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ISDS 2012 Conference Abstracts

Differentiating ZIP Codes in Syndromic Data; What Can
They Tell Us?
Marc Paladini, Romona Lall and Stephen E. Schachterle*

New York City Department of Health and Mental Hygiene, Queens, NY, USA

Objective
To classify visits to NYC emergency departments (ED) into NYC

residential, NYC PO Box or commercial building, commuters to
NYC, and out-of-town visitors. To describe patterns in each group, to
evaluate how they differ, and to consider how the differences can af-
fect syndromic surveillance analyses and results.

Introduction
The NYC Department of Health and Mental Hygiene (DOHMH)

ED syndromic surveillance system receives data from 95% of all ED
visits in NYC totaling 4 million visits each year. The data include
residential ZIP code as reported by the patient. ZIP code information
has been used by the DOHMH to separate visits into NYC and non-
NYC for analysis; and, a closer examination of non-NYC visits may
further inform disease surveillance.

Methods
Visits were initially differentiated into six home ZIP code types.

NYC residential ZIP codes, PO Boxes and commercial buildings
were identified with 2010 US Census and data from the SAS institute
(SAS Institute Inc., Cary, NC, USA). Commuter visits to the EDs
were classified as any ZIP codes from the NYC Core Based Statisti-
cal Area (CBSA; United States Office of Management and Budget).
Out of town visits were identified using with the 2010 US Census.
Unknown ZIP codes included all of those ZIP codes that were not
identified by any of the previous methods, and missing ZIP codes
were those that were blank. ZIP codes were verified with the United
States Postal Service website (www.usps.com). 

Once ZIP codes were categorized, spatial and temporal trends in
total ED visits by home ZIP code type were analyzed.

Results
Of the approximately 4 million ED visits in NYC during 2011, the

number of visits by commuters and out-of-town visitors were 125,236
(3.1%) and 45,158 (1.1%) respectively (Figure 1). There were 4,676
(0.1%) visits with a NYC PO Box or building ZIP codes and 48,077
(1.2%) visits with a missing or non-interpretable ZIP codes. The ma-
jority of commuter and out-of-town ED visits occur at a smaller set
of hospitals. Out-of town visitors mostly visited hospitals in Man-
hattan rather than hospitals in the outer boroughs. While the seasonal
trends and day-of-week patterns for the NYC residents and the com-
muters appear to be fairly similar, this is not the case for out-of-town
visitors. For example, total ED visit trends correlated well for NYC
residents and commuters (r=0.77), but there was no correlation be-
tween NYC residents and out-of-town visitors (r=-0.18) over time.
The number of ED visits among out-of-town visitors was higher dur-
ing summer months and the winter holiday season, and this trend may
have reflected the larger number of visitors during these periods. Day-

of-week patterns were similar for NYC residents and commuters with
weekdays associated with larger numbers of visits compared to week-
ends. However, the opposite was found true for out-of-town visitors
with larger number of visits occurring over the weekends compared
to weekdays.

Conclusions
Considerable differences in temporal trends were found among

out-of-town visitors, NYC residents, and commuters to NYC. Out-of-
town visitors also tend to visit EDs located in Manhattan rather than
in the outer boroughs. These results suggest that out-of-town visitors
represent a unique population ED visitors. Analyzing NYC residents,
commuters, and out-of-town visitors separately may provide addi-
tional information that could prove useful to daily syndromic sur-
veillance activities.

Figure 1: Total ED visits from the NYC Core Based Statistical Area (CBSA)
and the surrounding region.

Keywords
GIS; New York; Spatial Analysis

Acknowledgments

This work was carried out in conjunction with a grant from the Alfred P.
Sloan Foundation (#2010-12-14). We thank the members of the New York
City Department of Health and Mental Hygiene Syndromic Surveillance
Unit.

*Stephen E. Schachterle
E-mail: steve.schachterle@gmail.com

Online Journal of Public Health Informatics * ISSN 1947-2579 * http://ojphi.org * 5(1):e127, 2013