Hippocrates Archive

1. Hippocrates Archive John Brennan (jbren@wam.umd.edu) Hyunyoung Song (hsong@gmail.com) Nima Negahban (nimacn@gmail.com)

2. Introduction • Patient Data Management Application • Inherited application “Pattern Finder” • Pattern finder was using fake data • Conducted usability studies to make recommendations on the interface

3. Motivation • Twenty percent of the nations medical spending is on managing patient data • Paper Systems • Potential to be an invaluable tool for doctors and researchers

4. Previous Works • Lifeline • One of the first applications in this field • Very good at displaying large sets of data • Lacked the ability to make complex queries

5. Previous Works • KNAVE • Robust query system • Poor Visualization System

6. Pattern Finder • Medical History Search Application built by Jerry Fails, Amy Karlson, Layla Shahamet in Spring 2005 CMSC838S term project • System Spec • C# program on top of .NET Framework • Piccolo api for visualization

8. Dataset Test - Students • Original Data • Medication • Tests • Visits • Values • Imaginary values Test - Doctors • National Washington Hospital Data Set • Only tests (blood test) • Real values with reference level

9. Usability Study: 6 students • 3 scenarios with 3 tasks each • Participants used Pattern Finder with its default (phony) data • Tasks created to test several key fundamentals of the application • Understanding events • Creating simple and complex queries using each of the tools provided • Our study gave more focus to the query construction than visualization understanding

10. Observation User Troubles • 3 tier menu hierarchy • Understanding full query when more than 3 events have been created • Creating time spans between events • Difficulty querying medication changes (relative values feature)

11. Post-Test Result Used Shneiderman’s QUIS model (1-9 semantically anchored radio buttons)

12. Recommendation • Create text query window to display full query user is generating • Change editable span text to NumericUpDown controls • Change “relative values” text wording to “increasing/decreasing values” • Those using custom data for the system should use care when developing the event drop down menu hierarchy (naming and placement)

14. Usability Test : 2 Doctors • No need for scenarios • 6 Concrete Tasks • Desc: one from each query type • Measurement: Difficulty and Usefulness • Pilot Profile • Researcher who practiced Neurology 15 years ago => Researcher point of view • Gynecology and Obstetrics doctor who practiced over 30 years => Pure doctor point of view

15. Task 1 – E (Event) Task: Find Patients who have had 3 WBC (White Blood Cell) measurement.

16. Task 2 – E-FT(Event - Fixed Time span) Task: Find Patients whose HGB (Hemoglobin) measurement was between 10 ~ 14 Gm/dl (normal person reference level) but 2 day later it increased over 14 Gm/dl.

17. Task 3 – E-VT(Event – Variable Time span) Task: Find Patients whose HGB measurement was under 14 Gm/dl, but within 3 days it decreased under 14 Gm/dl.

18. Task 4 – E*-VT(Multiple Event – Variable Time span) Task: Find Patients whose WBC measurement is above 8.50 K/ul and BASO (basophilia ) lab test after 2 days

19. Task 5 - E*WC-VT (Multiple Event with Window Constraint – Variable Time span) Task: Find patients who had 5 or more HGB within 3 days followed by MCH measurement.

20. Task 6 – (E*WC)F-VT (Multiple Event with FunctionalWindow Constraint – Variable Time span) Task: Find patients who had 2 or more HGB test within 2 days that are less than the reference level (10~14 Gm/dl) within a range of 3 Gm/dl .

21. Results • Components • Most Intuitive (1)(7) • Confusing but useful (2)(3)(6) • Not much useful (4)(5)

22. Results

23. Conclusion • Visualization • Combinatorial display of results are redundant • Query Power • 3rd, 4th query are the most useful • Consumes exponential time when query becomes complicated • Medical Use • Potential for Patient monitoring system in ER

24. Futurework • Need for centralized patient data • Data from emergency room was only result of blood, urine and cerebral spinal fluid result for a month period. • Add various filters (currently the system has just two) to the search system

25. Special Thanks To.. • Professor Ben Shneiderman • Professor James Reggia, Doctor Yong Song for the Usability Study • Doctor Mike Gillam for providing the emergency room patient dataset and useful information

26. The End • John Brennan (jbren@wam.umd.edu) • Hyunyoung Song (hsong@cs.umd.edu) • Nima Negaban (nimacn@gmail.com)