<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/NCT03810638</url>
  </required_header>
  <id_info>
    <org_study_id>2000024317</org_study_id>
    <nct_id>NCT03810638</nct_id>
  </id_info>
  <brief_title>Creation of a Digital Heart Failure Registry Using a Novel Mobile Health Platform: HUGO-HF</brief_title>
  <acronym>HUGO-HF</acronym>
  <official_title>Creation of a Digital Heart Failure Registry Using a Novel Mobile Health Platform: HUGO-HF</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Yale University</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
  </sponsors>
  <source>Yale University</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>
      The investigators goal is to create a digital registry that allows for seamless integration&#xD;
      of patient reported outcomes, electronic health record data, and pharmacy information into&#xD;
      data collection. The investigators will accomplish this using a novel patient centered mobile&#xD;
      health platform called Hugo that will allow them to engage patients in an entirely novel&#xD;
      manner.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      Heart failure is the most common cause of mortality and morbidity in the United States and in&#xD;
      Western Europe. It is a complex and chronic illness, and patient journeys vary considerably.&#xD;
      However, to date, guidance about how to best treat patients has relied on large clinical&#xD;
      international trials that do not represent contemporary patients and only include snapshots&#xD;
      of the syndrome-at times when the patients interact with the health care system.&#xD;
      Additionally, patient participation in clinical research in the US is extremely low,&#xD;
      approximated at 3% in cancer and far lower for disease states such as heart failure.&#xD;
&#xD;
      One of the key reasons for this is a lack of patient engagement and trust in the research&#xD;
      enterprise, especially among the elderly and minorities, groups that are disproportionally&#xD;
      impacted by heart failure. To address this, the investigators plan to test a novel&#xD;
      patient-powered, smartphone-based mobile health platform (called Hugo) developed at Yale&#xD;
      School of Medicine for real-world surveillance of patient reported outcomes in heart failure&#xD;
      patients treated at 3 Major Academic Medical Centers. Participants will then be queried about&#xD;
      specific symptoms and health conditions at enrollment and prespecified time points for 2&#xD;
      years. The subgroup of participants who own devices that track their activity data will have&#xD;
      the option of syncing them to this mobile health platform to provide additional insights into&#xD;
      their health and health outcomes. Additionally, participants will have the option to learn&#xD;
      about opportunities to participate in heart failure clinical research. This digital registry&#xD;
      will also allow seamless integration of patient reported outcomes, electronic health record&#xD;
      (EHR) data, and pharmacy information into data collection.&#xD;
&#xD;
      Overall, the aim for this study is to create a digital registry using a novel patient&#xD;
      centered mobile health platform of heart failure patients across large health care systems&#xD;
      that allows investigators to engage patients in an entirely novel manner.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Completed</overall_status>
  <start_date type="Actual">January 15, 2019</start_date>
  <completion_date type="Actual">December 31, 2019</completion_date>
  <primary_completion_date type="Actual">November 25, 2019</primary_completion_date>
  <study_type>Observational [Patient Registry]</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>
  <target_duration>2 Years</target_duration>
  <primary_outcome>
    <measure>Changes in Quality of Life using the KCCQ-12</measure>
    <time_frame>2 Years</time_frame>
    <description>Short Version of the KCCQ will be used. The Kansas City Cardiomyopathy Questionnaire (KCCQ) is the most validated instrument to measure quality of life in heart failure.</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>Hospitalizations</measure>
    <time_frame>2 years</time_frame>
    <description>All-cause hospitalizations among patients in registry</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Death</measure>
    <time_frame>2 years</time_frame>
