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Interdisciplinary research community - Computer Science & Info Studies

Visualization of Electronic Health Records Ben Shneiderman ben@cs.umd.edu @ benbendc Founding Director (1983-2000), Human-Computer Interaction Lab Professor, Department of Computer Science Member, Institute for Advanced Computer Studies University of Maryland College Park, MD 20742.

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Interdisciplinary research community - Computer Science & Info Studies

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  1. Visualization ofElectronic Health RecordsBen Shneiderman ben@cs.umd.edu @benbendcFounding Director (1983-2000), Human-Computer Interaction LabProfessor, Department of Computer ScienceMember, Institute for Advanced Computer StudiesUniversity of MarylandCollege Park, MD 20742

  2. Visualization ofElectronic Health Records@benbendcUniversity of MarylandCollege Park, MD 20742

  3. Interdisciplinary research community - Computer Science & Info Studies - Psych, Socio, Poli Sci & MITH (www.cs.umd.edu/hcil)

  4. Design Issues Input devices & strategies Keyboards, pointingdevices,voice Direct manipulation Menus, forms, commands Output devices & formats Screens, windows, color, sound Text, tables, graphics Instructions, messages, help Collaboration &Social Media Help, tutorials, training Search www.awl.com/DTUI Fifth Edition: 2010 • Visualization

  5. HCI Pride: Serving 5B Users Mobile, desktop, web, cloud  Diverseusers: novice/expert, young/old, literate/illiterate, abled/disabled, cultural, ethnic & linguistic diversity, gender, personality, skills, motivation, ...  Diverse applications:E-commerce, law, health/wellness, education, creative arts, community relationships, politics, IT4ID, policy negotiation, mediation, peace studies, ...  Diverse interfaces: Ubiquitous, pervasive, embedded, tangible, invisible, multimodal, immersive/augmented/virtual, ambient, social, affective, empathic, persuasive, ...

  6. Information Visualization & Visual Analytics • Visual bands • Human percle • Trend, clus.. • Color, size,.. • Three challe • Meaningful vi • Interaction: w • Process mo 1999

  7. Information Visualization & Visual Analytics • Visual bandwidth is enormous • Human perceptual skills are remarkable • Trend, cluster, gap, outlier... • Color, size, shape, proximity... • Three challenges • Meaningful visual displays of massive da • Interaction: widgets & window coordinati • Process models for discovery 1999 2004

  8. Information Visualization & Visual Analytics • Visual bandwidth is enormous • Human perceptual skills are remarkable • Trend, cluster, gap, outlier... • Color, size, shape, proximity... • Three challenges • Meaningful visual displays of massive data • Interaction: widgets & window coordination • Process models for discovery 1999 2004 2010

  9. Treemap: Gene Ontology • Space filling • Space limited • Color coding • Size coding • - Requires learning (Shneiderman, ACM Trans. on Graphics, 1992 & 2003) www.cs.umd.edu/hcil/treemap/

  10. Treemap: Smartmoney MarketMap www.smartmoney.com/marketmap

  11. Market falls steeply Feb 27, 2007, with one exception

  12. Market mixed, February 8, 2008 Energy & Technology up, Financial & Health Care down

  13. Market rises, September 1, 2010, Gold contrarians

  14. Treemap: WHC Emergency Room (6304 patients in Jan2006) Group by Admissions/MF, size by service time, color by age

  15. Treemap: WHC Emergency Room (6304 patients in Jan2006) (only those service time >12 hours) Group by Admissions/MF, size by service time, color by age

  16. Information Visualization: Mantra • Overview, zoom & filter, details-on-demand • Overview, zoom & filter, details-on-demand • Overview, zoom & filter, details-on-demand • Overview, zoom & filter, details-on-demand • Overview, zoom & filter, details-on-demand • Overview, zoom & filter, details-on-demand • Overview, zoom & filter, details-on-demand • Overview, zoom & filter, details-on-demand • Overview, zoom & filter, details-on-demand • Overview, zoom & filter, details-on-demand

  17. Information Visualization: Data Types 1-D Linear Document Lens, SeeSoft, Info Mural 2-D Map GIS, ArcView, PageMaker, Medical imagery 3-D World CAD, Medical, Molecules, Architecture Multi-VarSpotfire, Tableau, Qliktech, Visual Insight Temporal LifeLines, TimeSearcher, Palantir, DataMontage Tree Cone/Cam/Hyperbolic, SpaceTree, Treemap Network Pajek, UCINet, NodeXL, Gephi, Tom Sawyer InfoVizSciViz. infosthetics.com visualcomplexity.com eagereyes.org flowingdata.com perceptualedge.com datakind.org visual.ly visualizing.org infovis.org

  18. Obama Unveils “Big Data” Initiative (3/2012) Big Data challenges: • Developing scalable algorithms for processing imperfect data in distributed data stores • Creating effective human-computer interaction tools for facilitating rapidly customizable visual reasoning for diverse missions. http://www.whitehouse.gov/sites/default/files/microsites/ostp/big_data_press_release_final_2.pdf `

