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sfghSan FranciscoGeneral Hospital

San FranciscoVA Medical Center

Medical CenterHeart & Vascular Center

UCSF

Cardiovascular Research Institute

Gladstone Instituteof Cardiovascular Disease

The Health eHeart StudyUsing big data to reduce heart disease

How You and Just About Everyone You Know Can Help Solve the Mysteries Underlying America’s Number 1 Killer

Health eHeart Study

Health eHeart Study

Where’s the Mystery?

Health eHeart Study

• Heart disease remains the leading cause of death

• More deaths due to heart disease than every cancer combined

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Health eHeart Study

• More than a third of adults are obese

• An American has a coronary event once every 34 seconds

• Cardiovascular disease accounts for 1 in every 3 deaths in the US

Health eHeart Study

Conventional Research Studies

HEART DISEASE

Health eHeart Study

Conventional Research Factors

“If you live to be 100, you’ve got it made. Very few people die past that age” - George Burns

Health eHeart Study

Conventional Research Studies

Atrial FibrillationAGE

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Health eHeart Study

My clinic

• 50 yo healthy man with atrial fibrillation

• 39 year old healthy woman with atrial fibrillation

• 34 year old…atrial fibrillation

• etc….

Health eHeart Study

Detective Work Through Massive Numbers

> 13 million people

Health eHeart Study

Detective Work Through Massive Numbers

> 13 million people

Health eHeart Study

Detective Work Using Dense Data

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Health eHeart Study

Cost of Clinical Research

Co

st

Time

Paper-based research

Electronic data capture

Electronic health record

Smartphone-based researchTechnology Trajectory

IOM “Transforming Clinical Research” 2012 Health eHeart Study

• Framingham Heart Study Budget Cut 40%

• Others affected “even more severely” per NHLBI

• “Offering a possible model for lower-cost, large cohort research, the University of California, San Francisco (UCSF), has launched a new study called the Health eHeart…”

Total US Population

Total online population

Consumer computers

Regular mobileInternet use

2016201520142013201220112010

350

300

250

200

150

100

50

0

(mill

ion

s)

Smartphone users Tablet users

Source: Forrester Research

U.S. Technology Use

Health eHeart Study

Smartphone Use

91% of smartphone owners keep their smartphones within

3 feet, 24 hours a day.—Morgan Stanley

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Health eHeart Study

External Sensors

Health eHeart Study

The Team: Principal Investigators

Greg Marcus Mark Pletcher Jeff Olgin

Health eHeart Study

What do we hope to accomplish?

• New paradigm for conducting clinical research

– More efficient & larger number of participants

– Nimble and Rapid deployment

• Develop more robust prediction algorithms

– Collect dense data

– Personalized pattern-based prediction

• Leverage & develop technology– New sensors & mHealth technologies

– Validation & translation into improved health

• Develop new paradigms for healthcare delivery– Testing ground for disease management strategies

Health eHeart Study

Clinical Research Paradigm Shift• Internet enrollment

– Engagement strategy

– Electronic consents

– Social media and virality

• eVisits

– No need for proximity to a study center

• “Real-life” and “real-time” data collection

– Blood pressures

– Weights

– Activity

– Alerts and reminders

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Health eHeart Study

Clinical Research Paradigm Shift

• New methods of outcome ascertainment

– Mobile apps

• “Geofencing”

