23 setembre 2014 fundacio idiap jordi gol health consensus reduced
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Transcript of 23 setembre 2014 fundacio idiap jordi gol health consensus reduced
Health & Collective [email protected]
Health & Collective Intelligence
Tino Martí, Josep Mª Monguet , Alex Trejo
23 de setembre de 2014 a IDIAP Jordi Gol
thepracticeofinnovation.net
Health & Collective Intelligence
Summary
Collective intelligence in the context of health
The “Health Consensus” system.
• Fields of applications
• Models & methodologies
Health & Collective Intelligence
Knowledge approach to CI
Tacit Knowledge
Explic
it knowledge
i i gi
ii
ii
i
i
go
o
g
g
gg
SocializationExternalisation
Internalisation combination
The Modes of Conversion – SECI Model (Nonaka,1994)
Health & Collective Intelligence
Applications and modalities
Health Consensus is a system developed by Onsanity Solutions based on the research done at UPC.
The research project began in 2006 when the original idea was applied to "design research“ thepracticeofinnovation.net
Health & Collective Intelligence
Participative assessmentCase
Assessment of the CAT Health Plan 2011 -15
Health & Collective Intelligence
Participants
3.616Health professions
18
Assessment of the CAT Health Plan 2011 -15
Health & Collective Intelligence
Question - example
Respecte al nivell de detecció de necessitats de salut comunitària:Level of detection of health community needs.
On podríem ser al 2015?Potential in 2015
Assessment of the CAT Health Plan 2011 -15
On som avui?Current
On serem al 2015?Expected in 2015
Health & Collective Intelligence
Assessment of the CAT Health Plan 2011 -15
On podríem ser al 2015?Potential in 2015
On som avui?Current
On serem al 2015?Expected in 2015
Question - example
Respecte al nivell de detecció de necessitats de salut comunitària:Level of detection of health community needs.
Health & Collective Intelligence
PRONÒSTIC
1 2 3 4 5 6
HORITZÓ POTENCIAL
On som On serem On podem ser
RECORREGUT
Avui 2015
Assessment of the CAT Health Plan 2011 -15
Health & Collective Intelligence
Publication
Paper persented at the … Collective Intelligence MIT Boston 2014 Link
Assessment of the CAT Health Plan 2011 -15
Health & Collective Intelligence
Collaborative design of modelsCase
Selection of chronic care indicators
Programa de Prevenció i Atenció a la Cronicitat
Health & Collective Intelligence
Selection of chronic care Indicators
100 25 96 415
215 85 52 36 18
Participants
Indicators
Rounds
Meetings& Focus g.
Pilot 1st
Round2o
Round
Health Consensus
First Approach
ConsensusExpress
Asynchronous Consensus
Initial number of indicators
Relevant and feasible indicators obtained by consensus
Health & Collective Intelligence
Selection of chronic care Indicators
Health & Collective Intelligence
Selection of chronic care Indicators
Health & Collective Intelligence
Selection of chronic care Indicators
Health & Collective Intelligence
Selection of chronic care Indicators
Health & Collective Intelligence
Selection of chronic care Indicators
Health & Collective Intelligence
Selection of chronic care Indicators
Health & Collective Intelligence
Meta results
Selection of chronic care Indicators
Communicating the strategy chronic (Learning)
Alignment of the system via consensus (Decision Making)
Collaboration for the establishment of priority indicators.
Broad participation of healthcare professionals in identifying needs and opportunities
Health & Collective Intelligence
Publication
Selection of chronic care Indicators
Paper in press …
Health & Collective Intelligence
Innovation participative spaceCase
Primary Care Innovation
Health & Collective Intelligence
Primary Care Innovation
Health & Collective Intelligence
Primary Care Innovation
Health & Collective Intelligence
Primary Care Innovation
Health & Collective Intelligence
Primary Care Innovation
Health & Collective Intelligence
Primary Care Innovation
Health & Collective Intelligence
Consensus on clinical cases. Case
Training on mental health
Health & Collective Intelligence
Training on mental health
Health & Collective Intelligence
Training on mental health
Health & Collective Intelligence
Training on mental health
Health & Collective Intelligence
Methods of application
Delphi Express Continuous
Health & Collective Intelligence
Methods of application Delphi Health Consensus
Components& Structure of
the model
Based on a set of Drivers
Presented as lists of Questions
People participating in consensus
Answering
Modelagreement
Stratification of agreement by attributes of participants
Weighting
Self assessing
Understanding the Model
Deciding &/or concluding about
the model
1 n2
Rounds of participation to assess the model
2 13
Leading team
pi participants in each round
Health & Collective Intelligence
Case type: - One or two days - Shared construct definition - Open online consensus and discussion - Direct publication of results on a blog.
Methods of applicationExpress Health Consensus
Health & Collective Intelligence
Methods of applicationExpress Health Consensus
The management and the understanding of people in a team depends in great part on how well one knows weakness and strong points of each other.
Health & Collective Intelligence
Stable users of a real time data system provided by people.
Territorial distribution of users.
Users introducing new questions with certain periodicity.
Frequently updated measures, opinions or perceptions about any relevant aspect.
Real time consensus visualization
Methods of applicationContinuous Health Consensus
Health & Collective Intelligence
Methods of application Continuous Health Consensus
Health & Collective Intelligence
“Guesscore”
This graphic shows how good or bad is the assessment I do of he projects reviewed in the class in relation to the scores of expert and average of group
Practice number 1 2 3 4 5 6(Me - Expert) 1,1 1,2 0,6 0,4 0,6 0,3 (My Group - Expert) 1,4 1,5 0,5 0,9 0,4 0,6(Big Group - Exert) 1,3 0,9 0,4 0,6 0,3 0,9
Methods of applicationContinuous Health Consensus
Health & Collective Intelligence
Conclusions
1. In the health area, professionals respond positively to the model of HC participation
2. The HC process is efficient and operational as shown by satisfaction levels and perception of involvement.
3. Professionals perceive that they provide value with their participation.
4. The results of participation are considered useful and relevant contributions.
Health & Collective Intelligence
Contributing to health system challenges:
• Improve the management of the system
• Validation of clinical practices
• Efficient use and meaning of information
• Integration of health services
• Efficiency of treatment
• Facilitate the adoption of innovation
• Doctor-patient relationship
Conclusions
Health & Collective Intelligence
Real Time Delphi
Participation
Collaboration
Decision making
Learning
Consensus
Health & Collective Intelligence
Thank you
Health & Collective [email protected]
Health & Collective Intelligence
Tino Martí, Josep Mª Monguet , Alex Trejo