Validation of a semiautomated system for surveillance of surgical site infection after cesarean section

Pnina Shitrit, Ravid Mudrik, Bat Sheva Gottesman, Michal Y. Chowers

Research output: Contribution to journalArticlepeer-review

Abstract

Surveillance of surgical site infection after cesarean section is challenging due to the high volume of these surgeries. A manual chart review of women undergoing cesarean section between January and June 2017 (675 charts, 40 infections) was compared to charts identified via an algorithm (141 charts, 39 infections). The algorithm achieved 97.5% sensitivity and 83.9% specificity and reduced the workload of infection control personnel.

Original languageEnglish
JournalInfection Control and Hospital Epidemiology
DOIs
StateAccepted/In press - 2021

Fingerprint

Dive into the research topics of 'Validation of a semiautomated system for surveillance of surgical site infection after cesarean section'. Together they form a unique fingerprint.

Cite this