Direction de santé publique
EMIS
Supporting Information-based
Decision-making in Montréal’s
Healthcare System
Carl Drouin
Direction de santé publique
Agence de la santé et des
services sociaux de Montréal
Community Data Canada Roundtable
March 9, 2011, Toronto
Presentation outline
 Context in which EMIS was created
 Key principles guiding our strategy in
public health data dissemination
 Demo of EMIS Website
Content and structure
Tools
 Concluding remarks
Organizational context
of EMIS
Data-related responsibilities
Ministry of health and
social services
18 regional ‘’agencies’’
Public health division
Local networks
12 local Health and Social Services
Centres (CSSS) in Montreal

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Medical service providers
Municipalities and boroughs
Community organizations
Schools and school boards
Etc.
 Manage and provide information on
the
health
(services
INFO
ONcare
THEsystem
HEALTH
SYSTEM
delivered, resources, performance,
etc.)
+
 Track the health status of Montrealers
INFO ON PEOPLE’S HEALTH
(surveillance)
 Inform the population and decision
= and its
makers about health
determinants
SUPPORT PLANNING IN HEALTH
Plan and provide services
according to population health
needs
Advantages of EMIS
 Organizational perspective





A single platform using same tools and technologies
More integration in data collection
Uniformity in data treatment
Less duplication in production and dissemination processes
Development and maintenance supported by a larger group with
complementary skills (IT, GIS, analytical expertise related to Service
programs and PH data)
 User’s perspective
 A single reference on health data in Montreal (with same structure,
interactive Web-based tools and analytical publications)
 Same data can be used for different purposes
 Participate in Website development and validation of further
improvements
 Provide settings to enhance data-driven decision-making
Key principles


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Go local when possible
Diversify products
Standardize analytical products and tools
Develop products and Website with
partners and data users
 Integrate within a larger Web strategy
(design, technology)
Provide local data
 Census geography (CTs and DAs)
 Health administrative units
 CSSS, CLSS, voisinages
 By health institutions (e.g. hospitals)
 Sometimes adapted to other geographies
(school boards)
 More and more of our PH publications are
done in series of 12 (CSSS)
 Working on a local survey program
111 neighbourhoods
Different products for
diversified users
Key
health
issues
Health profiles
(population /
space-based)
• Selection of key variables
for major themes
• Comparisons to others
• Trends
Microdata level
More meaningful
information
•= more efforts
•= more users?
•= used for
• decision- making?
Interactive tools
Standardized analytical
products
Chiffres-clés (Key numbers)
Place-based (neighbourhoods)
characteristics - Montreal
Partnerships
Partners
Local health centres
(through Data Users’ Committee and
working groups)
Information providers within
the organization
(mainly PH subdivisions)
Roles
Express needs, validate proposals;
test applications; promote use of data
Provide surveillance data within their
field of expertise; use available
technologies and products
Communications department Web strategy; support information
process; advise on best practices
Computer department
Advise on technological orientations;
support development
Agency’s Website
redevelopment
Agency’s
corporate
Website
Regional portal
Zone for
physicians
Other
health
data
Websites
EMIS
Local Websites
Zone for
professionals
Public health
director’s
Website
DEMO
Concluding remarks
Challenges to be met
 Allow the time required to increase the value of the data
 Keep a large amount of data and information up-to-date
 Continuous feeding of those involved in surveillance
 Support data utilization among local and community
partners
 Work on structural (e.g. menus) and technological (e.g.
indicators module instead of Excel and PDF files)
improvements
Key message
 Such type of Website requires to be part of a larger
information system (i.e. data – qualified HR – tools –
standardized processes)
Ideas for discussion
 How can data really provide bases
for reduction in social health
inequalities?