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Improving Quality of Care - Managing Atrial Fibrillation Through Care Teams and Health Information Technology (IQ-MATCH)

Primary Purpose

Atrial Fibrillation

Status
Completed
Phase
Not Applicable
Locations
Study Type
Interventional
Intervention
Intervention
Sponsored by
Brigham and Women's Hospital
About
Eligibility
Locations
Arms
Outcomes
Full info

About this trial

This is an interventional other trial for Atrial Fibrillation focused on measuring anticoagulants, NOACs, warfarin, randomized designed delay, intervention, machine learning algorithm, primary care

Eligibility Criteria

18 Years - undefined (Adult, Older Adult)All SexesDoes not accept healthy volunteers

Inclusion Criteria:

  • Non-valvular atrial fibrillation as identified by machine learning algorithms
  • Primary care provider within Brigham and Women's Hospital
  • No evidence of a prescription for an anticoagulant in medical record for at least 1 year

Exclusion Criteria:

-

Sites / Locations

    Arms of the Study

    Arm 1

    Arm 2

    Arm Type

    Experimental

    No Intervention

    Arm Label

    Intervention

    Usual Care

    Arm Description

    Primary care providers in the intervention arm will receive lists of their patients with AF who are identified as being at high risk of stroke but not currently on anticoagulation therapy. Along with this list, which includes information on risks and benefits of anticoagulation, primary care providers will receive an offer of assistance from a respected Anticoagulation Management Service within the hospital network to help manage anticoagulation for referred patients.

    Primary care providers will provide usual care.

    Outcomes

    Primary Outcome Measures

    Anticoagulation therapy
    the proportion of eligible patients who initiate anticoagulation therapy following randomization to intervention or usual care

    Secondary Outcome Measures

    Full Information

    First Posted
    April 6, 2016
    Last Updated
    January 15, 2019
    Sponsor
    Brigham and Women's Hospital
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    1. Study Identification

    Unique Protocol Identification Number
    NCT02734875
    Brief Title
    Improving Quality of Care - Managing Atrial Fibrillation Through Care Teams and Health Information Technology
    Acronym
    IQ-MATCH
    Official Title
    Improving Quality of Care - Managing Atrial Fibrillation Through Care Teams and Health Information Technology
    Study Type
    Interventional

    2. Study Status

    Record Verification Date
    January 2019
    Overall Recruitment Status
    Completed
    Study Start Date
    May 2016 (Actual)
    Primary Completion Date
    August 2017 (Actual)
    Study Completion Date
    August 2017 (Actual)

    3. Sponsor/Collaborators

    Responsible Party, by Official Title
    Principal Investigator
    Name of the Sponsor
    Brigham and Women's Hospital

