Epi Info™, OMS, and CRA Interoperability PHIN Conference Workgroup Meeting Wednesday, August 27, 2008 Joint Presentation by Jeanne Tropper, MS, MPH (CRA) Amy Thompson, Trainer (Epi Info™) William Duck, MS, MPH (OMS)

7/31/20082 Overarching Objective Build awareness, appreciation and understanding of how Epi Info™, OMS and CRA can collectively support common work practices during public health response

7/31/20083 Learning Objectives  Present brief synopsis of the following systems: Epi Info™, Outbreak Management System (OMS) and Countermeasure and Response Administration (CRA)  Illustrate how each application would be used in a fictional progressive outbreak scenario  Distinguish how each system relates to one another and their logical connectivity  Solicit partner input on future interoperability: short, medium and long term

7/31/ /2006 Iowa Outbreak Scenario  December 2005: first reports to the Iowa Department of Public Health (IDPH) of mumps-like illness at a university in eastern Iowa  January 2006: isolate from an unrelated patient was cultured and identified as mumps indicating multiple regions affected  February 2006: active surveillance initiated in seven geographical areas, including campuses of the three largest universities in Iowa  March 2006: additional persons with clinically compatible symptoms were being investigated in three neighboring states (Illinois, Minnesota, Nebraska); only 16% of total cases were linked epidemiologically suggesting frequent unapparent transmission  April 2006: Source unknown but mumps strain (genotype G) same as 2005 UK epidemic

7/31/20085 When Would Each System be Used? Outbreak Scenario Epi Info™ OMSCRA  Month 1: first reports of mumps-like illness at a university in Mid Western state  Month 2: isolate from an unrelated patient cultured; identified as mumps: multiple regions affected  Month 3: active surveillance initiated in seven geographical areas, including three largest universities  Month 4: additional persons with clinically compatible symptoms investigated in three neighboring states; only 16% of total cases were linked epidemiologically suggesting frequent unapparent transmission  Month 5: linked to UK strain

7/31/20086 Scenario Roles  Medical staff at student health center identify multiple mumps-like symptoms in college students; report to local county public health –Public health nurse develops initial questionnaire using Epi Info™ to begin tracking students  Index mumps case is identified; laboratory confirmed cases show multiple regions affected –Public health nurse refines Epi Info™ questionnaire to focus on mumps –Epi Info™ analysis tools shows multiple regions affected  Disease investigation specialist at regional level initiates coordinated six county field investigation –OMS activated to manage complex relationships among persons, organizations and events (contact tracing) –Questionnaire revision in field –Follow-up log  State health officials make a decision to vaccinate university students –CRA activated to support mass vaccination clinics at multiple college campuses in three states established –Aggregate reporting to state and CDC activated

7/31/20087 Scenario Roles  Assumptions –Scenario is fictitious; systems were not deployed during Iowa outbreak –States are familiar with and use the three tools –As the outbreak progresses additional tools are required to manage increasing complexity –As each tool is activated, it continues to play a role throughout the outbreak

System Demonstrations Epi Info™ OMS CRA

7/31/20089 Epi Info™ Demonstration  Brief background  Demonstrate initial questionnaire development –Existing questionnaire used (if available) or –Modified for specific investigation –Questionnaire tailored to the flow of the data sheet –Data validation and skip-patterns programmed into View to control data entry  Data merged at regional or state health department

7/31/ Epi Info™ Demonstration  Analyses and Maps show multi-county spread  Health department officials identify need for contact tracing/social networking analyses –Decision to use OMS –Data exported from Epi Info and imported into OMS  Epi Info report template (Epi Report) updated with current data to track and communicate infection frequency and spread

7/31/ Epi Info™ Future Opportunities  Seamless exchange of data between: –OMS and Epi Info –CRA and Epi Info  Continued ad-hoc analyses of OMS and CRA data - mapping and reporting results

7/31/ OMS Demonstration  Brief background  Mumps outbreak now in 6 counties within region, 12 lab-confirmed cases  Epi Info™ Epi Map tool used to show geospatial significance  1 university, 3 high schools identified as possible sites of infection  Over 300 potential close contacts identified via OMS contact tracing)  Field staff deployed to continue case finding and contact investigation interviews

7/31/ OMS Demonstration  OMS deployed with field staff to perform the following activities –Continued case management of confirmed and suspect cases including documenting further lab tests and vaccination history –Use custom mumps case report form (from Epi Info?) –Create relationships between multiple subject types –Initiate contact tracing investigation, create social networking diagram –Manage outbreak activity workload through follow- up log –Replicate and synchronize data collected from field investigators back to regional level

7/31/ OMS Demonstration  Mass immunization events are now planned at the university and 2 high schools  OMS collected information on vaccination type, dosage, administration, and contraindications for all prophylaxis recipients  Additional 2000 vials of MMR vaccine need to be ordered to support prophylaxis efforts  Case/Contact demographics along with countermeasure tracking information is exported from OMS to CRA repository

7/31/ OMS Future Opportunities  Enhanced data exchange and messaging between OMS and NEDSS-based notifiable disease reporting systems  Web-enabled data entry  Subject de-duplication via Master Patient Index  Improve stand alone AVR capability  Social networking integration

7/31/ CRA Demonstration  Brief background  State PH and CDC guidance indicates the following interventions: –5 days of isolation for all patients –Students and staff of campuses have had 2 doses of MMR or are immune  Mass vaccination clinics set up in gymnasiums in multiple colleges and universities in three state region  Cascading rapid data entry approach chosen to support quick through put at “end of the line” 1.Person demographics 2.Screening 3.Vaccination given 4.Data entered into CRA immediately

7/31/ Gymnasium Set up and Flow

7/31/ CRA Demonstration  Rapid data entry of vaccine  Capability to track multiple countermeasures (medical, non-medical interventions)  Custom event set up –Aggregate counts for state and federal reporting –Adverse event tracking –Follow up – multiple dose schedule  Patient registration to support alternate POD operations and event specific upload (i.e., immunization registries information)

7/31/ CRA Future Opportunities  Bi-directional messaging –Immunization Information Systems –OMS, other disease surveillance systems  Upload of medication inventory information, i.e., quantity, type, lot #; –Vaccines –SNS –State stockpiles and inventory systems  Alternate means of data entry –Driver’s license scanning –Bar coding

7/31/ CRA  Highly scalable: supports multiple users, clinics, sub-jurisdictions, jurisdictions  Non case reporting  Rapid data entry for mass tracking of countermeasures  Regional & National Aggregate Reporting Systems Overview Epi Info Forms generation Custom Data Entry/Validation Integration with SAS Geographical Information System Analysis Visualization & Reporting OMS Entity Management Social Networking Workload Management Shareable vocabulary/question set library

7/31/ Open Discussion  How do you see these systems working together for you?  Can you share real world examples of how these systems may have been or could be helpful to your operations?  Would interoperability of these systems be helpful? Why?  How do we collaborate moving forward? Working group? Community of Practice – part of OM or separate?

7/31/ Future Interoperability Short Term “Siloed”, Segregated use with no interoperability Mid Term Coordinated use with messaging and data exchange Long Term Interoperable platform that becomes “best of breed” Today Coordinated use, build same forms, use same vocabulary and meaning, joint training and implementation

7/31/ Key Contacts  Epi Info™  David Nitschke   OMS  William Duck   Gerald Jones   Araceli Rey   CRA  Jeanne Tropper 