Using and Improving EARS for Local Public Health Biosurveillance - - PowerPoint PPT Presentation

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Using and Improving EARS for Local Public Health Biosurveillance - - PowerPoint PPT Presentation

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Using and Improving EARS for Local Public Health Biosurveillance Susan K. Barnes, MPH Monterey County Health Department and Professor Ron Fricker Naval Postgraduate School August 23, 2010 Outline of Presentation Define biosurveillance

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Using and Improving EARS for Local Public Health Biosurveillance

Susan K. Barnes, MPH

Monterey County Health Department and

Professor Ron Fricker

Naval Postgraduate School

August 23, 2010

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  • Define biosurveillance
  • Discuss evolving need for syndromic

surveillance at Health Department

  • Describe the EARS program and its use within

Monterey County

  • Quantitative and qualitative analysis of

modifications to EARS‟ logic

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Outline of Presentation

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What is Biosurveillance?

  • Homeland Security Presidential Directive

HSPD-21 (October 18, 2007):

– “The term „biosurveillance‟ means the process of active data- gathering … of biosphere data … in order to achieve early warning of health threats, early detection of health events, and

  • verall situational awareness of disease activity.” [1]
  • Syndromic surveillance:

– “…surveillance using health-related data that precede diagnosis and signal a sufficient probability of a case or an outbreak to warrant further public health response.” [2]

3 [1] www.whitehouse.gov/news/releases/2007/10/20071018-10.html [2] CDC (www.cdc.gov/epo/dphsi/syndromic.htm, accessed 5/29/07)

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  • County Health Officer wanted greater use of

real-time surveillance data

  • Preparedness grants required enhanced

surveillance

  • Lag-time in receipt of reports from local

hospitals; reports from only two hospitals

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Need for Syndromic Surveillance

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Early Aberration Reporting System (EARS)

  • Developed by the CDC
  • Originally designed to monitor for bioterrorism

during large-scale events that often have little

  • r no baseline data
  • Now used by various state and local public

health departments for routine health surveillance purposes

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EARS Program

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  • Data stays at the local level
  • Flexibility to modify syndromes as needed
  • Analysis occurs on-site
  • Decreased lag-time in reporting
  • Program available at no cost

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Benefits of the EARS Program

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Data Collection and Reporting

Health Department

Syndrome Definitions

ILI & DOSE Reports

Data Collection Data Management Analysis Reporting

Hospital 1 Hospital 3 Hospital 2 County Clinics Hospital 4

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Daily Observational and Situational Evaluation (DOSE) Report

Green Yellow Orange Green Yellow Orange Red Red Three alert flags on the previous day or three consecutive days of single or double alert flags Syndromic Surveillance*: (EARS output for Monterey County aggregate w/o clinics) [Shown as # of patients] Three alert flags on the previous day or three consecutive days of single or double alert flags 9 Lower Respiratory No alert flags on the previous day One alert flag on the previous day Neurological Total Hospital Census Two alert flags on the previous day Influenza-Like Illness

**Note that the hospital ED aggregate and syndomic surveillance only includes data from facilities providing information for the reported days.

30 Upper Respiratory One alert flag on the previous day Clinic Services Visits 319 No alert flags on the previous day 29 ED Census and Clinic Services Census*: Two alert flags on the previous day Gastrointestinal 58 6 719

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ER ILI Visits for Monterey County and California, 2009-2010 Season To Date

Note: Restricted ILI syndrome definition Emergency Room Influenza-Like Illness Visits for Monterey County and California, 2009-2010 Season To Date

1 2 3 4 5 6 7 8 9

40 41 42 43 44 45 46 47 48 49 50 51 52 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

Week Percent Influenza-Like Illness Visits (%)

California Sentinel Providers Monterey County Aggregate

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  • Designed by the CDC to be a drop-in

surveillance system

  • Increasingly being used as standard

health surveillance system

– E.g., by the Monterey County Health Department

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Early Aberration Reporting System

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Assessing Modifications to EARS

  • Flexibility of EARS is a strength
  • However, what happens when the syndrome

definitions are changed?

