<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/NCT03001713</url>
  </required_header>
  <id_info>
    <org_study_id>HL133793-01A1</org_study_id>
    <nct_id>NCT03001713</nct_id>
  </id_info>
  <brief_title>CV Wizard: Does a Clinical Decision Support Tool Improve CVD Risk Factor Control in Safety Net Clinics?</brief_title>
  <acronym>CV_WIZARD</acronym>
  <official_title>CV Wizard: Does a Prioritized, Point-of-Care Clinical Decision Support Tool Improve Guideline-Based CVD Risk Factor Control in Safety Net Clinics?</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Kaiser Permanente</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
    <collaborator>
      <agency>OCHIN, Inc.</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>HealthPartners Institute</agency>
      <agency_class>Other</agency_class>
    </collaborator>
  </sponsors>
  <source>Kaiser Permanente</source>
  <oversight_info>
    <has_dmc>Yes</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 project aims to reduce disparities in cardiovascular disease (CVD) risk factor control&#xD;
      and in rates of heart attacks and strokes among the low-income, racially / ethnically diverse&#xD;
      Americans who receive primary care at safety net community health centers (CHCs). To achieve&#xD;
      this important objective, the investigators will adapt a successful clinical decision support&#xD;
      (CDS) system currently used in CVD care at several large, integrated health care systems, to&#xD;
      meet the patient needs and workflow processes of 60 CHCs. The investigators will determine if&#xD;
      use of this CDS improves CVD care, reduces disparities in CVD care and outcomes, and&#xD;
      increases patient engagement in CVD treatment choices, in CHCs. Results of this randomized&#xD;
      trial will help accelerate the translation of major investments in health informatics systems&#xD;
      into substantial clinical benefits for large numbers of high-risk, low-income patients.&#xD;
      Results will also provide a template for CVD care improvement that can be spread to other&#xD;
      CHCs and extended to other clinical conditions.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      The investigators seek to learn whether clinical decision support (CDS) systems from&#xD;
      well-resourced care settings are effective in safety net community health centers (CHCs), and&#xD;
      how to enhance such cross-setting implementation. Thus, the investigators propose a&#xD;
      clinic-randomized, pragmatic trial of the uptake and impact of the 'CV Wizard' CDS tool in 60&#xD;
      CHCs that share a linked electronic health record. CV Wizard summarizes each patient's&#xD;
      reversible CVD risks, generates prioritized, guideline-based care recommendations based on&#xD;
      those risks, and shows these in a 'provider view' and a 'patient view,' enabling patient&#xD;
      engagement. Use rates and satisfaction with this CDS were high in the large healthcare&#xD;
      delivery system where it was developed and tested. The investigators will: study its impact&#xD;
      in the CHC setting, assess uptake of the CDS system, assess strategies for integrating it&#xD;
      into CHC workflows, and its impact on patients' CVD risk and risk factor management. The&#xD;
      investigators hypothesize that this cutting-edge CDS will improve rates of guideline-based&#xD;
      CVD preventive care in CHC patients, who experience disparities in CVD risk factors, care and&#xD;
      outcomes. The 60 study clinics will be members of OCHIN, Inc., a non-profit health&#xD;
      center-controlled network and national leader in health information technology for CHCs.&#xD;
      OCHIN's leadership enthusiastically supports the proposed work and will help ensure that&#xD;
      recruitment goals are met. The investigators will partner with stakeholders / medical&#xD;
      leadership from OCHIN's member clinics at every step, via existing structures. This study&#xD;
      addresses gaps in guideline-based CVD care in high-risk populations, using targeted,&#xD;
      multi-level strategies; considers setting-specific needs; tests how CDS affects guideline&#xD;
      implementation in community clinics; and uses technology to support patient engagement.&#xD;
      Results will yield knowledge about providing CHCs with cutting-edge CDS, and associated&#xD;
      impacts on CVD disparities. The innovative study is the second trial to implement CDS tools&#xD;
      from private care settings in CHCs, and the first to do so with complex CDS tools that&#xD;
      address a range of CVD risk management guidelines, make prioritized care recommendations, and&#xD;
      facilitate point-of-care patient engagement. Results could lead to substantial improvements&#xD;
      in CVD prevention, care, and outcomes in CHCs nationwide.&#xD;
&#xD;
      Our overarching aims are to:&#xD;
&#xD;
      Aim 1. Conduct a clinic-randomized trial of the impact of an evidence-based point-of-care CDS&#xD;
      system on (i) overall CVD risk scores, and (ii) control of individual CVD risks (blood&#xD;
      pressure; HbA1c, lipid levels; aspirin use; smoking; body mass index), among high CVD risk&#xD;
      CHC adult patients. H1: High CVD risk patients in Arm 1 CHCs will have significantly lower&#xD;
      overall CVD risk scores over a 12-month post-index visit period, compared to those in Arm 2&#xD;
