{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,24]],"date-time":"2026-02-24T11:20:29Z","timestamp":1771932029885,"version":"3.50.1"},"reference-count":24,"publisher":"Cambridge University Press (CUP)","issue":"3","license":[{"start":{"date-parts":[[2026,1,6]],"date-time":"2026-01-06T00:00:00Z","timestamp":1767657600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/www.cambridge.org\/core\/terms"}],"content-domain":{"domain":["cambridge.org"],"crossmark-restriction":true},"short-container-title":["Infect. Control Hosp. Epidemiol."],"published-print":{"date-parts":[[2026,3]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec id=\"S0899823X25103796_as1\">\n                    <jats:title>Background:<\/jats:title>\n                    <jats:p>A semi-automated surveillance system for surgical site infections (SSIs), SPICMI (Surveillance and Prevention Program for Infectious Risk in Surgery and Interventional Medicine), has been implemented in French hospitals, leveraging data from electronic health records (EHRs).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"S0899823X25103796_as2\">\n                    <jats:title>Objective:<\/jats:title>\n                    <jats:p>To evaluate the performance of the SPICMI algorithm in detecting SSIs in orthopedic and digestive surgery.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"S0899823X25103796_as3\">\n                    <jats:title>Setting:<\/jats:title>\n                    <jats:p>Surveillance data were collected annually from the EHRs. The algorithm identified suspected SSIs based on two criteria: (1)\u00a0surgical revision during the index stay or readmission, (2) positive microbiological samples from the wound. Suspected SSIs identified were subsequently validated by surgeons.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"S0899823X25103796_as4\">\n                    <jats:title>Methods:<\/jats:title>\n                    <jats:p>A stochastic modeling approach was used to estimate probability intervals for performance indicators. Various detection scenarios were constructed based on SPICMI criteria. Logistic regression analysis was performed using surveillance data. Data unavailable in the database were estimated through a literature review and expert opinions.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"S0899823X25103796_as5\">\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>The probability of surgical revision following an SSI varied significantly between surgical specialties, ranging from 92% in orthopedic surgery to 45.2% in gynecology. In orthopedic and digestive surgery, the SPICMI algorithm demonstrated good reliability for detecting SSIs in minimizing false-negative and false-positive cases (Youden index: 0.96 and 0.79, respectively). Sensitivity (Se) was lower in digestive surgery (0.7\u20130.9) compared to orthopedic surgery (0.9\u20131), while specificity (Sp) remained high (0.9\u20131) in both specialties.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"S0899823X25103796_as6\">\n                    <jats:title>Conclusion:<\/jats:title>\n                    <jats:p>The SPICMI algorithm shows potential to support efficient use of time and resources in SSIs surveillance management. Further evaluation is needed with a broader panel of surgery procedures.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1017\/ice.2025.10379","type":"journal-article","created":{"date-parts":[[2026,1,6]],"date-time":"2026-01-06T09:13:54Z","timestamp":1767690834000},"page":"244-251","update-policy":"https:\/\/doi.org\/10.1017\/policypage","source":"Crossref","is-referenced-by-count":0,"title":["Semi-automated detection of surgical-site infections using a simple and effective hospital data-based algorithm in the national surveillance system in France"],"prefix":"10.1017","volume":"47","author":[{"given":"Ben Woodly","family":"Rigaud","sequence":"first","affiliation":[{"name":"Center for Prevention of Healthcare-Associated Infections (CPIAS)"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-4983-3005","authenticated-orcid":false,"given":"Nabil","family":"Benhajkassen","sequence":"additional","affiliation":[{"name":"Center for Prevention of Healthcare-Associated Infections (CPIAS)"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"B\u00e9atrice","family":"Nkoumazok","sequence":"additional","affiliation":[{"name":"Center for Prevention of Healthcare-Associated Infections (CPIAS)"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Isabelle","family":"Arnaud","sequence":"additional","affiliation":[{"name":"Center for Prevention of Healthcare-Associated Infections (CPIAS)"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rebecca","family":"Bauer","sequence":"additional","affiliation":[{"name":"Center for Prevention of Healthcare-Associated Infections (CPIAS)"},{"name":"Centre R\u00e9gional en Antibioth\u00e9rapie (CRAtb) - \u00cele-de-France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Juliette","family":"Auraix","sequence":"additional","affiliation":[{"name":"Center for Prevention of Healthcare-Associated Infections (CPIAS)"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Karin","family":"Lebascle","sequence":"additional","affiliation":[{"name":"Center for Prevention of Healthcare-Associated Infections (CPIAS)"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Delphine","family":"Verjat-Trannoy","sequence":"additional","affiliation":[{"name":"Center for Prevention of Healthcare-Associated Infections (CPIAS)"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Patrice","family":"Baillet","sequence":"additional","affiliation":[{"name":"Acad\u00e9mie nationale de chirurgie"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Niki","family":"Christou","sequence":"additional","affiliation":[{"name":"University Hospital of Limoges"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pascal","family":"Astagneau","sequence":"additional","affiliation":[{"name":"Center for Prevention of Healthcare-Associated Infections (CPIAS)"},{"name":"Sorbonne University, INSERM, Pierre Louis Institute of Epidemiology and Public Health"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"56","published-online":{"date-parts":[[2026,1,6]]},"reference":[{"key":"S0899823X25103796_ref5","doi-asserted-by":"publisher","DOI":"10.1089\/sur.2024.013"},{"key":"S0899823X25103796_ref19","doi-asserted-by":"publisher","DOI":"10.1093\/cid\/cit206"},{"key":"S0899823X25103796_ref11","doi-asserted-by":"publisher","DOI":"10.1017\/ice.2023.224"},{"key":"S0899823X25103796_ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmi.2021.02.028"},{"key":"S0899823X25103796_ref4","doi-asserted-by":"publisher","DOI":"10.1097\/QCO.0b013e32833ae7e3"},{"key":"S0899823X25103796_ref7","doi-asserted-by":"publisher","DOI":"10.1093\/oxfordjournals.aje.a113991"},{"key":"S0899823X25103796_ref24","unstructured":"24. Sant\u00e9 publique France. \u201c\u00c9tudes et enqu\u00eates \u2013 Surveillance des infections du site op\u00e9ratoire dans les \u00e9tablissements de sant\u00e9 fran\u00e7ais\u201d, r\u00e9seau ISO-Raisin; 2020."},{"key":"S0899823X25103796_ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijsu.2021.106136"},{"key":"S0899823X25103796_ref6","first-page":"104956","article-title":"Performance of machine learning algorithms for surgical site infection case detection and prediction: a systematic review and meta-analysis","volume":"84","author":"Wu","year":"2022","journal-title":"Ann Med Surg [Internet]"},{"key":"S0899823X25103796_ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.anplas.2023.06.013"},{"key":"S0899823X25103796_ref9","doi-asserted-by":"publisher","DOI":"10.1186\/s13756-016-0149-9"},{"key":"S0899823X25103796_ref8","doi-asserted-by":"publisher","DOI":"10.1016\/S1473-3099(14)70854-0"},{"key":"S0899823X25103796_ref14","unstructured":"14. Astagneau, P , Nkoumazok, B , Verjat-Trannoy, D , et al. Protocole national pour la surveillance semi-automatis\u00e9e du risque infectieux en chirurgie [Internet]. 2024. https:\/\/www.cpias-ile-de-france.fr\/spicmi\/surveillance\/presentation.php. Accessed October 13, 2024."},{"key":"S0899823X25103796_ref16","doi-asserted-by":"publisher","DOI":"10.1017\/ice.2023.123"},{"key":"S0899823X25103796_ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcrc.2022.154138"},{"key":"S0899823X25103796_ref23","doi-asserted-by":"publisher","DOI":"10.21105\/joss.00772"},{"key":"S0899823X25103796_ref10","doi-asserted-by":"publisher","DOI":"10.1186\/s12874-021-01369-9"},{"key":"S0899823X25103796_ref18","doi-asserted-by":"publisher","DOI":"10.1111\/j.1469-0691.2010.03202.x"},{"key":"S0899823X25103796_ref1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0083743"},{"key":"S0899823X25103796_ref15","unstructured":"15. CDC. Procedure-associated module: Surgical Site Infection (SSI) Event, 2024. National Healthcare Safety Network (NHSN)\/Patient Safety Component Manual. pp. 9\u201334. https:\/\/www.cdc.gov\/nhsn\/pdfs\/pscmanual\/9pscssicurrent.pdf. Accessed October 13, 2024."},{"key":"S0899823X25103796_ref22","doi-asserted-by":"publisher","DOI":"10.1128\/JCM.01602-10"},{"key":"S0899823X25103796_ref17","doi-asserted-by":"publisher","DOI":"10.1007\/s10479-010-0783-1"},{"key":"S0899823X25103796_ref21","doi-asserted-by":"publisher","DOI":"10.1186\/s13018-021-02813-8"},{"key":"S0899823X25103796_ref12","first-page":"194","article-title":"A framework to develop semiautomated surveillance of surgical site infections: an international multicenter study","author":"Van Rooden","year":"2019","journal-title":"Infect Control Hosp Epidemiol"}],"container-title":["Infection Control &amp; Hospital Epidemiology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.cambridge.org\/core\/services\/aop-cambridge-core\/content\/view\/S0899823X25103796","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,24]],"date-time":"2026-02-24T10:34:31Z","timestamp":1771929271000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.cambridge.org\/core\/product\/identifier\/S0899823X25103796\/type\/journal_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1,6]]},"references-count":24,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2026,3]]}},"alternative-id":["S0899823X25103796"],"URL":"https:\/\/doi.org\/10.1017\/ice.2025.10379","relation":{},"ISSN":["0899-823X","1559-6834"],"issn-type":[{"value":"0899-823X","type":"print"},{"value":"1559-6834","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1,6]]},"assertion":[{"value":"\u00a9 The Author(s), 2026. Published by Cambridge University Press on behalf of The Society for Healthcare Epidemiology of America","name":"copyright","label":"Copyright","group":{"name":"copyright_and_licensing","label":"Copyright and Licensing"}}]}}