IPDRA: Intelligent Patient Data Review Assistant

1. IPDRA: Intelligent Patient Data Review Assistant Phase I Final Briefing SBIR Topic OSD01-DHP11 Jim Ong Stottler Henke 17 June 2002 Stottler Henke Smarter Software Solutions

2. Stottler Henke 40 person applied research and software consulting company founded in 1988 Core competency: artificial intelligence (AI) San Mateo, CA Seattle, WA Boston, MA Education and training Information access Data mining Knowledge management Decision-support Planning and scheduling

3. IPDRA Mission Help clinicians review patient data more effectively before and during patient encounters Current state-of-the-art Limitations • Web application server • Relational database • Source-oriented queries • Minimal use of graphics • Time-consuming to select relevant patient data • Hard to integrate and data spanning multiple pages and data sources .

4. Jim Ong (PI) Stottler Henke Jane Dowling David Fram Stephen Porter, MD Seth Powsner, MD Ida Sim, MD, PhD Klein Associates SAIC II x x x x x x x x clinical & drug safety databases, data viz, AI web-based systems, Java, AI, adaptive UIs nursing, info architecture, medical device UIs medical databases, data mining, data viz emergency medicine, pediatrics, clinical sys UIs psychiatry, medical software, data viz internal medicine, informatics for EBM cognitive task analysis, decision-centered design, naturalistic decision-making Composite Health Care System (CHCS) Integrated Clinical Database (ICDB) Phase I x x x x x x x IPDRA Project Team

5. IPDRA Design Goals and Assumptions • Clinicians are busy before, during, and after visits • Organizations and clinicians vary by their: • preferences for data content and presentation method • willingness to delegate / trust • proficiency (using software and visualizing data) • IPDRA should: • adapt to the user, patient, type of visit, problem, etc. • be predictable and understandable • be extensible and maintainable • encourage best clinical practices • give precedence to user-supplied reporting decisions • provide default reporting using system’s knowledge

6. IPDRA Phase I Project Activities Reviewed research literature and relevant technologies (software and data) Gathered Clinician User Requirements Graphical Patient Data Summaries Powsner/Tufte, CrossGraphs lab graphs Plaisant et al Lifeline, PPD Patient Profile Current Generation Patient DBs (ICDB, Logicon) Medical Concept Queries (Zeng) Web-based reporting systems Java graph objects Apelon Terminology Server Unified Medical Language System (UMLS) Arden Syntax (medical logic) Project team discussions Clinician questionnaires Requested descriptions of data views for hypothetical patients Abstracted user needs from concrete examples

7. IPDRA Phase I Project Activities (2) Developed High-Level Design Prototyped Java applet display objects Created mock-ups of patient data views Developed Phase II Plan Views show clinically-meaningful data subsets Supports best clinical practices by displaying computed targets, benchmarks, checklists Authoring tool lets non-programmers create view Re-usable display objects for clinical data review Patient data object provides simpler data model and potentially improves performance via caching Timeline summary Clinical time-series graph array Combination timeline and time-series graphs Cardiac, Liver Tests, Hypertension View posted on www.shai.com/projects/ipdra Develop and evaluate operational prototype with initial set of views using the Integrated Clinical Database (ICDB) as the patient database

8. Example Clinician Data Review Goals current health, recent treatments, and response patient data related to current problem notice other patient problems requiring attention health maintenance identify compliance issues identify patient conditions affecting treatmentselection graph of most recent vitals, labs, medications, If current problem = headache, review cardiovascular disease risk factors if BP>135/85, see BP meds and/or other BP readings to determine if patient not Dx with HTN or inadequately treated immunizations up to date? last pap, mammogram/breast exam, psa, etc. compare data about when patient came for refill (stored in pharmacy DB) with treatment plan allergies, other meds, contraindications

9. Example: routine visit Current concerns Health state Last regular check up: Chronic conditions: Health maintenance: Current medications: Current allergies: Current vitals: Current weight: Is anything bothering this individual? Patient’s perception of own health status? When was it? Any issues that require monitoring? Known Dx? Related symptoms and health state. Recommended testing based on age and gender. Results of previous health maintenance studies. Prescriptions? Over the counters? Alternatives? To what meds, environmental/food elements. Reactions? Heart rate and BP compared to normal limits. Compared with 1 year ago and with norms

10. Example: problem visit / known issue Current concerns Health state Last problem visit: Health maintenance: Current medications: Current vitals: Current weight: Is anything bothering this individual? Patient’s perception of own health status? Of illness-specific health status? Change since last assessment? What were the active issues? What was the intervening plan of action? (testing, treatment, etc.) Test results? What testing is required for health maintenance on this problem? Have meds been altered from last visit? Patient response to any change in regimen? Refills required? Any blood tests required based on current meds?. Heart rate and BP compared to normal limits. Compared with 1 year ago and with norms

