<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/NCT03000751</url>
  </required_header>
  <id_info>
    <org_study_id>RSB-181191</org_study_id>
    <secondary_id>R01CA181191</secondary_id>
    <nct_id>NCT03000751</nct_id>
  </id_info>
  <brief_title>CT DOSE Collaboratory</brief_title>
  <official_title>CT Dose Optimization and Standardization Endeavor (DOSE) Collaboratory</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>University of California, San Francisco</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
    <collaborator>
      <agency>University of California, Davis</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>University Hospital, Basel, Switzerland</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>Center for Diagnostic Imaging</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>Community Health Network</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>Children's Mercy Hospital Kansas City</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>City of Hope Medical Center</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>Albert Einstein Healthcare Network</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>Universität Duisburg-Essen</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>East Texas Medical Center Regional Healthcare System</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>Emory University</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>Henry Ford Health System</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>Huntsville Hospital Health System</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>Nicklaus Children's Hospital f/k/a Miami Children's Hospital</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>Mount Sinai Hospital, New York</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>Maastricht University Medical Center</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>Olive View-UCLA Education &amp; Research Institute</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>Oxford University Hospitals NHS Trust</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>San Francisco VA Health Care System</agency>
      <agency_class>U.S. Fed</agency_class>
    </collaborator>
    <collaborator>
      <agency>St. Joseph Hospital of Orange</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>St. Luke's International Hospital, Japan</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>University of Virginia</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>University of California, Irvine</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>University of California, San Diego</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>National Cancer Institute (NCI)</agency>
      <agency_class>NIH</agency_class>
    </collaborator>
  </sponsors>
  <source>University of California, San Francisco</source>
  <oversight_info>
    <has_dmc>Yes</has_dmc>
  </oversight_info>
  <brief_summary>
    <textblock>
      This is a pragmatic stepped-wedge cluster randomized controlled trial to explore variation in&#xD;
      doses used for diagnostic CT by pooling radiation dose data across diverse healthcare&#xD;
      delivery systems.&#xD;
&#xD;
      To compare different strategies for lowering and optimizing dose and identify the barriers&#xD;
      and facilitators to implementing successful dose optimization strategies and standardizing&#xD;
      practice.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      The investigators are using a stepped-wedge cluster randomized controlled trial, collecting&#xD;
      radiation dose information on CT from across all collaborating health care facilities, and&#xD;
      leading several different interventions to optimize dose across facilities. In addition to&#xD;
      collecting the CT radiation dose data, and using these results to provide feedback to the&#xD;
      collaborating health care facilities, they will be conducting surveys of several individuals&#xD;
      at each site, including key informants, such as lead radiologists, technologists, and medical&#xD;
      physicist, and radiology administrators.&#xD;
&#xD;
      They will compare and identify facilitators and barriers (assessed through surveys of&#xD;
      participating facilities) associated with successful and failed implementation of dose&#xD;
      optimization.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Unknown status</overall_status>
  <last_known_status>Active, not recruiting</last_known_status>
  <start_date type="Actual">July 2016</start_date>
  <completion_date type="Anticipated">December 2020</completion_date>
  <primary_completion_date type="Anticipated">December 2020</primary_completion_date>
