Transcript Document

Implementing a Syndromic
Surveillance System: Objectives,
Policy and Cost
Aaron Fleischauer, PhD, MPH
Bioterrorism Preparedness and Response Program
National Center for Infectious Diseases
Objectives
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What is Syndromic Surveillance?
Where syndromic surveillance fits in?
How it works?
Challenges and limitations
Policy issues with implementing a system
Cost and burden
Definition
“The collection and analysis of healthrelated data that precede diagnosis and
signal a sufficient probability of case or an
outbreak to warrant further public health
response.”
Rationale
Number of Cases
PRODROME
SEVERE ILLNESS
RELEASE
0
1
2
3
4
5
6
7
8
9 10 11 12 13 14 15 16 17
Notifiable Disease Reporting
Syndromic Surveillance
Rationale
Number of Cases
PRODROME
SEVERE ILLNESS
EXPOSURE
0
1
2
3
4
5
6
7
8
9 10 11 12 13 14 15 16 17
Notifiable Disease Reporting
Syndromic Surveillance
Increase sensitivity &
timeliness of outbreak
detection
Strategies
1. Make outbreaks of any kind & individual cases of
unusual disease officially reportable 24/7
2. Routine use of PFGE fingerprinting (PulseNet) and
the Laboratory Response Network (LRN) with sharing
of information across states to identify clusters/ cases.
3. Automated analysis of reportable disease/lab data
4. Implement syndromic surveillance
5. Environmental monitoring (e.g., Biowatch, BDS)
Syndromic Surveillance Process
Laboratory Tests
EMS
Nursing Hotlines
Emergency
Departments
Syndromic
Surveillance
Data Sources
Poison
Control
Veterinarian Clinics
Prescription Drugs
School
Absentee
Over-the-counter
ED collects data
on each patient
Step 1
Syndromic
Surveillance
Process
Send data (e.g., 24 hours) via
secure server to Health Department
ED collects data
on each patient
Step 2
Syndromic
Surveillance
Process
Electronic ED Data
--
Date
Time Sex
Age Birth date Chief Complaint
---------------------------------------------------------08/08/2004 00:28 Female 13 01/31/1991 MIGRAINE NAUSEA
08/08/2004 00:38 Female 29 08/23/1974 COUGH,FEVER
08/08/2004 00:50 Male
48 09/01/1955 HUMAN BITE TO CHEST
08/08/2004 01:44 Male
53 07/29/1951 ABD PAIN, GENERAL
08/08/2004 09:00 Male
6 02/16/1998 N & VOMITING X 3
08/08/2004 09:21 Male
50 07/21/1954 SPRAIN ANKLE
08/08/2004 09:29 Female
1 03/21/2004 CRYING & FUSSINESS
08/08/2004 09:42
-CK
NG
s.
ER
x3
VA
- Hospital A, August 8, 2004
Syndromes
[]
Upper or lower respiratory tract infection with fever
[ ]
Diarrhea/ gastroenteritis
[ ]
Rash with fever
[ ]
Sepsis or non-traumatic shock
[ ]
Meningitis or encephalitis
[ ]
Botulism-like syndrome
[ ]
Unexplained death with history of fever
[ ]
Lymphadenitis with fever
[ ]
Localized cutaneous lesion
[ ]
Myalgia with fever/ rigors and malaise
Send data (e.g., 24 hours) via
secure server to HD
ED collects data
on each patient
Hospital can receive reports or
view data
Step 3
Syndromic
Surveillance
Process
HD performs
aberration
detection and
analyses
Early Aberration Reporting System (EARS)
Washington County
ALL HOSPITALS
Respiratory with
Fever/ ILI
Signal
Moving 7-day baseline
Send data (e.g., 24 hours) via
secure server to HD
ED collects data
on each patient
Hospital can receive reports or
view data
Step 4
Syndromic
Surveillance
Process
Signals require further
analysis and
interpretation
HD performs
aberration
detection and
analyses
Total GI (Last 24
Hrs): 2
Total GI (Last 24
Hrs): 0
Total GI (Last 24
Hrs): 0
Total GI (Last 24
Hrs): 1
Total GI (Last 24
Hrs): 0
Total GI (Last 24
Hrs): 3
Total GI (Last 24
Hrs): 1
Total GI (Last 24
Hrs): 2
Total GI (Last 24
Hrs): 4
Total GI (Last 24
Hrs): 1
Send data (e.g., 24 hours) via
secure server to HD
ED collects data
on each patient
Hospital can receive reports or
view data
Step 5
Epidemiologists
investigate
Signals
Syndromic
Surveillance
Process
Signals require further
analysis and
interpretation
HD performs
aberration
detection and
analyses
Phased Response
Phase I
System attributes
Strengths and limitations of statistical algorithms
Sensitivity and specificity of data types (e.g., over-thecounter pharmaceuticals, chief complaint, diagnoses)
Consideration of data source (e.g., Target population)
Phase II
Descriptive analysis
Performing stratified analyses (by age, gender, time,
geography)
Consistency of patient-specific reports
Phase III
Comparisons
Comparisons with alternate data sources
Phase IV
Investigation
Field investigation, (Phone call, Visit, Review of records)
Interpreting of data within context (e.g. OTC drug sales)
Challenges and Limitations
Signal
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What questions are being asked of
these data?
