Visualizing Data to Inform Decision Making, Strengthen Advocacy, and Assess PerformanceMason ForandoData Informatics, HANYS

Photo Credit: http://medcitynews.com/wp‐content/uploads/lightbulb‐idea.jpg

HANYS 2016 Healthcare Communications ConferenceAlbany, NYNov. 2, 2016

AgendaData Visualization Advantages

Data Visualization Disadvantages

Consumer Data Visualization

Media Data Visualization

HANYS’ Use of Data Visualization

Building Data Visualization Capabilities

Computer Programming

ArtMath

Source: http://www.ted.com/talks/david_mccandless_the_beauty_of_data_visualization?language=en

Sight

Touch

Hearing/Smell

Taste

1250 MB/second*

Same bandwidth as a computer network

125 MB/second*

USB Drive*Figures published in 2010

12.5 MB/second*

Hard Drive

Similarity

Continuation

Closure

Proximity Figure & Ground

Response Time

Message Retainment

Pattern Recognition

Information Context

Simplify the Message

Show the Big Picture

Consumer Engagement

Data Visualization Advantages

Response TimeRapidly communicate the structure of data set:

Relationship between data pointsComparison Groups and Benchmarks Distribution and OutliersPatterns and Trends

Enhanced through visual cues and text:ColorSize ShapeAnnotations

Data to Pixel (Ink) Ratio:Spreadsheet/Table vs. Data VisualizationText vs. Data Visualization

Tabular Reporting

Useful for quick mash-ups of data

Requires more time for interpretation/understanding

Tough to discover new questions & patterns

Impact of DSH Policy Alternatives by StateACA Formula Change Shift from Proxy to S‐10 Shift from Proxy to S‐10

(Incl. Medicaid Losses & GME Costs)

*Table shows change in Medicare DSH payments as a percent of total Medicare Inpatient payments

This data visualization shows: Consistency of ACA’s reduction across statesRedistributive Effect of PolicyEffect of Potential Policy to Include Medicaid Losses and GMENeed to retain the proxy until S-10 is ready and transition over time

Message Retainment: Texas DSH Policy ImpactACA Formula Change Shift from Proxy to S‐10 Shift from Proxy to S‐10

(Incl. Medicaid Losses & GME Costs)

*Table shows change in Medicare DSH payments as a percent of total Medicare Inpatient payments

This data visualization shows: Consistency of ACA’s reduction across statesRedistributive Effect of PolicyEffect of Potential Policy to Include Medicaid Losses and GMENeed to retain the proxy until S-10 is ready and transition over time

Information Context

Put data points in perspective against:Regional, Statewide, or National BenchmarksSimilar HospitalsPrevious Time Periods National BenchmarksCritical Values

CMS’ Hospital Star Preview Reports:Includes summary score and star ratingLacked Statewide comparisonNo information on Star Rating cutoff pointsStatistical Significance from other Star Ratings

Pattern Recognition

Source: http://blog.plot.ly/post/68951620673/why-graph-anscombes-quartet

Four different data sets

Same Mean, Variance, and Correlation

Summary statistics do not tell the complete story

Data Set I Data Set II

Data Set III Data Set IV

Anscombes Quartet

Pattern Recognition

Upstate Distressed Downstate Distressed

Financial Strength

Index

Days Cash On Hand

SurgeryPercent

CommercialPercent

MedicaidPercent

Lower %

OccupancyRate

HospitalSize

Good

BadHigher %

Largest Hospitals

Smallest Hospitals

Pattern Recognition

Financial Strength

Index

Days Cash On Hand

SurgeryPercent

CommercialPercent

MedicaidPercent

OccupancyRate Size

Financial Strength

Index

Days Cash On Hand

SurgeryPercent

CommercialPercent

MedicaidPercent

OccupancyRate

Size

Upstate Distressed Downstate Distressed

Lower Occupancy Rate

Small & Mid-Sized Hospitals

Less Than Average Surgery %

Unfavorable Payor Mix

Higher Occupancy Rate

Includes Larger Hospitals

Simplify the Message

The CMS’ Star Ratings Oversimplify 64 Quality

Measures and 7 Domains of Performance into a

single metric.

