The document discusses advanced analytics in healthcare in Singapore. It provides an overview of IHiS, the trusted technology partner in Singapore's public healthcare sector, and their work supporting over 40,000 healthcare users across hospitals, specialty centers, and polyclinics. It then discusses Singapore's healthcare landscape and vision for 2020, including regional health systems and better insurance. The document outlines how digital disruption is bringing more preventive, predictive, personalized and participatory approaches to healthcare through tools like risk assessment, genome analysis, wearables and online resources. It emphasizes that while healthcare analytics is important and relevant, it faces challenges around data availability, resources, and understanding how to apply analytic insights. Collaboration between IT, medical and data science experts is key

1. Advanced Analytics in Healthcare
Singapore Healthcare Landscape -
Analytics

2. 2
IHiS: Who We Are
VISION
INNOVATION
INTEGRITY
PASSION
TRUST & RESPECT
DYNAMISM
To be the trusted
technology partner
in healthcare
To lead and deliver
technology for
excellence in healthcare
IHiS architects and manages highly integrated award-winning systems
across Singapore’s public healthcare sector.

3. 3
IHiS: What We Do
supporting
40,000
Healthcare users
6 1
9 Hospitals
8 National
Specialty
Centers
18 Polyclinics
Clusters Agency
> 780
Systems and
Interfaces
Professionals
1,200

4. 4
IHiS: What We Do
Applications
Architecture &
Innovation
Technology
Management
HCLOUD
network services
D
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t
a
C
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t
r
e
CLUSTERINFRASTRUCTURE
Security
Services
BUSINESS
SYSTEMS
Patient Systems
Healthcare
Analytics
DevelopmentCentre
Diagnostics
C
P
S
S
2
S
C
M
Pharmacy
National
Architecture
Office
Innovation
Office

5. 5
IHiS: Our Customers

6. 6
Singapore Healthcare Landscape
Primary Care
- 18 Polyclinics (20%)
-1,500 private medical
clinics (80%)
Secondary & Tertiary
Care
- 9 Restructured Hospitals &
8 national specialty centres
(80%)
- 10 Private Hospitals (20%)
Step Down and Long
Term Care
- People Sector (70%)
- Community Hospitals ,
nursing homes , Day care
etc.

7. 7
Singapore - Healthcare 2020
 Regional Health Systems
 Team-based care disease management
models
 Community Health Assist Scheme
(CHAS)
 Better Insurance Scheme
 More drugs to be subsidised
 Powering Up the Intermediate &
Long-Term Care Sector

8. 8
Digital Disruption Wave

9. 9
Preventive
Predictive
Personalized
Participatory
Risk assessment and
preventive treatment
Genome analysis to predict
risk of diseases and devise
personalized treatment
Greater accessibility to
healthcare with wearables
and online resources
Data monitoring and
collection by patients to
mange their well being and
make informed decisions
Digital Disruption in Healthcare – 4P

10. 10
Everybody is talking about Big Data
Source: Big data; The Next Frontier for Innovation, Competition and Productivity – McKinsey Global Institute Report & comScore
,Radical Group

11. 11
AlphaGo vs Lee Sedol

12. 12
What is next after AlphaGo?

13. 13
Google is Not Alone

14. 14
Big Data – the BUZZ
“Many people buy an expensive camera thinking it will make them a
better photographer, when really better photographers have better
cameras.”
“In Healthcare we are
struggling with small
volume of data itself “

15. 15
Why Healthcare Analytics is SO HOT ?

16. 16SOURCE INFORMATION WEEK, MARCH 2013, “HEALTHCARE ORGANIZATIONS GO BIG FOR ANALYTICS”.
How relevant is Analytics to Healthcare ?

17. 17
Relevant yet difficult to evangelize
“We don’t have data readily available for analysis”
“We don’t have enough funds/resources for analytics projects”
“I want big data”
“ What do I do with the analytics output”
“ Which technology should I adopt”
“IT is responsible for project”

18. 18
Operational Transformation
Objective - Operational Excellence
Approach – Focus on business as usual
decision that will be repeated frequently
Outcome – Enable capability
to harness analytics in operations

19. 19
People
System
Operations
Ecosystem of Feedback Loop
Process
Generates data
Analytics
Insight
Execution
Inculcate the data driven culture
through people, operation and
technology

20. 20
Collaboration is the Key
• What information has been recorded
• Where is the data
• How to get the data
• How to deploy the model
• What is the problem
• What are the likely causes
• What do we need from the model
• How should we use the model
• How to frame the problem in modeling languages
• What models to use
• What variables to include – integrate information
from IT professional and medical professionals
• How to assess the model performance
IT Professionals
Medical Professionals
Data Scientists
Knowledge of the data
Knowledge of the problem
Knowledge of the technique
Analytics Solutions
• Relevant
• Accurate
• Easy to deploy