Source
Department of Epidemiology and Biostatistics, The University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Dr Mail Code 7933, San Antonio, TX, USA. jungi@uthscsa.edu
Abstract
BACKGROUND:
Automated electronic medical records may be useful for syndromic surveillance to quickly detect infectious disease outbreaks. Some syndromic surveillance systems include every encounter in the analysis, whereas others exclude individuals' repeat encounters within the same syndrome occurring within a short period of time, with the rationale that these represent follow-up visits rather than new episodes of illness.
METHODS:
We evaluate the effect of keeping all encounters as compared with removing repeat encounters. Using the prospective space-time permutation scan statistic, we performed daily analyses on all encounters versus on episodes defined as encounters new within 2, 6 or 12 weeks. Data were taken from a Massachusetts Health Maintenance Organization (HMO) for the calendar year 1999 for four different syndromes.
RESULTS:
We found extensive disagreement in the number of signals detected: 70, 68, 21 and 15 signals when using all encounters versus 15-20, 3, 4-5 and 0 signals when using only new episodes for lower respiratory, lower gastrointestinal, upper gastrointestinal and neurologic syndromes, respectively.
CONCLUSION:
Using all encounters in syndromic surveillance may not only create too many signals but may also miss some signals by masking the anomalies generated by actual episodes. However, it is also possible to miss signals when using episodes.