Show the Big Picture

Flow of funds by goal reported in Percentages (of Provider Category Spend)

Difficult to compare project investment between Provider Categories

Show the Big PictureSi

ze o

f Inv

estm

ent

DSRIP Takeaways:R

• Goals are separated into Domains/Subdomains

• Investment varies between Goals and Provider Category

• Funding strategy varies significantly between PPS’s

• Data visualization can provide context and communicate the larger picture

Consumer Engagement

Too much information, Not enough time

Limited Attention Span

Grab attention with visual

Guided LearningConsumer ExpectationsProvide Information Rapidly

http://hsnewsbeat.uw.edu/sites/default/files/sites/default/files/documents/Health%20Affairs%20infographics%20article.pdf

Data Visualization Disadvantages

Data Precision

Misinterpretation

Encoding Errors

Limitations on Media

Expensive/Time-Consuming to Develop1 1,800,000             

2 2,100,000             3 1,900,000             4 1,800,000             5 1,900,000             

1 1,800,000           2 2,100,000           3 1,900,000           4 1,800,000           5 1,900,000           

Consumer Data Visualization

Data Visualization in the Media

New York Timeshttps://flowingdata.com/tag/new-york-times/

Mike Bostockhttps://bost.ocks.org/mike/D3 (Data Driven Documents)https://d3js.org/

Census.gov

Albany Tableau Users Group (ANYTUG)

Arcadia Solutionshttp://datagallery.arcadiasolutions.com/index.html

Kaiser Health

Kaiser Health (Hospital Stars)

Kaiser Health (cont.)

Kaiser Health (cont.)

HANYS Use of Data Visualization

New Meeting Format

Internal Databook created to make key datasets consumable

Databook Mission:Self-ServiceConsumableCollaborativeAligned with HANYS Agenda

HANYS Use of Data Visualization

Data Visualization For Advocacy:Disproportionate Share Payment AdvocacyVulnerable HospitalsHospital StarsStaffing RatiosManaged Care

Member Facing Analytics:Hospital starsPotential Future Analyses:

- Hospital Financial Analysis- Managed Care Plan Analysis- DSRIP Reporting- TBD

Data Visualization Tools/Software

Visualization Flexibility

Time & Cost Involved

Choose data visualization software based on current expertise, cost considerations, and desired flexibility in reporting

Excel 2016/Power ViewCost-Effective

Minimal Training/Support Required

Mapping Capabilities

Excel Web Apps

New Visualizations (Excel 2016/add-ins)

http://www.vertex42.com/blog/help/excel‐help/6‐new‐awesome‐chart‐types‐in‐excel‐2016.html

Plot.lyMore Cost-Effective than Tableau Desktop/Server ($0-$33/Month)Cloud Based similar to Tableau Public/ServerIntegrated with R/D3/PythonEmbeddable on WebsitesMore Flexibility than ExcelData Security Concerns

Can be expensive depending on distribution modelTableau Reader (Free)Tableau DesktopTableau Server

Create modern visualization within weeks of training

Tableau Support Communityhttps://community.tableau.com/welcome

Default Visualizations look good without much work

Can be publicly posted on Tableau PublicPHI Considerations

Competitors:QlikviewSpotfireDomoPlot.ly

Tableau Reader/Desktop

JavaScript based Programming Language

Developed by Mike Bostock (former New York Times employee)

Highly flexible for visualizing data

Requires sophisticated developers & lengthy development time

Embeddable on Webpages

Client side data limitationhttps://d3js.org/

http://datagallery.arcadiasolutions.com/

Growing Your Data Visualization Capabilities

Leverage New Technology/Tools Excel 2016/Powerview ~ Tableau-LiteTableau: VizQL ~ SQLRaw.DensityDesign ~ D3Qlikview, Spotfire, Plot.ly, Domo

Always visualize your data

Build data visualization vocabularyParallel CoordinatesSunburst DiagramBubble ChartPareto ChartTreemap/TilechartSankey Diagram

Learn from othershttp://www.informationisbeautiful.net/http://www.datablick.com/http://datagallery.arcadiasolutions.com/index.htmlhttps://www.dataplusscience.com/https://github.com/d3/d3/wiki/Gallery

http://www.datavizcatalogue.com/

Questions