瑞典北部重症监护中抗菌药物消耗的自动监控:一项观察性个案研究。

IF 4.8 2区 医学 Q1 INFECTIOUS DISEASES
Andreas Winroth, Mattias Andersson, Peter Fjällström, Anders F Johansson, Alicia Lind
{"title":"瑞典北部重症监护中抗菌药物消耗的自动监控:一项观察性个案研究。","authors":"Andreas Winroth, Mattias Andersson, Peter Fjällström, Anders F Johansson, Alicia Lind","doi":"10.1186/s13756-024-01424-2","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>The digitalization of information systems allows automatic measurement of antimicrobial consumption (AMC), helping address antibiotic resistance from inappropriate drug use without compromising patient safety.</p><p><strong>Objectives: </strong>Describe and characterize a new automated AMC surveillance service for intensive care units (ICUs), with data stratified by referral clinic and linked with individual patient risk factors, disease severity, and mortality.</p><p><strong>Methods: </strong>An automated service collecting data from the electronic medical record was developed, implemented, and validated in a healthcare region in northern Sweden. We performed an observational study from January 1, 2018, to December 31, 2021, encompassing general ICU care for all ≥18-years-olds in a catchment population of 270000 in secondary care and 900000 in tertiary care. We used descriptive analyses to associate ICU population characteristics with AMC outcomes over time, including days of therapy (DOT), length of therapy, defined daily doses, and mortality.</p><p><strong>Results: </strong>There were 5608 admissions among 5190 patients with a median age of 65 (IQR 48-75) years, 41.2% females. The 30-day mortality was 18.3%. Total AMC was 1177 DOTs in secondary and 1261 DOTs per 1000 patient days and tertiary care. AMC varied significantly among referral clinics, with the highest total among 810 general surgery admissions in tertiary care at 1486 DOTs per 1000 patient days. Case-mix effects on the AMC were apparent during COVID-19 waves highlighting the need to account for case-mix. Patients exposed to more than three antimicrobial drug classes (N = 242) had a 30-day mortality rate of 40.6%, with significant variability in their expected rates based on admission scores.</p><p><strong>Conclusion: </strong>We introduce a new service and instructions for automating local ICU-AMC data collection. The versatile long-term ICU-AMC metrics presented, covering patient factors, referral clinics and mortality outcomes, are expected to be beneficial in refining antimicrobial drug use.</p>","PeriodicalId":7950,"journal":{"name":"Antimicrobial Resistance and Infection Control","volume":null,"pages":null},"PeriodicalIF":4.8000,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11186282/pdf/","citationCount":"0","resultStr":"{\"title\":\"Automated surveillance of antimicrobial consumption in intensive care, northern Sweden: an observational case study.\",\"authors\":\"Andreas Winroth, Mattias Andersson, Peter Fjällström, Anders F Johansson, Alicia Lind\",\"doi\":\"10.1186/s13756-024-01424-2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>The digitalization of information systems allows automatic measurement of antimicrobial consumption (AMC), helping address antibiotic resistance from inappropriate drug use without compromising patient safety.</p><p><strong>Objectives: </strong>Describe and characterize a new automated AMC surveillance service for intensive care units (ICUs), with data stratified by referral clinic and linked with individual patient risk factors, disease severity, and mortality.</p><p><strong>Methods: </strong>An automated service collecting data from the electronic medical record was developed, implemented, and validated in a healthcare region in northern Sweden. We performed an observational study from January 1, 2018, to December 31, 2021, encompassing general ICU care for all ≥18-years-olds in a catchment population of 270000 in secondary care and 900000 in tertiary care. We used descriptive analyses to associate ICU population characteristics with AMC outcomes over time, including days of therapy (DOT), length of therapy, defined daily doses, and mortality.</p><p><strong>Results: </strong>There were 5608 admissions among 5190 patients with a median age of 65 (IQR 48-75) years, 41.2% females. The 30-day mortality was 18.3%. Total AMC was 1177 DOTs in secondary and 1261 DOTs per 1000 patient days and tertiary care. AMC varied significantly among referral clinics, with the highest total among 810 general surgery admissions in tertiary care at 1486 DOTs per 1000 patient days. Case-mix effects on the AMC were apparent during COVID-19 waves highlighting the need to account for case-mix. Patients exposed to more than three antimicrobial drug classes (N = 242) had a 30-day mortality rate of 40.6%, with significant variability in their expected rates based on admission scores.</p><p><strong>Conclusion: </strong>We introduce a new service and instructions for automating local ICU-AMC data collection. The versatile long-term ICU-AMC metrics presented, covering patient factors, referral clinics and mortality outcomes, are expected to be beneficial in refining antimicrobial drug use.</p>\",\"PeriodicalId\":7950,\"journal\":{\"name\":\"Antimicrobial Resistance and Infection Control\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.8000,\"publicationDate\":\"2024-06-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11186282/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Antimicrobial Resistance and Infection Control\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1186/s13756-024-01424-2\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"INFECTIOUS DISEASES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Antimicrobial Resistance and Infection Control","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s13756-024-01424-2","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"INFECTIOUS DISEASES","Score":null,"Total":0}
引用次数: 0