    4. Oversight

    Data Monitoring Committee
    No

    5. Study Description

    Brief Summary
    This stepped wedge randomized intervention will apply machine learning algorithms in an electronic health record system to identify primary care patients with non-valvular atrial fibrillation (AF) who are at high risk of stroke and not on anticoagulation therapy. An Anticoagulant Management Service (AMS) will offer support to primary care providers regarding treatment for relevant patients (either warfarin and novel oral anticoagulants). This study seeks to: increase the proportion of appropriately anticoagulated patients with AF, understand the reasons for lack of anticoagulation, and document the proportion of patients with AF who are appropriately not anticoagulated (e.g. patient refusal, contraindication).
    Detailed Description
    Atrial fibrillation (AF) is the most common type of cardiac arrhythmia and is associated with significant mortality and morbidity from stroke, thromboembolism, and related cardiovascular conditions. While the risk of stroke for AF patients as a whole tends to be greater than the general population; within the AF patient population, the risk of stroke is modified by the presence or absence of additional risk factors such as age, comorbid conditions, and prior stroke history. There is a wealth of evidence for the effectiveness of anticoagulation therapy to prevent stroke and thromboembolism, but while anticoagulants have been demonstrated to be highly effective at preventing stroke and embolic events among AF patients, they are also known to increase the risk of major bleeding events. Anticoagulation with warfarin and other VKA drugs can be complex to manage. These drugs have narrow therapeutic windows and require close monitoring to stay within the target international normalized ratio (INR). They also have many known food and drug interactions. In the last few years, several novel oral anticoagulants (NOAC) such as dabigatran, rivaroxaban, and apixaban have entered the market. While each of the NOACs demonstrated non-inferiority to warfarin in a large randomized clinical trial prior to FDA approval, experience with NOACs is limited in practice. Our intervention will combine the ability of health information technology to filter large volumes of data with human capacity to understand subtleties and barriers for complex clinical decision making. Our intervention will facilitate a connection between patients, treating clinicians, and an established Anticoagulant Management Service (AMS) for coordinated care. We will use information from the EHR to direct additional efforts and resources toward reaching potentially unrecognized or undertreated atrial fibrillation patients with the greatest need for preventive anticoagulation therapy and lowest risk of adverse effects. This electronic safety net will assist with efficient allocation of scarce resources beyond usual care. The proposed clinical decision support/care-coordination process will be designed to address many of these identified barriers to appropriate anticoagulation therapy among AF patients. Here we define "appropriate" anticoagulation as a guideline informed shared decision between individual patients and their care team. This intervention utilizes a stepped wedge design involving 14 primary care clinics affiliated with the Brigham and Women's Hospital. The timing of clinic entry to the intervention arm will be randomized.

    6. Conditions and Keywords

    Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
    Atrial Fibrillation
    Keywords
    anticoagulants, NOACs, warfarin, randomized designed delay, intervention, machine learning algorithm, primary care

    7. Study Design

    Primary Purpose
    Other
    Study Phase
    Not Applicable
    Interventional Study Model
    Crossover Assignment
    Masking
    None (Open Label)
    Allocation
    Randomized
    Enrollment
    432 (Actual)

    8. Arms, Groups, and Interventions

    Arm Title
    Intervention
    Arm Type
    Experimental
    Arm Description
    Primary care providers in the intervention arm will receive lists of their patients with AF who are identified as being at high risk of stroke but not currently on anticoagulation therapy. Along with this list, which includes information on risks and benefits of anticoagulation, primary care providers will receive an offer of assistance from a respected Anticoagulation Management Service within the hospital network to help manage anticoagulation for referred patients.
    Arm Title
    Usual Care
    Arm Type
    No Intervention
    Arm Description
    Primary care providers will provide usual care.
    Intervention Type
    Other
    Intervention Name(s)
    Intervention
    Other Intervention Name(s)
    Anticoagulant
    Intervention Description
    The intervention arm offers primary care providers additional information on patient risks and benefits as well as an offer of assistance with managing a patient's anticoagulation from a respected service at BWH.
    Primary Outcome Measure Information:
    Title
    Anticoagulation therapy
    Description
    the proportion of eligible patients who initiate anticoagulation therapy following randomization to intervention or usual care
    Time Frame
    randomization to 1 month post randomization

    10. Eligibility

    Sex
    All
    Minimum Age & Unit of Time
    18 Years
    Accepts Healthy Volunteers
    No
    Eligibility Criteria
    Inclusion Criteria: Non-valvular atrial fibrillation as identified by machine learning algorithms Primary care provider within Brigham and Women's Hospital No evidence of a prescription for an anticoagulant in medical record for at least 1 year Exclusion Criteria: -
    Overall Study Officials:
    First Name & Middle Initial & Last Name & Degree
    Shirley Wang, PhD, ScM
    Organizational Affiliation
    Brigham and Women's Hospital
    Official's Role
    Principal Investigator

    12. IPD Sharing Statement

    Plan to Share IPD
    No
    IPD Sharing Plan Description
    There is no plan to share individual participant data outside of the staff and participants themselves.

    Learn more about this trial

    Improving Quality of Care - Managing Atrial Fibrillation Through Care Teams and Health Information Technology

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