1. This presentation was supported by Grant Number P01 HK000028-02 from the Centers for Disease Control and Prevention. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of CDC. Public Health Informatics Research for Future Disease Monitoring Public Health Informatics Research for Future Disease Monitoring Fundamentals of a Public Health Grid International D, Session A3 25 August 2008 Joe Lombardo Joe.Lombardo@jhuapl.eduhttp://essence.jhuapl.edu/ESSENCE

2. Lombardo 04/11/08 Where has disease surveillance community come from? Initial automation solutions What are the requirements? Important initiatives to move us in the right direction JHU/APL’s COE research Questions Presentation Outline

3. Lombardo 04/11/08

5. Initial Attempts at Surveillance Automation

6. Lombardo 04/11/08 Syndromic Groupings (A Start) Botulism-like Febrile Disease Fever Gastrointestinal Hemorrhagic Neurological Rash Respiratory Shock / Coma Chills Sepsis Body Aches Fatigue Malaise Fever only ICD-9 Based Syndrome Chief Complaint Based 038.8 Septicemia NEC 038.9 Septicemia NOS 066.1 Fever, tick-borne 066.3 Fever, mosquito-borne NEC 066.8 Disease, anthrop-borne viral NEC 066.9 Disease, anthrop-borne viral NOS 078.2 Sweating fever 079.89 Infection, viral NEC 079.99 Infection, viral NOS 780.31 Convulsions, febrile 780.6 Fever 790.7 Bacteremia 790.8 Viremia NOS 795.39 NONSP POSITIVE CULT NEC

7. Lombardo 04/11/08 Initial Disease Surveillance Analytics Approach Alerting & Notification for a Syndrome or Disease Alerting Detection of Abnormal Levels for a Syndrome ED Chief Complaints OTC Medication Sales Lab Requests / Results Temporal Algorithms Spatial Algorithms Temporal Algorithms Spatial Algorithms Temporal Algorithms Spatial Algorithms Adding data sources increases the statistical false positives Data collected from multiple sources usually not be linked to an individual patient

8. Lombardo 04/11/08 Limitations to Syndromic Surveillance 1)Many of the currently used syndrome groupings too large Creates a large noisy background level Signals must be large to be distinguished above the background Fixed number of predefined syndromes limit system usefulness for discovery of immediate health risks 2)Addition of multiple data streams Difficulty in forming corresponding groups across data types Creates additional false positives if the relationships among the data streams aren’t known Difficulty in identifying geographic clusters if geographic information is not preserved in the data provided.

9. Lombardo 04/11/08 Changing Environment for Public Health Information Systems Chief Complaint ICD-9 OTC Meds Early Event Detection Hospital Data Sources Analytics RHIO Public Health Situational Awareness Hospital A Urgent Care Clinic HMO Physician’s Group A Physician’s Group B Hospital B Hospital C Health Information Exchanges Analytics Existing Surveillance Focus Non Specific Data SourcesElectronic Medical Records

10. Lombardo 04/11/08 National Health Information Exchanges RHIO Health Dept. Hospital A Urgent Care Clinic HMO Physician’s Group A Physician’s Group B Hospital B Hospital C RHIO Health Dept. Hospital A Urgent Care Clinic HMO Physician’s Group A Physician’s Group B Hospital B Hospital C RHIO Health Dept. Hospital A Urgent Care Clinic HMO Physician’s Group A Physician’s Group B Hospital B Hospital C BioSense Must accommodate the Sharing of data and information National Health Informatio n Network Region 1 Region 2 Region N

11. Lombardo 04/11/08 Challenges in the Changing Environment 1.Initial automated surveillance systems focused on populations not individuals Need to maintain longitudinal records for individuals to best determine their fit into a class or case definition Should archiving individual’s health records be a function of health departments? Need to avoid additional PH burdens for maintaining separate archives. 2. Addition of new data and information sources to resolve immediate case -specific questions. 3.Information system support for user defined queries, analytics, and visualization tools. 4.Increasing collaboration among all public health agencies in an electronic environment

12. Lombardo 04/11/08 A Potential Solution Ref: Tom Savel, Ken Hall, Les Lenert

13. Lombardo 04/11/08 PHGrid Pros and Cons Pros Immediate access to a wide variety of data, information and services to address an immediate public health concern. Reduce the need for replicating and holding data locally. Access to latest improvements to services. Security and authentication issues transparent to the users. Cons Requires a significant change in culture for the entities on the grid to maximize its benefit. Will require legal barriers to be overcome. May require new security protocols and authentication methods. May involve new commercial opportunities / challenges Expense of adopting standardized database and formatting methods