– Facebook integration

– BlueButton+ and EMR integration

Health eHeart Study

Website: Engaging & Responsive Design

Health eHeart Study

Website: Landing Page InteractionClick Heatmap

Health eHeart Study

Website: Landing Page Interaction

Scroll Heatmap

100%

50%

0%

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Health eHeart Study

Modular Consenting

✔ Overall HeH Consent

✔ Biospecimen/DNA Collection

✔ In Clinic MeasuresVitals

Anthropometry

✔ In Clinic TestsECGETTEchoV02m6MWT

✔ HIPAA Authorization

Measurement App Suite

✔ Link with theirdataFitbit

iHealthWithings

EMR Link

PatientPortal Link

Health eHeart Study

REDCap: Skin & Responsive Design

• Help prompts• Sound files• Images

Health eHeart Study

REDCap: Help Functionality

Health eHeart Study

REDCap: Sound Files

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Health eHeart Study

REDCap: Pictures

PHQ-9PHQ-9

HADSHADS

Labs & MeasuresLabs & Measures

Health eHeart Study

Epidemiology&Biostatistics

Recruitment

• UCSF Cardiology Clinic

• UCSF Medicine Clinic

• Other institutions

• Partnerships

– Advocacy groups

– Insurance carriers

– Established cohorts

• Social Media

• Advertising

• News & traditional media

Built-in Validation Group

Health eHeart Study

Recruitment: Media

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Health eHeart Study

+

Health eHeart Study

Health eHeart AlliancePatient Powered Research Network

Progress to date

5500

Health eHeart Study

eVisits• Series of surveys & activities

– Spread out over ~1 month

– Can be done in small increments of ~1-5 minutes

– Mobile, tablet or desktop

– Email reminders

– Reward/engagement system

• Ability to update data between visits

– Frequent self-report

– Connected devices and apps

– EMR connections

• New eVisit every 6 months

• Additional activities/substudies

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Health eHeart Study

Connected Devices

Health eHeart Study

Connected Devices: Partners

Pulse Oximetry BP Wt/Body Comp

Health eHeart Study

Apps: HR/Rhythm/HRV & Sleep

Health eHeart Study

Apps: Diet Capture—Food Diary

DIETPhoto Diary

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Health eHeart Study

Apps: Facebook

• Integration with Facebook

• Collection of data from Facebook about social interactions

• May be important tool in determining “inter-relatedness”

• May be important tool for engagement and recruitment

• Interesting intervention trials

Health eHeart Study

Apps: Passive Data Collection

– Mobility & Activity

– Screen interaction, call/text interaction

– Behavior modeling

• Background continuous data collection from smartphone sensors

• Reminders/Messaging

• Contextual alerts

Health eHeart Study Health eHeart Study

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Health eHeart Study Health eHeart Study

Outcomes Ascertainment• Electronic Medical Record Integration

– Apex (UCSF)

– Other Epic

– PracticeFusion

• Personal Health Record

• National Death Index search

• Insurance claims

• Intermediate outcomes

– Data from apps and sensors

– Validated surveys

• Building novel technology for adjudication

Health eHeart Study

Outcome Ascertainment: Geofencing

• Determine hospitalizations

• Confirm with an alert (when they leave the hospital)

• Follow-up with detail survey

Have you been hospitalized?

Health eHeart Study

Validation Studies

• Built-in validation through UCSF patients

• Validation of all measurement apps & devices

• Validation of outcomes ascertainment

• Validation of self-report data from EMR

• Validation of novel methods

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Health eHeart Study

Data Security & Privacy

• Committee on Human Research (IRB) Approval

• HIPAA-compliant Docusign

– HIPAA Authorization

• Secure/encrypted website

• Data stored on HIPAA-compliant system

• Participant has username and password

• Data not sold or shared

• NIH Certificate of Confidentiality

• Transparency about Security and Privacy policy

Health eHeart Study

Engagement

• Engagement team

• Engaging, easy to use interface

• Automatic triggered messaging (email, SMS, push notifications)

• Gaming mechanics

– Device give-aways

– Status system

• Personalized approach

• Study updates

• Newsletters

• Social media

Health eHeart Study Health eHeart Study

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Health eHeart Study Health eHeart Study

Enrollment: Age & Gender

0%

5%

10%

15%

20%

25%

30%

Age

F40%M

60%

Gender

Health eHeart Study

Enrollment: Race/Ethnicity

Asian

Black

Native American

Other

Pac Islander

Unknown

White

Hispanic

Non‐hispanic

Unknown

Health eHeart Study

Enrollment: CV Diseases

0

5

10

15

20

25

30

35

40

45

50

Per

cen

t (%

)

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Health eHeart Study

How can it be used?

