>
  </id_info>
  <brief_title>Learning Health System for Asthma</brief_title>
  <official_title>Developing a National Learning Health System for Asthma to Reduce the Risk of Asthma Attacks and the Risk of Asthma Hospitalisations and Deaths</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>University of Edinburgh</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
    <collaborator>
      <agency>NHS Lothian</agency>
      <agency_class>Other</agency_class>
    </collaborator>
  </sponsors>
  <source>University of Edinburgh</source>
  <oversight_info>
    <has_dmc>No</has_dmc>
  </oversight_info>
  <brief_summary>
    <textblock>
      This study forms an initial phase of work aimed at developing a learning health system (LHS),&#xD;
      whereby data relating to asthma is extracted from patient electronic health records (EHRs)&#xD;
      across Scotland, analysed to explore variations in clinical practice and then shared with&#xD;
      general practices to highlight any improvements that can be made so that they can better&#xD;
      support people with asthma.&#xD;
&#xD;
      If successful, the investigators hope to progress to the main quality improvement phase&#xD;
      involving an increased number of practices and then incrementally build this up to cover the&#xD;
      whole of Scotland.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      The UK has amongst the highest rates of asthma in the world as well as some of the poorest&#xD;
      health outcomes from asthma.&#xD;
&#xD;
      Investigations into asthma deaths in the UK have found that the way patients were managed in&#xD;
      the time leading up to their death could be improved significantly and half of asthma deaths&#xD;
      are potentially avoidable. For most people with asthma, symptoms can come and go and&#xD;
      sometimes be erratic. To prevent these symptoms, there is a window of opportunity to&#xD;
      intervene with the appropriate care. This window occurs between when someone experiences&#xD;
      early symptoms like night cough or wheeze and when they experience a full-blown asthma&#xD;
      attack.&#xD;
&#xD;
      Most people with asthma receive care primarily in their general practice. General practices&#xD;
      have a history of using health information technology to care for their patients. The use of&#xD;
      this technology over time has resulted in the creation of rich electronic healthcare data.&#xD;
      Through this rich data there are opportunities to create a system whereby clinical management&#xD;
      can be benchmarked and improvements highlighted.&#xD;
&#xD;
      This study forms an initial phase of work aimed at developing a learning health system (LHS),&#xD;
      whereby data relating to asthma is extracted from patient electronic health records (EHRs)&#xD;
      across Scotland, analysed to explore variations in clinical practice and then shared with&#xD;
      general practices to highlight any improvements that can be made so that they can better&#xD;
      support people with asthma.&#xD;
&#xD;
      If successful, the investigators hope to progress to the main quality improvement phase&#xD;
      involving an increased number of practices and then incrementally build this up to cover the&#xD;
      whole of Scotland.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Unknown status</overall_status>
  <last_known_status>Not yet recruiting</last_known_status>
  <start_date>December 2016</start_date>
  <completion_date type="Anticipated">February 2017</completion_date>
  <primary_completion_date type="Anticipated">February 2017</primary_completion_date>
  <study_type>Observational</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <observational_model>Other</observational_model>
    <time_perspective>Retrospective</time_perspective>
  </study_design_info>
  <primary_outcome>
    <measure>Variations in clinical practice as assessed by data relating to asthma extracted from patient electronic health records.</measure>
    <time_frame>At study completion (3 months)</time_frame>
  </primary_outcome>
  <enrollment type="Anticipated">750000</enrollment>
  <condition>Asthma</condition>
  <intervention>
    <intervention_type>Other</intervention_type>
    <intervention_name>No intervention</intervention_name>
  </intervention>
  <eligibility>
    <study_pop>
      <textblock>
        Patients (with and without asthma) in Scotland registered with primary care practices from&#xD;
        2010-2015.&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Non-Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
        • Patients registered with general practices across Scotland.&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  Patients from general practices that do not to opt-in to the study.&#xD;
&#xD;
          -  Patients with a READ code recording dissent from use of their records for research&#xD;
             purposes.&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>N/A</minimum_age>
    <maximum_age>N/A</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <overall_contact>
    <last_name>Colin Simpson, BSc MSc PhD</last_name>
    <phone>0131 650 4151</phone>
    <email>c.simpson@ed.ac.uk</email>
  </overall_contact>
  <location>
    <facility>
      <name>University ot Edinburgh</name>
      <address>
        <city>Edinburgh</city>
        <zip>EH8 9AG</zip>
        <country>United Kingdom</country>
      </address>
    </facility>
    <contact>
      <last_name>Colin Simpson, BSc MSc PhD</last_name>
      <phone>0131 650 4151</phone>
      <email>c.simpson@ed.ac.uk</email>
    </contact>
    <investigator>
      <last_name>Colin Simpson, BSc MSc PhD</last_name>
      <role>Principal Investigator</role>
    </investigator>
  </location>
  <location_countries>
    <country>United Kingdom</country>
  </location_countries>
  <verification_date>August 2016</verification_date>
  <study_first_submitted>September 6, 2016</study_first_submitted>
  <study_first_submitted_qc>December 19, 2016</study_first_submitted_qc>
  <study_first_posted type="Estimate">December 22, 2016</study_first_posted>
  <last_update_submitted>January 20, 2017</last_update_submitted>
  <last_update_submitted_qc>January 20, 2017</last_update_submitted_qc>
  <last_update_posted type="Estimate">January 23, 2017</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>Asthma</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>No</sharing_ipd>
  </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/NCT03000491
org study id: AC16078
nct id: NCT03000491
lead sponsor: 
collaborator: 
has dmc: No
This study forms an initial phase of work aimed at developing a learning health system (LHS),
      whereby data relating to asthma is extracted from patient electronic health records (EHRs)
      across Scotland, analysed to explore variations in clinical practice and then shared with
      general practices to highlight any improvements that can be made so that they can better
      support people with asthma.

