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Climate & Health Syndromic Surveillance
Matthew Roach, MPH Climate & Health Program Manager
Arizona Department of Health Services Workshop on Syndromic Surveillance of Health and Climate-Related Impacts
3/17/2014
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Conflict of Interest Declaration
No Conflict of Interest
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What is Syndromic Surveillance?
• CDC Definition: “an investigational approach where health department staff, assisted by automated data acquisition and generation of statistical alerts, monitor disease indicators in real-time or near real-time to detect outbreaks of disease earlier than would otherwise be possible with traditional public health methods”
http://www.cdc.gov/mmwr/preview/mmwrhtml/su5301a3.htm
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What is Syndromic Surveillance? (2)
• Made for early detection of a large-scale release of a biologic agent – Current surveillance goals reach beyond terrorism
preparedness.
• The fundamental objective of syndromic surveillance is to: – identify illness clusters early, before diagnoses are
confirmed and reported to public health agencies
– and to mobilize a rapid response, thereby reducing morbidity and mortality. http://www.cdc.gov/mmwr/preview/mmw
rhtml/su5301a3.htm
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What is Syndromic Surveillance? (3)
• Specific definitions for syndromic surveillance are lacking, and the name itself is imprecise.
– Certain programs monitor surrogate data sources (e.g., over-the-counter prescription sales or school absenteeism), not specific disease syndromes.
• Emphasis on prediagnostic data
• Emphasis on monitoring the frequency of illnesses with a specific set of clinical features.
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Meaningful Use and Arizona’s Public Health Systems
• As a part of the American Recovery and Reinvestment Act, Congress authorized: – $25 billion in incentive payments to hospitals and healthcare
providers to facilitate the adoption of meaningful use of certified electronic health records (EHR’s).
– Incentive payments of up to $44,000 through the Medicare incentive program or $63,750 through the Medicaid incentive program can be made to eligible professionals (EPs) and hospitals.
• To receive incentive payments, providers must meet and
maintain a set of meaningful use measures using a certified EHR.
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Why do we need Meaningful Use?
Meaningful Use provides an opportunity to create
better integration between public health and health care
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Meaningful Use
• ADHS is using the Biosense system and the PHIN Messaging Guides for Syndromic Surveillance for Meaningful Use.
• Meaningful Use Objective Capability to submit electronic syndromic surveillance data to public health agencies and actual submission according to applicable law and practice.
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SYNDROMIC SURVEILLANCE AND BIOSENSE 2.0
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BioSense 2.0 System
• BioSense 2.0 is a cloud-enabled web application providing commercial hosting, provisioning, and support
• The BioSense 2.0 application/environment has been authorized to operate through the CDC Certification and Accreditation process and is governed by ASTHO
• The tool used to support Meaningful Use Public Health activities for Eligible Hospitals and Providers
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Data Elements – BioSense 2.0
Partial List of Current Elements
• Facility Information (name, address, city, zip, etc.)
• Visit Type
• Unique Patient ID
• Medical Record Number
• Demographics (age, gender, race)
• Triage Notes
• Diagnosis
Newly Added Elements
• Procedure Code, Text and Naming System
• Date of Birth
• Unique Visit ID
• Updated Visit
• Initial Emergency Department Assessment
• Patient Death Indicator, Death Date and Time
• Blood Pressure
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BioSense 2.0 • BioSense 2.0 website:
https://biosen.se
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Output from
Biosense 2.0
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How do we get more hospitals on BioSense/Syndromic Surveillance? • First, they have a huge incentive over the next
5 years because of Meaningful Use (Syndromic Surveillance is required in Stage 2 – begins 2014)
• Second, Local Health Departments can recruit hospitals and assist in establishing a DUA by leveraging relationships with local facilities
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International Climate/Health Syndromic Surveillance Workgroup -
Participants Signed Up: – 62 People – 21 States – 1 City & 1 County Health Department – 4 Canadian Public Health Agencies – Non-profits: CSTE, NRDC
Representatives from various levels of government and programs:
– CDC BRACE States & Cities – Environmental Public Health Tracking Network States – State Health Agency Syndromic Surveillance Programs – CDC – Health Canada – Health Agencies from Several Canadian Provinces
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Goals for Syndromic Surveillance System Workgroup
• Learn about climate and health syndromic surveillance systems in the US and Canada (how they are set up, time commitment, range of coverage, benefits, drawbacks, usefulness, who has access to the data/how is data shared)
• Learn about how agencies started and then maintained their syndromic surveillance system (including legislative action, partnerships, funding)
• Share information on best practices for improving and using data from syndromic surveillance systems for climate change
Overview
Florida Department of Public Health Syndromic
Surveillance System (ESSENCE)
Electronic Surveillance System for the Early
Notification of Community-based Epidemics
(ESSENCE)
Analytic tools used to identify outbreaks or unusual
trends more rapidly, leading to a more timely public
health response
Query Development
Heat-related illness queries are based on an
ESSENCE emergency department syndrome
category
Includes chief complaint search for:
-Heat casualty
-Heat emergency
-Heat exposure
-Heat injury
-Heat related
-Heat syncope
-Over heat
-Sun exposure
-Sun rash
-Heat cramp
-Heat exacerbation
-Heat fatigue
-Heat prostration
-Heat stress
-Heat syndrome
-Over heated
-Sun poison
-Sun stroke
-Heat cramping
-Heat exhaustion
-Heat illness
-Heat rash
-Heat stroke
-Heat trauma
-Over heating
-Sun poisoning
Chief complaint free text search
Limitations/Weaknesses
Data are available from 178 hospitals and urgent care clinics in 38 counties (57% of counties have at least one hospital reporting into ESSENCE) in Florida which represents ~85% of all ED visits.
