This is my eHealth 2012 presentation will focuse on the principles behind information design and how visualization best practices can be leveraged within context of healthcare data. It illustrates theory in action, by drawing specific attention to the successful public facing solution, the 2012 Canadian Hospital Reporting Project (CHRP). The CHRP tool is a pan-Canadian external facing solution with an audience of over 3000+ users; it received over 25,000 impressions in the first 24 hours, and was called by the Toronto Star as “an innovative online tool that is being heralded as the most advanced of its kind in the world.”

1. http://audreelapierre.com/portfolio/wp-content/uploads/2010/12/DataVisualizationDiagram.jpg
Stefan Popowycz
Visualizing Healthcare Data eHealth 2012 Conference
May 28 2012 (Room 18)
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2. Updated Overview
This presentation will focus on the theory and best practices behind information
design. Using tangible examples of production data visualizations published by
CIHI, namely the CHRP 2012 Custom Public Solution, I will demonstrate how
these principles can be best leveraged within context of visualizing healthcare
data. This presentation is to viewed starting point.
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3. Data Visualizations
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4. Me
• Stefan Popowycz, B.Sc., B.A.Hons., M.A
• Trained as a Medical Sociologist,
Statistician, Researcher
• Senior Business Systems Architect
• Lead Design and Information Architect
for the Canadian Hospital Reporting
Project 2012 Custom Public Reports.
• eReporting & Enterprise Data
Warehousing Service Team, CIHI
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5. Presentation Overview
• First, I will define Information Design and
describe the three elements behind this
approach.
• Second, I will briefly explain the CHRP
solution and provide an overview of the suite
of public interactive data visualizations that
were created.
• Lastly, I will outline the five main
components of Information Design, the
respective best practices associated with
each of these categories, and how these
were implemented in the CHRP solution.
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6. Information Design "6

7. Information Design (J&K O'Grady)
• Information
design represents
the clean and
effective
presentation of
information, and
involves a multi-
disciplinary
approach to
communication.
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8. Information Design
• Its goal is to communicate
a specific message to an
end user in a way that is
clear, accessible and easy
to understand.
• Combines graphic design,
communications theory,
technical and non-
technical practices, cultural
studies and psychology.
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9. Data Visualization
• Data visualization is a visual
representation of data that has a
main goal to communicate
quantitative information clearly and
effectively through graphical means.
• Objects/components/artefacts
generated during the Information
Design process.
• More analytical in nature, and can
be static, animated, or interactive.
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10. Infographics
• Infographics are graphic visual
representations of information, data or
knowledge, and present complex
information quickly and clearly, such as in
signs, maps, journalism, technical writing,
and education.
• Static and less analytic in nature. Also an
artefact of the information design process.
• Currently very popular with media and are
published almost on a weekly basis.
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11. Why?
• Healthcare data is both pervasive
and extremely important to all
Canadians.
• Traditionally, CIHI has had a clear
obligation to analyze these data,
publish and communicate the
results to all Canadians (Vision and
Mandate).
• Clear shift in the way people are
organizing, sharing, and
consuming data.
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12. Why?
• Intrinsically, healthcare data is
important as it is used to inform
decision makers on progress,
overall comparison, and most
importantly best practice.
• Proper data visualizations
facilitate the comprehension of
complex analysis and patterns.
• But, data visualizations do not
need to be boring and uninviting.
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13. Why?
• Although this represents CIHI's
first attempt at interactive data
visualizations and it is far from
perfect, but it represent a positive
step in the right direction.
• Strong belief in better
communication through
visualization.
• In the end, data wins!
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14. CHRP 2012 Data Visualizations "14

15. CHRP 2012 Public
• The Canadian Hospital Reporting Project is a
national quality improvement initiative providing
hospital decision makers, policy makers and
Canadians with access to clinical and financial
indicator results for more than 600 facilities,
from every province and territory in Canada.
• The Public Data Visualizations of the CHRP
project were designed with the intent to visually
and interactively communicate key messages
to end users using a web-based business
intelligence solution.
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16. CHRP Key Findings "16

