This presentation discuss major applications of AI in Healthcare including medical diagnostics, personalized treatments and optimizing US healthcare system. This presentation also discuss some of the challenges of implementing AI in healthcare.

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August, 2019
MAJOR APPLICATION OF
AI IN HEALTHCARE
Alex Ermolaev, Director of AI,
Change Healthcare

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The Change Healthcare Intelligent Healthcare Network…
• Extensive product/services, expertise, data,
and connectivity
• Tying our success to our customer: providers, payers
and consumers
• Independent, unbiased, & relentless drive
towards better healthcare
• Delivering practical innovation through
technology and partners
2,100
Payer Connections
1 in 5
US Patient
Records
$2 trillion
Healthcare Claims
Nearly 14 billion
Healthcare Transactions
5,500
Hospitals & Health Systems
800,000
Physicians117,000
Dentists
600
Laboratoriesh
Pervasive across healthcare

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Next Industrial Revolution: The Intelligence Age
Metallurgy
Railroads
Ships
Steel
Machinery
Chemistry
Automobiles
Planes
Electronics
Computing
Telecom
A.I.
Biotech
NanotechTextiles
Intelligence
Age
Information
Age
Industrial
Revolution
Steam
Electrical
Internal
Combustion
2015+1971+1771+ 1829+ 1875+ 1908+

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AI Accuracy Skyrockets After 2012
60%
65%
70%
75%
80%
85%
90%
95%
100%
1990 1992 1995 1997 2000 2002 2005 2007 2010 2012 2015 2017
Source: Microsoft Corp Speech Recognition Accuracy
Human Level Accuracy

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AI Adoption as of 2018
94%
of companies believe
AI is key to competitive
advantage
1 in 20
companies has extensively
incorporated AI in offering
or processes
Source: Paul Taylor, IBM Fellow, ODSC West 2018
Change Healthcare is one of the leaders!

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Why Apply AI to Healthcare?
US Industry by Revenue
R&D Budget
Number of AI Opportunities
Number of AI Startups
#1
#2
#1
#1
Most Important for Saving Lives#1

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AI in Healthcare
Early Diagnosis Health Monitoring Medical Imaging
Diagnostics
Precision Medicine Personalized Treatment Plans Clinical Trials
Personalization
Smart Electronic
Health Records
Payment Accuracy
Patient Identification
and Retention
Optimized
Healthcare
System

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Diagnostics
Early Diagnosis Health Monitoring Devices Medical Imaging

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Sepsis Diagnostics
1.6M diagnoses/year (US)
25%-30% Mortality Rate
#3 Cause of Death
#1 Hospital Cost in US
Antibiotics increase survival rate
7.6% per hour

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Sepsis Diagnostics (Continued)
Source: https://www.researchgate.net/publication/326661039_Applying_Artificial_Intelligence_to_Identify_Physiomarkers_Predicting_Severe_Sepsis_in_the_PICU

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Medical Devices

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Predicting Alzheimer 6 years earlier

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Brain
Subarachnoid Hemorrhage
Subdural hemorrhage
Extradural hemorrhage
Intraventricular hemorrhage
Parenchymal hemorrhage
Hydrocephalus
Midline shift
Descending transtentorial herniation
Ascending transtentorial herniation
Workflow Intelligence.AI
Intelligent Workflow driven by AI
Abdomen
Perforation / Free air
Bowel obstruction
Spinal epidural hemorrhage
Vertebral fracture
Chest
Pneumothorax
Aortic dissection
PE
Spinal epidural hemorrhage
Vertebral fracture
Neck
Retropharyngeal abscess
Spinal epidural hemorrhage
Vertebral fracture
Vertebral artery dissection

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Personalization
Precision
Medicine
Personalized Treatment
Plans
Drug Discovery &
Clinical Trials

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Precision
Medicine

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Personalized Treatment Plans
Source: https://www.media.mit.edu/publications/reinforcement-learning-for-designing-novel-clinical-trials-for-treating-cancer-patients/

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Clinical Trials
Oncology Trials
3.4%
of oncology clinical trials
are completed
Patients Enrolled
5%
of cancer patients are
enrolled in clinical trials
Sources: http://blogs.sciencemag.org/pipeline/archives/2018/02/02/a-new-look-at-clinical-success-rates
https://www.beckershospitalreview.com/quality/just-5-of-cancer-patients-participate-in-clinical-trials-5-things-to-know.html
"I don't think it's an unwillingness on the patients' part. I don't
even think it's an unwillingness on the physician's part. It’s really
a system error...” Scott Delacroix, MD, told PBS NewsHour.

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Optimized Healthcare System
Smart Electronic
Health Records
Payment Accuracy
and Streamlining
Patient Identification
and Retention

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About 1/3 of Healthcare Spending is Wasted
Sources: https://advocacy.consumerreports.org/research/engaging-consumers-on-health-care-cost-and-value-issues/
$10,000
$8,000
$6,000
$4,000
$2,000
$0
Average U.S. Healthcare
Spending per Person in 2014
$9,700
Total Wasted Spending per Person……… $2,910
Wasted
Spending
Necessary
Spending
Unnecessary Services
Example: Duplicate Tests $800
Inefficient Care Delivery
Example: Test Results Not Shared $495
Inflated Prices
Example: Excessive Profits $400
Fraud
Example: False Claims $285
Prevention Failures
Example: Missed Flu Shot $210
Excess Administrative Costs
Example: Billing Errors $720

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Medical Text
Understanding
Header ✓
Footer ✓
David A. Smith, M.D. ✓
Legalese ✓
Likely diagnoses ✓
Member info ✓

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Strange
ICD-10
Codes

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Problem: Medical Claims
1. Source: https://www.businesswire.com/news/home/20170626005391/en/Change-Healthcare-Analysis-Estimated-262-Billion-Healthcare
2. Source: Change Healthcare Internal Statistics
US Medical Claims:
$3T per year1
Claims Denied:
$262B per
year (9%)1
Cost of Rework:
$118 per claim1
Total Loss:
> $100B2

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Example: Dual Enrollment
1 - CMS Fast Facts, January 2018: https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/CMS-Fast-Facts/index.html
2- Kaiser Family Foundation: https://www.kff.org/medicare/state-indicator/medicare-beneficiaries-by-fpl/?currentTimeframe=0&sortModel=%7B%22colId%22:%22Location%22,%22sort%22:%22asc%22%7D
3- CMS, https://www.cms.gov/Medicare-Medicaid-Coordination/Medicare-and-Medicaid-Coordination/Medicare-Medicaid-Coordination-Office/DataStatisticalResources/Data-and-Statistical-Resources.html
Today
58.8M
Medicare beneficiaries
Live at or below
34%
of the federal poverty level
And only
10.6M
are dual-enrolled

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AI in Healthcare
Early Diagnosis Health Monitoring Medical Imaging
Diagnostics
Precision Medicine Personalized Treatment Plans Clinical Trials
Personalization
Smart Electronic
Health Records
Payment Accuracy
Patient Identification
and Retention
Optimized
Healthcare
System

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Healthcare
AI Startups
Source: CBInsights

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Embrace
Variety
Respect
Data
Understand
Workflow
AI in Healthcare Challenges

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Not All AI Projects are Viable Today
Source: An Empirical Model of Large-Batch Training, https://arxiv.org/pdf/1812.06162.pdf

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“In order to understand trust in the relationship
between humans and automation, we have to
explore trust in two dimensions: trust in the
technology and trust in the innovating firm.”
Source: https://hbr.org/2017/04/to-get-consumers-to-trust-ai-show-them-its-benefits

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