    <description>Rates of death among patients in registry</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Medication Usage</measure>
    <time_frame>2 years</time_frame>
    <description>Use of guideline directed medical therapies will be done by automatically syncing the patients portal with pharmacy data to provide the most uptodate medication information.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Activity Details</measure>
    <time_frame>2 years</time_frame>
    <description>Activity information based on synced devices</description>
  </secondary_outcome>
  <number_of_groups>1</number_of_groups>
  <enrollment type="Actual">85</enrollment>
  <condition>Heart Failure</condition>
  <arm_group>
    <arm_group_label>Heart Failure Patients</arm_group_label>
    <description>All Heart Failure Patients seen at 3 major academic medical centers.</description>
  </arm_group>
  <eligibility>
    <study_pop>
      <textblock>
        We will aim to recruit patients who are admitted to the hospital with a diagnosis of heart&#xD;
        failure at or seen in the heart failure clinic.&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Non-Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  Age&gt; 18 Years&#xD;
&#xD;
          -  English Speaking&#xD;
&#xD;
          -  Diagnosis of heart failure&#xD;
&#xD;
          -  Participant is willing and able to read and sign consent and participate in study&#xD;
&#xD;
          -  Participant has an email account&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
        - Unable to participate in registry&#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>Yale New Haven Hospital</name>
      <address>
        <city>New Haven</city>
        <state>Connecticut</state>
        <zip>06510</zip>
        <country>United States</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>United States</country>
  </location_countries>
  <link>
    <url>http://hugophr.com/</url>
    <description>A Novel Digital Platform for Research</description>
  </link>
  <reference>
    <citation>Ahmad T, Freeman JV, Asselbergs FW. Can advanced analytics fix modern medicine's problem of uncertainty, imprecision, and inaccuracy? Eur J Heart Fail. 2019 Jan;21(1):86-89. doi: 10.1002/ejhf.1370. Epub 2018 Dec 10. No abstract available.</citation>
    <PMID>30537243</PMID>
  </reference>
  <results_reference>
    <citation>Krumholz HM. Big data and new knowledge in medicine: the thinking, training, and tools needed for a learning health system. Health Aff (Millwood). 2014 Jul;33(7):1163-70. doi: 10.1377/hlthaff.2014.0053.</citation>
    <PMID>25006142</PMID>
  </results_reference>
  <results_reference>
    <citation>Bhavnani SP, Parakh K, Atreja A, Druz R, Graham GN, Hayek SS, Krumholz HM, Maddox TM, Majmudar MD, Rumsfeld JS, Shah BR. 2017 Roadmap for Innovation-ACC Health Policy Statement on Healthcare Transformation in the Era of Digital Health, Big Data, and Precision Health: A Report of the American College of Cardiology Task Force on Health Policy Statements and Systems of Care. J Am Coll Cardiol. 2017 Nov 28;70(21):2696-2718. doi: 10.1016/j.jacc.2017.10.018. No abstract available.</citation>
    <PMID>29169478</PMID>
  </results_reference>
  <verification_date>August 2020</verification_date>
  <study_first_submitted>January 17, 2019</study_first_submitted>
  <study_first_submitted_qc>January 17, 2019</study_first_submitted_qc>
  <study_first_posted type="Actual">January 22, 2019</study_first_posted>
  <last_update_submitted>August 3, 2020</last_update_submitted>
  <last_update_submitted_qc>August 3, 2020</last_update_submitted_qc>
  <last_update_posted type="Actual">August 4, 2020</last_update_posted>
  <responsible_party>
    <responsible_party_type>Sponsor</responsible_party_type>
  </responsible_party>
  <keyword>Heart Failure</keyword>
  <keyword>Heart Transplant</keyword>
  <keyword>Left Ventricular Assist Device</keyword>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Heart Failure</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/NCT03810638
org study id: 2000024317
nct id: NCT03810638
lead sponsor: 
has dmc: Yes
is fda regulated drug: No
is fda regulated device: No
The investigators goal is to create a digital registry that allows for seamless integration
      of patient reported outcomes, electronic health record data, and pharmacy information into
      data collection. The investigators will accomplish this using a novel patient centered mobile
      health platform called Hugo that will allow them to engage patients in an entirely novel
      manner.
