Explains about Evolution of IT in Healthcare, how analytics can make a difference and evolution of IT in healtcare. For more information visit: http://www.transformhealth-it.org/

1. Predictive Health
Population Analytics
Veera S Raghavan
Executive Director & Global Practice Head
Healthcare and Life Sciences
Dell Services
October 2015
Veeraraghavan@dell

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Modifiable health
Adapted by DrNick from 2009 Continua Health Alliance -Brigitte Piniewski, MD
0 25 65
IllnessPre-IllnessWellness
Unpredictable Health
Predictable (Rules-based) Health
Age
Death
60-80% Lifestyle

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To put it another way….
Adapted by DrNick from 2009 Continua Health Alliance -Brigitte Piniewski, MD
0 25 65 Age
IllnessPre-IllnessWellness
Death
Fun
No Fun

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Challenges: US example
$840B Annual healthcare spending with little or
no effect on outcomes
$17B Annual avoidable readmission costs for
Medicare patients
200-400K Annual deaths as a result of
“preventable harm” in hospitals
>3,300 Annual deaths due to asthma. Many of
which are avoidable.

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Analytics can make a difference: US example
UPMC Health Plan
reduced
readmission rates
37%
by identifying at-risk patients and
providing personalized transition care
and follow-up
58%
reduction in surgical site infections at
University of Iowa Hospitals and
Clinics by providing real-time
analytics during surgery
asthma care with email notifications
to emergency rooms, case managers
and asthma patients forecasting events
likely to exacerbate symptoms
Optimize
tests and overnight stays for ER patients
by using analytics and historic data to more
accurately predict test outcomes and
likelihood of impending cardiac events
reduceER doctors
were able to

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Evolution of IT in healthcare delivery
As healthcare delivery evolves towards collaborative care models, the ability to share
data and use it to improve decision making will be a key transformative milestone
Manage patient health
Capture and digitize records
Electronic medical record
Patient health management
EMR
Information
driven
decision
making
Lab/eRx
Hospital
Physician
Payer
EMR
Interoperability
BI & analytics
Phase 1 Phase 2 Phase 3
Move and exchange data
Analyze and manage data
Population
health records
EMR
EMR

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What can you do with your big data?
From reporting to search, discovery and prediction
RetrospectiveDataReporting
Real-time
Unstructured
Multiple
sources
Volume
Population Analytics
Personalized Medicine
Performance Mgmt
Outcome Improvement
Clinical Decision Support
Disease Mgmt/Patient Compliance
Patient Profiling
Cohort Analysis
Fraud Detection
Health Economics & Outcome Research
Performance-based pricing Drug Discovery
R&D Resource Allocation
Clinical Trial Design
Personalized Medicine
Consumer Segmentation
Infectious Disease and Outbreak Detection
Patient Satisfaction & Behavior Analytics
Readmissions
Operation Mgmt
Payment/Pricing
R&D
Public Health
CRM
Marketing Promotion/Health Campaigns
Comparative Effectiveness Research
Population
health records

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Information-driven healthcare
Seamlessly integrate big data and analytics into your workflow
• Operational
reports
• Adhoc reports
• Basic quality
reports
• Emergency
dashboard
• Readmission
rates
• HAI trends
• Gaps in care
• Physician
scorecards and
benchmarking
• Labor
forecasting
• Population risk
stratification
• Disease based
risk models
• Readmission
prediction
• Prescriptive
analytics
• Patient flow
optimization
• Network
leakage and
design
Reporting
Visualization
Inferences/
exceptions
Predictive
analytics
Optimization
Hindsight
Insight
Foresight
Data Integration and Management
Enterprise Data Warehouse
Master Data Management/ Governance
Model Development
Change
Mgmt.

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Delivery – highly unorganized in diff formatsDelivery – highly unorganized in diff formats
Focus on India
60%
40
20
0
58
45
34
31
13
11
7
World average: 18
India Indo
nesia
China Brazil Norway US South
Africa
Out of Pocket Health Expenditure (as a % of total expenditure on health)

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Where & how do we start?
Collect targeted operational data – wait times, time &
motion studies, inventory to focus on operational
analytics to drive bottom-line improvements
Collect targeted patient experience and satisfaction
data through surveys, correlate with healthcare services
and physicians, monitor trends over time to drive traffic
CSAT and predictive customer (patient & referring
physician) behavior for top-line improvements
Implement a light weight EMR to collect key clinical
data points smartly. Drive outcomes research and
clinical quality improvements. De-identify data to
enable clinical trials, open new opportunities
Role of
Government,
Health Ministry,
Industry
associations in
defining and
enforcing data
standards
Regulate
Industry
through data

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Hospital-IT-in-a-Box solution
Core 4-stack solution
Secure orchestrated Public cloud
Business Intelligence – Clinical Research, Executives & Operations
EMR (clinical functions)
• Medical record
• Diagnosis
• Treatment plans
• Prescription
• Discharge
summary
• CPOE
ERP functions
• Finance & accounting
• HCM & payroll
• Supply chain management
Administrative & finance functions (non-clinical)
Lab, Radiology &
pharmacy mgmt
OP & IP management Housekeeping Blood Bank
Patient Billing / claims
mgmt
Ward management OT & CSSD Diet management
Hospital chain 1
Hospital chain 2
Hospital chain 3
SaaS
SaaS
SaaS
Enterpriseimage
management
PRM
Tele
medicine
BPM
Analyse Design Develop
Enhance Deploy
CRM
Sales force automation
Referrals
Camp
module
Dell
end-to-end
solution

12. Thank you
Veera_s_raghavan@dell.com