Data analyzed based on free text query. Patients presenting with other chief complaints due to physical activity or other underlying chronic conditions that heat exposure may have exacerbated will be missed in this analysis. Similarly, final physician diagnosis might differ for some of the heat- related illness cases.
There are limited details about the mode and duration of exposure to heat.
No occupational data are available.
Distribution During times of excessive heat, reports on heat-
related illness are distributed to partners for situational awareness using a listserv
Also post to EpiCom – system used to distribute public health information to partners statewide
AHEDD System Data Flow NH DPHS
1. Reviews alerts 2. Queries syndromes &
symptoms 3. Investigates & monitors
health activity
4. Follows up with hospitals
Disease Surveillance:
Heat-Related Illness Query Process Create query from CDC case definition
Start with CDC symptoms
Tweak with actual values from hospital data
Build & run real-time Chief Complaint query +heat+excessive:+heat+exhaust:+heat+exposure:+heat+fatigue:+heat+stroke:+heat+syncope:+heatstroke:+hyper+thermia:+heat+dehydra (includes and/or/exclusionary logic)
Values are pasted from Word document into AHEDD custom query tool (MS Access with Oracle database) and run
Build & run ICD-9-CM code confirmatory query 708.2, 992.0 - 992.6, 992.8, 992.9, E900.0, E900.9
Values are selected from AHEDD ICD9 Look-up query tool and run
Yearly review and modification (for greater accuracy)
Custom Query Tool
ED Syndrome Coding (1)
• Only includes chief complaint field -- availability of diagnostic
field fluctuates, potentially influencing ability to track trends
• ED syndrome searches chief complaint field for keywords:
– “HEAT ” (first word in complaint), “ HEAT ”
(surrounded by spaces), “HOT”, “992”, “HEAT ST”,
“HEATST”, “SUNSTR”, “OVERHEAT”,
“HYPERTHERMIA”, “ 992”
– “HEAT” AND any of the following words: CRAMP,
EDEMA, PASS, DIZZY, FAINT, WEAK, SYNCOPE,
PROSTRA, RASH, EX, PYREX, BREATH
Syndrome Coding (2)
• Many exclusions necessary to account for misspellings &
similar phrases in ED chief complaint, for example:
– DOG, FLASH, COUGH, PAD, HEATER, HEAT RATE,
GREAS, HOT LI, COFFEE, HEAT PALP, HEAT PULP,
HEAT RAC, ALLERG, THROAT, DIARRHEA,
INFECTION, CHEAT, DIAPER etc.
