Syndromic surveillance for emerging infections in office practice using billing data.
OBJECTIVE
We wanted to evaluate the feasibility of conducting syndromic surveillance in a primary care office using billing data.


METHODS
A 1-year study was conducted in a primary care practice; comparison data were obtained from emergency department records of visits by county residents. Within the practice, a computer program converted billing data into de-identified daily summaries of International Classification of Diseases, Ninth Revision (ICD-9) codes by sex and age-group; and a staff member generated daily summaries and e-mailed them to the analysis team. For both the practice and the emergency departments, infection-related syndromes and practice-specific thresholds were calculated using the category 1 syndrome codes and an analytical method based upon the Early Aberration Reporting System of the Centers for Disease Control and Prevention.


RESULTS
A mean of 253 ICD-9 codes per day was reported. The most frequently recorded syndromes were respiratory illness, gastrointestinal illness, and fever. Syndromes most commonly exceeding the threshold of 2 standard deviations for the practice were lymphadenitis, rash, and fever. Generating a daily summary took 1 to 2 minutes; the program was written by the software vendor for a fee of dollar 1,500. During the 2003-2004 influenza season, trend line patterns of the emergency department visits reflected a pattern consistent with that of the state, whereas the trend line in primary case practice cases was less consistent, reflecting the variation expected in data from a single clinic. Still, spikes of activity that occurred in the practice before the emergency department suggest the practice may have seen patients with influenza earlier.


CONCLUSIONS
This preliminary study showed the feasibility of implementing syndromic surveillance in an office setting at a low cost and with minimal staff effort. Although many implementation issues remain, further development of syndromic surveillance systems should include primary care offices.
Sloane
Philip D
PD
Department of Family Medicine, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. psloane@med.unc.edu
MacFarquhar
Jennifer K
JK
Sickbert-Bennett
Emily
E
Mitchell
C Madeline
CM
Akers
Roger
R
Weber
David J
DJ
Howard
Kevin
K
D021821:Communicable Diseases, Emerging / Q000453:epidemiology*; D004196:Disease Outbreaks / Q000706:statistics & numerical data*; D005240:Feasibility Studies; D005251:Fees, Medical; D006801:Humans; D008499:Medical Records; D009657:North Carolina / Q000453:epidemiology; D009819:Office Visits / Q000191:economics / Q000706:statistics & numerical data; D010350:Patient Credit and Collection; D011320:Primary Health Care / Q000191:economics / Q000706:statistics & numerical data*; D018571:Sentinel Surveillance