14. Lombardo 04/11/08 How do we get there? PH User Locally held applications and archives Shared Environment Firewall

15. Lombardo 04/11/08 User Centric Solutions are Required for the PHGrid Air Sample Analysis Water Sample Analysis Intelligence Medical Encounters Over the Counter Sales Non-Traditional Indicators Radiology Rapid Diagnostics & Lab Medications ICD-9 & CPT Codes User Interfaces Advanced Query Tool Statistical Analytics Tools Decision Support Tools Data Fusion Analytics User must be able to access data and services to resolve current public health issues. Services must be usable for a variety of different problems and not tied to a specific data set. Initially Grid users may have higher level of skills. For broad acceptance Grid solutions must be driven by the average user.

16. Lombardo 04/11/08 Disease Surveillance Using PHGrid Services Detection / Classification Analytics Service InfoShare Data / Information Sharing Service Medical Records Generator Data Service PHGrid Services Globus Toolkit Components SecurityOGSA-DAIGrid FTP User Client Requests Interaction Data Management User Interfaces User Client Requests Interaction Data Management User Interfaces User Client Requests Interaction Data Management User Interfaces Analysis Visualization Service … NIH OTC CDC HIE PHGrid Resources Data Bases Computational Public Health Community Users

17. Lombardo 04/11/08 JHU/APL COE Research Emphasis 1.Public health use of RHIO / HIE archived data 2.Availability of data for use in research, development, evaluation training, etc. 3.User customizable analysis tools to support a variety of public health requirements 4.Sharing of information among public health entities

18. Lombardo 04/11/08 Accessing Linking Medical Records for Public Health Situational Awareness Phone Triage Chief Complaint ICD-9 & CPT Codes Clinic Notes Lab Requests & Results Radiology Requests & Reports Medications Alerting with Severity Index Disease Identification Outbreak Management Emerging Risks Effective use of the Electronic Medical Record Enables Situational Awareness

19. Lombardo 04/11/08 Query Builder Wizards (MohammadHashemian and Colleen Martin CDC) (Mohammad Hashemian and Colleen Martin CDC)

20. Lombardo 04/11/08 Creating Synthetic Medical Record Data (Linda Moniz, Anna Buczak, John Copeland CDC) Synthetic data is needed for research, development training, evaluation, etc. The data must contain a variety of outbreaks under a variety of scenarios. Not aware of any available synthetic medical records containing outbreaks. Process extracts treatment protocols for use in generating records. Synthetic medical record generator must be made available as a service.

21. Lombardo 04/11/08 … Realistic But Not Real Electronic Medical Records Individual patient care models extracted from data Step 2 Step 3 Patient care descriptors HVisit RX Order HVisitLab OrderLab Result RX OrderRadResultRadOrder Lab Result HVisitLab Order Lab Result HVisit RX Order HVisitLab OrderLab Result RX OrderRadResultRadOrder Lab Result HVisitLab Order Lab Result Care Model HVisit RX Order HVisitLab OrderLab Result RX OrderRadResultRadOrder Lab Result HVisitLab Order Lab Result HVisit RX Order HVisitLab OrderLab Result RX OrderRadResultRadOrder Lab Result HVisitLab Order Lab Result Care Model HVisit RX Order HVisitLab OrderLab Result RX OrderRadResultRadOrder Lab Result HVisitLab Order Lab Result HVisit RX Order HVisitLab OrderLab Result RX OrderRadResultRadOrder Lab Result HVisitLab Order Lab Result Care Model HVisit RX Order HVisitLab OrderLab Result RX OrderRadResultRadOrder Lab Result HVisitLab Order Lab Result HVisit RX Order HVisitLab OrderLab Result RX OrderRadResultRadOrder Lab Result HVisitLab Order Lab Result Care Model HVisit RX Order HVisitLab OrderLab Result RX OrderRadResultRadOrder Lab Result HVisitLab Order Lab Result HVisit RX Order HVisitLab OrderLab Result RX OrderRadResultRadOrder Lab Result HVisitLab Order Lab Result Care Model HVisit RX Order HVisitLab OrderLab Result RX OrderRadResultRadOrder Lab Result HVisitLab Order Lab Result HVisit RX Order HVisitLab OrderLab Result RX OrderRadResultRadOrder Lab Result HVisitLab Order Lab Result Care Model HVisit RX Order HVisitLab OrderLab Result RX OrderRadResultRadOrder Lab Result HVisitLab Order Lab Result HVisit RX Order HVisitLab OrderLab Result RX OrderRadResultRadOrder Lab Result HVisitLab Order Lab Result Care Model HVisit RX Order HVisitLab OrderLab Result RX OrderRadResultRadOrder Lab Result HVisitLab Order Lab Result HVisit RX Order HVisitLab OrderLab Result RX OrderRadResultRadOrder Lab Result HVisitLab Order Lab Result Care Model Identifying Patterns of Care in EMR Data