17. CHRP Key Findings
• The first type of data visualization
created for the CHRP we called a
Key Finding. These are intended
to be quick fact sheets that print
neatly on a legal sized document.
• It's summary level data, at 2-3
different levels of analysis for a
specific indicator of interest, and
represent an interactive approach
to data presentation.
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18. CHRP Standalone Solutions "18

19. CHRP Standalone Solution
• The second category of data
visualizations created are what I
like to term standalone
interactive solutions.
• These consist of more complex
data visualizations that combine
several types of data within an
interactive real-estate frame.
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20. CHRP Standalone Solution
• Contains guided analysis,
allowing the end user to focus
in on information of interest.
• Layered views of the same data
provides better contextual
understanding of the whole
message being communicated.
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21. Information Design Components "21

22. Three Essential Elements
• There are three essential
elements for information
design: the classic
relationship between
content, function and form.
• A delicate balance needs
to be maintained between
all three in order to achieve
an effective data
visualization.
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23. Three Essential Elements
• Content: the information that
you want to communicate
• Function: the intended actions
associated with the object you
are designing.
• Form: the size, shape,
dimension and other distinct
parameters of the object you
are designing.
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24. Negotiation
• Preconceived notions of what
type of data visualizations are
appropriate hinder the overall
information design process.
• Developers need to participate
in gentle negotiation between
the business and all three
elements.
• Ex: academic vs graphic art
(boxplots vs data variability).
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25. Five Design Components
• Key messages (critical analysis)
• Types of underlying data
• Typography (fonts)
• Colour selection
• Design and layout
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26. Key Messages "26

27. Key Messages
• It is important to clearly define
3-5 key messages that you
want to communicate?
• This requires that you distill
the various components of
your critical analysis into
nuggets of information.
• What are they key metrics?
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28. Key Messages Best Practice
• Important to be explicit when
defining your key messages, and
try to contextualize them as
much as possible.
• Arrange them hierarchically, as it
will allow you to get a better
understanding of the overall
message you want to
communicate.
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29. CHRP Key Findings
Best Practice in Action
• 30-Day Readmission example.
• Three key messages clearly
defined and levels arranged
hierarchically in all Key Findings.
• Graphs are clean and crisp.
• Colour palette is muted and
maintained throughout all the key
findings.
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30. Types of Data "30

31. Types of Data
• Important to assess the types of
data available for development.
• Compare data to the key messages
in order to assess if all necessary
fields are available or if additional
data collection is necessary.
• Why? The data visualization
techniques for one data type may
not be appropriate for another type
of data.
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32. Types of Data (Stephen Few)
• Time series analysis (trends,
variability, rate of change)
• Part to whole and ranking
analysis (bar, pie, Pareto)
• Deviation analysis (categorical,
comparative, thresholds)
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33. Types of Data (Stephen Few)
• Distribution analysis (histogram,
box plots, categorical)
• Correlation analysis (scatter plot)
• Multivariate analysis (heat,
multiple line)
• Each type has an appropriate
graphic technique associate
with it.
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34. Data Type Best Practice
• Select the appropriate chart type
and units of measurement.
• Include a reference line (if possible).
• Optimize the aspect ratio of the
graph (zero line).
• Maintain consistency throughout the
graph: fonts, colours, design.
• Avoid 3D graphs.
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35. CHRP Key Findings
Best Practices in Action
• Cost per Weighted Case example.
• Mix of traditional and aesthetic
visualizations (negotiation between
traditional content and current
design standards).
• Scatter plot (correlation), bar graph
over multiple fiscals (time series
and part to whole), categorical
analysis (deviation).
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36. CHRP Key Findings
Best Practices in Action
• 30-Day Mortality example.
• Reference line used to indicate
thresholds. Error bars indicate
confidence intervals.
• Pervasive meta data provides
contextual information
• Narrative flow is simple
(description, left, right, left flow)
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37. Typography "37

