Sivasankar Shivani, Goldman Jennifer L, Hoffman Mark A
Department of Pediatrics, Children's Mercy Hospital, Kansas City, MO, USA.
School of Medicine, University of Missouri-Kansas City, Kansas City, MO, USA.
JAC Antimicrob Resist. 2023 Jan 2;5(1):dlac128. doi: 10.1093/jacamr/dlac128. eCollection 2023 Feb.
Antibiotic resistance (AR) is a global public health threat. Surveillance of baseline AR and trends and emerging resistance among priority bacterial isolates with respect to the age of the patients and the type of healthcare setting are required due to differences in antimicrobial need and use in these populations.
We performed a retrospective study using deidentified electronic health record (EHR) data in the Cerner Health Facts™ data warehouse. Antibiotic susceptibility data were extracted for all bacterial isolates of interest at 166 non-affiliated healthcare facilities reporting microbiology susceptibility results of the FDA recommended antibiotics between the years 2012 to 2017. We assessed and visualized the slope coefficient from linear regression to compare changes in resistance over time for the four patient care groups.
The trends in resistance rates to clinically relevant antibiotics were influenced by age and care setting. For example, ertapenem-resistant isolates from children overall increased significantly compared with adults (0.7% to 9.8%, 2.1% to 2.8%, = 0.00013) and isolates from children in paediatric facilities increased significantly compared with facilities treating adults and children (0.1% to 27.1%, 0.9% to 3.8%, = 0.0002).
Large-scale analysis of EHR data from 166 facilities shows that AR patterns for some bug-drug combinations vary by care setting and patient age. We describe novel data visualizations to interpret large-scale EHR data on the prevalence and trends of AR that should influence antimicrobial prescribing and antimicrobial stewardship programme interventions.
抗生素耐药性是全球公共卫生威胁。由于这些人群对抗菌药物的需求和使用存在差异,因此需要监测基线抗生素耐药性以及重点细菌分离株中耐药性的趋势和新出现的耐药情况,同时考虑患者年龄和医疗环境类型。
我们使用Cerner Health Facts™数据仓库中去识别化的电子健康记录(EHR)数据进行了一项回顾性研究。提取了2012年至2017年间在166家非附属医疗机构报告美国食品药品监督管理局(FDA)推荐抗生素微生物敏感性结果的所有感兴趣细菌分离株的抗生素敏感性数据。我们评估并可视化了线性回归的斜率系数,以比较四个患者护理组随时间的耐药性变化。
对临床相关抗生素的耐药率趋势受年龄和护理环境影响。例如,与成人相比,儿童中对厄他培南耐药的分离株总体显著增加(从0.7%增至9.8%,从2.1%增至2.8%,P = 0.00013),儿科设施中儿童的分离株与治疗成人和儿童的设施相比显著增加(从0.1%增至27.1%,从0.9%增至3.8%,P = 0.0002)。
对166家医疗机构的EHR数据进行的大规模分析表明,某些病菌 - 药物组合的抗生素耐药模式因护理环境和患者年龄而异。我们描述了新颖的数据可视化方法,以解释关于抗生素耐药性流行率和趋势的大规模EHR数据,这应会影响抗菌药物处方和抗菌药物管理计划干预措施。