Leveraging Big Data & Emerging Artificial Intelligence ...Leveraging Big Data & Emerging Artificial...

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11/16/2015 1 Leveraging Big Data & Emerging Artificial Intelligence Techniques to Stratify a Patient Population Patient Population Global Population Health was valued at $12.8 billion in 2013 and is poised to grow at a CAGR of 26% from 2013 to 2018, to reach $40.6 billion by 2018. Sitaramesh Emani, MD Darren Selsky, MS, MHA Disclosures S Emani Thoratec/St. Jude – consultant, grant funding Abiomed travel reimbursement Abiomed travel reimbursement CareDx – Advisory Board D Selsky VP, Marketing & Business Development, Capsenta Consultant, Heart Rhythm Society

Transcript of Leveraging Big Data & Emerging Artificial Intelligence ...Leveraging Big Data & Emerging Artificial...

Page 1: Leveraging Big Data & Emerging Artificial Intelligence ...Leveraging Big Data & Emerging Artificial Intelligence Techniques to Stratify a PatientPopulationPatient Population Global

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Leveraging Big Data & Emerging Artificial Intelligence Techniques to Stratify a

Patient PopulationPatient Population

Global Population Health was valued at $12.8 billion in 2013 and is poised to grow at a CAGR of 26% from 2013 to 2018, to reach

$40.6 billion by 2018.

Sitaramesh Emani, MD

Darren Selsky, MS, MHA

Disclosures

S Emani Thoratec/St. Jude – consultant, grant funding Abiomed – travel reimbursementAbiomed travel reimbursement CareDx – Advisory Board

D Selsky VP, Marketing & Business Development, Capsenta Consultant, Heart Rhythm Society

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Epidemiology Heart Failure in the U.S.

Major public health problem

5 million Americans with heart failure

650 000 di d h 650,000 new cases diagnosed each year

Lifetime risk of having HF is 20% (> 40 yo)

Most frequent cause of hospitalization in patients older than 65 years

1-Year mortality rate is about 10-15%

5-Year mortality rate approaches 50%y pp

Epidemiology of Heart Failure

Despite current therapies and disease management approaches, the rate of heart failure hospitalization remains unacceptably high

> 1.1 million heart failure hospitalizations annually

#1 cause of hospitalization for those ≥ 65 years

#1 cause of hospital readmission

> 25% readmission rate at 1 month

$18 billi i l di t t f h it li ti > $18 billion in annual direct costs of hospitalization

Current methods for monitoring and managing heart failure patients have not adequately addressed this problem

Aghababian RV. Rev Cardiovasc Med 2002; 3:S3; Jong P, et al. Arch Intern Med 2002; 162:1689; Jencks and Williams, NEJM 2009; 360:1418; www.hospitalcompare.gov

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Natural History of Heart Failure

Normal ♥ Chronic HF Death

Initial

Fun

ctio

nal A

bilit

y

Initial myocardial injury

First ADHF admission

Acute Exacerbations Cause Progressive HF

Time

Late ADHF – ICU admission and rescue therapy

Epidemiology

Miller & Guglin, JACC 2013

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HF Topography

NYHA I

1 year mortality of NYHA III HF is 10-15%

A HF hospitalization is a strong predictor of mortality (NYHA IIIb-IV)

NYHA II

NYHA IVNYHA I No limitation of activity

NYHA II Slight limitation of activity; normal activity causes fatigue, dyspnea

NYHA III Marked limitation of activity; less than ordinary activity causes fatigue, dyspnea

NYHA IV Symptoms at rest; unable to perform even minimal levels of activity

Scrutenid et al, EHJ 1994Gheorghiade et al, JACC 2013

The danger of late referrals

Profile Description

1 Critical cardiogenic shock / “Crash & Burn”

o k? 2 Progressive decline on inotropes

3 Stable but inotrope dependent

4 Resting symptoms on home oral therapies

5 Exertion intolerant

6 Exertion limited

Too

sick

Not sick

enough?

7 Advanced NYHA III symptoms

Stevenson et al, JHLT 2009

k ?

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Outcomes by Profile

Kirklin et al, JHLT 2013

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Treating End-Stage Heart Failure

Ventricular Assist Devices (VADs) are used to treat end-stage heart failure

End-Stage Heart Failure Persistent severe symptoms of HF despite optimal Persistent, severe symptoms of HF despite optimal

medical therapy Limited life-expectancy due to underlying cardiac

disease

Not all patients with end-stage HF are candidates Therapy has complications Will not help certain cardiac conditions Will not help non-cardiac co-morbidities

Axial Flow Pumps

Courtesy of Thoratec Corp.