• Study questions within the cohort

• Data collection for clinical research

– Easy development of both coordinator-entered instruments or self-report

– Eg. Adult Congenital genetic study

• Intervention trials for a specific disease

• Development and testing of mobile health technology or sensor

• Secondary data analysis

Health eHeart Study

How can you contribute?

• Enrollment criteria: ≥ 18 years old and internet connection

• www.health-eheartstudy.org

– Ideally Chrome, Firefox, Safari

• Geographically agnostic

• Can contribute while waiting on line somewhere

• Be an ambassador

• Contribute data (download apps, connect devices, report hospitalizations, fill out surveys)

• Spread the word

Health eHeart Study

Why do people participate?

• Altruism

• Altruism

• Altruism

• Interesting

• Cutting edge

– Medicine

– Gadgets

• Meaningful

• Family member with heart disease

• Have suffered from heart disease

• FunHealth eHeart Study

Thank You

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Health eHeart Study

Social Networks and Health

James Fowler, PhDProfessor of Medical Genetics and Social ScienceUC San Diego

Intersection between natural and social sciences. Focuses on social networks, behavioral science, genetics, health and big data

Health eHeart Study

Intervention Trials

• Ability to rapidly identify CV disease populations and sub-populations

– Example: NYHA Class III-IV Heart Failure patients

• Ability to rapidly invite to participate

• Ability to rapidly electronically consent and randomize

• Ability to provide behavioral or monitoring interventions electronically

• Ability to provide drug interventions rapidly

• Ability to monitor measures and outcomes

Health eHeart Study

Engagement: Their Data

Health eHeart Study

Apps: Diet Capture—Food Diary

TADAtechnology assisteddietary assessment

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Health eHeart Study

Biospecimen Collection

DNA/Serum/WBC’sIn Person

DNA-Spit KitRemote

Health eHeart Study

Biospecimen Collection (future)

• Salivette

• Blood testing devices

• “Chain” labs

Health eHeart Study

Individualized Prediction Algorithms

Time

TimeHealth eHeart Study

0

500

1000

1500

2000

2500

Timeline: Enrollment

3/8/13 3/15/13 3/22/13 3/29/13 4/5/13

WSJ

SF Chronicle

4/12

FUNDING HIRED TEAM

DESIGN& DEVELOPMENT

ENROLLMENT BEGAN

Oct 2012 Nov 2012 March 2013

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Health eHeart Study

Disease Management Trials• Identify those at most need for followup or

intervention

– Remote monitoring

– Electronic visits

– EMR computerized abstraction

– “Air traffic control” panel to highlight those in need of attention

• Intervention directed at specific problem

– Medication adjustment

– Medication compliance

– Diet compliance

– Lifestyle compliance

– Co-morbiditiesHealth eHeart Study

Rigorous mHealth testing ground

• Many companies and startups have taken a consumer electronics approach

• Low bar for FDA approval

– Often 510K approval

• Misperception that doctors want and need “more data”

