Visualizing Healthcare Data with Tableau (Toronto Central LHIN Presentation)


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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.

Published in: Design, Business, Technology

Visualizing Healthcare Data with Tableau (Toronto Central LHIN Presentation)

  1. 1. Visualizing Healthcare Data with TableauStefan Popowycz, BSc, BAH, MASenior Information DesignerSenior Business Systems AnalystCanadian Institute for Health InformationApril 16 2012 at Toronto Central LHIN
  2. 2. Presentation Overview• Who I am, what I do, what CIHIdoes, and why our work isimportant.• Explain the CHRP solution, thedata, the challenges we faced,and detailed examples.• Why we used Tableau Desktopand Public Premium.• Information design principles.• Things to remember, authors toread, questions.
  3. 3. Data Visualization Teaser3 I created:Visualization I did not create:
  4. 4. Who am I• Stefan Popowycz, BSc, BAH, MA• Trained as a Medical Sociologist,Statistician, Researcher• Senior Information Designer / SeniorBusiness Systems Analyst• Lead Design and Information Architectfor the Canadian Hospital ReportingProject 2012 Custom Public Reports.• Information Access & Delivery Team,Canadian Institute for HealthInformation
  5. 5. CIHI• The Canadian Institute for Health Information(CIHI) is an independent, not-for-profitcorporation that aims to contribute to theimprovement of the health of Canadians andthe health care system by disseminatingquality health information.• Additionally, CIHIs data and reports areprovided to help inform health policies,support the effective delivery of healthservices and to raise awareness amongCanadians in general on current research andtrends in the healthcare industry thatcontribute to better health outcomes.
  6. 6. Why is our work important?• Healthcare is extremelyimportant for all Canadians.• Healthcare data is used to informdecision makers on progress,overall comparison, and mostimportantly best practice.• Traditionally, CIHI has had a clearobligation to analyze these data,and communicate the results toall Canadians (vision & mandate).
  7. 7. Why is our work important?• However, there is a clearshift in the way people areorganizing, sharing, andconsuming data.• Proper data visualizationsfacilitates thecomprehension of complexanalyses and patterns.• But, data visualizations donot need to be boring anduninviting.
  8. 8. Challenges• We needed to design asolution that was sexy, fast,inviting and easily accessibleto all Canadians.• Most importantly, thesolution needed to be publicfacing.
  9. 9. Challenges• Added bonus, if it was functionalon a mobile platform with socialmedia capabilities.• Aside from great visualizations,there was a critical requirementthat detailed contextual metadata(tooltips) be available for endusers.
  10. 10. Tool Agnostic• I consider myself to betool agnostic, adheringthe principles ofinformation design.• I want to be able to tellthe datas completestory, and not belimited by the toolbeing used to analyze ordisplay metrics.
  11. 11. Why Tableau?• Tableau was the only tool that allowedus to quickly create and publish datavisualizations with many best practicefeatures already inherent within thesoftware.• Strong belief in better communicationthrough visualization• Never done before: cloud computingand aggregated health care metrics.
  12. 12. Behind the Scenes• Needed to convincesenior managementthat this was the rightthing to do.• Levels of approval:Privacy and legal, SMG,IT OperationalCommittee, VPs.• Needed to create proofof concept projects.
  13. 13. Behind the Scenes• Extremely beneficialthat I was able torapidly create aninteractive prototype toshare.• Pretty, fast, and mobileready (iPad POC).
  14. 14. Why Tableau Public Premium?• The Tableau Public Premiumenvironment has the capacity tosustain tens of thousands ofsimultaneous hits.• Proved invaluable as 10Kimpressions within 24 hours, 40Kwithin 4 months.• The 99% SLA was an importantselling feature.
  15. 15. Why Tableau Public Premium?• Some might question, why noserver?• Purchasing Tableau Serverwas too cost prohibitive atthe time and Public Premiumproved to be a relativelyinexpensive solution forpublic reporting.• Easier to convince a VP of$10K vs $180k-$220K.• Stepping stone analysis.