摘要

背景:信息系统数字化可自动测量抗菌药物消耗量(AMC):信息系统的数字化使得抗菌药物消耗量(AMC)的自动测量成为可能,这有助于在不影响患者安全的前提下解决因用药不当而产生的抗生素耐药性问题:描述并描述重症监护病房(ICU)新的抗菌药物消耗量自动监测服务的特点,数据按转诊诊所分层,并与患者的个体风险因素、疾病严重程度和死亡率相关联:方法:我们在瑞典北部的一个医疗保健地区开发、实施并验证了一项从电子病历中收集数据的自动化服务。我们在 2018 年 1 月 1 日至 2021 年 12 月 31 日期间开展了一项观察性研究,研究对象包括所有≥18 岁的普通 ICU 患者,其中二级医疗机构的覆盖人群为 27 万人,三级医疗机构的覆盖人群为 90 万人。我们使用描述性分析方法将重症监护室的人口特征与AMC随时间变化的结果联系起来,包括治疗天数(DOT)、治疗时间、规定的日剂量和死亡率:5190 名患者中有 5608 人入院,中位年龄为 65(IQR 48-75)岁,女性占 41.2%。30 天死亡率为 18.3%。二级医疗机构的AMC总量为1177次/1000患者日,三级医疗机构为1261次/1000患者日。各转诊诊所的 AMC 差异很大,其中三级医疗机构的 810 例普外科住院患者的 AMC 总量最高,为每 1000 个患者日 1486 次 DOT。在 COVID-19 波期间,病例组合对 AMC 的影响非常明显,这凸显了考虑病例组合的必要性。暴露于三种以上抗菌药物类别的患者(N = 242)的 30 天死亡率为 40.6%,根据入院评分,其预期死亡率存在显著差异:我们介绍了一种新的服务和本地 ICU-AMC 数据自动收集说明。所介绍的多用途 ICU-AMC 长期指标涵盖了患者因素、转诊诊所和死亡率结果,预计将有助于改进抗菌药物的使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automated surveillance of antimicrobial consumption in intensive care, northern Sweden: an observational case study.

Background: The digitalization of information systems allows automatic measurement of antimicrobial consumption (AMC), helping address antibiotic resistance from inappropriate drug use without compromising patient safety.

Objectives: Describe and characterize a new automated AMC surveillance service for intensive care units (ICUs), with data stratified by referral clinic and linked with individual patient risk factors, disease severity, and mortality.

Methods: An automated service collecting data from the electronic medical record was developed, implemented, and validated in a healthcare region in northern Sweden. We performed an observational study from January 1, 2018, to December 31, 2021, encompassing general ICU care for all ≥18-years-olds in a catchment population of 270000 in secondary care and 900000 in tertiary care. We used descriptive analyses to associate ICU population characteristics with AMC outcomes over time, including days of therapy (DOT), length of therapy, defined daily doses, and mortality.

Results: There were 5608 admissions among 5190 patients with a median age of 65 (IQR 48-75) years, 41.2% females. The 30-day mortality was 18.3%. Total AMC was 1177 DOTs in secondary and 1261 DOTs per 1000 patient days and tertiary care. AMC varied significantly among referral clinics, with the highest total among 810 general surgery admissions in tertiary care at 1486 DOTs per 1000 patient days. Case-mix effects on the AMC were apparent during COVID-19 waves highlighting the need to account for case-mix. Patients exposed to more than three antimicrobial drug classes (N = 242) had a 30-day mortality rate of 40.6%, with significant variability in their expected rates based on admission scores.

Conclusion: We introduce a new service and instructions for automating local ICU-AMC data collection. The versatile long-term ICU-AMC metrics presented, covering patient factors, referral clinics and mortality outcomes, are expected to be beneficial in refining antimicrobial drug use.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Antimicrobial Resistance and Infection Control
Antimicrobial Resistance and Infection Control PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH -INFECTIOUS DISEASES
CiteScore
9.70
自引率
3.60%
发文量
140
审稿时长
13 weeks
期刊介绍: Antimicrobial Resistance and Infection Control is a global forum for all those working on the prevention, diagnostic and treatment of health-care associated infections and antimicrobial resistance development in all health-care settings. The journal covers a broad spectrum of preeminent practices and best available data to the top interventional and translational research, and innovative developments in the field of infection control.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信