  <phase>N/A</phase>
  <study_type>Interventional</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <allocation>Randomized</allocation>
    <intervention_model>Factorial Assignment</intervention_model>
    <primary_purpose>Health Services Research</primary_purpose>
    <masking>None (Open Label)</masking>
  </study_design_info>
  <primary_outcome>
    <measure>Mean Effective Dose (ED)</measure>
    <time_frame>First: 3-6 months post-audit versus 9-12 months prior to audit (excluding the 4-week post-audit period as a washout). Second: 3-6 months post MCI versus 2-6 months prior to MCI (excluding the 2-week post MCI as a washout).</time_frame>
    <description>We will assess the change in the mean effective dose after the audit and multicomponent interventions (MCI) in comparison to before the audit and multicomponent interventions.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Proportion of CT scans with an Effective dose above benchmarks</measure>
    <time_frame>First: 3-6 months post-audit versus 9-12 months prior to audit (excluding the 4-week post-audit period as a washout). Second: 3-6 months post MCI versus 2-6 months prior to MCI (excluding the 2-week post MCI as a washout).</time_frame>
    <description>We will assess the change in the proportion of examinations with an effective dose above the benchmark after the audit and after MCI in comparison to doses before the audit and MCI. The benchmark for each anatomic area is defined as the 75th percentile of the dose distribution during the pre-intervention period.</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>Mean Dose length product</measure>
    <time_frame>First: 3-6 months post-audit versus 9-12 months prior to audit (excluding the 4-week post-audit period as a washout). Second: 3-6 months post MCI versus 2-6 months prior to MCI (excluding the 2-week post MCI as a washout).</time_frame>
    <description>We will assess the change in the dose length product after the audit and MCI in comparison to before the audit and MCI.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Proportion of CT scans with a dose length product above benchmark</measure>
    <time_frame>First: 3-6 months post-audit versus 9-12 months prior to audit (excluding the 4-week post-audit period as a washout). Second: 3-6 months post MCI versus 2-6 months prior to MCI (excluding the 2-week post MCI as a washout).</time_frame>
    <description>We will assess the change in the proportion of examinations with a dose length product above the benchmark after the audit and after the MCI in comparison to doses before the audit and MCI. The benchmark for each anatomic area is defined as the 75th percentile of the dose distribution during the pre intervention period.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Mean CTDIvol</measure>
    <time_frame>First: 3-6 months post-audit versus 9-12 months prior to audit (excluding the 4-week post-audit period as a washout). Second: 3-6 months post MCI versus 2-6 months prior to MCI (excluding the 2-week post MCI as a washout).</time_frame>
    <description>We will assess the change in the CTDIvol after the audit and MCI in comparison to before the audit and multicomponent intervention.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Proportion of CT scans with a CTDIvol above benchmark</measure>
    <time_frame>First: 3-6 months post-audit versus 9-12 months prior to audit (excluding the 4-week post-audit period as a washout). Second: 3-6 months post MCI versus 2-6 months prior to MCI (excluding the 2-week post MCI as a washout).</time_frame>
    <description>We will assess the change in the proportion of examinations with a CTDIvol above the benchmark after the audit and after multicomponent intervention in comparison to doses before the audit and multicomponent intervention. The benchmark for each anatomic area is defined as the 75th percentile of the dose distribution during the pre intervention period.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Mean Effective dose</measure>
    <time_frame>12-15 mos post-MCI versus: 9-12 months before the audit and 3-6 months after the audit (allowing for a 4 week washout period) and 2-6 months prior to MCI and 3-6 months post-MCI (allowing a 2-week washout period).</time_frame>
    <description>We will assess the delayed effects of the intervention on mean effective dose.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Proportion of examinations with an Effective dose above the benchmark</measure>
    <time_frame>12-15 mos post-MCI versus: 9-12 months before the audit and 3-6 months after the audit (allowing for a 4 week washout period) and 2-6 months prior to MCI and 3-6 months post-MCI (allowing a 2-week washout period).</time_frame>
