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Predictive Health Analytics & Genomics
in Population Health Management
 Daniel Hoemke, VP of Global BD
 Dr. Hossein Fakhrai-Rad, Founder & CSO
HIMSS
Las Vegas- March 2016
Today’s Discussion
CHALLENGE
2
INFORM
INSPIRE
…thinking about predictive analytics and application in
personal and population health management
…consideration of the possibilities and the value
that can be derived
…you on next generation science and technology
3
The Challenge
FOCUS
RELIANCE
FAILURE
…on management of high cost, high risk population cohorts
…to favorably bend cost trends or improve population health
…on hindsight, retrospective claims and clinical data
UNSUSTAINABILITY …Health costs for US families has doubled
over past 10 years and tripled since 2001
4
Today’s Limited Population Health Focus
Chronic Conditions – 12% Catastrophic Conditions – 1%
Strong Retrospective Visibility
Financial Saving Potential with Prevention
1995 2000 2005 2010 2015 2020 2025 2030
118 125 133 141 149
157
164
171
If Prevention Is Not Systematically Approached,
By 2025, 49% of Americans Will Have Chronic Diseases
1000 individuals
Depression
Allergic Rhinitis
Hypertension
Heart Disease
Asthma
Type 2 Diabetes
Cancer
75
56
32
12
7
6
2
Annual
Progression
to Disease
Additional annual
cost due to disease:
$325,000
Annual additional cost of treatment due to progression to disease in a population of 1000 individuals
Source: Wu, Shin-Yi and Green, Anthony. Projection of Chronic Illness Prevalence and Cost Inflation. RAND Corporation, 10/2000 5
Confluence of Market Factors
6
Health Science
and Technology
Healthcare
Consumerism
Healthplan Payer
and Plan Sponsor
Roles
Healthcare Delivery
and Payment
Ecosystems
7
Today’s Total Population Health Potential
Chronic Conditions – 12%
Catastrophic Conditions – 1%
Prospective Visibility for Disease Risk
For Which 7 Out of 10 Will Become Chronically Ill
Enhanced Prospective Visibility
for Comorbidity Risk
Well/Acute Episodic Conditions – 87%
Comprehensive Health Assessment
Factors That Impact Our Health°
Exogenous Factors
60%
Genomics Factors
30%
Clinical
Factors
10%
BaseHealth Analytics
Individual Risk Population Risk Recommendations Drug Response Food Response
BaseHealth predictive engine does not require the availability of all four data sets. The more data available, however, the more
complete the assessment.
° Source: IBM Watson
GenomicsLifestyle
(Wearables)
EHR DataEnvironment
Lipid Panel
Vitamin D
Homocysteine
C-Reactive Protein
8
Independent and Objective BaseHealth Score
A Predictive Score Between 0 and 1000
Reducing Risk Factor Values – 42%
Reducing Disease Risk – 35%
Completing Profile – 10%
Creating an Action Plan – 3%
Tracking Actions – 10 %
9
698
BaseHealth Technology Makes Prevention A Reality
Biometrics/
Wearables
Low Cost Genome
Sequencing
Cloud Computing/
Integration
Machine Learning
Smart Phones
10
Data Sources
> 30K Scientific Publications
> 70M People Health Data
> 20K
Genetic Risk
Factors
> 660
Non-Genetic Risk
Factors
Factors Analyzed Modeled on Platform
>1200 Unique Genetic Risk
Factors
>75 Unique Non-Genetic Risk
Factors
Nutrients
14
Drugs
24
Diseases
41
11
Analysis and Integration of Massive Scientific Data
12
International Journal of Medical Technology, ISSN: 2051-574X, Vol.23, Issue.1 1116
Predictive Value of Personalized Risk Assessment to
Prevent Multifactorial, Complex and Chronic Diseases
Submitted for publication to: International Journal of Medical Informatics (Elsevier)
Application of Personalized Risk Assessment to
Prevent Chronic Diseases Using Aggregate
Population Based Data
Scientific Validation / Excellent C-Stats Results
About BaseHealth
Company originated at Stanford Genome Technology Center
Headquartered in Redwood Shores, CA
Comprehensive cloud-based Health Predictive Analytics platform
offered via an API solution or a SaaS platform
Strong team of visionaries, entrepreneurs, with previous leadership
roles in companies such as Affymetrix, ParAllele Biosciences,
Oracle, Humana, Aetna, Visa International, and academic
institutions such as Harvard, Stanford, and Karolinska Institute
HIPAA Compliant, TRUSTe, CLIA, and CAP Certified
13
www.basehealth.com
Booth #14113
For More Information, Please Contact Parsi at:
parsinejad@basehealth.com

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HIMSS 2016 "Predictive Analytics & Genomics in Population Health Management

