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

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

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

Total of Houses: 70 millions 1. MOTIVATION Brazilian Digital Divide Problem 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%

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

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

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

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

1. MOTIVATION Digital Belt Project

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

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

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

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

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

= 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… =

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.

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 …

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

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

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.

5) PROPOSAL: LARISSA FRAMEWORK

6) PROPOSAL: LARISSA FRAMEWORK Local health context model

6) PROPOSAL: LARISSA FRAMEWORK Global health context model

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.

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

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

6) APPLICATIONS: Health Agent Scenario

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

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