      CHCs. H2: High CVD risk patients in Arm 1 CHCs who have poor control of specific CVD risk&#xD;
      factors at an index visit will have significantly better control of those factors over a 12&#xD;
      month post-index visit period, compared to those in Arm 2 CHCs. H3: Disparities in specific&#xD;
      CVD risk factor control between CHC patients' versus national CVD risk factor control rates&#xD;
      will be significantly reduced by 18 months post-implementation in each Arm (secondary&#xD;
      analysis).&#xD;
&#xD;
      Aim 2. Develop and hone need-based implementation support protocols to help Arm 1 CHCs&#xD;
      implement the CV Wizard CDS system into their standard workflows; assess whether use of the&#xD;
      protocols developed for Arm 1 CHCs accelerates implementation and adoption of the CDS system&#xD;
      in the Arm 2 CHCs. H4: CDS uptake into CHC workflows will be significantly faster in Arm 2&#xD;
      CHCs than in Arm 1 CHCs.&#xD;
&#xD;
      Aim 3. Conduct a mixed methods process evaluation, guided by the Technology Acceptance Model,&#xD;
      to identify and address patient, provider, and delivery system barriers to uptake / impact of&#xD;
      this CDS in CHCs.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Active, not recruiting</overall_status>
  <start_date type="Actual">February 22, 2018</start_date>
  <completion_date type="Anticipated">February 28, 2023</completion_date>
  <primary_completion_date type="Actual">March 31, 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>Parallel Assignment</intervention_model>
    <primary_purpose>Health Services Research</primary_purpose>
    <masking>None (Open Label)</masking>
  </study_design_info>
  <primary_outcome>
    <measure>Comparison of CVD outcomes for patients in CHCs</measure>
    <time_frame>Up to 36 months</time_frame>
    <description>Compare patients' CVD outcomes in the 30 Arm 1 vs. 30 Arm 2 CHCs, in months 13-30 (Aim 1); assess whether the revised implementation support materials expedite CDS adoption (Aim 2); and use mixed methods to identify multi-level barriers / facilitators to adoption of the CDS tool (Aim 3).</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>Reach: Encounters affected</measure>
    <time_frame>Up to 36 months</time_frame>
    <description>% clinic encounters where CV Wizard suggests running the full risk assessment tool, i.e., identified a target patient.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Effectiveness (impact): Patient outcomes - 10 year pooled ASCVD risk score</measure>
    <time_frame>Up to 36 months</time_frame>
    <description>(i) ASCVD risk score (American College of Cardiology-ACC/ American Heart Association - AHA) 10-year pooled ASCVD risk score, 40-75 year olds</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Effectiveness (impact): Patient outcomes - Framingham 30-year CVD risk score</measure>
    <time_frame>Up to 36 months</time_frame>
    <description>(i) Framingham 30-year CVD risk score, 20-39 year olds.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Effectiveness (impact): Patient outcomes - last BP ≤140/90</measure>
    <time_frame>Up to 36 months</time_frame>
    <description>(ii) Control of individual CVD risk factors: last BP ≤140/90</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Effectiveness (impact): Patient outcomes - last A1c≤8</measure>
    <time_frame>Up to 36 months</time_frame>
    <description>(ii) Control of individual CVD risk factors: last A1c≤8</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Effectiveness (impact): Patient outcomes - last LDL&lt;100</measure>
    <time_frame>Up to 36 months</time_frame>
    <description>(ii) Control of individual CVD risk factors: last LDL&lt;100</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Effectiveness (impact): Patient outcomes - appropriate aspirin use</measure>
    <time_frame>Up to 36 months</time_frame>
    <description>(ii) Control of individual CVD risk factors: appropriate aspirin use</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Effectiveness (impact): Patient outcomes - not current smoker</measure>
    <time_frame>Up to 12 months</time_frame>
    <description>(ii) Control of individual CVD risk factors: not current smoker</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Effectiveness (impact): Patient outcomes - last BMI ≤25</measure>
    <time_frame>Up to 36 months</time_frame>
    <description>(ii) Control of individual CVD risk factors: last BMI≤25</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Effectiveness (impact): Patient outcomes - appropriate cardioprotective medications</measure>
    <time_frame>Up to 36 months</time_frame>
    <description>(ii) Control of individual CVD risk factors: appropriate cardioprotective prescriptions (e.g., statins).</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Adoption: CDS uptake</measure>
    <time_frame>Up to 36 months</time_frame>
    <description>% of encounters where care team member opts to run the CV Wizard risk assessment.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Implementation: User perceptions</measure>
    <time_frame>Up to 36 months</time_frame>
    <description>Perceived ease of use, usefulness, acceptability of CV Wizard; intent to use it.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Maintenance over time</measure>
