This is the presentation I gave to the Toronto Central LHIN about using Tableau to visualizing healthcare metrics (April 16 2013). I also have a section on how Information Design best practices can be leveraged in order to effectively communicate your key messages to your end users.

1. Visualizing Healthcare Data with Tableau
Stefan Popowycz, BSc, BAH, MA
Senior Information Designer
Senior Business Systems Analyst
Canadian Institute for Health Information
April 16 2012 at Toronto Central LHIN

2. Presentation Overview
• Who I am, what I do, what CIHI
does, and why our work is
important.
• Explain the CHRP solution, the
data, the challenges we faced,
and detailed examples.
• Why we used Tableau Desktop
and Public Premium.
• Information design principles.
• Things to remember, authors to
read, questions.

3. Data Visualization Teaser
3
http://pinterest.com/stefanpopowycz/information-design/
Visualizations I created:
Visualization I did not create:

4. Who am I
• Stefan Popowycz, BSc, BAH, MA
• Trained as a Medical Sociologist,
Statistician, Researcher
• Senior Information Designer / Senior
Business Systems Analyst
• Lead Design and Information Architect
for the Canadian Hospital Reporting
Project 2012 Custom Public Reports.
• Information Access & Delivery Team,
Canadian Institute for Health
Information

5. CIHI
• The Canadian Institute for Health Information
(CIHI) is an independent, not-for-profit
corporation that aims to contribute to the
improvement of the health of Canadians and
the health care system by disseminating
quality health information.
• Additionally, CIHI's data and reports are
provided to help inform health policies,
support the effective delivery of health
services and to raise awareness among
Canadians in general on current research and
trends in the healthcare industry that
contribute to better health outcomes.

6. Why is our work important?
• Healthcare is extremely
important for all Canadians.
• Healthcare data is used to inform
decision makers on progress,
overall comparison, and most
importantly best practice.
• Traditionally, CIHI has had a clear
obligation to analyze these data,
and communicate the results to
all Canadians (vision & mandate).

7. Why is our work important?
• However, there is a clear
shift in the way people are
organizing, sharing, and
consuming data.
• Proper data visualizations
facilitates the
comprehension of complex
analyses and patterns.
• But, data visualizations do
not need to be boring and
uninviting.

8. Challenges
• We needed to design a
solution that was sexy, fast,
inviting and easily accessible
to all Canadians.
• Most importantly, the
solution needed to be public
facing.

9. Challenges
• Added bonus, if it was functional
on a mobile platform with social
media capabilities.
• Aside from great visualizations,
there was a critical requirement
that detailed contextual metadata
(tooltips) be available for end
users.

10. Tool Agnostic
• I consider myself to be
tool agnostic, adhering
the principles of
information design.
• I want to be able to tell
the data's complete
story, and not be
limited by the tool
being used to analyze or
display metrics.

11. Why Tableau?
• Tableau was the only tool that allowed
us to quickly create and publish data
visualizations with many best practice
features already inherent within the
software.
• Strong belief in better communication
through visualization
• Never done before: cloud computing
and aggregated health care metrics.

12. Behind the Scenes
• Needed to convince
senior management
that this was the right
thing to do.
• Levels of approval:
Privacy and legal, SMG,
IT Operational
Committee, VPs.
• Needed to create proof
of concept projects.

13. Behind the Scenes
• Extremely beneficial
that I was able to
rapidly create an
interactive prototype to
share.
• Pretty, fast, and mobile
ready (iPad POC).

14. Why Tableau Public Premium?
• The Tableau Public Premium
environment has the capacity to
sustain tens of thousands of
simultaneous hits.
• Proved invaluable as 10K
impressions within 24 hours, 40K
within 4 months.
• The 99% SLA was an important
selling feature.

15. Why Tableau Public Premium?
• Some might question, why no
server?
• Purchasing Tableau Server
was too cost prohibitive at
the time and Public Premium
proved to be a relatively
inexpensive solution for
public reporting.
• Easier to convince a VP of
$10K vs $180k-$220K.
• Stepping stone analysis.

16. Data
• Created and analytical
datamart (denormalized
data).
• ETL coded in SAS and
exported to Excel.
• We also had the
requirement of not
permitting the end user
to download the
underlying dataset.

17. Data
• So why aggregate the
data? It guaranteed
performance within the
Tableau Public Premium
environment.
• Unknown architecture,
taking a risk.

18. What is CHRP?
• The Canadian Hospital
Reporting Project (CHRP) 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.

19. What is CHRP?
• 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.
• In essence, we wanted to
create interactive infographics.
• We create two (2) categories of
data visualizations.

20. CHRP Key Findings
• The first category of visualization
we created we called “Key
Findings”. Nuggets of information.
• It's summary level data, at 2-3
different levels of analysis for a
specific indicator of interest, and
represents an interactive
approach to data presentation.
• We created two (2) clinical and
two (2) financial key findings, but
also French.