– I.e., how do the changes affect detection performance (sensitivity and specificity)?

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Test Outcome

Positive Negative

Actual Status

Sick

TP FN

(Type II error) Healthy

FP

(Type I error)

TN

#TP Sensitivity = #TP #FN  #TN Specificity = #TN #FP 

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Creating Syndromes

  • Syndromes derived by searching for key

words in chief complaints

  • Three important parts to the process:

– Defining symptom aliases

  • Lists of words, abbreviations, and medical jargon that are

mapped to a specific symptom

– Text matching algorithms

  • Computer logic that specifies when a match has occurred

– Syndrome definitions

  • Syndromes can be derived from the symptoms in a variety
  • f ways

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ILI Symptom Aliases

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Symptom Alias Symptom Symptom Alias Symptom Symptom Alias Symptom

SROETHROAT SORETHROAT

COL COLD C0UGH COUGH

SSORE THROAT SORETHROAT

NOSE COLD C9UGH COUGH

ST SORETHROAT

URI COLD CCOUGH COUGH

TBROAT SORETHROAT

EAR PAIN COLD CIUGH COUGH

THROAT SORETHROAT

DISCH COLD CKUGH COUGH

TH4OAT SORETHROAT

OM COLD OUGH COUGH

Actual Chief Complaint Examples: 1) NP FOR HIV TEST PER VERONICA/CHART MADE/LM

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ILI Symptom Aliases

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Symptom Alias Symptom Symptom Alias Symptom Symptom Alias Symptom

SROETHROAT SORETHROAT

COL COLD C0UGH COUGH

SSORE THROAT SORETHROAT

NOSE COLD C9UGH COUGH

ST SORETHROAT

URI COLD CCOUGH COUGH

TBROAT SORETHROAT

EAR PAIN COLD CIUGH COUGH

THROAT SORETHROAT

DISCH COLD CKUGH COUGH

TH4OAT SORETHROAT

OM COLD OUGH COUGH

Chief Complaint Examples: 1) NP FOR HIV TEST PER VERONICA/CHART MADE/LM 2) RTN RE-COLPO/LM

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ILI Symptom Aliases

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Symptom Alias Symptom Symptom Alias Symptom Symptom Alias Symptom

SROETHROAT SORETHROAT

COL COLD C0UGH COUGH

SSORE THROAT SORETHROAT

NOSE COLD C9UGH COUGH

ST SORETHROAT

URI COLD CCOUGH COUGH

TBROAT SORETHROAT

EAR PAIN COLD CIUGH COUGH

THROAT SORETHROAT

DISCH COLD CKUGH COUGH

TH4OAT SORETHROAT

OM COLD OUGH COUGH

Chief Complaint Examples: 1) NP FOR HIV TEST PER VERONICA/CHART MADE/LM 2) RTN RE-COLPO/LM 3) R/S PREV APPT CALL NOT GOING THROUGH

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Text Matching Logic Example: ILI

  • EARS (CDC) Logic

If an ILI symptom alias is found anywhere within the chief complaint text, then it will be flagged as an ILI indicator

  • Enhanced (NPS) Logic

– For short words (≤3 characters)

  • No variations on alias words allowed
  • Example: ST

– NP FOR HIV TEST PER VERONICA/CHART MADE/LM

  • Example: COL

– RTN RE-COLPO/LM

– For longer words (≥4 characters)

  • Variations on one side of the alias word is allowed
  • Example: COUGH

– PT COUGHING FOR 4 DAYS

  • Example: OUGH

– R/S PREV APPT CALL NOT GOING THROUGH 16

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ILI Syndrome Definitions

  • Expanded (MCHD) def‟n:

– “cold” or – “cough” or – “fever “or – “chills” or – “muscle pain” or – “headache” or – “flu” and not “shot”

  • Restricted (MCHD) def‟n:

– “fever” and “cough” or – “fever” and “sore throat” or – “fever” and “cough” and “sore throat” or – “flu” and not “shot”