  16. 16. Data• Created and analyticaldatamart (denormalizeddata).• ETL coded in SAS andexported to Excel.• We also had therequirement of notpermitting the end userto download theunderlying dataset.
  17. 17. Data• So why aggregate thedata? It guaranteedperformance within theTableau Public Premiumenvironment.• Unknown architecture,taking a risk.
  18. 18. What is CHRP?• The Canadian HospitalReporting Project (CHRP) is anational quality improvementinitiative providing hospitaldecision makers, policy makersand Canadians with access toclinical and financial indicatorresults for more than 600facilities, from every provinceand territory in Canada.
  19. 19. What is CHRP?• The public data visualizationsof the CHRP project weredesigned with the intent tovisually and interactivelycommunicate key messages toend users using a web-basedbusiness intelligence solution.• In essence, we wanted tocreate interactive infographics.• We create two (2) categories ofdata visualizations.
  20. 20. CHRP Key Findings• The first category of visualizationwe created we called “KeyFindings”. Nuggets of information.• Its summary level data, at 2-3different levels of analysis for aspecific indicator of interest, andrepresents an interactiveapproach to data presentation.• We created two (2) clinical andtwo (2) financial key findings, butalso French.
  21. 21. CHRP Key Findings• These follow information designbest practice with regards tocontent, colour, typography,interactivity, and design.• Things to note: 4 key findings intotal; 4 vizs in each dashboard;increasing hierarchy; all titles andheading done in Adobe Illustratorat 300 dpi; all embedding withinour web ECM.
  22. 22. CHRP Stand Alone Solution• The second category of datavisualizations created we called“Stand Alone Interactive Solution”.• These consist of more complexdata visualizations that combineseveral types of data within aninteractive real-estate.• Contains guided analysis, allowingthe end user to focus in oninformation of interest.
  23. 23. CHRP Stand Alone Solutions• Layered views of the same dataprovides better contextualunderstanding of the wholemessage being communicated.• Things to note: 2 completesolutions; 2 tabs, first tabs havearound 5 vizs, second tabaround 9; all headings and titlesdone in Adobe Illustrator; allembedded within our web ECM.
  24. 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 (publicreporting).• Tableau server can become expensive(you may require an administrator)• Some inherent functionality (auto sortbutton) may be confusing for end users• Using Digital, you are at the mercy ofTableau 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 sometimesneed to be coerced into place
  25. 25. CHRP Key Finding Links••
  26. 26. CHRP Stand Alone Links••
  27. 27. Information Design
  28. 28. Information Design• Information designrepresents the clean andeffective presentation ofinformation, and involves amulti-disciplinary approach tocommunication. Jen & Ken O’Grady• Combines graphic design,communications theory,technical and non-technicalpractices, cultural studies andpsychology.
  29. 29. Data Visualization• Data visualization is a visualrepresentation of data that hasa main goal to communicatequantitative informationclearly and effectively throughgraphical means.• Objects/components/artefactsgenerated during theInformation Design process.• More analytical in nature, andcan be static, animated, orinteractive.
  30. 30. Infographics• Infographics are graphic visualrepresentations of information,data or knowledge, and presentcomplex information quicklyand clearly, such as in signs,maps, journalism, technicalwriting, and education.• Static and less analytic innature. Also an artefact of theinformation design process.• Currently very popular withmedia and are published almoston a weekly basis.
  31. 31. Information Design Components
  32. 32. Content, Function, Form• The essential elements forinformation design arecontent, function and form.• A delicate balance needs tobe maintained between allthree in order to achieve aneffective data visualization.
  33. 33. Form Follows Function• Content: the information that youwant to communicate• Function: the intended actionsassociated with the object you aredesigning.• Form: the size, shape, dimension andother distinct parameters of theobject you are designing.
