1 / 22

Real-time Monitoring of ED Chief Complaints for Anomaly Investigation

Learn how Real-time Outbreak and Disease Surveillance (RODS) system uses existing data from hospital registration databases to interpret and map chief complaints into syndrome categories. This system provides continuous alerts and responses for monitoring and investigating anomalies in emergency department chief complaints.

annawade
Download Presentation

Real-time Monitoring of ED Chief Complaints for Anomaly Investigation

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Successful Alerts and Responses: Real-time Monitoring of ED Chief Complaints and Investigation of Anomalies CDC Public Health Preparedness Conference February 23, 2005 Loren Shaffer, MPH Ohio Department of Health

  2. Real-time Outbreak and Disease Surveillance (RODS) • Developed by team at the University of Pittsburgh led by Mike Wagner, MD, PhD • Utilizes existing data (HL7 format) from hospital’s registration database • Interprets and maps free-text chief complaint into syndrome category • Interprets and maps sales of over-the-counter medication • Accessed by end user via the internet

  3. Syndromic SurveillanceData Flow Continuous Daily Emergency Department Categorize Into Syndromes Daily Totals Totals Higher Than Expected? Continuous Alert Chief Complaint and Patient Demographics In HL7 messages Review Trends Historical Models Updated monthly Valid Alert? Initiate Response

  4. Age & Gender Zip code Free-text chief complaint Visit date and time Sample HL7 ADT Message MSH|^~\&||xxx||RODS|200202241715||ADT^A04|2002022XXXXXXXX|P|2.3<CR> PID|||||||^020|M|||^^^^84204|||||<CR> PV1||E|||||||||||||||||98765432||||||||||||||||||||||||200202151830||<CR> DG1||||SORE THROAT,COUGH<CR> IN1||||||||||||||||||||||||||||||||||||||||||||^^^^84056<CR> <ETX>

  5. RODSNavigation – EpiPlot Screen

  6. RODSNavigation – Mapplot

  7. RODSNavigation – Chief Complaints

  8. Local Health Departments HC Epi Hospitals CEO ICP Ohio’s Approach

  9. Some BottomLines (Incentives) for Hospitals • Cost for RODS installation paid for by ODH with HRSA grant money • Minimal configuration time - via telephone with assistance of RODS engineers • Runs in background – No additional duties for ED or IT personnel • Data are secure and “de-identified” – patient privacy is maintained • HIPAA compliant • JCAHO Standards

  10. RODS ProjectProgress

  11. RODS ProjectProgress

  12. GeographicCoverage

  13. Example #1:Respiratory Visits • 12/24/2004 @ 14:58: alert for all Ohio • Normalized increase from 11.5% to 15%

  14. Example #1:Respiratory Visits • 12/23/2004: Severe ice storm results in massive power outages. • Stores throughout area sell out of kerosene and other supplemental heating units. • Review of chief complaints reveals carbon monoxide poisoning as culprit. • Total preliminary investigation: 10 minutes

  15. Example #2:Norwalk Virus Outbreak • January 11, 2005: Norwalk-like outbreak involving 4 staff and 7 residents of nursing home reported to State. Later confirmed via bulk stool analysis. • January 4, 2005: Disease first reported locally with nausea, diarrhea, and vomiting lasting between 12 and 48 hours.

  16. Example #2:Norwalk Virus Outbreak • 12/31/2004: >3 SD from moving average for anti-diarrhea medications in ZIP code 44024 • Possibility: community infection brought into nursing home by employee/visitor

  17. Example #3:Influenza • Influenza surveillance includes lab results, ILI sentinel providers, VA Clinic Visits, Class B, OTC sales, and school closings,

  18. Example #3:Influenza

  19. Example #3:Influenza • Franklin Co. resident confirmed with influenza A (H3N2) via lab isolate:1/19/05 • Specimen date:1/4/2005 • Illness Onset date:1/1/2005

  20. Integrating RODS Into Ohio’s Surveillance Program • Establishing intrastate user visibility • Who gets access • Area of surveillance • Data made available • Inter-state visibility • Identifying other states using • How much visibility into each other’s jurisdiction

  21. IntegrationContinued • Review and analysis • Frequency • At what level • Standardization of analysis • What to do with alerts • Who is alerted • Preliminary investigation • Documentation • Protocol for monitoring, responding, etc. 24/7

  22. Ohio Department of HealthEarly Event Surveillance Staff • Loren Shaffer, Supervisor • lshaffer@odh.ohio.gov • Shannon Rowe, Immunization Epidemiologist • srowe@odh.ohio.gov • Brian Fowler, Syndromic Surveillance Epi. • bfowler@odh.ohio.gov • Muhammad Abbasi, Bio-terrorism Epi. • mabassi@odh.ohio.gov • Brenda Mocarski, Infec. Dis. Control Consultant • bmocarsk@odh.ohio.gov

More Related