• Few have clinical trials showing impact on clinical outcomes or cost

• Reimbursement models rarely considered

Health eHeart Study

Remote Measures

• BP

• HR

• HR variability

• Weight

• Edema

• Vascular reactivity

• ECG

• O2 Sat

• Glucose/Ha1c

• Biomarkers

• Metabolism

• 6MWT

• Sleep

• Diet

• Activity

• Behavior

• New sensors

• New measures

Health eHeart Study

Rigorous mHealth testing ground

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Health eHeart Study

Apps: Diet Capture—FFQ

FFQ

Health eHeart Study

Disease Management Trials

• Manage a team of non-medical and medical personnel

• Early Disease Management Projects

– Hypertension

– Heart Failure

– CAD

– Atrial Fibrillation

Health eHeart Study

eVisits

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Health eHeart Study

Healthcare Costs

UC Atlas of Global Inequality, UCSC Health eHeart Study

Health eHeart: Data Collection

• Survey data

– Self-report

• Measurements

– Self-report

– Connected devices

– Apps

– EMR

– In-person visits

• Outcomes

Health eHeart Study

Funding

• Initial grant from SalesForce

– Startup

– Infrastructure

• Anticipating additional projects funded by NIH and other sources

Health eHeart Study

Engagement: Reinforcement

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Health eHeart Study

Engagement: Reinforcement

Health eHeart Study

Engagement: Personal Touch

• Personalized emails

Hi Jeff,Welcome, and thank you for signing up for the Health eHeart Study! I'm excited to have you join us in the fight against heart disease. Every minute someone dies of a heart attack in the U.S., but it's people like you who will help change that shocking statistic for the better.

First of all, let me introduce myself. My name is Kourtney and I'll be your coordinator for the Health eHeart Study. That means that if you have any questions, need more information, or want to comment on how we're doing, I'm your go-to person. Feel free to get in touch any time at coordinator@Health-eHeartStudy.org or (415) 504-2941.

Looking forward to making a difference together!Kourtney ImburgiaClinical Research Coordinator

Health eHeart Study

Engagement: Personal Touch

Health eHeart Study

Healthcare Costs

UC Atlas of Global Inequality, UCSC

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Health eHeart Study

Smartphone Use

0%

10%

20%

30%

40%

50%

60%

2009 2011 2013

Smartphone Use Age 55+

Source: Nielson 2013 Health eHeart Study

UCSF Cardiology Clinic

Health eHeart Study

Vision• Develop, understand, and define the next

generation of cardiovascular assessment/care

• Integrate new technology into cardiac research to help drive change in:

– Cardiac assessment

– Chronic care management

– Patient engagement

– Public Health

• Develop a solution collect and analyze “big data” in a mega cardiovascular cohort study

• Provide a test-bed for emerging tools and techniques in cardiovascular digital health

Goals

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Health eHeart Study

Participant Recruitment

Cardiology Ambulatory PracticeCV Prevention PracticeGeneral Medicine Practice

100,000 to 1 Million participants

Health eHeart Study

Data Collection: Geofencing

• Determine hospitalizations and doctor visits

• Contextual reminders/surveys

• Drive timely patient engagement

Have you been hospitalized?

Health eHeart Study

Data Collection: Surveys

Health eHeart Study

Data Collection: Measurement App

• Physiologic monitoring from smartphone

– Without external sensors

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Health eHeart Study

Data Collection: Biospecimens

SF Based Remote

DNA Spit Kit

DATA REPOSITORYHealth eHeart Study

Data Collection: Medical Records

Data Repository

Health eHeart Study

Technical Framework

Data Collection

Data Repository

SurveysAppsSensorsBiospecimensMedical Records

Health eHeart Study

Data Repository Considerations

• Multi-modal

– Traditional survey data

– Nonsequitur passive data

– Continuous monitoring data

• Multi-site

– In-house data collection

– Multiple vendors

– Multiple devices

• Medical records

– Pulled from our EMR

– Transmitted from other MRs

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Health eHeart Study

Participant Engagement

• Recognized as very important

• Hired engagement specialist (formerly at Keas)

– Risk scores

– Feedback

– Gaming

– Other engagement strategies

• UCSF CTSI participant recruitment and engagement (Nariman Nasser) services

• Developing plan for testing

Health eHeart Study

Sustainability: Infrastructure

• Infrastructure built to be nimble and not requiring large personnel team

– Easy to develop/deploy new surveys

– Study “dashboard” to manage participants and new studies

– Easy and real-time sub-cohort selection

– Communications hub for communication with participants

• Leverage existing UCSF infrastructure

– Redcap

– Salesforce

– Cloud storage

– New UCSF long-term relationships

Health eHeart Study

Sustainability: Funding• American Heart Association

– Have already had discussions with AHA and they are interested in using Health eHeart for their stats data collection

