1. Mauro Oliveira & Odorico Andrade
A Context-Aware Framework for Health Care Governance Decision-Making Systems: A model based on the Brazilian Digital TV
Mauro Oliveira & Odorico Andrade

3. LARIISA Mauro Oliveira, Odorico Andrade, Regis Moura
Laboratoire Application Réseaux Intelligence Intégration Santé
Mauro Oliveira, Odorico Andrade, Regis Moura
Claude Sicotte, J-L Denis, Stenio Fernandes
José Bringel, Hervé Martin, Jérôme Gensel
Canada
France
Brazil

4. LARIISA: Laboratoire Application Réseaux Intelligence Intégration Santé
OUTLINE
MOTIVATION: Governance Model for Decision Making on Health Care Systems
2) OBJECTIVE: Context-aware System based on the Family Information
3) LARIISA: Riiso + Lara Projects
- Prof Odorico: RIISO Project  Health Care APPLICATION
- Prof Mauro: LARA Project  Communication INFRASTRUCTURE
4) CONCEPTS: Models for LARIISA Framework
- Integration of Health care
- Knowledge To Action
- Unified Service Delivery Platform
5) PROPOSAL: Larissa Framework
6) APPLICATIONS:
- DENGUE Study Case
- Health Agent Scenario
7) CONCLUSIONS:
- Taua Pilot Project
- PNBL, High Bandwidth Brazilian Program

5. Total of Houses: 70 millions
1. MOTIVATION
Brazilian Digital Divide Problem
Total of Houses: 70 millions
Coockle ,7%
Television 95,7%
Refrigerator 86,7%
Mobile phone 61,2%
Telephone 54,0%
Microcomputador: 16,91%
Internet access 15,08%

6. Interactive Digital TV
1. MOTIVATION
Interactive Digital TV
Today
Analógico
Analógico
Digital

7. Interactive Digital TV
1. MOTIVATION
Interactive Digital TV
(Passive)
(Passive)
(Active)
(Active)

8. Interactive Digital TV
1. MOTIVATION
Interactive Digital TV
High Definition
Mobility
Interactivity
Multiprogramming

9. Interactive Digital TV 1. MOTIVATION Network Audio Video Data
Data Carrossel
Network 9

10. 1. MOTIVATION
Digital Belt Project

11. 2. OBJECTIVE
LARIISA: Laboratoire Application Réseaux Intelligence Intégration Santé
Digital
Belt
Project
ITU-T
J.200 Recommendation
Brazilian Digital TV Model

12. Decision MakingApplication
2. OBJECTIVE
Context-Aware Health
Agent APPLICATION
Decision Making
in Governance
Decision MakingApplication
Context-Aware Health
Agent PERSONALIZATION
Context-aware Services
Agent
Personalized
message
Agent
Personalized
Information
IF-THEN RULE-BASED APPROACH
IF blood sugar exceeds a threshold, THEN should not take certain food.
IF the room is too dry, THEN turn on the humidity generator
IF the user is at lunch, THEN send the message later.
IF the user is not at office, THEN send the call to the mobile.
(5) IF a PC is accessible, THEN present the message as video.
(3,4)
(5)
(2)
Context
Detection
Two ways to capture the health data
(1)
Interactive Programs
Sensors

13. 2. OBJECTIVE (Andrade, 2010) Real Situation
"Once we realized the lack of a system able to provide reliable data and information in real time, offering correct information for making decisions, we have decided to transfer the Office of Health Secretary and his staff to the Control Center of Endemic Diseases and Zoonoses”.
(Andrade, 2010)
Real Situation
LARIISA: Context-Aware System
Real-time Information
 Set-top-box and Digital Belt
2) Health Knowledge
 Ontology Representation (OWL)
3) Professional Experience
 Context Reasoning Component
4) Decision-making
 Decision-making Application

14. 3. LARIISA Project Diga-Ginga
Prof Mauro: LARA Project  Communication INFRASTRUCTURE
Diga-Ginga
(FINEP Project)

15. 3. LARIISA Project
Prof Odorico: RIISO Project  Health Care APPLICATION (for governance model)

16. = 3. LARIISA Project IF… Coockle 97,7% Television 95,7%
Refrigerator 86,7%
Mobile phone 61,2%
Telephone 54,0%
Microcomputador: 16,91%
Internet access 15,08%
and …
How...
IF… =

17. 4) MODELS FOR LARIISA FRAMEWORK
Knowledege to Action for healthcare system
I.D.Graham, J.Logan, M.B. Harrison, S.E.Straus, J.Tetroe, W.Caswell, N.Robinson
The Journal of Continuing Education in the Health Professions, Vol 26 N°1, 2006 – Wiley InterScience.

