Simple methodology for detecting time shifts in surgical site infections: a study in digestive, breast, and thoracic surgery.
To simplify the data mining surveillance system for the monitoring of surgical site infections (SSIs), electronic analysis of a total of 3100 patients was done. Using Layered Analyses, the Cross-Table option of a globally available software detected emerging or disappearing SSIs according to specific parameters. This methodology may facilitate the detection of SSI shifts.
Yoshida
Junichi
J
Department of Surgery, Shimonoseki City Central Hospital, Shimonoseki 750-8520, Japan. cokeieik@city.shimonoseki.yamaguchi.jp
Umeda
Shuyo
S
Shinohara
Masahiro
M
Matsuo
Kenichi
K
D000293:Adolescent; D000328:Adult; D000368:Aged; D003628:Database Management Systems; D006801:Humans; D017053:Infection Control / Q000379:methods / Q000706:statistics & numerical data*; D016247:Information Storage and Retrieval / Q000379:methods*; D007564:Japan / Q000453:epidemiology; D008875:Middle Aged; D012189:Retrospective Studies; D018571:Sentinel Surveillance; D013530:Surgical Wound Infection / Q000453:epidemiology*; D013997:Time Factors