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Specific questions to non-specific
data
Limitations
Signal to noise (false positives)
 Signal desensitization
 Cost and resources
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Sufficient Probability
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Assessed by performing validations
1.
2.
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Validate syndrome case definitions
Validate system to detect outbreaks
Sensitivity and specificity
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Improving sensitivity
Increase false positive rate
Response
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What signals warrant further public health
response?
 Thresholds
 Sufficient
size of the event
 Among Syndromes
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Do all data sources have a response?
 Emergency
Departments
 Over-the-counter Pharmaceuticals
Policy Issues
Example: The Boston City
Health Commission
Background
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Previous outbreak detection systems
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Reportable Disease Surveillance
Volume-based ED surveillance
Both mandated by City Regulation
Democratic National Convention
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Pressure to implement electronic
ED-based syndromic surveillance
Stakeholders
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All Hospitals and Urgent Care Centers operating
an Emergency Department in Boston
HIPAA
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Privacy rule expressly permits use of protected
health information for:
 Reportable
disease reporting
 Public health surveillance
 Epidemiologic investigation
Includes patient identifiable information
 Limited Data Set Rule
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Public Health Regulation
DISEASE SURVEILLANCE AND REPORTING
REGULATION
PREAMBLE
WHEREAS, The Boston Public Health Commission is charged with protecting,
preserving and promoting the health and well-being of all Boston residents,
particularly those who are most vulnerable.
WHEREAS, The Boston Public Health Commission is charged with…
Disease Surveillance
Regulation
All health care facilities in the City of Boston that operate or maintain an
emergency department and/or an urgent care facility, shall report for
each visit during a twenty-four (24) hour period, to such emergency
department or urgent care facility, the following information about each
patient:
a. Age;
b. Gender;
c. Race/Ethnicity;
d. Residential zip code;
e. Chief complaint; and
f. Diagnostic code (if available).
CSTE concerns
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Cost implications of monitoring syndromic
surveillance systems and following up aberrations
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With BT funding decreasing, evaluation of cost
and effectiveness relative to other strategies for
early detection of diseases of concern is badly
needed
Estimating Cost
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Difficult to measure
Parameters requiring estimates
Software packages
 Data transfer mechanisms
 Person-time and dedicated staff
 R&D and Maintenance
 Investigation of aberrations
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Estimated Costs: NYC
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Start-up costs
Developed from post-9/11 drop-in system
 Paper-based with deployed staff to area hospitals
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Electronic system
Direct annual costs estimated at $150,000/ year
 Not including cost associated with:
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 Research
and development
 Surveillance for non-infectious outcomes
 Data transmission costs incurred by hospitals
Aberration Detection
Software
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EARS (Early Aberration Reporting System)
Developed by CDC (Lori Hutwagner)
 Shareware, available free of cost
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RODS (Real-time Outbreak Detection Software)
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Shareware, with ~$350/hour support/consult fees
Other packages from private vendors
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May average ~$50,000
Final Thoughts
CSTE Recommendation
Need evaluation of syndromic surveillance and a
critical determination made as to whether it should
be used routinely for aberration detection – or only in
special circumstances (public health events)?
We should not be expanding it without evaluation.
CSTE Position on
Syndromic/ Bioterrorism
Surveillance
Recommendations:
CDC form an advisory group to review all efforts
at improving BT surveillance and advise re:
which are worth keeping and funding, which
should be encouraged of all states, and which
should be scrapped.
www.cste.org - position statements
For more information:
Websites:
www.syndromic.org
http://www.cdc.gov/epo/dphsi/syndromic
http://www.bt.cdc.gov/surveillance/ears
Signal
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Detection scenario
Stoto et al. Chance 2004; 17(1): 19-24
 Excess
of 9 cases over two days
 3X
daily average
 50% probability of alarm
 Excess
of 18 cases over 9 days
until 9th day
 50% probability of alarm
 Not