    <time_frame>Up to 36 months</time_frame>
    <description>All measures over 2.5 years of follow-up, Arm 1; 1.5 years, Arm 2.</description>
  </secondary_outcome>
  <number_of_arms>2</number_of_arms>
  <enrollment type="Anticipated">60</enrollment>
  <condition>Heart Attack</condition>
  <condition>Stroke</condition>
  <condition>Cardiovascular Diseases</condition>
  <arm_group>
    <arm_group_label>Arm 1: Immediate implementation</arm_group_label>
    <arm_group_type>Active Comparator</arm_group_type>
    <description>30 safety net community health centers (CHCs) will be randomized to implement the sophisticated CV Wizard clinical decision support (CDS) system at the start of study year 2. Arm 1 CHCs will receive implementation support that will be pragmatically iterated to address any barriers to adoption / sustained use of the CDS that are identified through study activities. The investigators will apply these learnings to improve adoption rates in Arm 2.</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Arm 2: Delayed implementation</arm_group_label>
    <arm_group_type>Active Comparator</arm_group_type>
    <description>30 safety net community health centers (CHCs) will be randomized to implement the sophisticated CV Wizard clinical decision support (CDS) system 18 months later than Arm 1. The investigators will measure the intervention's impact on CVD risk factor control in CHCs.</description>
  </arm_group>
  <intervention>
    <intervention_type>Behavioral</intervention_type>
    <intervention_name>CV WIZARD</intervention_name>
    <description>This project will determine whether a sophisticated CDS system will be effective in CHCs. The innovative, point-of-care, web-based CDS system we will test (&quot;CV Wizard&quot;) generates a guideline-based prioritized summary of each patient's major CVD risk factors, then presents patient and provider 'views' of this summary, with individualized care recommendations.</description>
    <arm_group_label>Arm 1: Immediate implementation</arm_group_label>
    <arm_group_label>Arm 2: Delayed implementation</arm_group_label>
  </intervention>
  <eligibility>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  Adult clinic attendees with high CVD risk, including women and minorities&#xD;
&#xD;
          -  Persons aged 18-21 with high-CVD risk&#xD;
&#xD;
          -  Some subjects with mental health conditions of various types&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
        -Children aged younger than 18&#xD;
&#xD;
        Note: The investigators are not enrolling patients for this clinic-randomized study, but&#xD;
        rather studying the uptake and impact of a set of EHR-based clinical decision support tools&#xD;
        into regular care at the participating clinics. In this clinic-randomized trial, the&#xD;
        intervention / randomization are clinic level.&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>18 Years</minimum_age>
    <maximum_age>N/A</maximum_age>
    <healthy_volunteers>Accepts Healthy Volunteers</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Rachel Gold, PhD, MPH</last_name>
    <role>Principal Investigator</role>
    <affiliation>Kaiser Permanente</affiliation>
  </overall_official>
  <location>
    <facility>
      <name>Kaiser Permanente Center for Health Research</name>
      <address>
        <city>Portland</city>
        <state>Oregon</state>
        <zip>97227</zip>
        <country>United States</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>United States</country>
  </location_countries>
  <verification_date>May 2022</verification_date>
  <study_first_submitted>December 14, 2016</study_first_submitted>
  <study_first_submitted_qc>December 22, 2016</study_first_submitted_qc>
  <study_first_posted type="Estimate">December 23, 2016</study_first_posted>
  <last_update_submitted>May 25, 2022</last_update_submitted>
  <last_update_submitted_qc>May 25, 2022</last_update_submitted_qc>
  <last_update_posted type="Actual">May 27, 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>Cardiovascular Diseases</mesh_term>
    <mesh_term>Myocardial Infarction</mesh_term>
  </condition_browse>
  <!-- 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/NCT03001713
org study id: HL133793-01A1
nct id: NCT03001713
lead sponsor: 
collaborator: 
collaborator: 
has dmc: Yes
is fda regulated drug: No
is fda regulated device: No
This project aims to reduce disparities in cardiovascular disease (CVD) risk factor control
      and in rates of heart attacks and strokes among the low-income, racially / ethnically diverse
      Americans who receive primary care at safety net community health centers (CHCs). To achieve
      this important objective, the investigators will adapt a successful clinical decision support
      (CDS) system currently used in CVD care at several large, integrated health care systems, to
      meet the patient needs and workflow processes of 60 CHCs. The investigators will determine if
      use of this CDS improves CVD care, reduces disparities in CVD care and outcomes, and
      increases patient engagement in CVD treatment choices, in CHCs. Results of this randomized
      trial will help accelerate the translation of major investments in health informatics systems
      into substantial clinical benefits for large numbers of high-risk, low-income patients.