38. Typography
• Font selection is extremely
important when thinking about
information design and
communication.
• Rule of thumb, keep it simple
and ensure the legibility of your
design.
• Aesthetics vs communicability.
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39. Typography Best Practice
• Compromise between visual impact
and the richness of data.
• Try not to use all caps, stylized fonts,
or angled fonts. Different types of
fonts can be mixed, but be careful.
• Adjust the size, weight, colour of the
font for additional impact.
• Integrating Corporate standards and
design.
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40. CHRP Key Findings
Best Practices in Action
• Large chunky fonts used to draw
end users attention to top.
• Sans serif font employed
throughout (web and print).
• All titles are two points larger than
the text for impact.
• This pattern is maintained though
all data visualizations created for
the CHRP public.
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41. Colour "41

42. Colour
• Selecting a colour scheme is
also very important when
designing data visualizations.
• Allows the designer to set the
tone of the data visualization.
• Colours used as categorical
highlight (performance allocation)
• Corporate colours?
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43. Colour Best Practice
• Try to keep the representation
consistent across your data
visualizations.
• Altering the hues and intensity are
a good way to draw distinctions
and make comparisons.
• Do not use distracting colours.
• Print everything in black and white.
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44. CHRP Standalone Solution
Best Practice in Action
• Clean, crisp, and simple.
• Contrasting colours differentiate
between values that are above
national average and those that
are not.
• The colour scheme is carried
over into the interactive graph.
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45. CHRP Standalone Solution
Best Practice in Action
• In the performance allocation
example, the shape and colour
indicate these stability and
performance of the result.
• Both schemes carried over to
the scatterplot below.
• Similar pattern for key findings.
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46. Design and Layout "46

47. Analytical Design
• Selecting the proper design and
layout for your data visualization
is also very important.
• Adhering to simplicity and being
aware of narrative flow, will
greatly aid in communicating.
• The information should flow with
ease for the consumer.
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48. Analytical Design Best Practice
• Designing the data visualization
environment requires some key
features: comparing, sorting,
filtering, highlighting,
aggregating, re-expressions,
re-visualization, zooming and
panning, re-scaling, access to
details on demand, annotation
and bookmarking
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49. Analytical Design Best Practice
• Trellises and cross tabs:
provides more contextual view
of the data you would like to
present.
• Web and social media
integration.
• Designed with printing in mind.
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50. CHRP Standalone Solution
Best Practice in Action
• Trellises and cross tabs: provides
more contextual view of the data
you would like to present.
• Multiple concurrent views of the
data provides helps to provide
contextual understanding of your
key message.
• Facebook and Twitter functionality,
and JavaScript embedding.
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51. CHRP Standalone Solution
Best Practice in Action
• Entire key finding is interactive.
• Analytical techniques and
practices, such as directed vs
exploratory navigation,
hierarchical navigation
• Hover over meta data on every
data point.
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52. Lightweight BI Tools
• Gartner Magic Quadrant for
Business Intelligence Platforms
• Why are they so important? They
have a lot of the best practices
built into them, so it makes it
easier for the developer to create
effective data visualizations.
• Many have social media
functionality and web integration
build directly in.
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53. Things to Remember
• Look at you data: What story do
you want to tell? How will they
consume the info?
• Keep it simple. Less is more.
• Design, don't decorate.
• Remember that a chart is always
more memorable than a table.
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54. Authors to Read
• Stephen Few
• Jen and Ken O'Grady
• Donna Wong
• Edward Tufte
• Nathan Yaw
• Manuel Lima
• David McCandless
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55. Websites to See
• good.is
• visualnews.com
• thedailyviz.com
• datavisualization.ch
• pinterest.com
• printmag.com
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56. Questions?
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57. Thanks!
Stefan Popowycz
Email: spopowycz@cihi.ca
Website: www.cihi.ca
Pinterest: http://pinterest.com/
stefanpopowycz/information-design/
LinkedIn: http://ca.linkedin.com/pub/
stefan-popowycz/1a/141/649
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