NYC Syndromic Surveillance

IFH HIT Meaningful Use Workshop10/1/2010

Marlena Plagianos, MSNYCDOHMH

mplagian@health.nyc.gov

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What is Biosurveillance?• “Collection and integration of timely health-

related information for public health action achieved through the early detection, characterization, and situation awareness of exposures and acute human health events of public health significance.”

Aaron T Fleischauer, PhD; Pamela S Diaz, MD; Daniel M Sosin MD . Biosurveillance:A Definition, Scope and Description of Current Capability for a National Strategy.Advances in Disease Surveillance 2008;5:175

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Traditional Surveillance• Case definitions• Historically low

compliance• Laboratory

confirmation can be slow

• Still important (e.g. H1N1 in NYC)

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Laboratory Confirmation

•Making firm diagnosis commonly relies on lab result•Limited in-house testing in outpatient setting (minutes)•Commercial laboratory testing takes time (days-weeks)

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Traditional Reporting is Labor Intensive

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Traditional Reporting is Labor Intensive

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Syndromic Surveillance• Pre-diagnostic indicators of disease• Readiness scenarios: bioterrorism,

pandemics• Objectives:

– Timely, sensitive, specific surveillance– Detect outbreak before ‘astute clinician’

• Typical Process

Collect data

Process & code data

Establish baseline

Identify outbreak

Sound alarm

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New and Exciting Data Types

Data source Level of data

Data type Setting Care phase

Medication sales Aggregate Drug category Pre-clinical Pre-diagnosticSchool absences Aggregate Frequency Pre-clinical Pre-diagnosticNurse hotline call Individual Call type Pre-clinical Pre-diagnostic

Chief complaint / Reason for Visit

Individual Text, brief Clinical Pre-diagnostic

EMS call Individual Run type Clinical Pre-diagnosticTemperature Individual Vital sign Clinical Pre-diagnosticRadiology Report Individual Text, narrative Clinical Pre-diagnosticChest X-ray Individual CPT code Clinical Pre-diagnosticDiagnosis code Individual ICD9 code Clinical DiagnosticProgress Note Individual Text, narrative Clinical Diagnosis

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EHR Syndromic Surveillance• The Primary Care Information Project (PCIP) uses

different EHR data sources to conduct & pilot its syndromic surveillance activities

• Some syndromes tracked using EHR data are:– Influenza-like Illness (ILI)– Fever– Gastrointestinal Illness (GI)

• Case definitions for these syndromes based upon text in these structured fields:– Chief Complaint– Measured Temperature– Diagnosis (ICD-9 CM Code)

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System Screenshot

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Aggregate Level Syndromic Data

• Only “Count” Data is collected

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Data processing and syndrome coding

Respiratory conditions

%Macro Resp; *Respiratory; IF CC=:'COUGH' OR CC=:'COUGHING' OR CC=:'SOB' OR CC=:'DIFFICULTY BREATHING' OR CC='BREATHING PROBLEMS' OR CC=:'SHORTNESS OF BREA' OR CC=:'DIFF BREA' CC='URI' ORTHEN RESP=1; ELSE DO; RESP=

Misspelling INDEX(CC,"COUG") + INDEX(CC,"COUH") +Shortness of breath

INDEX(CC,"S.O.B") + INDEX(CC,"SOB") + INDEX(CC,"S O B") + INDEX(CC,"S O B") + INDEX(CC,"S.OB");

Difficulty breathing

INDEX(CC,"BREAT") + INDEX(CC,"BEATH") + INDEX(CC,"DIB") + INDEX(CC,"D I B") + INDEX(CC,"D.I.B") + INDEX(CC,"BRATHING") + INDEX(CC,"DIFF BR") + INDEX(CC,"DIFF, BR") +

Upper respiratory infection

INDEX(CC,"URI ") + INDEX(CC,"URI/") + INDEX(CC,"URI;") + INDEX(CC,"U R I") + INDEX(CC,"URI,") + INDEX(CC,"U.R.I") +

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Analysis:Calculate Baseline

Expected disease level

• Approaches: Moving average, regression, time series methods.• Length of baseline: Years, months, days

Adjustments

• Long: Seasonal, secular, environmental (e.g. heat, pollen)• Short: Day of week, weekend/weekday, holidays, reporting failures

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Analysis:Test Observed vs. Expected

Significance tests

Predetermined number of standard deviations

Crossing statistical thresholds Signal

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Analysis:Test Observed vs. Expected

Electronic Health Record Syndromic SurveillanceDuring 2009 Pandemic

H1N1 in NYC

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Friday

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Saturday

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Sunday

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Monday

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Tuesday

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Wednesday

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Thursday

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Friday

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Saturday

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Sunday

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Monday – Memorial Day

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Tuesday

H1N1 in New York City:

Where did patients seek treatment?

Emergency Departments or

Primary Care Clinics?

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Objective• To determine whether the timing of the

increase in patient visits was different at emergency departments from primary care clinics during the spring 2009 H1N1 influenza outbreak across the 5 boroughs of NYC

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Study Sitesl 58 Primary Care

Providers (PCP): – 9 Institute for Family

Health (IFH) clinics– 49 practices enrolled

in the NYCDOHMH PCIP (30 visits/day)

v 50 Emergency Departments– 247 visits/day

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Methods• Influenza-like Illness (ILI) as a broad

estimate of H1N1

• Fever + respiratory related reason for visit or diagnosisPCP

• Chief complaint of fever + a sore throat or cough, or a chief complaint of fluED

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MethodsCompared number of days to a significant increase at EDs to PCP clinics using a log-rank test

• City-wide• By borough to see if there was a geographic difference

Two Waves:

• 4/24-5/8• 5/14-6/4

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ED, IFH and PCIP ILI Visits

ED, IFH and PCIP ILI Visits

ED, IFH and PCIP ILI Visits

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Facilities with a significant increase in ILI volume

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Results, April 24-May 8Median Days to Increase in ILI

Facilities with Increase in ILI

1-sided log rank

Borough ED PCP ED PCP p-valueAll 4 12 43/50 (86%) 36/58 (62%) <0.0001

Bronx 5 12 8/9 (88%) 10/17 (59%) 0.045

Brooklyn 3 14 12/15 (80%) 6/9 (67%) 0.025

Manhattan 4 13 13/15 (87%) 11/19 (58%) 0.008

Queens 3 7 8/8 (100%) 6/7 (86%) 0.007

Staten Island 14 10 2/3 (67%) 3/3 (100%) 0.902

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Results, May 14-June 4Median Days to Increase in ILI

Facilities with Increase in ILI

1-sided log rank

Borough ED PCP ED PCP p-valueAll 4 8 47/50 (94%) 50/58 (86%) <0.0001

Bronx 1 6 9/9 (100%) 16/17 (82%) 0.004

Brooklyn 4 12 13/15 (87%) 7/9 (78%) 0.039

Manhattan 4 7 14/15 (93%) 17/19 (89%) 0.016

Queens 4 8 8/8 (100%) 5/7 ( 71%) 0.091

Staten Island 5 8 3/3 (100%) 3/3 (100%) 0.012

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Findings• Emergency Departments experienced an

increase in patients with ILI before Primary Care Providers

• PCPs were vastly under-utilized during the outbreak

• NYCDOHMH changed messaging to encourage visiting PCPs instead of EDs for mild illness

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Future of Syndromic Surveillance

Meaningful Use

• Capability to submit syndromic data to health departments Regional Health Information Organizations (RHIOS), Hubs

Data Validation and Quality Assurance

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Online ResourcesCDC Flu Surveillancehttp://www.cdc.gov/flu/weekly/fluactivity.htm

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