      Results will also provide a template for CVD care improvement that can be spread to other
      CHCs and extended to other clinical conditions.
The investigators seek to learn whether clinical decision support (CDS) systems from
      well-resourced care settings are effective in safety net community health centers (CHCs), and
      how to enhance such cross-setting implementation. Thus, the investigators propose a
      clinic-randomized, pragmatic trial of the uptake and impact of the 'CV Wizard' CDS tool in 60
      CHCs that share a linked electronic health record. CV Wizard summarizes each patient's
      reversible CVD risks, generates prioritized, guideline-based care recommendations based on
      those risks, and shows these in a 'provider view' and a 'patient view,' enabling patient
      engagement. Use rates and satisfaction with this CDS were high in the large healthcare
      delivery system where it was developed and tested. The investigators will: study its impact
      in the CHC setting, assess uptake of the CDS system, assess strategies for integrating it
      into CHC workflows, and its impact on patients' CVD risk and risk factor management. The
      investigators hypothesize that this cutting-edge CDS will improve rates of guideline-based
      CVD preventive care in CHC patients, who experience disparities in CVD risk factors, care and
      outcomes. The 60 study clinics will be members of OCHIN, Inc., a non-profit health
      center-controlled network and national leader in health information technology for CHCs.
      OCHIN's leadership enthusiastically supports the proposed work and will help ensure that
      recruitment goals are met. The investigators will partner with stakeholders / medical
      leadership from OCHIN's member clinics at every step, via existing structures. This study
      addresses gaps in guideline-based CVD care in high-risk populations, using targeted,
      multi-level strategies; considers setting-specific needs; tests how CDS affects guideline
      implementation in community clinics; and uses technology to support patient engagement.
      Results will yield knowledge about providing CHCs with cutting-edge CDS, and associated
      impacts on CVD disparities. The innovative study is the second trial to implement CDS tools
      from private care settings in CHCs, and the first to do so with complex CDS tools that
      address a range of CVD risk management guidelines, make prioritized care recommendations, and
      facilitate point-of-care patient engagement. Results could lead to substantial improvements
      in CVD prevention, care, and outcomes in CHCs nationwide.

      Our overarching aims are to:

      Aim 1. Conduct a clinic-randomized trial of the impact of an evidence-based point-of-care CDS
      system on (i) overall CVD risk scores, and (ii) control of individual CVD risks (blood
      pressure; HbA1c, lipid levels; aspirin use; smoking; body mass index), among high CVD risk
      CHC adult patients. H1: High CVD risk patients in Arm 1 CHCs will have significantly lower
      overall CVD risk scores over a 12-month post-index visit period, compared to those in Arm 2
      CHCs. H2: High CVD risk patients in Arm 1 CHCs who have poor control of specific CVD risk
      factors at an index visit will have significantly better control of those factors over a 12
      month post-index visit period, compared to those in Arm 2 CHCs. H3: Disparities in specific
      CVD risk factor control between CHC patients' versus national CVD risk factor control rates
      will be significantly reduced by 18 months post-implementation in each Arm (secondary
      analysis).

      Aim 2. Develop and hone need-based implementation support protocols to help Arm 1 CHCs
      implement the CV Wizard CDS system into their standard workflows; assess whether use of the
      protocols developed for Arm 1 CHCs accelerates implementation and adoption of the CDS system
      in the Arm 2 CHCs. H4: CDS uptake into CHC workflows will be significantly faster in Arm 2
      CHCs than in Arm 1 CHCs.

