A Context-Aware Framework for Health Care Governance Decision-Making Systems: A model based on the Brazilian Digital TV

Mauro Oliveira & Odorico Andrade

Mauro Oliveira, Odorico Andrade, Regis Moura

Claude Sicotte, J-L Denis, Stenio Fernandes

José Bringel, Hervé Martin, Jérôme Gensel

France BrazilCanada

LARIISALaboratoire Application Réseaux Intelligence Intégration Santé

1) 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

LARIISA: Laboratoire Application Réseaux Intelligence Intégration Santé

OUTLINE

Total of Houses: 70 millions

– Coockle 97,7%– Television 95,7%– Refrigerator 86,7%– Mobile phone 61,2%– Telephone 54,0%– Microcomputador: 16,91%

Internet access 15,08%

Brazilian Digital Divide ProblemBrazilian Digital Divide Problem

1. MOTIVATION

AnalógicoAnalógico

Today Interactive Digital TV

Digita

l

1. MOTIVATION

(Passive)

(Passive)

(Active)

Interactive Digital TV

(Active)

1. MOTIVATION

High Definition

Interactivity Multiprogramming

Mobility

Interactive Digital TV

1. MOTIVATION

NetworkNetwork

Audio

Video

DataData Carrossel

1. MOTIVATION

Interactive Digital TV

1. MOTIVATION

Digital Belt Project

BST-OFDM

MPEG-2 System

H.264 HP@L4.0 H.264 BP@L1.3

MPEG - 4 HE-AAC@L4 MPEG - 4 HE-AAC@L3

Ginga

APL1 APL2 APLn...

DemoduladorDecod. do Canal

Dec. Áudio

Dec. Vídeo

CPUMemória

VC

RF

IR CR

Video out

AudioSurround

Audio outRF out

RedeExterna

RF in

API SO

...

LARIISA: Laboratoire Application Réseaux Intelligence Intégration Santé

2. OBJECTIVE

ITU-T J.200 Recommendation

Brazilian Digital TV Model

Digital BeltProject

(1)

(2)

(3,4)

(5)

AgentPersonalizedmessage

AgentPersonalizedInformation

Context Detection

IF-THEN RULE-BASED APPROACH

(1) IF blood sugar exceeds a threshold, THEN should not take certain food.(2) IF the room is too dry, THEN turn on the humidity generator(3) IF the user is at lunch, THEN send the message later.(4) 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.

Context-aware Services

Context-Aware Health Agent APPLICATION

Context-Aware Health Agent PERSONALIZATION

Decision Making in Governance

Decision MakingApplication

2. OBJECTIVE

Two ways to capture the health data

- Interactive Programs- Sensors

1) Real-time Information

2) Health Knowledge

3) Professional Experience

4) Decision-making

"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)

Set-top-box and Digital Belt

Ontology Representation (OWL)

Context Reasoning Component

Decision-making Application

Real Situation LARIISA: Context-Aware System

2. OBJECTIVE

Prof Mauro: LARA Project Communication INFRASTRUCTURE

3. LARIISA Project

Diga-Ginga(FINEP Project)

Prof Odorico: RIISO Project Health Care APPLICATION (for governance model)

3. LARIISA Project

IF…

and …

IF…

3. LARIISA Project

– Coockle 97,7%

– Television 95,7%

– Refrigerator 86,7%

– Mobile phone 61,2%

– Telephone 54,0%

– Microcomputador: 16,91%

Internet access 15,08%

=

How...

4) MODELS FOR LARIISA FRAMEWORK

I.D.Graham, J.Logan, M.B. Harrison, S.E.Straus, J.Tetroe, W.Caswell, N.RobinsonThe Journal of Continuing Education in the Health Professions, Vol 26 N°1, 2006 – Wiley InterScience.

Knowledege to Action for healthcare system

Knowledge Creation

Knowledge to Action Process (KAP)

TailoringKnowledge

Action Cycle (Application)

Adaptation - Query

Context Provider 1 Context Provider 2 Context Provider N…

5) PROPOSAL: LARISSA FRAMEWORK

OntologyBase

Service Adaptation

Adaptation - Aggregation

Context Reasoning

Context-aware Service 1 Context-aware Service 2 Context-aware Service N…

(Context-awareness)

Container

…

OntologyBase

Service Adaptation

Adaptation - Query

Adaptation - Aggregation

Context Provider 1 Context Provider 2 Context Provider N…

Context Reasoning

5) PROPOSAL: LARISSA FRAMEWORK

(Context-awareness)Knowledge to Action Process (KAP) Action Cycle (Application)

Knowledge Creation

LARISSA framework v2.1

Context-aware Services Context-aware Services Context-aware Services

Decision MakingApplication

Containers

7) PROPOSAL: LARISSA FRAMEWORKKNOWLEDGE TO ACTION (KTA)

Knowledge Creation(Process)

Decision Making in Governance

LARISSA framework v2.1

(Information for the Knowledge Creation)

Action Cycle (Application)

5) PROPOSAL: LARISSA FRAMEWORK

…

OntologyBase

Service Adaptation

Adaptation - Query

Adaptation - Aggregation

Context Provider 1 Context Provider 2 Context Provider N…

Context Reasoning

Context-aware Services Context-aware Services

Systemic Normative

Clinical and Epidemiology Administration Share

ManagementKnowledge

Management

Context-aware Services

5) PROPOSAL: LARISSA FRAMEWORK

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.

AgentPersonalizedmessage

AgentPersonalizedInformation

Context Detection

Decision Making in Governance

5) PROPOSAL: LARISSA FRAMEWORK

6) PROPOSAL: LARISSA FRAMEWORK

Local health context model

6) PROPOSAL: LARISSA FRAMEWORK

Global health context model

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.

Applying DENGUE Study Case to LARIISA

Administration Case

Decision Making in

Administration

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

Decision: Creating an Emergency (ER) for the clinical management of severe cases (ER-SC)

6) APPLICATIONS:

Taua Pilot Project

Epidemiology Case

Decision Making in

Epidemiology

High Level GLOBAL Decision:Reallocating Health Agents !

High Level LOCAL Decision:Updating the Agent’s Agenda !

6) APPLICATIONS:

BST-OFDM

MPEG-2 System

H.264 HP@L4.0 H.264 BP@L1.3

MPEG - 4 HE-AAC@L4 MPEG - 4 HE-AAC@L3

Ginga

APL1 APL2 APLn...

DemoduladorDecod. do Canal

Dec. Áudio

Dec. Vídeo

CPUMemória

VC

RF

IR CR

Video out

AudioSurround

Audio outRF out

RedeExterna

RF in

API SO

...

6) APPLICATIONS: Health Agent Scenario

BST-OFDM

MPEG-2 System

H.264 HP@L4.0 H.264 BP@L1.3

MPEG - 4 HE-AAC@L4 MPEG - 4 HE-AAC@L3

Ginga

APL1 APL2 APLn...

DemoduladorDecod. do Canal

Dec. Áudio

Dec. Vídeo

CPUMemória

VC

RF

IR CR

Video out

AudioSurround

Audio outRF out

RedeExterna

RF in

API SO

...

LARIISA: Laboratoire Application Réseaux Intelligence Intégration Santé

7. CONCLUSION

Tauá Pilot Project(Proof of Concept)

PNBL

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