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Centrifugal Flow Ventricular Assist Device

CXR – Pre-VAD

Pre-VAD Post-VADExplant Heart

w/ VAD

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Left ventricular assist devices (LVAD) therapy: expenses and gains.

Leslie W. Miller et al. Circulation. 2013;127:743-748

Left ventricular assist devices (LVAD) early costs are comparable with other life-saving therapies.

Leslie W. Miller et al. Circulation. 2013;127:743-748Copyright © American Heart Association, Inc. All rights reserved

• Cost effectiveness of VAD therapy as DT is improving but has yet to achieve the goal of <$100 000 USD/QALY

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Rehospitalizations

Setoguchi S, et al, AHJ 2007

Project Charter – LVAD StratificationChart Reviews just don’t work…

OSU HF Chart Review:

18/ 47 HF readmissions were “missed” due to readmission onto non-cardiology services.onto non cardiology services.

30 instances of high-risk medications (i.e. inotropes) ordered by non-cardiac services during that time.

Conservative estimates would suggest ~ 20 patients every 60 days that are “high-risk” 120 pts/yr (~ 30 pts – LVAD)

$6.75 M

FY 2013 CMS Median Payment for MS-DRG 1 ≈ $202,000 High cost cases may qualify for outlier payments

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High Risk HF Characteristics

HF Sx that fail to respond to medical therapy

Intolerance to HF meds (esp new intolerance)Hypotension Hypotension

Renal dysfunction Bradycardia

Frequent hospitalizations 2 in 3 months 3 in 6 months Need for inotropes during hospital stay

Adapted from J Stehlik, Univ of Utah

Heart Failure

HF Charcteristics

• HF Sx that fail to respond to medical therapy

• Intolerance to HF meds (esp new

Simpler Referral Triggers

• NYHA III-IV & ≥1 or NYHA II & ≥ 2 of the following:

• Intolerance to HF meds (esp new intolerance)• Hypotension• Renal dysfunction• Bradycardia

• Frequent hospitalizations• 2 in 3 months• 3 in 6 months• Need for inotropes during

• SBP ≤ 90 mmHg• Hgb ≤ 12 mg/dl• Cr ≥ 1.6• Not on RAAS inhibition• Not on β-blocker

Adapted from J Stehlik, Univ of Utah

p ghospital stay

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Example – Colorectal CancerWho is at greater risk?

Patient 1 Patient 2

Risk calculators can assist with assessments

• 65 male• No family history• Diet with vegetables• Non-obese• No previous polyps

• 55 male• Strong family history• Poor diet• Obese• No previous

colonoscopy

Risk calculators can assist with assessments

Time consuming/manual entry

Require data elements to be available

Can available stored data (i.e., EHR data) be accessed to help calculate risk?

How can screening tools be implemented?

Version 1 Patient is in office leading to an alert when chart accessed

Version 2 Automatic alerts generated electronically when certain criteria are

triggered Cholesterol panels Lab work for certain medications Flu shots

Associated with improved adherence to recommend care processes

Hi h f h lth t i Higher performance on healthcare process metrics

Data analytics can help healthcare delivery

Ancker, JS et al, JAMIA, 2015, vol 22: 4, 664-671

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Rudimentary nature of current technology

Use basic data structures

Look at simple/singular metrics

R l “ i l” li bilit Rely on “universal” applicability

Do not capture complex situations or assimilate complex data

How can we leverage our EMR to help

Identification

• Patients who may have “fallen through the cracks”

Perfect EMR

• Search well-defined parameters

• Exclude “noise” and

Real Life EMRs

• High degree of variability in parameters

• Search parameters can yield results

• But, may be prone to erroneous or missed identification

inaccurate parameters• Return simple, easy to

interpret results

• Chronic systolic HF• Acute systolic HF• Acute on chronic

systolic HF• Acute exacerbation

of HF• Cardiogenic shock

• In OSU system, EF not il h bleasily searchable

May not be equipped with internal search algorithms

Garbage In… Garbage Out

Updated medical histories?