  • 1. Predictive Health Analytics & Genomics in Population Health Management  Daniel Hoemke, VP of Global BD  Dr. Hossein Fakhrai-Rad, Founder & CSO HIMSS Las Vegas- March 2016
  • 2. Today’s Discussion CHALLENGE 2 INFORM INSPIRE …thinking about predictive analytics and application in personal and population health management …consideration of the possibilities and the value that can be derived …you on next generation science and technology
  • 3. 3 The Challenge FOCUS RELIANCE FAILURE …on management of high cost, high risk population cohorts …to favorably bend cost trends or improve population health …on hindsight, retrospective claims and clinical data UNSUSTAINABILITY …Health costs for US families has doubled over past 10 years and tripled since 2001
  • 4. 4 Today’s Limited Population Health Focus Chronic Conditions – 12% Catastrophic Conditions – 1% Strong Retrospective Visibility
  • 5. Financial Saving Potential with Prevention 1995 2000 2005 2010 2015 2020 2025 2030 118 125 133 141 149 157 164 171 If Prevention Is Not Systematically Approached, By 2025, 49% of Americans Will Have Chronic Diseases 1000 individuals Depression Allergic Rhinitis Hypertension Heart Disease Asthma Type 2 Diabetes Cancer 75 56 32 12 7 6 2 Annual Progression to Disease Additional annual cost due to disease: $325,000 Annual additional cost of treatment due to progression to disease in a population of 1000 individuals Source: Wu, Shin-Yi and Green, Anthony. Projection of Chronic Illness Prevalence and Cost Inflation. RAND Corporation, 10/2000 5
  • 6. Confluence of Market Factors 6 Health Science and Technology Healthcare Consumerism Healthplan Payer and Plan Sponsor Roles Healthcare Delivery and Payment Ecosystems
  • 7. 7 Today’s Total Population Health Potential Chronic Conditions – 12% Catastrophic Conditions – 1% Prospective Visibility for Disease Risk For Which 7 Out of 10 Will Become Chronically Ill Enhanced Prospective Visibility for Comorbidity Risk Well/Acute Episodic Conditions – 87%
  • 8. Comprehensive Health Assessment Factors That Impact Our Health° Exogenous Factors 60% Genomics Factors 30% Clinical Factors 10% BaseHealth Analytics Individual Risk Population Risk Recommendations Drug Response Food Response BaseHealth predictive engine does not require the availability of all four data sets. The more data available, however, the more complete the assessment. ° Source: IBM Watson GenomicsLifestyle (Wearables) EHR DataEnvironment Lipid Panel Vitamin D Homocysteine C-Reactive Protein 8
  • 9. Independent and Objective BaseHealth Score A Predictive Score Between 0 and 1000 Reducing Risk Factor Values – 42% Reducing Disease Risk – 35% Completing Profile – 10% Creating an Action Plan – 3% Tracking Actions – 10 % 9 698
  • 10. BaseHealth Technology Makes Prevention A Reality Biometrics/ Wearables Low Cost Genome Sequencing Cloud Computing/ Integration Machine Learning Smart Phones 10
  • 11. Data Sources > 30K Scientific Publications > 70M People Health Data > 20K Genetic Risk Factors > 660 Non-Genetic Risk Factors Factors Analyzed Modeled on Platform >1200 Unique Genetic Risk Factors >75 Unique Non-Genetic Risk Factors Nutrients 14 Drugs 24 Diseases 41 11 Analysis and Integration of Massive Scientific Data
  • 12. 12 International Journal of Medical Technology, ISSN: 2051-574X, Vol.23, Issue.1 1116 Predictive Value of Personalized Risk Assessment to Prevent Multifactorial, Complex and Chronic Diseases Submitted for publication to: International Journal of Medical Informatics (Elsevier) Application of Personalized Risk Assessment to Prevent Chronic Diseases Using Aggregate Population Based Data Scientific Validation / Excellent C-Stats Results
  • 13. About BaseHealth Company originated at Stanford Genome Technology Center Headquartered in Redwood Shores, CA Comprehensive cloud-based Health Predictive Analytics platform offered via an API solution or a SaaS platform Strong team of visionaries, entrepreneurs, with previous leadership roles in companies such as Affymetrix, ParAllele Biosciences, Oracle, Humana, Aetna, Visa International, and academic institutions such as Harvard, Stanford, and Karolinska Institute HIPAA Compliant, TRUSTe, CLIA, and CAP Certified 13
  • 14. www.basehealth.com Booth #14113 For More Information, Please Contact Parsi at: parsinejad@basehealth.com