      Aim 3. Conduct a mixed methods process evaluation, guided by the Technology Acceptance Model,
      to identify and address patient, provider, and delivery system barriers to uptake / impact of
      this CDS in CHCs.
allocation: Randomized
intervention model: Parallel Assignment
primary purpose: Health Services Research
masking: None (Open Label)
measure: Comparison of CVD outcomes for patients in CHCs
time frame: Up to 36 months
description: Compare patients' CVD outcomes in the 30 Arm 1 vs. 30 Arm 2 CHCs, in months 13-30 (Aim 1); assess whether the revised implementation support materials expedite CDS adoption (Aim 2); and use mixed methods to identify multi-level barriers / facilitators to adoption of the CDS tool (Aim 3).
measure: Reach: Encounters affected
time frame: Up to 36 months
description: % clinic encounters where CV Wizard suggests running the full risk assessment tool, i.e., identified a target patient.
measure: Effectiveness (impact): Patient outcomes - 10 year pooled ASCVD risk score
time frame: Up to 36 months
description: (i) ASCVD risk score (American College of Cardiology-ACC/ American Heart Association - AHA) 10-year pooled ASCVD risk score, 40-75 year olds
measure: Effectiveness (impact): Patient outcomes - Framingham 30-year CVD risk score
time frame: Up to 36 months
description: (i) Framingham 30-year CVD risk score, 20-39 year olds.
measure: Effectiveness (impact): Patient outcomes - last BP ≤140/90
time frame: Up to 36 months
description: (ii) Control of individual CVD risk factors: last BP ≤140/90
measure: Effectiveness (impact): Patient outcomes - last A1c≤8
time frame: Up to 36 months
description: (ii) Control of individual CVD risk factors: last A1c≤8
measure: Effectiveness (impact): Patient outcomes - last LDL<100
time frame: Up to 36 months
description: (ii) Control of individual CVD risk factors: last LDL<100
measure: Effectiveness (impact): Patient outcomes - appropriate aspirin use
time frame: Up to 36 months
description: (ii) Control of individual CVD risk factors: appropriate aspirin use
measure: Effectiveness (impact): Patient outcomes - not current smoker
time frame: Up to 12 months
description: (ii) Control of individual CVD risk factors: not current smoker
measure: Effectiveness (impact): Patient outcomes - last BMI ≤25
time frame: Up to 36 months
description: (ii) Control of individual CVD risk factors: last BMI≤25
measure: Effectiveness (impact): Patient outcomes - appropriate cardioprotective medications
time frame: Up to 36 months
description: (ii) Control of individual CVD risk factors: appropriate cardioprotective prescriptions (e.g., statins).
measure: Adoption: CDS uptake
time frame: Up to 36 months
description: % of encounters where care team member opts to run the CV Wizard risk assessment.
measure: Implementation: User perceptions
time frame: Up to 36 months
description: Perceived ease of use, usefulness, acceptability of CV Wizard; intent to use it.
measure: Maintenance over time
time frame: Up to 36 months
description: All measures over 2.5 years of follow-up, Arm 1; 1.5 years, Arm 2.
arm group label: Arm 1: Immediate implementation
arm group type: Active Comparator
description: 30 safety net community health centers (CHCs) will be randomized to implement the sophisticated CV Wizard clinical decision support (CDS) system at the start of study year 2. Arm 1 CHCs will receive implementation support that will be pragmatically iterated to address any barriers to adoption / sustained use of the CDS that are identified through study activities. The investigators will apply these learnings to improve adoption rates in Arm 2.
arm group label: Arm 2: Delayed implementation
arm group type: Active Comparator
description: 30 safety net community health centers (CHCs) will be randomized to implement the sophisticated CV Wizard clinical decision support (CDS) system 18 months later than Arm 1. The investigators will measure the intervention's impact on CVD risk factor control in CHCs.
intervention type: Behavioral
intervention name: CV WIZARD
description: This project will determine whether a sophisticated CDS system will be effective in CHCs. The innovative, point-of-care, web-based CDS system we will test ("CV Wizard") generates a guideline-based prioritized summary of each patient's major CVD risk factors, then presents patient and provider 'views' of this summary, with individualized care recommendations.
arm group label: Arm 1: Immediate implementation
arm group label: Arm 2: Delayed implementation
criteria: 
gender: All
minimum age: 18 Years
maximum age: N/A
healthy volunteers: Accepts Healthy Volunteers
last name: Rachel Gold, PhD, MPH
role: Principal Investigator
affiliation: Kaiser Permanente
facility: 
country: United States
responsible party type: Sponsor
mesh term: Cardiovascular Diseases
mesh term: Myocardial Infarction