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The Goal

Identify patients who could benefit from advanced therapies early

Try not to use advanced therapies as “salvage therapy”

Challenges

Data is stored in many different places

Data has many synonymsData has many synonyms

Data may live in notes, dictations & scanned reports

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Just for fun…

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How does LinkedIn know that someone has a 3rd generation connection?How does Facebook build their footprint of friends and friendship tags?How does Google summarize data on their search screen?

Works for

Spouse of

Father of

Mo

the

r of

Brother of

Colleague of

Alumni of

Works forMother of

Alumni ofFather of

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Works for

Spouse of

Father of

Mo

the

r of

Brother of

Colleague of

Alumni of

Works forMother of

Alumni ofFather of

Identify Heart Failure Patients indicated for a LVAD

Echo Mgmt

(Siemens)CDM Data

(MySQL)Epic

(Mumps)

(MySQL)

Goals Driven

Patient Stratification

Health Outcomes

Use Existing Infrastructure

Use Industry Standards

• Identify at-risk patients for timely interventions • Improve care management delivered at point

of care• Aggregate data for population analytic

reasoning. • Search HF Patient Population to understand

patient cohort

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Taking it one step further…LVAD Use Case

LHA - Left heart assist operationLVAD - Implantation of left ventricular assist deviceImplantation of left ventricular assist device (procedure)

Left Ventricular Assist DeviceLVAdEnd Diastolic Area

SNOMED HCPCS CMO ICD

SEMANTICS

device (procedure)ALVAD - Aorta-left ventricular assist device

LVDaCardiac Assist Pump

VAD DRIVELINE, MAINTENANCE KIT CM#DT18355

VAD DRIVELINE, MANAGEMENT TRAY CM#DT15340

VAD DRIVELINE MAINTENANCE KIT MED#DYNDC1488

ICD 9: Insertion of percutaneous external heart assist device (37.68)ICD 10 - Presence of heart assist device (Z95.811)

Why technology is ripe for population health

Community outreach to improve adherence.

Immunization registries

Clinical Trial opportunitiesClinical Trial opportunities

Retrospective and real time analysis of patient outcomes

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Value of Data Virtualization for Healthcare

Simplified Data Access.

Continued ROI of Existing Infrastructure.

Data Storage and Cost Reduction.

Improved Care Quality.

Compliance and Data Governance Support.

Assay Experiment

Help Me Fail Faster

Genomics

External

Patent

NDF, CHEMBL

G l D i

Flexibility Dashboarding

Analysis Adhoc Query

Clinical Discovery Reporting

Goals Driven1. Stop unnecessary clinical research2. Are there patent infringements?3. Has this already been done?4. Help me speed time to Stage II Clinical Trials

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Medical Device IdentificationImplants

ER

Medtronic

Boston Scientific

St Jude Medical

Biotronik

Sorin

Nursing Home

Clinic

OR

Nursing HomeHospital Inpatient

Master Provider Management

Hospital A

Hospital B

Hospital C

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Patient Stratification - AF• What Classifies as a Cardiac Arrhythmia?

• What are the common conditions (CV and non-CV)?

• What are the AF Contraindications?

• What are the indicated meds?What are the indicated meds?

• What are Meds that “May be Treating AF?”

• What are the biomarkers/ Risk Factors?

Multiple Theories of the etiology of AF

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Privacy/HIPAA Concerns

IRB Approval – research or “not” research

BAA

Follow-up directed to PCP or primary cardiologist

Conducting quality assessment and improvement activities, including outcomes evaluation and development of clinical guidelines, provided that the obtaining of

generalizable knowledge is not the primary purpose of any studies resulting from such activities; patient safety activities (as defined in 42 CFR 3.20); population-based activities

relating to improving health or reducing health care costs, protocol development, case management and care coordination, contacting of health care providers and patients

with information about treatment alternatives; and related functions that do notwith information about treatment alternatives; and related functions that do not include treatment; §164.501 of HHS Regulations (January 2013)

Thank you

Sitaramesh Emani, MDAssistant Professor of MedicineAdvanced Heart Failure & Cardiac TransplantThe Ohio State University Wexner

Darren SelskyVP, Business Development5525 Fossil Rim RoadAustin, TX 78746

The Ohio State University WexnerMedical Center473 W. 12th Ave, Suite 200 DHLRIColumbus, OH 43210P: 614-293-4967 | F: [email protected]

Mobile: 484-356-6037

[email protected]