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Implementing Digital Health in a Learning Health System (ASE-INNOVATE)

The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. Know the risks and potential benefits of clinical studies and talk to your health care provider before participating. Read our disclaimer for details. Identifier: NCT03713333
Recruitment Status : Not yet recruiting
First Posted : October 19, 2018
Last Update Posted : October 19, 2018
West Virginia University
Information provided by (Responsible Party):
Sanjeev Bhavnani MD, Scripps Health

Brief Summary:
The need for new models of integrated care that can improve the efficiency of healthcare and reduce the costs are key priorities for health systems across the United States. Treatment costs for patients with at least one chronic medical or cardiovascular condition make up over 4-trillion dollars in spending on healthcare, with estimations of a population prevalence of 100-million affected individuals within the next decade. Therefore, the management of chronic conditions requires innovative and new implementation methods that improve outcomes, reduce costs, and increase healthcare efficiencies. Digital health, the use of mobile computing and communication technologies as an integral new models of care is seen as one potential solution. Despite the potential applications, there is limited data to support that new technologies improve healthcare outcomes. To do so requires; 1) robust methods to determine the impact of new technologies on healthcare outcomes and costs; and 2) evaluative mechanisms for how new devices are integrated into patient care. In this regard, the proposed clinical trial aims to advance the investigator's knowledge and to demonstrate the pragmatic utilization of new technologies within a learning healthcare system providing services to high-risk patient populations.

Condition or disease Intervention/treatment Phase
Cardiovascular Diseases Hypertension Heart Failure Atrial Fibrillation Metabolic Syndrome Genetic Disease Diagnostic Test: Digital Health Device Diagnostics Not Applicable

Detailed Description:

Objective #1: Determine the effectiveness of handheld imaging and digital health devices on long term health and patient-reported outcomes through pragmatic and randomized clinical trial designs.

Objective #2: Assess the impact of digital health devices on measures of healthcare efficiency.

Handheld imaging and digital technologies provide a rapid diagnostic assessment at the time of a healthcare encounter. As such, the potential of such devices to improve healthcare efficiency is significant. Measures of healthcare efficiency directly related to digital health technologies include: identify which interventions can improve care; define the variations in care and; demonstrate within which patient populations digital health technologies are most effective.

Objective #3: Apply integration methods for handheld imaging and digital health devices used for clinical decisions at the point-of-care.

Achieving integration and interoperability—the ability of different information technology systems and software applications to communicate and exchange data with each other—requires identification for precisely how new innovations merge into systems of care and are applied to various practice settings.

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Study Type : Interventional  (Clinical Trial)
Estimated Enrollment : 500 participants
Allocation: Randomized
Intervention Model: Sequential Assignment
Intervention Model Description: Pragmatic, multisite, cluster randomized trial comparing technology-enabled healthcare visitations with digital health devices and handheld imaging to standard-care
Masking: Triple (Care Provider, Investigator, Outcomes Assessor)
Masking Description: Treating physicians and clinical practitioners will not be concealed to the randomized allocation of individual clinics or the patients that are seen in these encounters. Physicians in the interventional group will participate in conducting technology-enabled visitations before a patient encounter and therefore are not blinded to the assessment. For the standard care group handheld imaging and digital health screening will be performed after the patient-physician encounter. Principal investigators, outcome adjudicators, and statisticians are blinded to randomization, device findings, and treatment decisions.
Primary Purpose: Screening
Official Title: Implementation of High Definition Screening Using Handheld Imaging and Digital Health Technologies Within a Learning Health System to Identify Cardiovascular Disease at the Point-of-care: The ASE-INNOVATE Program
Estimated Study Start Date : October 20, 2018
Estimated Primary Completion Date : October 20, 2019
Estimated Study Completion Date : October 20, 2019

Resource links provided by the National Library of Medicine

Arm Intervention/treatment
Experimental: Technology-Enabled Visitations
Technology-enabled visitations with digital health will include the following devices used at the time of a patient-physician encounter. These findings will be available to the treating physician at the time the visitation and to be used for clinical decisions.
Diagnostic Test: Digital Health Device Diagnostics

Technology-enabled visitations with digital health will include the following devices used at the time of a patient-physician encounter. These findings will be available to the treating physician at the time the visitation and to be used for clinical decisions.

  • Handheld imaging - focused echocardiographic examination (Butterfly IQ)
  • Smartphone iECG for cardiac rhythm assessments (Alivecor)
  • Blood Pressure (CloudDX)
  • Oxygen Saturation (CloudDX)
  • Weight (CloudDX)
  • Point-of-Care Genetic Testing (Phosphorous)

No Intervention: Standard-Care Visitations
Standard-care is defined as the range of services available during usual patient care. Handheld Imaging and digital health screening will be performed in the control group after the patient-physician encounter. As such, patients and physicians will be blinded to the diagnostic findings unless an abnormal finding is detected that requires physician review and triage for further care.

