TY - JOUR
T1 - Validation of a semiautomated system for surveillance of surgical site infection after cesarean section
AU - Shitrit, Pnina
AU - Mudrik, Ravid
AU - Gottesman, Bat Sheva
AU - Chowers, Michal Y.
N1 - Publisher Copyright:
© The Author(s), 2021. Published by Cambridge University Press on behalf of The Society for Healthcare Epidemiology of America.
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85108889787&partnerID=8YFLogxK
U2 - 10.1017/ice.2021.264
DO - 10.1017/ice.2021.264
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AN - SCOPUS:85108889787
JO - Infection Control and Hospital Epidemiology
JF - Infection Control and Hospital Epidemiology
SN - 0899-823X
ER -