    <description>We will assess the delayed effects of the intervention on the proportion of examinations with an effective dose above the benchmark.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Mean Dose Length Product</measure>
    <time_frame>12-15 mos post-MCI versus: 9-12 months before the audit and 3-6 months after the audit (allowing for a 4 week washout period) and 2-6 months prior to MCI and 3-6 months post-MCI (allowing a 2-week washout period).</time_frame>
    <description>We will assess the delayed effects of the intervention on mean Dose Length Product.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Proportion of examinations with a Dose Length Product above the benchmark</measure>
    <time_frame>12-15 mos post-MCI versus: 9-12 months before the audit and 3-6 months after the audit (allowing for a 4 week washout period) and 2-6 months prior to MCI and 3-6 months post-MCI (allowing a 2-week washout period).</time_frame>
    <description>We will assess the delayed effects of the intervention on the proportion of examinations with a Dose Length Product above the benchmark.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Mean CTDIvol</measure>
    <time_frame>12-15 mos post-MCI versus: 9-12 months before the audit and 3-6 months after the audit (allowing for a 4 week washout period) and 2-6 months prior to MCI and 3-6 months post-MCI (allowing a 2-week washout period).</time_frame>
    <description>We will assess the delayed effects of the intervention on mean effective dose.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Proportion of examinations with a CTDIvol above the benchmark</measure>
    <time_frame>12-15 mos post-MCI versus: 9-12 months before the audit and 3-6 months after the audit (allowing for a 4 week washout period) and 2-6 months prior to MCI and 3-6 months post-MCI (allowing a 2-week washout period).</time_frame>
    <description>We will assess the delayed effects of the intervention on the proportion of examinations with a CTDIvol above the benchmark.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Mean Effective Dose</measure>
    <time_frame>3-6 months post-audit vs 9-12 months prior to audit (excluding 4-week washout); 3-6 months post MCI vs 2-6 months prior to MCI (excluding 2 week washout); 12-15 months post MCI vs 9-12 months before the audit and 2-6 months prior to MCI</time_frame>
    <description>We will use mixed-methods approaches to identify facility-level factors (assessed through surveys of participating facilities) associated with effective dose levels and associated with successful and failed implementation of dose optimization.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Proportion of examinations with an effective dose above the benchmark</measure>
    <time_frame>3-6 months post-audit vs 9-12 months prior to audit (excluding 4-week washout); 3-6 months post MCI vs 2-6 months prior to MCI (excluding 2 week washout); 12-15 months post MCI vs 9-12 months before the audit and 2-6 months prior to MCI</time_frame>
    <description>We will use mixed-methods approaches to identify facility-level factors (assessed through surveys of participating facilities) associated with the proportion of examinations with effective dose above the benchmarks and associated with successful and failed implementation of dose optimization.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Organ Doses: Brain Dose for Head CT; Lung Dose For Chest CT; Colon and Liver Dose for Abdomen CT</measure>
    <time_frame>3-6 months post-audit vs 9-12 months prior to audit (excluding 4-week washout); 3-6 months post MCI vs 2-6 months prior to MCI (excluding 2 week washout); 12-15 months post MCI vs 9-12 months before the audit and 2-6 months prior to MCI</time_frame>
    <description>The organ doses most closely reflect the areas that receive dose from any given CT scan and thus are a more direct reflecting of the CT settings. They also will be more highly correlated with future cancer risk</description>
  </secondary_outcome>
  <number_of_arms>3</number_of_arms>
  <enrollment type="Anticipated">1200000</enrollment>
  <condition>Ionizing Radiation Exposure</condition>
  <condition>Quality Improvement</condition>
  <arm_group>
    <arm_group_label>Track A</arm_group_label>
    <arm_group_type>Active Comparator</arm_group_type>
    <description>Simple Audit Report In-Person Meeting Multi-Component Intervention</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Track B</arm_group_label>
    <arm_group_type>Active Comparator</arm_group_type>
    <description>In-Person Meeting Simple Audit Report Multi-Component Intervention</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Track C</arm_group_label>
