identifying flu like illness agenda sit found program data analysis – results sit found program...
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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
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)
IDENTIFYING FLU LIKE ILLNESS
07/15/2
007
08/12/2
007
09/09/2
007
10/07/2
007
11/04/2
007
12/02/2
007
12/30/2
007
01/27/2
008
02/24/2
008
03/23/2
008
04/20/2
008
05/18/2
008
06/15/2
008
07/13/2
008
08/10/2
008
09/07/2
008
10/05/2
008
11/02/2
008
11/30/2
008
12/28/2
008
01/25/2
009
02/22/2
009
03/22/2
009
04/19/2
009
05/17/2
009
06/14/2
009
07/12/2
0092.0%
7.0%
12.0%
17.0%
22.0%
27.0%
CHART A - Percent of Incidents with Flu SymptomsJuly 1, 2007 - July 30, 2009(14 day moving average)
January 28, 2009May 13, 2009
<--Oct 07 – Apr 08-->
Flu Season
<--Oct 08 – Apr 09-->Flu Season
March 11, 2008
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)
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)
AGE GROUP Sit Found
Form 20B
0-2 yrs 4% 3%
2-4 yrs 2% 1%
5-17 yrs 3% 4%
18-44 yrs 23% 23%
45-64 yrs 29% 29%
>=65 yrs 39% 40%
AGE GROUP SitF - Male
F20B-Male
SitF-Female
F20B-Female
0-2 yrs 5% 4% 3% 3%
2-4 yrs 3% 2% 1% 1%
5-17 yrs 4% 4% 3% 3%
18-44 yrs 21% 21% 25% 24%
45-64 yrs 33% 33% 25% 26%
>=65 yrs 35% 37% 42% 44%
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.
Medical Incident Types of Patients with Flu Symptoms & MD Mech
Inc# inctype_descrip Cnt % Cum%
221Respiratory-Respiratory difficulty ( shortness of breath, asthma, COPD, emphysema) 2082 27% 27%
241 Abdominal-Abdominal pain 904 12% 39%
249 Abdominal-Other abdominal (incl. Nausea, vomiting, diarrhea) 867 11% 50%299 Other Illness-Other illness 740 10% 59%284 Other Illness-Fever/Infection 651 8% 68%229 Respiratory-'Other respiratory 404 5% 73%232 Neurologic-Syncope 175 2% 75%281 Other Illness-Non-cardiac chest pain 171 2% 78%231 Neurologic-Seizure 125 2% 79%212 Cardiovascular-Suspected MI 124 2% 81%214 Cardiovascular-CHF (incl. Pulmonary edema) 121 2% 82%242 Abdominal-Internal bleeding 115 1% 84%288 Other Illness-Anaphylaxis 90 1% 85%236 Neurologic-Decreased level of consciousness 87 1% 86%239 Neurologic-Other neurologic 73 1% 87%282 Other Illness-Undefined musculo-skeletal pain 70 1% 88%219 Other cardiac 68 1% 89%279 Pediatric-Other pediatric 67 1% 90%
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.
Patients with MD Mechanism and Flu SymptomsSymptom Count Percent CumRespiratory 2356 33.4% 33.4%Gastro 1850 26.2% 59.6%Fever 619 8.8% 68.4%CoughResp 516 7.3% 75.7%Cough 294 4.2% 79.9%FeverGastro 269 3.8% 83.7%CoughFeverResp 266 3.8% 87.5%FeverResp 178 2.5% 90.0%Rash 135 1.9% 91.9%CoughFever 118 1.7% 93.6%CoughFeverGastroResp 75 1.1% 94.6%CoughGastro 71 1.0% 95.6%GastroResp 55 0.8% 96.4%FeverGastroResp 51 0.7% 97.2%CoughFeverGastro 46 0.7% 97.8%RashResp 43 0.6% 98.4%CoughGastroResp 40 0.6% 99.0%FeverRash 17 0.2% 99.2%GastroRash 13 0.2% 99.4%CoughRashResp 10 0.1% 99.5%FeverGastroRash 5 0.1% 99.6%FeverRashResp 5 0.1% 99.7%
Distribution of Incident Types: MD Mech Code vs. All Sit Found Incidents All Incidents
Symptom Count Percent CumRespiratory 2760 33.0% 33.0%Gastro 2201 26.3% 59.4%Fever 730 8.7% 68.1%CoughResp 576 6.9% 75.0%Cough 389 4.7% 79.6%FeverGastro 311 3.7% 83.4%CoughFeverResp 306 3.7% 87.0%Rash 200 2.4% 89.4%FeverResp 200 2.4% 91.8%CoughFever 133 1.6% 93.4%CoughGastro 86 1.0% 94.4%CoughFeverGastroResp 85 1.0% 95.5%GastroResp 64 0.8% 96.2%FeverGastroResp 56 0.7% 96.9%RashResp 55 0.7% 97.5%CoughFeverGastro 52 0.6% 98.2%CoughGastroResp 44 0.5% 98.7%FeverRash 23 0.3% 99.0%GastroRash 18 0.2% 99.2%CoughRashResp 17 0.2% 99.4%FeverRashResp 8 0.1% 99.5%CoughFeverRashResp 7 0.1% 99.6%FeverGastroRash 6 0.1% 99.6%CoughFeverGastroRashResp 6 0.1% 99.7%CoughFeverRash 5 0.1% 99.8%CoughRash 5 0% 100%CoughGastroRash 4 0% 100%GastroRashResp 4 0% 100%FeverGastroRashResp 3 0% 100%CoughGastroRashResp 3 0% 100%
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).
