23 setembre 2014 fundacio idiap jordi gol health consensus reduced

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Presentation of Health Consensus

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Health & Collective Intelligencejm.monguet@upc.edu

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 Intelligencejm.monguet@upc.edu

Health & Collective Intelligence

Tino Martí, Josep Mª Monguet , Alex Trejo

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