Surveillance is an acknowledged method to decrease nosocomial infections, such as surgical site infections (SSIs). Electronic healthcare records create the opportunity for automated surveillance. While approaches for different types of surgeries and indicators already exist, there are very few for obstetrics and gynaecology. To analyse the sensitivity and workload reduction of semi-automated surveillance in obstetrics and gynaecology. In this retrospective, single-centre study at a 1438-bed tertiary care hospital in Germany, semi-automated SSI surveillance using the indicators ‘antibiotic prescription’, ‘microbiological data’ and ‘administrative data’ (diagnosis codes, readmission, post-hospitalization care) was compared with manual analysis and categorization of all patient files. Breast surgeries (BSs) conducted in 2018 and caesarean sections (CSs) that met the inclusion criteria between May 2013 and December 2019 were included. Indicators were analysed for sensitivity, number of analysed procedures needed to identify one case, and potential workload reduction in detecting SSIs in comparison with the control group. The reference standard showed nine SSIs in 416 BSs (2.2%). Sensitivities for the indicators ‘antibiotic prescription’, ‘diagnosis code’, ‘microbiological sample taken’, and the combination ‘diagnosis code or microbiological sample’ were 100%, 88.9%, 66.7% and 100%, respectively. The reference standard showed 54 SSIs in 3438 CSs (1.6%). Sensitivities for the indicators ‘collection of microbiological samples’, ‘diagnosis codes’, ‘readmission/post-hospitalization care’, and the combination of all indicators were 38.9%, 27.8%, 85.2% and 94.4%, respectively. Semi-automated surveillance systems may reduce workload by maintaining high sensitivity depending on the type of surgery, local circumstances and thorough digitalization.

中文翻译：

---

建立妇产科半自动化感染监测

监测是减少手术部位感染 (SSI) 等医院感染的公认方法。电子医疗记录为自动监控创造了机会。虽然不同类型的手术和指标已经存在，但妇产科的方法和指标却很少。分析妇产科半自动监测的敏感性和工作量减少情况。在这项在德国一家拥有 1438 个床位的三级护理医院进行的回顾性单中心研究中，使用“抗生素处方”、“微生物学数据”和“管理数据”（诊断代码、再入院、出院后指标）等指标进行半自动 SSI 监测护理）与所有患者档案的手动分析和分类进行了比较。包括2018年进行的乳腺手术（BS）和2013年5月至2019年12月期间符合纳入标准的剖腹产手术（CS）。与对照组相比，对指标进行了灵敏度分析、识别一个病例所需的分析程序数量以及检测 SSI 的潜在工作量减少。参考标准显示 416 个 BS 中有 9 个 SSI (2.2%)。 “抗生素处方”、“诊断代码”、“采集的微生物样本”以及“诊断代码或微生物样本”组合的敏感性分别为100%、88.9%、66.7%和100%。参考标准显示 3438 个 CS 中有 54 个 SSI (1.6%)。 “微生物样本采集”、“诊断代码”、“再入院/出院后护理”以及所有指标组合的敏感性分别为 38.9%、27.8%、85.2% 和 94.4%。半自动监测系统可以根据手术类型、当地情况和彻底的数字化保持高灵敏度，从而减少工作量。