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)
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
07/15/2
007
08/01/2
007
08/18/2
007
09/04/2
007
09/21/2
007
10/08/2
007
10/25/2
007
11/11/2
007
11/28/2
007
12/15/2
007
01/01/2
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01/18/2
008
02/04/2
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02/21/2
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03/09/2
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03/26/2
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04/12/2
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04/29/2
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05/16/2
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06/02/2
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06/19/2
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07/06/2
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07/23/2
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08/09/2
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08/26/2
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09/12/2
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09/29/2
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10/16/2
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11/02/2
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11/19/2
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12/06/2
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12/23/2
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01/09/2
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01/26/2
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02/12/2
009
03/01/2
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03/18/2
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04/04/2
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04/21/2
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05/08/2
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05/25/2
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06/11/2
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06/28/2
009
07/15/2
0090.0%
2.0%
4.0%
6.0%
8.0%
10.0%
12.0%
14.0%
CHART A - Fever and All Other Combo of Symptoms (Excl. single symptom incidents of Cough, Respiratory, Gastro, Rash)
July 1, 2007 to July 30, 200914-Day Moving Avg
<----Oct 07 to Apr 08 ---->Flu Season
<----Oct 08 to Apr 09 ---->Flu Season
07/15/2
007
08/01/2
007
08/18/2
007
09/04/2
007
09/21/2
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10/08/2
007
10/25/2
007
11/11/2
007
11/28/2
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12/15/2
007
01/01/2
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01/18/2
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02/04/2
008
02/21/2
008
03/09/2
008
03/26/2
008
04/12/2
008
04/29/2
008
05/16/2
008
06/02/2
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06/19/2
008
07/06/2
008
07/23/2
008
08/09/2
008
08/26/2
008
09/12/2
008
09/29/2
008
10/16/2
008
11/02/2
008
11/19/2
008
12/06/2
008
12/23/2
008
01/09/2
009
01/26/2
009
02/12/2
009
03/01/2
009
03/18/2
009
04/04/2
009
04/21/2
009
05/08/2
009
05/25/2
009
06/11/2
009
06/28/2
009
07/15/2
0090.0%
2.0%
4.0%
6.0%
8.0%
10.0%
12.0%
14.0%
16.0%
18.0%
20.0%
CHART B- Percent of Incidents with Cough or Fever or Respiratory (plus combinations of these 3 plus
any combination that includes Gastro or Rash)July 1, 2007 - July 29, 2009
<--Sep 07 to Apr 08 -->
Flu Season
<--Sep 08 to Apr 09 -->
Flu Season
07/15/2
007
08/01/2
007
08/18/2
007
09/04/2
007
09/21/2
007
10/08/2
007
10/25/2
007
11/11/2
007
11/28/2
007
12/15/2
007
01/01/2
008
01/18/2
008
02/04/2
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02/21/2
008
03/09/2
008
03/26/2
008
04/12/2
008
04/29/2
008
05/16/2
008
06/02/2
008
06/19/2
008
07/06/2
008
07/23/2
008
08/09/2
008
08/26/2
008
09/12/2
008
09/29/2
008
10/16/2
008
11/02/2
008
11/19/2
008
12/06/2
008
12/23/2
008
01/09/2
009
01/26/2
009
02/12/2
009
03/01/2
009
03/18/2
009
04/04/2
009
04/21/2
009
05/08/2
009
05/25/2
009
06/11/2
009
06/28/2
009
07/15/2
0090.0%
2.0%
4.0%
6.0%
8.0%
10.0%
12.0%
14.0%
16.0%
18.0%
20.0%
CHART C - Combined Chart B and Chart CJuly 1, 2007 to July 30, 2009 - 14-Day Moving Avg
Correlation Coef.: 0.876
Fever and Other Combo Cough,Fever,Resp and Other Combo
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.
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.
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).
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:
(1)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.
(2)CDC recommendations for 9-1-1 call center dispatching.
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.
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.
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
09/0
1/20
07
10/0
1/20
07
11/0
1/20
07
12/0
1/20
07
01/0
1/20
08
02/0
1/20
08
03/0
1/20
08
04/0
1/20
08
05/0
1/20
08
06/0
1/20
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07/0
1/20
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08/0
1/20
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09/0
1/20
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10/0
1/20
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11/0
1/20
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12/0
1/20
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01/0
1/20
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02/0
1/20
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03/0
1/20
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04/0
1/20
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05/0
1/20
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06/0
1/20
09
07/0
1/20
09
0.00
0.50
1.00
1.50
2.00
2.50
CHART E - 14 Day Mov Avg of Incidents with Flu Symp & Dispatcher Comments (Febrile, Fever, Cough, PPE, Respiratory)
April 18, 2009
7 2007
8 2007
9 2007
10 2007
11 2007
12 2007
1 2008
2 2008
3 2008
4 2008
5 2008
6 2008
7 2008
8 2008
9 2008
10 2008
11 2008
12 2008
1 2009
2 2009
3 2009
4 2009
5 2009
6 2009
7 2009
0
20
40
60
80
100
120
CHART F - All PPE Advised Incidents & PPE Advised With Flu Symptoms by Month
Correlation Coeff: 0.828
PPEAdvised-All WithFlu
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.