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  • Standard EARS (CDC) def‟n:

– “sore throat” or – “cold” or – “cough”

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18 Base Case EARS Text Matching Logic EARS Symptoms Aliases EARS Syndrome Definitions

9,093 total “flu” (out of 153,696 total records)

Qualitative Comparisons Aug 1, 2008 – July 31, 2009

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19 Base Case EARS Text Matching Logic EARS Symptoms Aliases EARS Syndrome Definitions Variant 1a EARS Text Matching Logic Expanded Symptoms Aliases Expanded Syndrome Definitions Variant 2a EARS Text Matching Logic Restricted Symptoms Aliases Restricted Syndrome Definitions

9,093 total “flu” (out of 153,696 total records) 5,154 added 291 deleted 13,956 total “flu” 51 added 8,410 deleted 734 total “flu”

Qualitative Comparisons Aug 1, 2008 – July 31, 2009

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20 Base Case EARS Text Matching Logic EARS Symptoms Aliases EARS Syndrome Definitions Variant 1a EARS Text Matching Logic Expanded Symptoms Aliases Expanded Syndrome Definitions Variant 2a EARS Text Matching Logic Restricted Symptoms Aliases Restricted Syndrome Definitions Variant 2b Enhanced Text Matching Logic Restricted Symptom Aliases Restricted Syndrome Definitions Variant 1b Enhanced Text Matching Logic Expanded Symptoms Aliases Expanded Syndrome Definitions

9,093 total “flu” (out of 153,696 total records) 5,154 added 291 deleted 13,956 total “flu” 2 added 8,544 deleted 5,414 total “flu” 51 added 8,410 deleted 734 total “flu” 0 added 111 deleted 623 total “flu”

Qualitative Comparisons Aug 1, 2008 – July 31, 2009

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Qualitative Comparisons Aug 1, 2008 – July 31, 2009

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Expanded ILI Syndrome Counts vs. California Sentinel Providers

Emergency Room Influenza-Like Illness Visits for Monterey County and California, 2008-2009 Season

5 10 15 20 25 30 35 40 45

40 41 42 43 44 45 46 47 48 49 50 51 52 53 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33

Week Percent Influenza-Like Illness Visits (%)

California Sentinel Providers Monterey County Aggregate

Note: 1. Graph based on ILI chief complaint data as proportion of all patients accessing services for a given week from California sentinel providers and an aggregate from Monterey County Hospitals CHOMP, SVMH, and Mee, and Monterey County Clinical

  • Services. 2. Missing data points for Weeks 19 through 27 will be incorporated at a later date.

Source: MCHD Influenza-like Illness (ILI) Surveillance Report Week 33 Ending 8/22/09

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Restricted ILI Syndrome Counts vs. California Sentinel Providers

Note: Restricted ILI syndrome definition Emergency Room Influenza-Like Illness Visits for Monterey County and California, 2009-2010 Season To Date

1 2 3 4 5 6 7 8 9

40 41 42 43 44 45 46 47 48 49 50 51 52 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

Week Percent Influenza-Like Illness Visits (%)

California Sentinel Providers Monterey County Aggregate

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Assessing the Effects of Changes

  • How to figure out which combination of

methods works best?

  • Attempted to compare to ICD-9 codes,

but codes for Monterey clinic data not sufficiently precise

  • Currently evaluating EARS performance

in detecting 2009 H1N1 outbreak using the various definitions and logic

– Comparing signals to known cases

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In Conclusion

  • Small changes in syndrome definitions,

symptom aliases, and text-matching logic can have large effects on the resulting syndrome counts and overall “trend”

  • Recommend on-going research that conducts

comparisons between methods under various conditions

– Must assess how changes affect sensitivity and specificity

  • Exercise caution!!

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Questions?

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Susie Barnes, MPH Public Health Epidemiologist Monterey County Health Department 831-755-4698 BarnesS@co.monterey.ca.us Ron Fricker, Ph.D. Operations Research Department Naval Postgraduate School Monterey, California rdfricker@nps.edu

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Contact Information