IDENTIFYING FLU LIKE ILLNESS

1. IDENTIFYING FLU LIKE ILLNESS • AGENDA • Sit Found Program • Data analysis – Results • Sit Found Program Recommendations • Monitoring influenza-like illness (ILI) with dispatcher protocols • Dispatcher Protocol recommendations

2. IDENTIFYING FLU LIKE ILLNESS Situation Found Program Results: → 52,400 incidents cleared through the Sit Found program between July 2007 and July 2009 → 8,300 incidents with flu symptoms → Average percent of incidents with flu symptoms: 16% Range: 15.8% to 16.6% (based on 95% confidence interval)

3. IDENTIFYING FLU LIKE ILLNESS

4. IDENTIFYING FLU LIKE ILLNESS • Situation Found Program Results - continued: • → Flu symptoms started to increase in late April 2009, peaked in May and returned to normal levels in June. (H1N1 outbreak period) • → No difference between ‘flu seasons’ – i. e., flu-like symptoms found during the 2007 and 2008 flu seasons are about the same. • → Lower number of flu symptoms were found during the “non-flu season” periods than during the flu seasons. (Which should be expected)

5. IDENTIFYING FLU LIKE ILLNESS Situation Found Program Results - continued: → Comparing Age Groups from Sit Found with Age Groups on medical incident reports (Form 20B): → Not much difference in what is being collected thru Sit Found and what is recorded on the Form 20B (F20B)

6. IDENTIFYING FLU LIKE ILLNESS • Situation Found Program Results - continued: • → 92% of patients with flu symptoms had a “medical illness” mechanism (from Form 20B data) • Of those 90% had medical conditions indicating an illness, • However, many illnesses identified on the medical reports are not flu – e. g., asthma) • → The next slide/table shows the distribution of Medical Incident Types for patients that had flu symptoms and “MD” mechanisms.

7. Medical Incident Types of Patients with Flu Symptoms & MD Mech

8. IDENTIFYING FLU LIKE ILLNESS Situation Found Program Results - continued: → Combinations of some symptoms were not prevalent or closely associated with a medical illness. → As indicated in the next slide.

9. Distribution of Incident Types: MD Mech Code vs. All Sit Found Incidents

10. IDENTIFYING FLU LIKE ILLNESS Situation Found Program Results - continued: → Pre-dominant symptoms: Respiratory, Gastro, Fever, Cough. → Respiratory – by itself - may not be a useful measure of ILI. → Gastro – by itself - may not be a useful measure of ILI. → Rash may not be a useful measure of ILI either by itself or in combination with other symptoms (< 4% of incidents).

11. IDENTIFYING FLU LIKE ILLNESS • Situation Found Program Results - continued: • → Other than FEVER a single symptom may not be an effective measure of influenza-like illness • “Effectiveness” meaning that we are capturing enough “positive-positive” data and minimizing “false-positive” data for purposes of the determining if and when an outbreak is occurring. • → The next slide shows the distribution of medical illnesses for patients that Fever or any other combination of flu symptom (excluding individual symptoms of Rash, Gastro, Respiratory and Cough)

12. IDENTIFYING FLU LIKE ILLNESS • Situation Found Program Results - continued: • → The following two charts show the trends for: • Chart A: Patients that had Fever OR any other combination of flu symptom that included fever, cough, respiratory, etc. This chart excludes patients/incidents were a single instance of Rash, Gastro, Respiratory or Cough was found • Chart B: Patients that had Fever, or Cough or Respiratory OR any other combination of flu symptom. This chart excludes patients/incidents were a single instance of Rash or Gastro was found

16. IDENTIFYING FLU LIKE ILLNESS Situation Found Program Recommendations: → Improve performance of the software program used by firefighters in the field to increase the timeliness of reporting (and as a result the alerting) → Reduce the amount of information being collected. E. g. drop the following: (1) Travel, exposure (2) Rash (3) Age & Sex → Consider combination symptom buttons (instead of individual symptoms) OR modify program to require combinations to be entered if Respiratory, Rash, Gastro or Cough are selected. I. e., you can’t just pick one.

17. IDENTIFYING FLU LIKE ILLNESS • Situation Found Program Recommendations: • → Revise triggers and alerting AND develop response plans accordingly. • Drop individual flu symptom alerts (but still monitor) • Use only one flu symptom trigger that is based on Fever (alone) and combinations of symptoms (Cough with Fever, Respiratory with Cough, etc.) • Re-establish 2X Std Dev as threshold to be consistent with other jurisdictions and agencies using syndromic surveillance.

18. IDENTIFYING FLU LIKE ILLNESS Situation Found Program Recommendations: → Incorporate use of the First Watch surveillance/alerting system into the Department Pandemic Flu Plan. → Coordinate use of the First Watch surveillance/alerting system with KC Public Health and NORCOM (Eastside Communications Center which is also using First Watch).

19. IDENTIFYING FLU LIKE ILLNESS • Using Dispatcher Protocols and Comments: • → Almost all jurisdictions monitoring flu outbreak use dispatch protocols (along with other sources) to measure flu outbreak. • Ref: • The Australian pre-hospital pandemic risk perception study and an examination of new public health roles in pandemic response for ambulance service. University of Queensland & Monash University 2008. • CDC recommendations for 9-1-1 call center dispatching.

20. IDENTIFYING FLU LIKE ILLNESS • Using Dispatcher Protocols and Comments: • → In June 2009 the First Watch program started monitoring protocols and dispatcher comments: • PPE Advised (based on responses to Breathing questions) • Protocol 12./8 (Breathing – Other respiratory) • Protocol 32/7 (Sick Unknown – Fever or Cough) • Alerts have not been set yet until SFD evaluates the data and monitoring so far.

21. IDENTIFYING FLU LIKE ILLNESS From an evaluation of historical data: → 89% of incidents dispatched July 1, 2007 – June 29, 2009 with “PPE Advised” had flu symptoms found at the scene. → 75% of incidents dispatched with “febrile, fever, cough or respiratory” in the dispatcher comments (no PPE Advised) had flu symptoms found at the scene. → 82% of incidents dispatched with protocol 32/7 had flu symptoms found at the scene. → 54% of incidents dispatched with protocol 12./8 had flu symptoms found at the scene.

22. IDENTIFYING FLU LIKE ILLNESS From an evaluation of historical data: Comments: → “Match rate” between PPE Advised, illness comments, 32/7 and Sit Found would be higher if compliance was higher. → Match rate between PPE Advised and Sit Found would be higher if ‘’PPE Advised’ received some emphasis in call processing. → Protocol 12./8 is too generic to be associated with flu-like illness

25. IDENTIFYING FLU LIKE ILLNESS • Using Dispatch Protocols and Comments - Recommendations: • → Continue with current protocols and emphasize consistent use of PPE Advised for flu-like illness. • → Continue monitoring of protocol 32/7; drop 12./8 • → Consider modifying protocols to: • Ask question or questions at the end of EMD about fever, cough, etc. Incorporate flu symptom question into an • existing protocol • → Incorporate dispatch procedures into the SFD Pandemic Flu Plan • I. e., describe what will be monitored, what thresholds are set and what the SFD reaction will be when thresholds are exceeded.