11. IPDRA Patient Data View Concept • IPDRA maintains a library of views • Each view facilitates rapid data review via effective integration and presentation of a clinically-meaningful subset of the patient’s data • IPDRA automatically selects relevant views for visit • Views support best clinical practices by presenting patient data and guideline data side-by-side • Views provide drill-down and inter-view navigation • Users can define views via GUI authoring tool by selecting and configuring variable calculations and text/graphics subviews and display objects. • Users can create and save ad hoc views

12. roll over  short text notes mouse click  html detail Show/hide panel reference date scroll in normal range zoom high

13. navigation 1 month normal range compliance subview

14. mouse click  date highlighted in all graphs roll over  exact value and date

15. View Logic Requirements Database retrievals (time stamped data) Data transformations and computations Conditional logic (if-then) Iterations (for-each loops) Actions Display BP measurements (all, last, within n years) Compute target BP for patient on HTN drug according to guidelines If BP>135/85 ... For each possible AE for this drug… Set variable value(s) or add/modify display object used in view

16. View Logic Implementation Borrow concepts from the Arden Syntax for Medical Logic Systems Augment SQL access with patient data object View variables can be scalars or lists and tables of time-stamped values Assign values to view variables via database mapping and calculation statements, specified via GUI Use variable values in logic and action statements to control the content or appearance of the view. A display object property can be associated with a view variable value. Provides simple object-oriented access to raw/computed patient data

17. Example KB-Driven Problem View For a problem For each risk factor For each related problem For each prescribed, indicated drug For each reported AE For each possible AE Show relevant clinical data in timeline with treatments Show risk factor and related data Show problem and related clinical data Show drug dose and period Show target drug levels Show AE Show clinical data for the AE

18. Medical Knowledge Base Supports Views unique medical concept Ids relationships among concepts knowledge base (or ontology) + Related comorbid indication contraindication has risk factor Risk factor Problem Treatment shown by possible AE shown by shown by Adverse Event Clinical Data

19. Automated View Selection Based on: Type of visit Clinician specialty Current problems Individual user Patient data Routine, problem (initial), problem (follow-up) Primary care, cardiology, etc. Shortness of breath, chest pain Dr. Jones 50 year old male chronic problems: hypertension, diabetes current meds: Atenolol Example view selection rules: If chronic problems include hypertension then add Hypertension View If specialty is cardiology then add Cardiology View

20. Adaptive View Selection, View Definitions Page A Page B Page C Panel 1 Panel 2 Panel 3 Panel 4 Panel 5 C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 Always display these alerts Always display this standard view Sometimes display this standard view Always included Conditionally included

21. 1 2 IBUPROFEN 600 MG TAB Qty: 90 for 30 days MAGNESIUM OXIDE 400 MG Tqy: 90 for 90 days ACETAMINOPHEN 325 MG TAB: Qty: 100 for 30 days Authoring Views Author configures a display object to specify data content and appearance Author includes display objects in a subview to create a reusable reporting object

22. T P R BP 96.7 F 68 20 120/80 3 Authoring Views (2) Author includes subviews in the view subviews display objects IBUPROFEN 600 MG TAB Qty: 90 for 30 days MAGNESIUM OXIDE 400 MG Tqy: 90 for 90 days ACETAMINOPHEN 325 MG TAB: Qty: 100 for 30 days

23. IPDRA Phase II Project Goal Develop and evaluate an operational prototype that convincingly demonstrates IPDRA’s feasibility and utility. Deliverables Testbed • IPDRA view generation web server • Authoring tool • Display objects library • Medical knowledge base and tools • Initial set of view definitions • Integrated Clinical Database (ICDB) .

24. Display object Java applets Authoring Tool IPDRA web app server View selection rules View and subview definitions html Web browser KB editor / loader Knowledge Base Patient Database IPDRA Phase II Architecture

25. IPDRA Phase II: Access ICDB Data Web browser ICDB web app server IPDRA web app server ICDB database (Oracle) CHCS database (MUMPS) HL7

26. 0 4 8 12 16 20 24 IPDRA Phase II Project Plan Month Create View Mock-ups Basic View Generation (display applets, database access patient data object, html generation) Advanced View Generation (KB-driven, ad hoc) Knowledge Base (select data sources, editor / loader) Authoring Tool Evaluate System Deliver Spec/Design Develop/Test User Test