21. CHRP Key Findings
• These follow information design
best practice with regards to
content, colour, typography,
interactivity, and design.
• Things to note: 4 key findings in
total; 4 vizs in each dashboard;
increasing hierarchy; all titles and
heading done in Adobe Illustrator
at 300 dpi; all embedding within
our web ECM.

22. CHRP Stand Alone Solution
• The second category of data
visualizations created we called
“Stand Alone Interactive Solution”.
• These consist of more complex
data visualizations that combine
several types of data within an
interactive real-estate.
• Contains guided analysis, allowing
the end user to focus in on
information of interest.

23. CHRP Stand Alone Solutions
• Layered views of the same data
provides better contextual
understanding of the whole
message being communicated.
• Things to note: 2 complete
solutions; 2 tabs, first tabs have
around 5 vizs, second tab
around 9; all headings and titles
done in Adobe Illustrator; all
embedded within our web ECM.

24. Advantages Disadvantages
• Easy to use (Interface, Importing Data)
• Inherent best practice (Colour, Graphs)
• Easy to publish online (Public)
• Tableau Digital (99% SLA)
• Analytical Engine (Tableau Server)
• Allows you tweak the data
• Visualizations are pretty
• Pixel perfect PDFs
• JavaScript embed function (Ipad)
• Social Media (Twitter and Facebook)
• Can use denormalized, 3NF structures
• Wide variety for input formats
• Wide range of graphing formats
• JS API complicated
• Some functionality is not perfect (public
reporting).
• Tableau server can become expensive
(you may require an administrator)
• Some inherent functionality (auto sort
button) may be confusing for end users
• Using Digital, you are at the mercy of
Tableau regarding uptime. Server?
• Sometimes the data exports generated
(crosstabs) are confusing for end users
• SAS file type is not an import option
• Layout boxes are finicky, and sometimes
need to be coerced into place

25. CHRP Key Finding Links
• http://public.tableausoftware.
com/shared/6W78QWZHY
• http://www.cihi.ca/cihi-ext-
portal/internet/en/document/
health+system+performance/i
ndicators/performance/chrp_i
report_findings_b

26. CHRP Stand Alone Links
• http://public.tableausoftware
.com/shared/KWB7FMHPS
• http://www.cihi.ca/cihi-ext-
portal/internet/en/document
/health+system+performance
/indicators/performance/chrp
_ireport_financial

27. Information Design

28. Information Design
• Information design
represents the clean and
effective presentation of
information, and involves a
multi-disciplinary approach to
communication. Jen & Ken O’Grady
• Combines graphic design,
communications theory,
technical and non-technical
practices, cultural studies and
psychology.

29. 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.

30. 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.

31. Information Design Components

32. Content, Function, Form
• The essential elements for
information design are
content, function and form.
• A delicate balance needs to
be maintained between all
three in order to achieve an
effective data visualization.

33. Form Follows Function
• 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.

34. 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).

35. Five Design Components
• Key messages (critical analysis)
• Types of underlying data
• Typography (fonts)
• Colour selection
• Design and layout

36. Key Messages

37. 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?

38. Key Messages
• Important to be explicit when
defining your key messages, and
try to contextualize them as much
as possible.
• Maybe arrange them
hierarchically, as it will allow you
to get a better understanding of
the overall message you want to
communicate.

39. Types of Data

40. 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.

41. Types of Data
• Time series analysis (trends, variability,
rate of change)
• Part to whole and ranking analysis (bar,
pie, Pareto)
• Deviation analysis (categorical,
comparative, thresholds)
• 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.

42. Types of Data
Some best practices:
• 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.

43. Typography

44. 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.

45. Typography
• 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.
• Donna Wong

46. Colour

47. 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?

48. Colour
• 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.

49. Design and Layout

50. Design and Layout
• 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.

51. Design and Layout
• 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

52. Design and Layout
• 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.

53. Things to Remember
• Look at your data: what
story do you want to tell?
• Who is your audience.
• How will people consume
this information?
• Remember that a chart is
always more memorable
than a table.
• Keep it simple. Less is more.
• Design, don't decorate.

54. Authors to Read
• David McCandless
• Manuel Lima
• Stephen Few
• Jen and Ken O'Grady
• Donna Wong
• Edward Tufte
• Nathan Yaw
• Jason Lankow, Josh
Ritchie and Ross Crooks

55. Websites to See
• good.is
• visual.ly
• visualnews.com
• columnfivemedia.com
• thedailyviz.com
• datavisualization.ch
• pinterest.com
• printmag.com

56. Questions

57. Thanks!
• Stefan Popowycz
• Email: spopowycz@cihi.ca
• Website: www.cihi.ca
• Information Design Pinterest:
http://pinterest.com/stefanpopowycz/inf
ormation-design/
• LinkedIn:
ca.linkedin.com/in/stefanpopowycz