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Lessons Learned from the National Syndromic Surveillance Conference

Gain insights into passive and active syndromic surveillance systems, legal mandates, data sources, privacy, goals, and investigation methods discussed at the National Syndromic Surveillance Conference. Explore potential sources of data and future directions for research.

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Lessons Learned from the National Syndromic Surveillance Conference

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  1. Lessons Learned from the National Syndromic Surveillance Conference Sponsored by the Centers for Disease Control and Prevention NYC Department of Health and Mental Hygiene New York Academy of Medicine September 23-24, 2002 New York City

  2. What is Syndromic Surveillance? • “Passive” Systems • Minimal burden • Designed to detect and monitor large # usual/mild illnesses • “Active” Systems- • Educational Outreach Tool • Designed to detect and report small # unusual/severe syndromes

  3. Legal Mandate:Who Should be Doing This? • Public Health Practice • Local health officers shall exercise due diligence in ascertaining the existence of outbreaks of illness or the unusual prevalence of diseases, and shall immediately investigate the causes of same • New York State Sanitary Code, 10 NYCRR Chapter 1, Section 2.16(a) • Research & Development • Non-traditional data sources • Academia (training) & contractors • Authorized agents of public health departments

  4. Privacy and Confidentiality • Health departments have strong tradition of maintaining security of confidentiality information • Public health provisions in HIPAA • Data collected under auspices of bioterrorism surveillance de-linked from any identifiers for non-BT surveillance

  5. Goals • Early detection of large outbreaks • Characterization of size, spread, and tempo of outbreaks once detected • Monitoring of disease trends

  6. Potential Syndromic Surveillance Data Sources • Day 1- feels fine • Day 2- headaches, fever- buys Tylenol • Day 3- develops cough- calls nurse hotline • Day 4- Sees private doctor: “flu” • Day 5- Worsens- calls ambulance seen in ED • Day 6- Admitted- “pneumonia” • Day 7- Critically ill- ICU • Day 8- Expires- “respiratory failure”

  7. Potential Syndromic Surveillance Data Sources • Day 1- feels fine • Day 2- headaches, fever- buys Tylenol • Day 3- develops cough- calls nurse hotline • Day 4- Sees private doctor: “flu” • Day 5- Worsens- calls ambulance seen in ED • Day 6- Admitted- “pneumonia” • Day 7- Critically ill- ICU • Day 8- Expires- “respiratory failure” Pharmaceutical Sales Nurse’s Hotline Managed Care Org Absenteeism Ambulance Dispatch (EMS) ED Logs Traditional Surveillance

  8. Pharmacy Emergency Department Data Transfer EMS

  9. Data requirements • Core variables • Hospital name • Date of visit • Time of visit • Age • Sex • Chief complaint (free text) • Home zip code • +/- Unique identifier • Discharge diagnosis not generally available in timely manner • Need to consider response protocols – patient identification, logistics

  10. Electronic coding of chief complaints into clinical syndromes • Performed in SAS • Text-string recognition • Mutually exclusive vs. overlapping • Hierarchy of coding • Iterative refinement of syndrome definition • Entire dataset can be recoded easily – allows for changes in definition and addition of new syndromes

  11. Electronic ED logs AGE SEX TIME CHIEF COMPLAINT ZIP 15 M 01:04 ASSAULTED YESTERDAY, RT EYE REDDENED.11691 1 M 01:17 FEVER 104 AS PER MOTHER. 11455 42 F 03:20 11220 4 F 01:45 FEVER, COUGH, LABORED BREATHING. 11507 62 F 22:51 ASTHMA ATTACK. 10013 48 M 13:04 SOB AT HOME. 10027 26 M 06:02 C/O DIFFICULTY BREATHING. 66 M 17:01 PT. MOTTLED AND CYANOTIC. 10031 Text Recognition with SAS IF index(cc,"FEV")>0 or index(cc,"HIGH TEMP")>0 or index(cc,"NIGHT SWEAT")>0 or (index(cc,"CHILL")>0 and index(cc,"ACHILLES")=0) or index(cc,"780.6") etc. then FEVER=1;

  12. Data Summary EMS ED Pharmacy

  13. Data Summary EMS ED Pharmacy

  14. Data Summary EMS ED

  15. Denominator Surveillance is Less Sensitive than Syndromic Total Visits Fever/Respiratory GI/ Vomiting

  16. Selected Antibiotic and Antiviral Prescriptions 1997-2002

  17. ED Respiratory Visits, Nov-May

  18. ED respiratory visits EMS calls Pharmacy Antiviral Rx Subway worker- “flu”

  19. West Nile Virus ActivityThrough September 2001

  20. Tabletop Drills REDEX (2001) Test of 911-EMS System SANDBOX (2002) Test of ED System

  21. Nov 12 9.17 am Flight AA 587 Crashes in Rockaways Respiratory Zip Code Signal (7 zips) 27 Observed / 10 Expected p<0.001 Hospital Signal 31 Observed/ 16 Expected p<0.05

  22. Investigation • Key Questions • True increase or natural variability? • Bioterrorism or self-limited illness? • Available Methods • “Drill down” • Query clinicians/ laboratories • Chart reviews • Patient followup • Increased diagnostic testing

  23. Investigation • Checked same-day logs at 2 hospitals Increase not sustained • Chart review in one hospital (9 cases) • Smoke Inhalation (1 case) • Atypical Chest Pain/ Anxious (2 cases) • Shortness of Breath- “Psych” (1 case) • Asthma Exacerbation (3 cases) • URI/LRI (2 cases)

  24. Future Directions • Research Agenda • More evaluations- Simulation models and “spiked” validation datasets • Better cluster detection software • Signal Integration • Optimizing response protocols- Inexpensive (and accurate) rapid diagnostics • Emergency Department Surveillance • Chief Complaint and/or Discharge Diagnosis • HL7 Standards • Need standard cc->syndrome coder (SAS)

  25. Is It Worth the Effort? • Costs • Implementation costs can be modest • Operational costs=time of public health staff, investigations • Benefits • Possibility of huge benefit if early detection • Characterization • Strengthening traditional surveillance • Dual Use

  26. “Dual Use” • Opportunity to use new syndromic surveillance infrastructure other public health activities as well as for bioterror events • Can enhance all public health efforts • Sets higher standard for all surveillance (e.g., laboratory)

  27. Cipro and Doxycycline Prescriptions

  28. Drug Overdose • Epidemiology of drug overdoses • Detection of outbreaks Day of Week Sat Fri Day of Month

  29. New Year’s

  30. Suicidal Ideation/AttemptsNov. 2001 to Sept. 19, 2002

  31. Asthma ED Visits and EMS Calls

  32. Improvement in Asthma Treatment

  33. So What? • Strengthened surveillance systems in place • Potential to better monitor all public health situations • Even if there are no more bioterror attacks, preparation can strengthen our public health infrastructure and ability to respond • “Syndromic” surveillance vs. better surveillance

  34. Acknowledgements NYCDOH Syndromic Surveillance Team: Joel Ackelsberg Sharon Balter Katie Bornschlegel Bryan Cherry Hyunok Choi Debjani Das Jessica Hartman Rick Heffernan Adam Karpati Marci Layton Jennifer Leng Karen Levin Mike Phillips Sudha Reddy Rich Rosselli Polly Thomas Don Weiss Field teams MIS staff

  35. Spatial ScanStatistic • Developed by Martin Kulldorff • Flexible windows in time and space • Probability through Monte Carlo simulations • Controls for multiple comparisons • Modified for infectious disease surveillance

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