  34. 34. Negotiation• Preconceived notions of whattype of data visualizations areappropriate hinder the overallinformation design process.• Developers need to participatein gentle negotiation betweenthe business and all threeelements.• Ex: academic vs.. graphic art(boxplots vs. data variability).
  35. 35. Five Design Components• Key messages (critical analysis)• Types of underlying data• Typography (fonts)• Colour selection• Design and layout
  36. 36. Key Messages
  37. 37. Key Messages• It is important to clearly define3-5 key messages that youwant to communicate?• This requires that you distillthe various components ofyour critical analysis intonuggets of information.• What are they key metrics?
  38. 38. Key Messages• Important to be explicit whendefining your key messages, andtry to contextualize them as muchas possible.• Maybe arrange themhierarchically, as it will allow youto get a better understanding ofthe overall message you want tocommunicate.
  39. 39. Types of Data
  40. 40. Types of Data• Important to assess the types ofdata available for development.• Compare data to the key messagesin order to assess if all necessaryfields are available or if additionaldata collection is necessary.• Why? The data visualizationtechniques for one data type maynot be appropriate for another typeof data.
  41. 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, boxplots, categorical)• Correlation analysis (scatter plot)• Multivariate analysis (heat, multiple line)• Each type has an appropriate graphictechnique associate with it.
  42. 42. Types of DataSome best practices:• Select the appropriate chart typeand units of measurement.• Include a reference line (ifpossible).• Optimize the aspect ratio of thegraph (zero line).• Maintain consistency throughoutthe graph: fonts, colours, design.• Avoid 3D graphs.
  43. 43. Typography
  44. 44. Typography• Font selection is extremelyimportant when thinking aboutinformation design andcommunication.• Rule of thumb, keep it simpleand ensure the legibility of yourdesign.• Aesthetics vs. communicability.
  45. 45. Typography• Compromise between visualimpact and the richness of data.• Try not to use all caps, stylizedfonts, or angled fonts. Differenttypes of fonts can be mixed, butbe careful.• Adjust the size, weight, colour ofthe font for additional impact.• Integrating Corporate standardsand design.• Donna Wong
  46. 46. Colour
  47. 47. Colour• Selecting a colour scheme isalso very important whendesigning data visualizations.• Allows the designer to set thetone of the data visualization.• Colours used as categoricalhighlight (performanceallocation)• Corporate colours?
  48. 48. Colour• Try to keep the representationconsistent across your datavisualizations.• Altering the hues andintensity are a good way todraw distinctions and makecomparisons.• Do not use distracting colours.• Print everything in black andwhite.
  49. 49. Design and Layout
  50. 50. Design and Layout• Selecting the proper design andlayout for your datavisualization is also veryimportant.• Adhering to simplicity andbeing aware of narrative flow,will greatly aid incommunicating.• The information should flowwith ease for the consumer.
  51. 51. Design and Layout• Designing the data visualizationenvironment requires some keyfeatures: comparing, sorting,filtering, highlighting,aggregating, re-expressions, re-visualization, zooming andpanning, re-scaling, access todetails on demand, annotationand bookmarking
  52. 52. Design and Layout• Trellises and cross tabs:provides more contextualview of the data you wouldlike to present.• Web and social mediaintegration.• Designed with printing inmind.
  53. 53. Things to Remember• Look at your data: whatstory do you want to tell?• Who is your audience.• How will people consumethis information?• Remember that a chart isalways more memorablethan a table.• Keep it simple. Less is more.• Design, dont decorate.
  54. 54. Authors to Read• David McCandless• Manuel Lima• Stephen Few• Jen and Ken OGrady• Donna Wong• Edward Tufte• Nathan Yaw• Jason Lankow, JoshRitchie and Ross Crooks
  55. 55. Websites to See••••••••
  56. 56. Questions
  57. 57. Thanks!• Stefan Popowycz• Email:• Website:• Information Design Pinterest:•