Heart failure is the most common cause of mortality and morbidity in the United States and in
      Western Europe. It is a complex and chronic illness, and patient journeys vary considerably.
      However, to date, guidance about how to best treat patients has relied on large clinical
      international trials that do not represent contemporary patients and only include snapshots
      of the syndrome-at times when the patients interact with the health care system.
      Additionally, patient participation in clinical research in the US is extremely low,
      approximated at 3% in cancer and far lower for disease states such as heart failure.

      One of the key reasons for this is a lack of patient engagement and trust in the research
      enterprise, especially among the elderly and minorities, groups that are disproportionally
      impacted by heart failure. To address this, the investigators plan to test a novel
      patient-powered, smartphone-based mobile health platform (called Hugo) developed at Yale
      School of Medicine for real-world surveillance of patient reported outcomes in heart failure
      patients treated at 3 Major Academic Medical Centers. Participants will then be queried about
      specific symptoms and health conditions at enrollment and prespecified time points for 2
      years. The subgroup of participants who own devices that track their activity data will have
      the option of syncing them to this mobile health platform to provide additional insights into
      their health and health outcomes. Additionally, participants will have the option to learn
      about opportunities to participate in heart failure clinical research. This digital registry
      will also allow seamless integration of patient reported outcomes, electronic health record
      (EHR) data, and pharmacy information into data collection.

      Overall, the aim for this study is to create a digital registry using a novel patient
      centered mobile health platform of heart failure patients across large health care systems
      that allows investigators to engage patients in an entirely novel manner.
observational model: Cohort
time perspective: Prospective
measure: Changes in Quality of Life using the KCCQ-12
time frame: 2 Years
description: Short Version of the KCCQ will be used. The Kansas City Cardiomyopathy Questionnaire (KCCQ) is the most validated instrument to measure quality of life in heart failure.
measure: Hospitalizations
time frame: 2 years
description: All-cause hospitalizations among patients in registry
measure: Death
time frame: 2 years
description: Rates of death among patients in registry
measure: Medication Usage
time frame: 2 years
description: Use of guideline directed medical therapies will be done by automatically syncing the patients portal with pharmacy data to provide the most uptodate medication information.
measure: Activity Details
time frame: 2 years
description: Activity information based on synced devices
arm group label: Heart Failure Patients
description: All Heart Failure Patients seen at 3 major academic medical centers.
study pop: 
sampling method: Non-Probability Sample
criteria: 
gender: All
minimum age: 18 Years
maximum age: N/A
healthy volunteers: No
facility: 
country: United States
url: http://hugophr.com/
description: A Novel Digital Platform for Research
citation: Ahmad T, Freeman JV, Asselbergs FW. Can advanced analytics fix modern medicine's problem of uncertainty, imprecision, and inaccuracy? Eur J Heart Fail. 2019 Jan;21(1):86-89. doi: 10.1002/ejhf.1370. Epub 2018 Dec 10. No abstract available.
PMID: 30537243
citation: Krumholz HM. Big data and new knowledge in medicine: the thinking, training, and tools needed for a learning health system. Health Aff (Millwood). 2014 Jul;33(7):1163-70. doi: 10.1377/hlthaff.2014.0053.
PMID: 25006142
citation: Bhavnani SP, Parakh K, Atreja A, Druz R, Graham GN, Hayek SS, Krumholz HM, Maddox TM, Majmudar MD, Rumsfeld JS, Shah BR. 2017 Roadmap for Innovation-ACC Health Policy Statement on Healthcare Transformation in the Era of Digital Health, Big Data, and Precision Health: A Report of the American College of Cardiology Task Force on Health Policy Statements and Systems of Care. J Am Coll Cardiol. 2017 Nov 28;70(21):2696-2718. doi: 10.1016/j.jacc.2017.10.018. No abstract available.
PMID: 29169478
responsible party type: Sponsor
mesh term: Heart Failure
sharing ipd: No