Primary Outcome Measures :
  1. Patient-Reported Outcome Measures [ Time Frame: 30 days ]
    Veterans Research and Development Corporation-12 Patient Reported Outcomes (mean total score 50 +/- 10) where higher values are associated with greater mental and physical debility

  2. Patient-Reported Experience Measures [ Time Frame: 30 days ]
    Agency for Healthcare Research and Quality Consumer Assessment of Healthcare Providers and Systems (average scores and difference between randomized arms) where higher scores are associated with greater patient satisfaction and patient experience

  3. Health Economic Outcomes [ Time Frame: 180 days ]
    Economic difference between the total costs of care between randomized arms including; clinic visitations, hospitalizations, emergency room visitations, and diagnostic testing. Collected as cumulative diagnosis-related group (DRG) and current procedural terminology (CPT) amounts in United States Dollars

Secondary Outcome Measures :
  1. Mobile Cardiac Telemetry [ Time Frame: 180 days ]
    Number of referrals for mobile cardiac telemetry monitoring between randomized arms

  2. Diagnostic Imaging [ Time Frame: 180 days ]
    Number of referrals for diagnostic imaging with transthoracic echocardiography between randomized arms

  3. Heart Failure [ Time Frame: 180 days ]
    Incidence of heart failure diagnosed between randomized arms

  4. Atrial Fibrillation [ Time Frame: 180 days ]
    Incidence of atrial fibrillation diagnosed between randomized arms

  5. Emergency Department Visitations [ Time Frame: 180 days ]
    Percentage of patients presenting to the emergency department for a cardiac condition (example; myocardial infarction, heart failure, atrial fibrillation, and stroke) between randomized arms

  6. Hospitalization [ Time Frame: 180 days ]
    Percentage of patients hospitalized for a cardiac condition (example; myocardial infarction, heart failure, atrial fibrillation, and stroke) between randomized arms

  7. Clinic Visitations [ Time Frame: 180 days ]
    Percentage of patients presenting for a clinical visitation for a cardiac condition (example; myocardial infarction, heart failure, atrial fibrillation, and stroke) between randomized arms

  8. Medical Therapy [ Time Frame: 180 days ]
    Percentage of patients initiating medical therapy for a cardiac condition including: heart failure, coronary artery disease, atrial fibrillation, and/or hypertension between randomized arms

Information from the National Library of Medicine

Choosing to participate in a study is an important personal decision. Talk with your doctor and family members or friends about deciding to join a study. To learn more about this study, you or your doctor may contact the study research staff using the contacts provided below. For general information, Learn About Clinical Studies.

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Ages Eligible for Study:   18 Years and older   (Adult, Older Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No

Inclusion Criteria:

  • All participants of the ASE 2018 Outreach Event who are at least 18 years old who are referred for a cardiac evaluation

Exclusion Criteria:

  • Those not willing to consent

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its identifier (NCT number): NCT03713333

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Contact: Partho P Sengupta, MD 304-598-4478
Contact: Lan Hu 304-598-4478

Sponsors and Collaborators
Scripps Health
West Virginia University
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Principal Investigator: Partho Sengupta, MD West Virginia University Heart and Vascular Institute
Study Director: Sanjeev Bhavnani, MD Scripps Clinic

Publications of Results:
US Burden of Disease Collaborators, Mokdad AH, Ballestros K, Echko M, Glenn S, Olsen HE, Mullany E, Lee A, Khan AR, Ahmadi A, Ferrari AJ, Kasaeian A, Werdecker A, Carter A, Zipkin B, Sartorius B, Serdar B, Sykes BL, Troeger C, Fitzmaurice C, Rehm CD, Santomauro D, Kim D, Colombara D, Schwebel DC, Tsoi D, Kolte D, Nsoesie E, Nichols E, Oren E, Charlson FJ, Patton GC, Roth GA, Hosgood HD, Whiteford HA, Kyu H, Erskine HE, Huang H, Martopullo I, Singh JA, Nachega JB, Sanabria JR, Abbas K, Ong K, Tabb K, Krohn KJ, Cornaby L, Degenhardt L, Moses M, Farvid M, Griswold M, Criqui M, Bell M, Nguyen M, Wallin M, Mirarefin M, Qorbani M, Younis M, Fullman N, Liu P, Briant P, Gona P, Havmoller R, Leung R, Kimokoti R, Bazargan-Hejazi S, Hay SI, Yadgir S, Biryukov S, Vollset SE, Alam T, Frank T, Farid T, Miller T, Vos T, Bärnighausen T, Gebrehiwot TT, Yano Y, Al-Aly Z, Mehari A, Handal A, Kandel A, Anderson B, Biroscak B, Mozaffarian D, Dorsey ER, Ding EL, Park EK, Wagner G, Hu G, Chen H, Sunshine JE, Khubchandani J, Leasher J, Leung J, Salomon J, Unutzer J, Cahill L, Cooper L, Horino M, Brauer M, Breitborde N, Hotez P, Topor-Madry R, Soneji S, Stranges S, James S, Amrock S, Jayaraman S, Patel T, Akinyemiju T, Skirbekk V, Kinfu Y, Bhutta Z, Jonas JB, Murray CJL. The State of US Health, 1990-2016: Burden of Diseases, Injuries, and Risk Factors Among US States. JAMA. 2018 Apr 10;319(14):1444-1472. doi: 10.1001/jama.2018.0158.

Other Publications:

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Responsible Party: Sanjeev Bhavnani MD, Principal Investigator - Healthcare Innovation, Scripps Health Identifier: NCT03713333     History of Changes
Other Study ID Numbers: Pro00029622
First Posted: October 19, 2018    Key Record Dates
Last Update Posted: October 19, 2018
Last Verified: October 2018
Individual Participant Data (IPD) Sharing Statement:
Plan to Share IPD: Undecided

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Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: Yes
Device Product Not Approved or Cleared by U.S. FDA: No
Pediatric Postmarket Surveillance of a Device Product: No
Product Manufactured in and Exported from the U.S.: Yes
Keywords provided by Sanjeev Bhavnani MD, Scripps Health:
digital health
handheld ultrasound
smartphone ECG
mobile health
point of care genomics
big data
artificial intelligence
learning health system
Additional relevant MeSH terms:
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Atrial Fibrillation
Genetic Diseases, Inborn
Metabolic Syndrome
Cardiovascular Diseases
Heart Diseases
Arrhythmias, Cardiac
Pathologic Processes
Insulin Resistance
Glucose Metabolism Disorders
Metabolic Diseases