22. Lombardo 04/11/08 Creation of the Synthetic Patient Medical Records (for each patient) Characteristics of Individual Patient to Inject Distance Measure Injected Disease/Victim Generation Model Injected Victim Medical Record Closest Care Model Injection algorithm Specific Disease Care Modifiers Adjusted Care Model Patient Descriptors

23. Lombardo 04/11/08 Examples of Injected Medical Records

24. Lombardo 04/11/08 Electronic MEdical Records GEnerator A Synthetic Medical Records Data Service BioSense HIEs RBNR Client Existing Data Sets Yes No Request For Background Data Send Data to the Requestor Request Parameters Care Model Identification Disease Outbreak Model Modified Background Patient Injection Model Potential Future PHGrid Data Services EMERGE Grid User JHU/APL Demo Client Web Application / Portal Requests Interaction Data Management User Interfaces Reviews Existing Data Sets to Match Background & Outbreak Data Merge

25. Lombardo 04/11/08 Fusing Clinical Data and Non-Linked Health Indicators (Zara Mnatsakanyan) © Copyright 2006 The Johns Hopkins University Applied Physics Laboratory. All Rights Reserved.

26. Lombardo 04/11/08 Visit Counts and Severity Score Counts Daily Respiratory Visits Daily Counts for Severity Score

27. Lombardo 04/11/08 Visit Counts and Severity Score Counts Daily Respiratory Visits Daily Counts for Severity Score Non Sever Resp. Levels Sever Resp. Levels

28. Lombardo 04/11/08 Intelligent Decision Support Service Mohammad R. Hashemian JHU/APL Demo Client Web Application / Portal Requests Interaction Data Management User Interfaces Future PHGrid Resources Computational

29. Lombardo 04/11/08 Additional Information on Electronic Medical Records Processing Managing Intelligent Decision Support Networks in BioSurveillance Mohammad R. Hashemian Session G1, International B Wednesday, August 27, 2008 Exploring Electronic Medical Records For Public Health Surveillance Zaruhi R. Mnatsakanyan Session H3, International B Thursday, August 28, 2008

30. Lombardo 04/11/08 Information Sharing Among Health Agencies (Wayne Loschen, Nathaniel Tabernero)

31. Lombardo 04/11/08 InfoShare Data and Information Sharing Grid Service Member of the Federation Client Future Federation of Surveillance Systems InfoShare Grid Service Creator Viewer Editor Local HD State HD Regional System BioSense HIE Care Provider Get Ref. Lists Archive Create View Mark Read Get Field Info. GIS Graphing Auto MSG Creation Subscription Notification Future Implemented InfoShare Clients can use the Reference Implementation or their own. Edit Reference Implementation

32. Lombardo 04/11/08 Additional Information on Collaboration Tools Disease Surveillance Information Sharing Nathaniel R. Tabernero Poster Session South/West Halls 8/24-8/27

33. Lombardo 04/11/08 Demo Surveillance Application Using PHGrid Services JHU/APL Demo Client Web Application / Portal Requests Interaction Data Management User Interfaces Medical Records Detection / Classification IDSS Service InfoShare Information Sharing Service EMERGE Synthetic Medical Records Generator Data Service JHU/APL Research Grid Services Globus Toolkit Components SecurityOGSA-DAIGrid FTP

34. Lombardo 04/11/08 Surveillance Concept Demonstration Research Grid Services to Support Disease Surveillance JHU/APL Center of Excellence Team International D, Session E3 Tuesday, August 26, 2008

35. Lombardo 04/11/08 Summary Current disease surveillance applications are limited in their expandability and ultimate usefulness. Public health needs a variety of data services available to respond to urgent health risks. Long development programs will not be tolerated in the future. Public health informatics professionals will need to find solutions that simplify access to data and services. It is hoped that the research currently being provided by NCPHI and the Centers will lay the foundation for future applications. Questions?