• NIH Funding

– Excellent track record amongst team

• Industry funding

– Digital health companies

• Crowd sourced funding

• Other philanthropic support

– For faculty recruitment

– Fellow support

• Monetized by-productsHealth eHeart Study

Sustainability: UCSF Commitment

UCSF Information Services(Bawa)

UCSF Center for Digital Innovation(Blum)

UCSF Cardiology(Olgin)

UCSF Office of Innovation, Technology & Alliances

(Lium/Sinha)

UCSF Data ManagementEpidemiology

(Pletcher)

UCSF CTSI(Nasser)

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Health eHeart Study

The Team: Investigators

• Jeff Olgin, MD—Cardiology/Clinical Trials

• Mark Pletcher, MD, MPH—Epidemiology

• Greg Marcus, MD, MAS—Cardiology/Epidemiology

• Mike Blum, MD—Medical Informatics

• James Folwer, PhD—Social Scientist

• Ida Sim, MD—mHealth

• TBA—Machine Learning/Big Data

Health eHeart Study

The Team: Operations Staff

Operations

• Opinder Bawa, CTO School of Medicine

• Tuhin Sinha, PhD—Technical Project Director

• Carol Maguire—Research Coordinator

• Leslie Ziani—Project Management

Health eHeart Study

The Team: Technical StaffProduct Development/Management

• Ed Martin—UCSF Deputy Director SaaS

• Nina Jameson—ISU Business Analyst

• Todd Parsnick—Web App Developer

• Christa Smith—Web Front End Developer

• Laura Bettencourt—Data Management

Patient Recruitment/Engagement

• Nariman Nasser (UCSF CTSI)—Recruitment/engagement

• Tracy Strickroth—Recruitment/Engagement

• Chris York (formerly of Keas)—Web Design/Engagement psychology

• Heidi Kotansky (formerly of Keas)—Writer

Health eHeart Study

The Team: Post-doctoral fellows• Gabrielle Brooks, MD—Postdoc fellow

• Alexis Beaty, MD, MAS—Fellow

• Geoffrey Tison, MD, MPH—Fellow

• David Ouyang—PhD candidate

• TBA (MIT Media lab)—post-doc

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Health eHeart Study

Partners• Ginger.io—Passive data collection smartphone

app

• Azumio—Measurement app

• AliveCor—mobile ECG

• Wireless Medical—wearable sensors

• Vital connect—wearable sensors

• MC10—wearable sensors

• Salesforce– engagement platform

• …

Health eHeart Study

Progress

• IRB Approval pending

– Submitted and pre-reviewed

• Website design nearly complete

– Website

• Mobile app development active

• Website development active

Health eHeart Study

Stewardship Plan

• Naming?

– Website

• 6 month progress report

• Ad hoc reports for major milestones

– Release dates

– Press

– Big findings/publications

• Other?

Health eHeart Study

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Health eHeart Study Health eHeart Study

Health eHeart Study

Rigorous mHealth testing ground

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Health eHeart Study

Data Collection: External Sensors

DATA REPOSITORY

Measurement Sensors Wearable Sensors

Health eHeart Study

Credit Card Fraud Detection

• Small purchase at gas station followed by a very large purchase (often electronic store)

• Lots of internet purchases

• Training set to establish a baseline• Machine learning to adjust baseline• Detect deviations from baseline

Health eHeart Study

Nimble study implementation

Design intervention

Cohort Selection

Develop Data Collection Tools

& Database

Patient Recruitment

Consent & Randomization

Traditional Health eHeart

Months Months

Days-WeeksMonths

Month/Years Minutes

Years Days-Weeks

Days-WeeksMonth/Years

Recruitment

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Health eHeart Study

Recruitment: Traditional Media

Health eHeart Study

Recruitment: Social Media