    <arm_group_type>Other</arm_group_type>
    <description>Simple Audit Report Multi-Component Intervention</description>
  </arm_group>
  <intervention>
    <intervention_type>Other</intervention_type>
    <intervention_name>Simple Audit Report</intervention_name>
    <description>The simple audit provides comparison and feedback on radiation doses.</description>
    <arm_group_label>Track A</arm_group_label>
    <arm_group_label>Track B</arm_group_label>
    <arm_group_label>Track C</arm_group_label>
  </intervention>
  <intervention>
    <intervention_type>Other</intervention_type>
    <intervention_name>Multi-Component Intervention</intervention_name>
    <description>The multi-component intervention gives tailored feedback on needed changes plus guidance using quality improvement methods that facilitate organizational change. Provides access to experts, detailed audit, collaborative calls, and site visits (as needed).</description>
    <arm_group_label>Track A</arm_group_label>
    <arm_group_label>Track B</arm_group_label>
    <arm_group_label>Track C</arm_group_label>
  </intervention>
  <intervention>
    <intervention_type>Other</intervention_type>
    <intervention_name>In-Person Meeting</intervention_name>
    <description>Collaborator meeting with an emphasis on quality improvement.</description>
    <arm_group_label>Track A</arm_group_label>
    <arm_group_label>Track B</arm_group_label>
  </intervention>
  <eligibility>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  Diagnostic CT scans of the head, chest, and/or abdomen/pelvis performed within the&#xD;
             study period&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  non-diagnostic scans that are not of the head, chest, and/or abdomen/pelvis&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>N/A</minimum_age>
    <maximum_age>99 Years</maximum_age>
    <healthy_volunteers>Accepts Healthy Volunteers</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Rebecca Smith-Bindman, MD</last_name>
    <role>Principal Investigator</role>
    <affiliation>University of California, San Francisco</affiliation>
  </overall_official>
  <overall_official>
    <last_name>Judy Yee, MD</last_name>
    <role>Principal Investigator</role>
    <affiliation>San Francisco Veterans Administration</affiliation>
  </overall_official>
  <overall_official>
    <last_name>Tom Nelson, PhD</last_name>
    <role>Principal Investigator</role>
    <affiliation>University of California, San Diego</affiliation>
  </overall_official>
  <overall_official>
    <last_name>Tony Seibert, PhD</last_name>
    <role>Principal Investigator</role>
    <affiliation>University of California, Davis</affiliation>
  </overall_official>
  <overall_official>
    <last_name>Mayil Krishnam, MD</last_name>
    <role>Principal Investigator</role>
    <affiliation>University of California, Irvine</affiliation>
  </overall_official>
  <overall_official>
    <last_name>Michael Flynn, PhD</last_name>
    <role>Principal Investigator</role>
    <affiliation>Henry Ford Health System</affiliation>
  </overall_official>
  <overall_official>
    <last_name>Mary Cocker, MSc, Csci</last_name>
    <role>Principal Investigator</role>
    <affiliation>Oxford University Hospitals NHS Trust</affiliation>
  </overall_official>
  <overall_official>
    <last_name>William Boswell, MD</last_name>
    <role>Principal Investigator</role>
    <affiliation>City of Hope Medical Center</affiliation>
  </overall_official>
  <overall_official>
    <last_name>Sebastian Schindera, MD</last_name>
    <role>Principal Investigator</role>
    <affiliation>University Hospital of Basel</affiliation>
  </overall_official>
  <overall_official>
    <last_name>Erin Bell, MHP</last_name>
    <role>Principal Investigator</role>
    <affiliation>Community Health Network</affiliation>
  </overall_official>
  <overall_official>
    <last_name>Phuong-Anh Duong, MD</last_name>
    <role>Principal Investigator</role>
    <affiliation>Emory University</affiliation>
  </overall_official>
  <overall_official>
    <last_name>Nima Kasraie, PhD, MSc</last_name>
    <role>Principal Investigator</role>
    <affiliation>Children's Mercy Hospital Kansas City</affiliation>
  </overall_official>
  <overall_official>
    <last_name>Pavlina Pike, PhD</last_name>
    <role>Principal Investigator</role>
    <affiliation>Huntsville Hospital</affiliation>
  </overall_official>
  <overall_official>
    <last_name>Luisa Cervantes, MD</last_name>
    <role>Principal Investigator</role>
    <affiliation>Nicklaus Children's Hospital f/k/a Miami Children's Hospital</affiliation>
  </overall_official>
  <overall_official>