• EMS call-type = “heat”
Limits & Notes
• Relative indicator of heat-related illness, not a tally of all
“cases”
– Misclassification
– Variability of chief complaint coding methods, availability of
diagnostic codes
– Hospital reporting issues
• Absolute impact can only be assessed after the event
– Not a replacement for traditional surveillance of heat stroke
and illness
• Refinements can be made after each season to improve
performance as necessary
MICHIGAN SYNDROMIC SURVEILLANCE:
THE BASICS
The objective of the Michigan Syndromic
Surveillance System (MSSS) is to detect
bioterrorism, emerging infections, and naturally
occurring outbreaks more rapidly than through
normal physician detection and reporting
MICHIGAN SYNDROMIC SURVEILLANCE:
THE BASICS
Based on Real-Time Outbreak Detection System (RODS) developed at the University of Pittsburgh
Virtual Private Network (VPN) HL7, a healthcare messaging standard, to exchange data in real-time between participants and MDCH
Each message consists of:
Patient age, sex, home ZIP code
Visit date and time
Data exchange and acknowledgement information
Chief complaint
MICHIGAN SYNDROMIC SURVEILLANCE:
THE BASICS
Chief complaints classified into 1 of 9
syndromic categories that can be aggregated
for review and analysis
Detection algorithms runs every hour and an
alert is generated if aberration in the levels of a
syndrome is detected
Users have the ability to create Ad Hoc
searches
MSSS HEAT ILLNESS SURVEILLANCE:
OVERVIEW
Ad hoc search created
Data was downloaded and analyzed in a separate program
Maximum daily temperatures were recorded
MDCH Regional Epidemiologists created statewide heat-related illness reports weekly
A final summary for the season was also created
MSSS HEAT ILLNESS SURVEILLANCE:
AD HOC SEARCH Filter: Sun2
OR: dehyd sun prostration heat hyperthermia
NOT: Sunday heater heatrate cheat heatlh wheat flower beat
MSSS HEAT ILLNESS SURVEILLANCE:
SYNDROMES
Visits were categorized based on chief complaint
Sun-associated: sunburn, sun poisoning, sunscreen reactions
Heat-associated: heat exhaustion, heat stroke, heat reaction
Dehydration
Presentation by syndrome was monitored daily
Statewide Heat-Related ED Visits by Syndrome (April 1 – August 31, 2013)
STRENGTHS AND WEAKNESSES OF
HEAT-RELATED ILLNESS SURVEILLANCE
Strengths High statewide coverage allows for the detection of heat-
related illness anomalies sooner than healthcare provider diagnosis
Allows public health to relay important information about situational severity and groups at risk for illness
Weaknesses Potential for non-differential misclassification which is a
limitation of this study
Number of heat-related illness registrations is small which makes the data vulnerable to aberrations and geographic analysis difficult to interpret
Heat illness syndromes
• For both ED and EMS data, we track three syndromes:
– “Narrow Heat” (includes heat, heat stroke, heat
exhaustion, heat stress, hyperthermia, sunstroke, and
related terms)
– “Broad Heat” (includes above plus dehydration,
syncope, and related terms)
– “Dehydration” (includes just dehydration and related
terms)
July 4-7, 2013 Heat Event:
SS for ED Visits
Dehydration syndrome
Broad heat syndrome
Narrow heat syndrome
Results of review
ED Case Not ED Case Total Detected by SSS Narrow 15 37 52
Not Detected by SSS Narrow 121 unknown Total 136
0%
5%
10%
15%
20%
25%
30%
35%
40%
Narrow Broad Dehydration
SSS Category
Matching SSS Data to ED Visits Sensitivity for detectingED visitPositive Predictive Value
ED Case Not ED Case Total Detected by SSS Broad 49 636 685
Not Detected by SSS Broad 87 unknown Total 136
ED Case Not ED Case Total Detected by SSS Dehydration 8 111 119
Not Detected by SSS Dehydration
128 unknown
Total 136
Sensitivity of SSS Narrow for detecting ED case = 11% Positive predictive value of SSS Narrow for ED case = 29%
Sensitivity of SSS Broad for detecting ED case = 36% Positive predictive value of SSS Broad for ED case = 7%
Sensitivity of SSS Dehydration for detecting ED case = 6% Positive predictive value of SSS Dehydration for ED case = 7%
Benefits
• Good coverage of state’s population
• Near-real-time (when no other source of data is available within less than ~2 years)
• For ED data, narrow heat illness syndrome is sensitive to heat events; usually shows aberrant increase in visits during prolonged hot weather
• EMS run data may be even more sensitive to heat events - all heat syndromes show aberrant increases
• Best (only!) resource we have for understanding health effects of heat events in time to take action
Weaknesses
• Coverage of state is not complete
– ME-CDC is working to recruit more hospitals into system
• Some hospitals do not report in near-real-time – may report less frequently, or have prolonged interruptions
• Recent review showed SSS cases do not overlap well with diagnosed heat illness cases
– Transition to Biosense 2.0 may help with this; diagnosis codes could be submitted along with chief complaint field
– SSS may also capture more than just heat illness (i.e., dehydration, syncope) – important to know about those cases too
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Acknowledgements
• Arizona Department of Health Services
• Florida Department of Health
• NYC Department of Health and Mental Hygiene
• Michigan Department of Community Health
• Minnesota Department of Health
• New Hampshire Division of Public Health Services
• Maine Center for Disease Control
• Climate & Health Syndromic Surveillance Workgroup
• CDC - Climate & Health Program/BRACE Cooperative Agreement - CDC-RFA-EH13-1305
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Thank you & Questions!
Contact Information:
Matthew Roach, MPH
Climate & Health Program Manager
Arizona Department of Health Services
(602)364-3673