<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/NCT04408976</url>
  </required_header>
  <id_info>
    <org_study_id>P1746</org_study_id>
    <nct_id>NCT04408976</nct_id>
  </id_info>
  <brief_title>Implementation Study With Decision Support Based on Data</brief_title>
  <official_title>Implementation Study With Machine Learning Based Decision Support Software for Treatment of Urinary Tract Infections in General Practice.</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Leiden University Medical Center</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
    <collaborator>
      <agency>Pacmed BV</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>Zorgverzekeraar CZ</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>Zorgverzekeraar Zilveren Kruis</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>Zorgverzekeraar Menzis</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>Academisch Medisch Centrum - Universiteit van Amsterdam (AMC-UvA)</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>Netherlands Instititute for Health Services Research</agency>
      <agency_class>Other</agency_class>
    </collaborator>
  </sponsors>
  <source>Leiden University Medical Center</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>
      This study evaluates the implementation of a machine learning based clinical decision support&#xD;
      system for treatment of patients presenting with an urinary tract infection in general&#xD;
      practice. The software was developed to support general practitioners in the choice of&#xD;
      antibiotic regimen.&#xD;
    </textblock>
  </brief_summary>
  <overall_status>Completed</overall_status>
  <start_date type="Actual">November 13, 2017</start_date>
  <completion_date type="Actual">May 16, 2018</completion_date>
  <primary_completion_date type="Actual">May 16, 2018</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>Prospective</time_perspective>
  </study_design_info>
  <primary_outcome>
    <measure>Non-recurrent UTI</measure>
    <time_frame>28 days</time_frame>
    <description>A subsequent period of time after treatment, in which no new UTI treatment was needed</description>
  </primary_outcome>
  <number_of_groups>2</number_of_groups>
  <enrollment type="Actual">16824</enrollment>
  <condition>Urinary Tract Infections</condition>
  <arm_group>
    <arm_group_label>Software practices</arm_group_label>
    <description>Patients with urinary tract infection in practices using the clinical decision support software</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Control practices</arm_group_label>
    <description>Patients with urinary tract infection in practices not using the clinical decision support software</description>
  </arm_group>
  <eligibility>
    <study_pop>
      <textblock>
        Patients with a urinary tract infection diagnosed by the general practitioner&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Non-Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  Patients with a urinary tract infection in general practice&#xD;
&#xD;
          -  Age &gt; 12 years.&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  No.&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>12 Years</minimum_age>
    <maximum_age>N/A</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Willem Herter</last_name>
    <role>Study Director</role>
    <affiliation>Leiden University Medical Center</affiliation>
  </overall_official>
  <overall_official>
    <last_name>Tobias Bonten</last_name>
    <role>Principal Investigator</role>
    <affiliation>Leiden University Medical Center</affiliation>
  </overall_official>
  <location>
    <facility>
      <name>Netherlands Institute for Health Services Research</name>
      <address>
        <city>Utrecht</city>
        <country>Netherlands</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>Netherlands</country>
  </location_countries>
  <verification_date>May 2020</verification_date>
  <study_first_submitted>May 26, 2020</study_first_submitted>
  <study_first_submitted_qc>May 26, 2020</study_first_submitted_qc>
  <study_first_posted type="Actual">June 1, 2020</study_first_posted>
  <last_update_submitted>May 26, 2020</last_update_submitted>
  <last_update_submitted_qc>May 26, 2020</last_update_submitted_qc>
  <last_update_posted type="Actual">June 1, 2020</last_update_posted>
  <responsible_party>
    <responsible_party_type>Principal Investigator</responsible_party_type>
    <investigator_affiliation>Leiden University Medical Center</investigator_affiliation>
    <investigator_full_name>Tn Bonten</investigator_full_name>
    <investigator_title>Assistant Professor</investigator_title>
  </responsible_party>
  <keyword>Machine learning</keyword>
  <keyword>Clinical Decision Support Systems</keyword>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Infections</mesh_term>
    <mesh_term>Urinary Tract Infections</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/NCT04408976
org study id: P1746
nct id: NCT04408976
lead sponsor: 
collaborator: 
collaborator: 
collaborator: 
collaborator: 
collaborator: 
collaborator: 
has dmc: No
is fda regulated drug: No
is fda regulated device: No
This study evaluates the implementation of a machine learning based clinical decision support
      system for treatment of patients presenting with an urinary tract infection in general
      practice. The software was developed to support general practitioners in the choice of
      antibiotic regimen.
observational model: Cohort
time perspective: Prospective
measure: Non-recurrent UTI
time frame: 28 days
description: A subsequent period of time after treatment, in which no new UTI treatment was needed
arm group label: Software practices
description: Patients with urinary tract infection in practices using the clinical decision support software
arm group label: Control practices
description: Patients with urinary tract infection in practices not using the clinical decision support software
study pop: 
sampling method: Non-Probability Sample
criteria: 
gender: All
minimum age: 12 Years
maximum age: N/A
healthy volunteers: No
last name: Willem Herter
role: Study Director
affiliation: Leiden University Medical Center
last name: Tobias Bonten
role: Principal Investigator
affiliation: Leiden University Medical Center
facility: 
country: Netherlands
responsible party type: Principal Investigator
investigator affiliation: Leiden University Medical Center
investigator full name: Tn Bonten
investigator title: Assistant Professor
mesh term: Infections
mesh term: Urinary Tract Infections
sharing ipd: No