    <last_name>Joachim Wildberger, PhD</last_name>
    <role>Principal Investigator</role>
    <affiliation>Maastricht University Medical Center</affiliation>
  </overall_official>
  <overall_official>
    <last_name>Michael Forsting, MD</last_name>
    <role>Principal Investigator</role>
    <affiliation>University of Duisburg-Essen</affiliation>
  </overall_official>
  <overall_official>
    <last_name>Fady Kassem, PhD</last_name>
    <role>Principal Investigator</role>
    <affiliation>St. Joseph Hospital of Orange</affiliation>
  </overall_official>
  <overall_official>
    <last_name>Darrell Fendrick, CT</last_name>
    <role>Principal Investigator</role>
    <affiliation>East Texas Medical Center</affiliation>
  </overall_official>
  <overall_official>
    <last_name>Sugoto Mukherjee, MD</last_name>
    <role>Principal Investigator</role>
    <affiliation>University of Virginia Health System</affiliation>
  </overall_official>
  <overall_official>
    <last_name>Brad Delman, MD</last_name>
    <role>Principal Investigator</role>
    <affiliation>Icahn School of Medicine at Mount Sinai</affiliation>
  </overall_official>
  <overall_official>
    <last_name>Jodi Roehm</last_name>
    <role>Principal Investigator</role>
    <affiliation>Center for Diagnostic Imaging</affiliation>
  </overall_official>
  <overall_official>
    <last_name>Anokh Pahwa, MD</last_name>
    <role>Principal Investigator</role>
    <affiliation>Olive View - UCLA</affiliation>
  </overall_official>
  <overall_official>
    <last_name>Ryan Lee, MD, MBA</last_name>
    <role>Principal Investigator</role>
    <affiliation>Einstein Medical Center</affiliation>
  </overall_official>
  <overall_official>
    <last_name>Jay Starkey, MD</last_name>
    <role>Principal Investigator</role>
    <affiliation>St. Luke's International Hospital, Tokyo</affiliation>
  </overall_official>
  <overall_official>
    <last_name>Diana Miglioretti, PhD</last_name>
    <role>Principal Investigator</role>
    <affiliation>University of California, Davis</affiliation>
  </overall_official>
  <overall_official>
    <last_name>Saravanabavaan Suntharalingam, MD</last_name>
    <role>Principal Investigator</role>
    <affiliation>University of Duisburg-Essen</affiliation>
  </overall_official>
  <overall_official>
    <last_name>Sara Lewis, MD</last_name>
    <role>Principal Investigator</role>
    <affiliation>Icahn School of Medicine at Mount Sinai</affiliation>
  </overall_official>
  <link>
    <url>http://ctdose.ucsf.edu</url>
    <description>The website explores and focuses on studying the impact of medical imaging on health, minimizing the harms of medical imaging and and providing rigorous evidence to aid policymakers regarding use of medical imaging.</description>
  </link>
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  <verification_date>March 2020</verification_date>
  <study_first_submitted>December 12, 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>March 23, 2020</last_update_submitted>
  <last_update_submitted_qc>March 23, 2020</last_update_submitted_qc>
  <last_update_posted type="Actual">March 25, 2020</last_update_posted>
  <responsible_party>
    <responsible_party_type>Sponsor</responsible_party_type>
  </responsible_party>
  <keyword>CT scan</keyword>
  <keyword>CT exam</keyword>
  <keyword>ionizing radiation</keyword>
  <keyword>medical imaging</keyword>
  <keyword>cat scan</keyword>
  <keyword>radiation</keyword>
  <patient_data>
    <sharing_ipd>No</sharing_ipd>
  </patient_data>
  <provided_document_section>
    <provided_document>
      <document_type>Study Protocol and Statistical Analysis Plan</document_type>
      <document_has_protocol>Yes</document_has_protocol>
      <document_has_icf>No</document_has_icf>
      <document_has_sap>Yes</document_has_sap>
      <document_date>August 29, 2017</document_date>
      <document_url>https://ClinicalTrials.gov/ProvidedDocs/51/NCT03000751/Prot_SAP_001.pdf</document_url>
    </provided_document>
  </provided_document_section>
  <pending_results>
    <submitted>December 24, 2021</submitted>
    <returned>January 21, 2022</returned>
    <submitted>September 27, 2022</submitted>
    <returned>October 24, 2022</returned>
    <submitted>September 1, 2023</submitted>
  </pending_results>
  <!-- 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/NCT03000751
org study id: RSB-181191
secondary id: R01CA181191
nct id: NCT03000751
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has dmc: Yes
This is a pragmatic stepped-wedge cluster randomized controlled trial to explore variation in
      doses used for diagnostic CT by pooling radiation dose data across diverse healthcare
      delivery systems.

