Displaying results 1 - 6 of 6
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In Denial: Symptom Negation in New York City Emergency Department Chief Complaints
Content Type: Abstract
In July 2016, 77% of ED data was transmitted daily via Health Level 7 (HL7) messages, compared to only 27% in July 2015 (Figure). During this same period, chief complaint (CC) word count has increased from an average of 3.8 words to 6.0 words, with… read more -
Building a Better Syndromic Surveillance System: the New York City Experience
Content Type: Abstract
The New York City (NYC) syndromic surveillance system has monitored syndromes from NYC emergency department (ED) visits since 2001, using the temporal and spatial scan statistic in SaTScan for aberration detection. Since our syndromic system was… read more -
Detecting Changes in Chief Complaint Word Count: Effects on Syndromic Surveillance
Content Type: Abstract
The New York City (NYC) Department of Health and Mental Hygiene (DOHMH) receives daily ED data from 49 of NYC’s 52 hospitals, representing approximately 95% of ED visits citywide. Chief complaint (CC) is categorized into syndrome groupings using… read more -
A Survey of Data Recording Procedures at New York City Emergency Departments
Content Type: Abstract
Data is collected daily by the DOHMH from 49 of the 52 NYC EDs, representing approximately 95% of all ED visits in NYC. Variability in data fields between and within EDs has been noticed for some time. Differences in chief complaint (CC)… read more -
Evaluation of Temporal Aberration Detection Methods in New York City Syndromic Data
Content Type: Abstract
The NYC syndromic surveillance system has been monitoring syndromes from NYC emergency department (ED) visits for over a decade. We applied several aberration detection methodologies to a time series of ED visits in NYC spiked with synthetic… read more -
Evaluating a Seasonal ARIMA Model for Event Detection in New York City
Content Type: Abstract
ARIMA models use past values (autoregressive terms) and past forecasting errors (moving average terms) to generate future forecasts, making it a potential candidate method for modeling citywide time series of syndromic data [1]. While past research… read more