  19. EHRs: Temporal categorical data Category Numerical Event Patient ID: 45851737 Stock: Microsoft Event 04/26/2010 10:00 31.03 04/26/2010 10:15 31.01 04/26/2010 10:30 31.02 04/26/2010 10:45 31.08 04/26/2010 11:00 31.16 12/02/2008 14:26 Arrival 12/02/2008 14:36 Emergency12/02/2008 22:44 ICU 12/05/2008 05:07 Floor 12/14/2008 06:19 Exit Time Arrival Emergency ICU Floor Exit A type of time series

  20. Patient Histories: Our Research www.cs.umd.edu/hcil/toolname

  21. Patient Histories: Our Research www.cs.umd.edu/hcil/toolname

  22. LifeLines: Patient Histories www.cs.umd.edu/hcil/lifelines

  23. Patient Histories: Our Research www.cs.umd.edu/hcil/toolname

  24. LifeLines2: Align-Rank-Filter & Summarize www.cs.umd.edu/hcil/lifelines

  25. LifeLines2: Align-Rank-Filter & Summarize www.cs.umd.edu/hcil/lifelines2

  26. Patient Histories: Our Research www.cs.umd.edu/hcil/toolname

  27. Similan: Search www.cs.umd.edu/hcil/similan

  28. Patient Histories: Our Research www.cs.umd.edu/hcil/toolname

  29. LifeFlow: Aggregation Strategy Temporal Categorical Data (4 records) LifeLines2 format Tree of Event Sequences LifeFlow Aggregation www.cs.umd.edu/hcil/lifeflow

  30. LifeFlow: Interface with User Controls

  31. Patient Histories: Our Research www.cs.umd.edu/hcil/toolname

  32. EventFlow: Original Dataset

  33. LABA_ICSs Merged

  34. SABAs Merged

  35. Align by First LABA_ICS

  36. Reduce Window Size

  37. Original Dataset

  38. Discovery Process: Systematic Yet Flexible Preparation • Own the problem & define the schedule • Data cleaning & conditioning • Handle missing & uncertain data • Extract subsets & link to related information

  39. Discovery Process: Systematic Yet Flexible Preparation • Own the problem & define the schedule • Data cleaning & conditioning • Handle missing & uncertain data • Extract subsets & link to related information Purposeful exploration – Hypothesis testing • Range & distribution • Relationships & correlations • Clusters & gaps • Outliers & anomalies • Aggregation & summary • Split & trellis • Temporal comparisons & multiple views • Statistics & forecasts

  40. Discovery Process: Systematic Yet Flexible Preparation • Own the problem & define the schedule • Data cleaning & conditioning • Handle missing & uncertain data • Extract subsets & link to related information Purposeful exploration – Hypothesis testing • Range & distribution • Relationships & correlations • Clusters & gaps • Outliers & anomalies • Aggregation & summary • Split & trellis • Temporal comparisons & multiple views • Statistics & forecasts Situated decision making - Social context • Annotation & marking • Collaboration & coordination • Decisions & presentations

  41. UN Millennium Development Goals To be achieved by 2015 • Eradicate extreme poverty and hunger • Achieve universal primary education • Promote gender equality and empower women • Reduce child mortality • Improve maternal health • Combat HIV/AIDS, malaria and other diseases • Ensure environmental sustainability • Develop a global partnership for development

  42. 30th Anniversary!!! www.cs.umd.edu/hcil@benbendc

  43. Office of National Coordinator: SHARP Strategic Health IT Advanced Research Projects - Security of Health Information Technology - Patient-Centered Cognitive Support - Healthcare Application and Network Platform Architectures - Secondary Use of EHR Data Univ of Maryland HCIL tasks - Missing Laboratory Reports - Medication Reconciliation - Wrong Patient Errors www.cs.umd.edu/hcil/sharp

  44. Medication Reconciliation: Current Form Univ of Maryland HCIL tasks - Missing Laboratory Reports - Medication Reconciliation - Alarms and Alerts Management www.cs.umd.edu/hcil/sharp www.youtube.com/watch?v=ZGf1EiuIIIM

  45. Twinlist: Medication Reconciliation “Best reconciliation app I have ever seen” Dr. Shawn Murphy, PartnersHealthcare & Harvard Medical “Super-cool demo” Dr. Jonathan Nebeker, Univ of Utah & VA “Twinlist concept is brilliant” Dr. Kevin Hughes, Harvard Medical School Tiffany Chao, Catherine Plaisant, Ben Shneideman Based on class project of : Leo Claudino, SamehKhamis, RanLiu, Ben London, Jay Pujara Students of CMSC734 Information Visualization class www.youtube.com/watch?v=YoSxlKl0pCo

  46. Twinlist: Medications Grouped

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