      To compare different strategies for lowering and optimizing dose and identify the barriers
      and facilitators to implementing successful dose optimization strategies and standardizing
      practice.
The investigators are using a stepped-wedge cluster randomized controlled trial, collecting
      radiation dose information on CT from across all collaborating health care facilities, and
      leading several different interventions to optimize dose across facilities. In addition to
      collecting the CT radiation dose data, and using these results to provide feedback to the
      collaborating health care facilities, they will be conducting surveys of several individuals
      at each site, including key informants, such as lead radiologists, technologists, and medical
      physicist, and radiology administrators.

      They will compare and identify facilitators and barriers (assessed through surveys of
      participating facilities) associated with successful and failed implementation of dose
      optimization.
allocation: Randomized
intervention model: Factorial Assignment
primary purpose: Health Services Research
masking: None (Open Label)
measure: Mean Effective Dose (ED)
time frame: First: 3-6 months post-audit versus 9-12 months prior to audit (excluding the 4-week post-audit period as a washout). Second: 3-6 months post MCI versus 2-6 months prior to MCI (excluding the 2-week post MCI as a washout).
description: We will assess the change in the mean effective dose after the audit and multicomponent interventions (MCI) in comparison to before the audit and multicomponent interventions.
measure: Proportion of CT scans with an Effective dose above benchmarks
time frame: First: 3-6 months post-audit versus 9-12 months prior to audit (excluding the 4-week post-audit period as a washout). Second: 3-6 months post MCI versus 2-6 months prior to MCI (excluding the 2-week post MCI as a washout).
description: We will assess the change in the proportion of examinations with an effective dose above the benchmark after the audit and after MCI in comparison to doses before the audit and MCI. The benchmark for each anatomic area is defined as the 75th percentile of the dose distribution during the pre-intervention period.
measure: Mean Dose length product
time frame: First: 3-6 months post-audit versus 9-12 months prior to audit (excluding the 4-week post-audit period as a washout). Second: 3-6 months post MCI versus 2-6 months prior to MCI (excluding the 2-week post MCI as a washout).
description: We will assess the change in the dose length product after the audit and MCI in comparison to before the audit and MCI.
measure: Proportion of CT scans with a dose length product above benchmark
time frame: First: 3-6 months post-audit versus 9-12 months prior to audit (excluding the 4-week post-audit period as a washout). Second: 3-6 months post MCI versus 2-6 months prior to MCI (excluding the 2-week post MCI as a washout).
description: We will assess the change in the proportion of examinations with a dose length product above the benchmark after the audit and after the MCI in comparison to doses before the audit and MCI. The benchmark for each anatomic area is defined as the 75th percentile of the dose distribution during the pre intervention period.
measure: Mean CTDIvol
time frame: First: 3-6 months post-audit versus 9-12 months prior to audit (excluding the 4-week post-audit period as a washout). Second: 3-6 months post MCI versus 2-6 months prior to MCI (excluding the 2-week post MCI as a washout).
description: We will assess the change in the CTDIvol after the audit and MCI in comparison to before the audit and multicomponent intervention.
measure: Proportion of CT scans with a CTDIvol above benchmark
time frame: First: 3-6 months post-audit versus 9-12 months prior to audit (excluding the 4-week post-audit period as a washout). Second: 3-6 months post MCI versus 2-6 months prior to MCI (excluding the 2-week post MCI as a washout).
description: We will assess the change in the proportion of examinations with a CTDIvol above the benchmark after the audit and after multicomponent intervention in comparison to doses before the audit and multicomponent intervention. The benchmark for each anatomic area is defined as the 75th percentile of the dose distribution during the pre intervention period.