      If successful, the investigators hope to progress to the main quality improvement phase
      involving an increased number of practices and then incrementally build this up to cover the
      whole of Scotland.
The UK has amongst the highest rates of asthma in the world as well as some of the poorest
      health outcomes from asthma.

      Investigations into asthma deaths in the UK have found that the way patients were managed in
      the time leading up to their death could be improved significantly and half of asthma deaths
      are potentially avoidable. For most people with asthma, symptoms can come and go and
      sometimes be erratic. To prevent these symptoms, there is a window of opportunity to
      intervene with the appropriate care. This window occurs between when someone experiences
      early symptoms like night cough or wheeze and when they experience a full-blown asthma
      attack.

      Most people with asthma receive care primarily in their general practice. General practices
      have a history of using health information technology to care for their patients. The use of
      this technology over time has resulted in the creation of rich electronic healthcare data.
      Through this rich data there are opportunities to create a system whereby clinical management
      can be benchmarked and improvements highlighted.

      This study forms an initial phase of work aimed at developing a learning health system (LHS),
      whereby data relating to asthma is extracted from patient electronic health records (EHRs)
      across Scotland, analysed to explore variations in clinical practice and then shared with
      general practices to highlight any improvements that can be made so that they can better
      support people with asthma.

      If successful, the investigators hope to progress to the main quality improvement phase
      involving an increased number of practices and then incrementally build this up to cover the
      whole of Scotland.
observational model: Other
time perspective: Retrospective
measure: Variations in clinical practice as assessed by data relating to asthma extracted from patient electronic health records.
time frame: At study completion (3 months)
intervention type: Other
intervention name: No intervention
study pop: 
sampling method: Non-Probability Sample
criteria: 
gender: All
minimum age: N/A
maximum age: N/A
healthy volunteers: No
last name: Colin Simpson, BSc MSc PhD
phone: 0131 650 4151
email: c.simpson@ed.ac.uk
facility: 
contact: 
investigator: 
country: United Kingdom
responsible party type: Sponsor
mesh term: Asthma
sharing ipd: No