start-ver=1.4 cd-journal=joma no-vol=85 cd-vols= no-issue=4 article-no= start-page=282 end-page=288 dt-received= dt-revised= dt-accepted= dt-pub-year=2013 dt-pub=201312 dt-online= en-article= kn-article= en-subject= kn-subject= en-title= kn-title=Multicentred surgical site infection surveillance using partitioning analysis en-subtitle= kn-subtitle= en-abstract= kn-abstract=Background: Surgical site infection (SSI) is an ongoing major public health problem throughout the world that increases healthcare costs. Utilizing a methodology that can help clinicians to continuously collect data about SSIs, analyse it and implement the feedback into routine hospital practice has been identified as a top national priority in Japan. Aim: To conduct an intervention study through 'operations research' using partitioning at multiple facilities, and to reduce the incidence and consequences of SSI. Methods: The Setouchi SSI Surveillance Group, which consists of seven institutes, started SSI surveillance in 2006. Until May of 2008, there were four surveillance periods (A-D). In all, 3089 patients underwent gastrointestinal surgery and were followed up for 30 days after their operations. Twenty-six factors that have been reported to be related to SSI were evaluated for all patients. The top three factors from each surveillance period were determined and then actual practice improvements were planned for each subsequent period. Findings: The total SSI occurrence was 6.9% for period A, 6.3% for period B, 6.4% for period C and 3.9% for period D. Comparing periods A and D, there was a statistical significance in the decrease of SSI occurrence (P = 0.012). Conclusion: Using the results and partitioning analysis of active SSI surveillance to contribute to action plans for improving clinical practice was effective in significantly reducing SSIs. en-copyright= kn-copyright= en-aut-name=FujiwaraY. en-aut-sei=Fujiwara en-aut-mei=Y. kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=1 ORCID= en-aut-name=YamadaT. en-aut-sei=Yamada en-aut-mei=T. kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=2 ORCID= en-aut-name=NaomotoY. en-aut-sei=Naomoto en-aut-mei=Y. kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=3 ORCID= en-aut-name=YamatsujiT. en-aut-sei=Yamatsuji en-aut-mei=T. kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=4 ORCID= en-aut-name=ShirakawaY. en-aut-sei=Shirakawa en-aut-mei=Y. kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=5 ORCID= en-aut-name=TanabeS. en-aut-sei=Tanabe en-aut-mei=S. kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=6 ORCID= en-aut-name=NomaK. en-aut-sei=Noma en-aut-mei=K. kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=7 ORCID= en-aut-name=KimuraT. en-aut-sei=Kimura en-aut-mei=T. kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=8 ORCID= en-aut-name=AokiH. en-aut-sei=Aoki en-aut-mei=H. kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=9 ORCID= en-aut-name=MatsukawaH. en-aut-sei=Matsukawa en-aut-mei=H. kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=10 ORCID= en-aut-name=KimuraM. en-aut-sei=Kimura en-aut-mei=M. kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=11 ORCID= en-aut-name=NonakaY. en-aut-sei=Nonaka en-aut-mei=Y. kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=12 ORCID= en-aut-name=SasakiH. en-aut-sei=Sasaki en-aut-mei=H. kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=13 ORCID= en-aut-name=OnodaT. en-aut-sei=Onoda en-aut-mei=T. kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=14 ORCID= en-aut-name=OtawaY. en-aut-sei=Otawa en-aut-mei=Y. kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=15 ORCID= en-aut-name=TakaokaM. en-aut-sei=Takaoka en-aut-mei=M. kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=16 ORCID= en-aut-name=FukazawaT. en-aut-sei=Fukazawa en-aut-mei=T. kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=17 ORCID= en-aut-name=OhnoY. en-aut-sei=Ohno en-aut-mei=Y. kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=18 ORCID= en-aut-name=FujiwaraT. en-aut-sei=Fujiwara en-aut-mei=T. kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=19 ORCID= affil-num=1 en-affil= kn-affil=Okayama Univ, Grad Sch Med Dent & Pharmaceut Sci, Dept Surg Gastroenterol affil-num=2 en-affil= kn-affil=Kawasaki Med Univ, Dept Gen Surg affil-num=3 en-affil= kn-affil=Kawasaki Med Univ, Dept Gen Surg affil-num=4 en-affil= kn-affil=Kawasaki Med Univ, Dept Gen Surg affil-num=5 en-affil= kn-affil=Okayama Univ, Grad Sch Med Dent & Pharmaceut Sci, Dept Surg Gastroenterol affil-num=6 en-affil= kn-affil=Okayama Univ, Grad Sch Med Dent & Pharmaceut Sci, Dept Surg Gastroenterol affil-num=7 en-affil= kn-affil=Okayama Univ, Grad Sch Med Dent & Pharmaceut Sci, Dept Surg Gastroenterol affil-num=8 en-affil= kn-affil=Okayama Saiseikai Gen Hosp, Dept Surg affil-num=9 en-affil= kn-affil=Hiroshima City Hosp, Dept Surg affil-num=10 en-affil= kn-affil=Hiroshima City Hosp, Dept Surg affil-num=11 en-affil= kn-affil= affil-num=12 en-affil= kn-affil=Tsuyama Cent Hosp, Dept Surg affil-num=13 en-affil= kn-affil=Shobara Red Cross Hosp, Dept Surg affil-num=14 en-affil= kn-affil=Shobara Red Cross Hosp, Dept Surg affil-num=15 en-affil= kn-affil=Chugoku Cent Hosp, Dept Surg affil-num=16 en-affil= kn-affil=Kawasaki Med Univ, Dept Gen Surg affil-num=17 en-affil= kn-affil=Kawasaki Med Univ, Dept Gen Surg affil-num=18 en-affil= kn-affil=Osaka Univ, Grad Sch Med, Dept Math Hlth Sci affil-num=19 en-affil= kn-affil=Okayama Univ, Grad Sch Med Dent & Pharmaceut Sci, Dept Surg Gastroenterol en-keyword=Active surveillance kn-keyword=Active surveillance en-keyword=Partitioning analysis kn-keyword=Partitioning analysis en-keyword=Surgical site infection kn-keyword=Surgical site infection END