measure: Mean Effective dose
time frame: 12-15 mos post-MCI versus: 9-12 months before the audit and 3-6 months after the audit (allowing for a 4 week washout period) and 2-6 months prior to MCI and 3-6 months post-MCI (allowing a 2-week washout period).
description: We will assess the delayed effects of the intervention on mean effective dose.
measure: Proportion of examinations with an Effective dose above the benchmark
time frame: 12-15 mos post-MCI versus: 9-12 months before the audit and 3-6 months after the audit (allowing for a 4 week washout period) and 2-6 months prior to MCI and 3-6 months post-MCI (allowing a 2-week washout period).
description: We will assess the delayed effects of the intervention on the proportion of examinations with an effective dose above the benchmark.
measure: Mean Dose Length Product
time frame: 12-15 mos post-MCI versus: 9-12 months before the audit and 3-6 months after the audit (allowing for a 4 week washout period) and 2-6 months prior to MCI and 3-6 months post-MCI (allowing a 2-week washout period).
description: We will assess the delayed effects of the intervention on mean Dose Length Product.
measure: Proportion of examinations with a Dose Length Product above the benchmark
time frame: 12-15 mos post-MCI versus: 9-12 months before the audit and 3-6 months after the audit (allowing for a 4 week washout period) and 2-6 months prior to MCI and 3-6 months post-MCI (allowing a 2-week washout period).
description: We will assess the delayed effects of the intervention on the proportion of examinations with a Dose Length Product above the benchmark.
measure: Mean CTDIvol
time frame: 12-15 mos post-MCI versus: 9-12 months before the audit and 3-6 months after the audit (allowing for a 4 week washout period) and 2-6 months prior to MCI and 3-6 months post-MCI (allowing a 2-week washout period).
description: We will assess the delayed effects of the intervention on mean effective dose.
measure: Proportion of examinations with a CTDIvol above the benchmark
time frame: 12-15 mos post-MCI versus: 9-12 months before the audit and 3-6 months after the audit (allowing for a 4 week washout period) and 2-6 months prior to MCI and 3-6 months post-MCI (allowing a 2-week washout period).
description: We will assess the delayed effects of the intervention on the proportion of examinations with a CTDIvol above the benchmark.
measure: Mean Effective Dose
time frame: 3-6 months post-audit vs 9-12 months prior to audit (excluding 4-week washout); 3-6 months post MCI vs 2-6 months prior to MCI (excluding 2 week washout); 12-15 months post MCI vs 9-12 months before the audit and 2-6 months prior to MCI
description: We will use mixed-methods approaches to identify facility-level factors (assessed through surveys of participating facilities) associated with effective dose levels and associated with successful and failed implementation of dose optimization.
measure: Proportion of examinations with an effective dose above the benchmark
time frame: 3-6 months post-audit vs 9-12 months prior to audit (excluding 4-week washout); 3-6 months post MCI vs 2-6 months prior to MCI (excluding 2 week washout); 12-15 months post MCI vs 9-12 months before the audit and 2-6 months prior to MCI
description: We will use mixed-methods approaches to identify facility-level factors (assessed through surveys of participating facilities) associated with the proportion of examinations with effective dose above the benchmarks and associated with successful and failed implementation of dose optimization.
measure: Organ Doses: Brain Dose for Head CT; Lung Dose For Chest CT; Colon and Liver Dose for Abdomen CT
time frame: 3-6 months post-audit vs 9-12 months prior to audit (excluding 4-week washout); 3-6 months post MCI vs 2-6 months prior to MCI (excluding 2 week washout); 12-15 months post MCI vs 9-12 months before the audit and 2-6 months prior to MCI
description: The organ doses most closely reflect the areas that receive dose from any given CT scan and thus are a more direct reflecting of the CT settings. They also will be more highly correlated with future cancer risk
arm group label: Track A
arm group type: Active Comparator
description: Simple Audit Report In-Person Meeting Multi-Component Intervention
arm group label: Track B
arm group type: Active Comparator
description: In-Person Meeting Simple Audit Report Multi-Component Intervention
arm group label: Track C
arm group type: Other
description: Simple Audit Report Multi-Component Intervention
intervention type: Other
intervention name: Simple Audit Report
description: The simple audit provides comparison and feedback on radiation doses.