18. 5) PROPOSAL: LARISSA FRAMEWORK
Knowledge to Action Process (KAP)
Knowledge
Creation
Action Cycle (Application)
Tailoring
Knowledge
(Context-awareness)
Context-aware Service 1
Context-aware Service 2
Context-aware Service N …
Adaptation - Query
Container
Ontology
Base
Service
Adaptation
Adaptation - Aggregation
Context Reasoning
Context Provider 1
Context Provider 2
Context Provider N …

19. 5) PROPOSAL: LARISSA FRAMEWORK
Decision MakingApplication
Knowledge to Action Process (KAP)
Action Cycle (Application)
(Context-awareness) …
Knowledge
Creation
Context-aware Services
Context-aware Services
Context-aware Services
Containers
Adaptation - Query
Ontology
Base
Service
Adaptation
Context Reasoning
Adaptation - Aggregation …
Context Provider 1
Context Provider 2
Context Provider N
LARISSA framework v2.1

20. 7) PROPOSAL: LARISSA FRAMEWORK
KNOWLEDGE TO ACTION (KTA)
Action Cycle (Application)
Decision Making in Governance
Knowledge
Management
Systemic Normative
Clinical and
Epidemiology
Administration
Share
Management
Knowledge
Creation
(Process) …
Context-aware Services
Context-aware Services
Context-aware Services
Adaptation - Query
Ontology
Base
Service
Adaptation
Context Reasoning
Adaptation - Aggregation
(Information for the
Knowledge Creation) …
Context Provider 1
Context Provider 2
Context Provider N
LARISSA framework v2.1

21. 5) PROPOSAL: LARISSA FRAMEWORK
Decision Making
in Governance
Agent
Personalized
message
Agent
Personalized
Information
Context
Detection
CONTEXT CATEGORIES (Zhang and all.):
(1) Personal Health Context : physiological and mental context
(2) Environment Contex: temperature, light, humidity, noise, etc.
(3) Task Context: goals, task, actions, activities, events, etc.
(4) Spatio-temporal Context: time and location
(5) Terminal Context: terminal type, interface, media supported, etc.

22. 5) PROPOSAL: LARISSA FRAMEWORK

23. 6) PROPOSAL: LARISSA FRAMEWORK
Local health context model

24. 6) PROPOSAL: LARISSA FRAMEWORK
Global health context model

25. Applying DENGUE Study Case to LARIISA
6) APPLICATIONS:
Applying DENGUE Study Case to LARIISA
Decision Making in Knowledge Management
Decision Making in Systemic Normative
Decision Making in Clinical and Epidemiology
Decision Making in Share Management
Decision Making in Administration
Decision: Creating an Emergency for the clinical management of severe cases (ER-SC)
Rule: IF the patient had Dengue more than once
AND lives in an area with high infestation rate
AND has symptoms A,B and C,
THEN you must consult the ER-SC about this case
Results: lower mortality due to a series of actions, in special the use of the rule above.

26. Applying DENGUE Study Case to LARIISA
6) APPLICATIONS:
Applying DENGUE Study Case to LARIISA
Decision Making in
Decision: Creating an Emergency (ER) for the clinical management of severe cases (ER-SC)
Administration
Administration Case
IF the patient had Dengue more than once
AND lives in an area with high infestation indice
AND has symptoms A,B and C,
THEN you must consult the ER-SC about this case
Results:
lower mortality due to a series of actions, in special the use of the rule above

27. Taua Pilot Project 6) APPLICATIONS: Decision Making in
High Level GLOBAL Decision:
Reallocating Health Agents !
High Level LOCAL Decision:
Updating the Agent’s Agenda !
Decision Making in
Epidemiology
Epidemiology Case

28. 6) APPLICATIONS: Health Agent Scenario

29. 7. CONCLUSION
LARIISA: Laboratoire Application Réseaux Intelligence Intégration Santé
Tauá Pilot Project
(Proof of Concept)
PNBL

30. MUITO OBRIGADO