1. A Visual Analytics Framework for Emergency Room Clinical Encounters 1 Department of Computer Science 2 Department of Emergeny Medicine Zhiyuan Zhang 1, Supriya Garg 1, Arunesh Mittal 1, Alex Dimitriyadi 1, IV Ramakrishnan 1, Rong Zhao 1, Klaus Mueller 1, Asa Viccellio 2

2. Medical Record As old as Hippocrates (around 400 BC) father of Western medicine Should: accurately reflect the course of disease indicate the probable cause of disease

3. Paper-Based Medical Record

4. Electronic Medical Record (EMR) Transaction-driven: documentation + tables Non-intuitive interfaces Fragmented display of patient information

5. Typical Information Flow in the ER Obtain Patients Information Current History Past History Family History Social History Review of System Physical Examination Order Laboratory Data Request and obtain consultation Take appropriate action within an appropriate time Reevaluate and readjust therapy and diagnosis

6. Typical Information Flow in the ER Obtain Patients Information Current History Past History Family History Social History Review of System Physical Examination Order Laboratory Data Request and obtain consultation Take appropriate action within an appropriate time Reevaluate and readjust therapy and diagnosis Obtain Patients History Current History Past History Family History Social History Review of System Physical Examination Order Laboratory Data Request and obtain consultation Take appropriate action within an appropriate time Reevaluate and readjust therapy and diagnosis Obtain Patients History Current History Past History Family History Social History Review of System Physical Examination Order Laboratory Data Request and obtain consultation Take appropriate action within an appropriate time Reevaluate and readjust therapy and diagnosis Obtain Patients Information Current History Past History Family History Social History Review of System Physical Examination Order Laboratory Data Request and obtain consultation Take appropriate action within an appropriate time Reevaluate and readjust therapy and diagnosis

7. System Objectives Support and enhance the clinical decision-making Simple Interface to make data and information exploration easier Assimilation of data from different sources Visualization and visual reasoning is key Ease of data and information access is key

8. System Overview

9. The 5-W Scheme Use a strongly structured paradigm, the 5-W WHO : the patient and the history WHAT : Symptoms, tests and results, diagnosis, treatments and medications, etc. WHERE : locations (when appropriate) of the WHAT on the human body WHEN : time and duration of the WHAT WHY : cause and effect of the various WHAT constituents

10. Visualize the 5-W Scheme WHO : Basic Info and Vital Signs WHAT : Integrated in WHERE, WHEN, and WHY. WHERE : Human map WHEN : Time line WHY : Directed causal graph

11. Visualize Who, What and Where (0) Start Screen

12. Visualize Who, What and Where (a) Results of triage (name, weight, age, vitals with high fever)

13. Visualize Who, What and Where (b) Populating the spatial map with symptoms (head problems)

14. Visualize Who, What and Where (c) Adding past history (lung cancer in remission)

15. Visualize Who, What and Where (d) Social history indicates patient has a history of smoking

16. Visualize Who, What and Where (e) The diagnostic process begins, immediate actions

17. Visualize Who, What and Where (e) The diagnostic process begins, using the Diagnostic Sandbox

18. Visualize Who, What and Where (f) The diagnostics determines epidural hematoma

19. Visualizing When Each entry is classified into: Symptoms; Tests; Diagnosis; Treatments.

20. Visualizing When Each sub-track within one track represents an event.

21. Visualizing When Each sub-track has an explanation.

22. Visualizing When Abnormal results or severe symptoms are highlighted in red to draw the physicians attention.

23. Visualizing When Brushing operation

24. Visualizing Why Symptom->Test/Data->Diagnosis->Treatment/Medication A modified version of the force-directed layout All symptoms have incoming edges from a node representing a visit to the physician. A convex hull is drawn for each visit.

25. Visualizing Why Enable quick mental analysis Help detect errors in diagnoses

26. Visualize Why

27. Visualizing Why Case Study

28. Visualize Why

29. Conclusions Implemented an emerging visual analytics system For clinical encounters in emergency room scenarios Clinician and patient-focused Unifies all EMR information fragments into a single interactive visual framework Voice and multi-touch interaction capabilities

30. Current/Future Work Improvements, fine-tuning, and additional features Include more formal user and affordance studies to fine- tune the various modules of our system. A more geometrically structured temporal plot for the casual graph. Treatment Outcome Integrate more analytics in the system.

31. Thanks For Listening…