arm group label: Track A
arm group label: Track B
arm group label: Track C
intervention type: Other
intervention name: Multi-Component Intervention
description: The multi-component intervention gives tailored feedback on needed changes plus guidance using quality improvement methods that facilitate organizational change. Provides access to experts, detailed audit, collaborative calls, and site visits (as needed).
arm group label: Track A
arm group label: Track B
arm group label: Track C
intervention type: Other
intervention name: In-Person Meeting
description: Collaborator meeting with an emphasis on quality improvement.
arm group label: Track A
arm group label: Track B
criteria: 
gender: All
minimum age: N/A
maximum age: 99 Years
healthy volunteers: Accepts Healthy Volunteers
last name: Rebecca Smith-Bindman, MD
role: Principal Investigator
affiliation: University of California, San Francisco
last name: Judy Yee, MD
role: Principal Investigator
affiliation: San Francisco Veterans Administration
last name: Tom Nelson, PhD
role: Principal Investigator
affiliation: University of California, San Diego
last name: Tony Seibert, PhD
role: Principal Investigator
affiliation: University of California, Davis
last name: Mayil Krishnam, MD
role: Principal Investigator
affiliation: University of California, Irvine
last name: Michael Flynn, PhD
role: Principal Investigator
affiliation: Henry Ford Health System
last name: Mary Cocker, MSc, Csci
role: Principal Investigator
affiliation: Oxford University Hospitals NHS Trust
last name: William Boswell, MD
role: Principal Investigator
affiliation: City of Hope Medical Center
last name: Sebastian Schindera, MD
role: Principal Investigator
affiliation: University Hospital of Basel
last name: Erin Bell, MHP
role: Principal Investigator
affiliation: Community Health Network
last name: Phuong-Anh Duong, MD
role: Principal Investigator
affiliation: Emory University
last name: Nima Kasraie, PhD, MSc
role: Principal Investigator
affiliation: Children's Mercy Hospital Kansas City
last name: Pavlina Pike, PhD
role: Principal Investigator
affiliation: Huntsville Hospital
last name: Luisa Cervantes, MD
role: Principal Investigator
affiliation: Nicklaus Children's Hospital f/k/a Miami Children's Hospital
last name: Joachim Wildberger, PhD
role: Principal Investigator
affiliation: Maastricht University Medical Center
last name: Michael Forsting, MD
role: Principal Investigator
affiliation: University of Duisburg-Essen
last name: Fady Kassem, PhD
role: Principal Investigator
affiliation: St. Joseph Hospital of Orange
last name: Darrell Fendrick, CT
role: Principal Investigator
affiliation: East Texas Medical Center
last name: Sugoto Mukherjee, MD
role: Principal Investigator
affiliation: University of Virginia Health System
last name: Brad Delman, MD
role: Principal Investigator
affiliation: Icahn School of Medicine at Mount Sinai
last name: Jodi Roehm
role: Principal Investigator
affiliation: Center for Diagnostic Imaging
last name: Anokh Pahwa, MD
role: Principal Investigator
affiliation: Olive View - UCLA
last name: Ryan Lee, MD, MBA
role: Principal Investigator
affiliation: Einstein Medical Center
last name: Jay Starkey, MD
role: Principal Investigator
affiliation: St. Luke's International Hospital, Tokyo
last name: Diana Miglioretti, PhD
role: Principal Investigator
affiliation: University of California, Davis
last name: Saravanabavaan Suntharalingam, MD
role: Principal Investigator
affiliation: University of Duisburg-Essen
last name: Sara Lewis, MD
role: Principal Investigator
affiliation: Icahn School of Medicine at Mount Sinai
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