Feasibility study of hospital antimicrobial stewardship analytics using electronic health records.
Feasibility study of hospital antimicrobial stewardship analytics using electronic health records.
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使用电子健康记录进行医院抗菌药物管理分析的可行性研究。
DOI：
10.1093/jacamr/dlab018
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发表时间：
2021-03
影响因子：
3.4
通讯作者：
Fuller C
中科院分区：
文献类型：
--
作者：
Dutey-Magni PF;Gill MJ;McNulty D;Sohal G;Hayward A;Shallcross L;Anderson N;Crayton E;Forbes G;Jhass A;Richardson E;Richardson M;Rockenschaub P;Smith C;Sutton E;Traina R;Atkins L;Conolly A;Denaxas S;Fragaszy E;Horne R;Kostkova P;Lorencatto F;Michie S;Mindell J;Robson J;Royston C;Tarrant C;Thomas J;West J;Williams H;Elsay N;Fuller C
医院抗菌药物管理（AMS）计划是优化抗菌药物使用的多学科举措。大多数医院依靠耗时的人工审计来监控临床医生的处方。但所需的大部分信息可以来自电子健康记录（EHR）。发展一种信息学方法，利用常规电子处方和实验室记录分析医院AMS实践的特征。使用英国伯明翰伊丽莎白女王医院六个专科的成人患者的电子处方、实验室和临床编码记录进行可行性研究（2017年9月至2018年8月）。该研究涉及：（i）医疗辅助队的护理标准的审查;（ii）他们的翻译成可衡量的概念，从常用的电子健康记录;和（iii）试点应用在电子健康记录队列研究（n = 61679入院）。我们开发了数据建模方法来表征抗菌药物的使用（抗菌药物治疗事件关联方法、治疗表、治疗变化）。处方与抗菌治疗事件相关（平均2.4张处方/事件;平均治疗时间为5.8天），从而获得了几项可采取行动的结果。例如，22%的低严重度社区获得性肺炎治疗事件与处方指南一致，倾向于使用广谱抗生素。治疗变化分析显示，从IV转为口服治疗平均延迟3.6天（95% CI：3.4-3.7）。只有22%的抗菌药物处方在治疗开始前进行了微生物培养。所提出的方法使细粒度监测AMS实践下降到专业，病房和个人的临床团队的情况下组合，使更有意义的同行比较。它是可行的，使用医院EHR构建快速，有意义的措施，处方质量与潜在的支持质量改进干预措施（审计/反馈处方），与一线临床医生优化处方，AMS的影响评估研究。
Hospital antimicrobial stewardship (AMS) programmes are multidisciplinary initiatives to optimize antimicrobial use. Most hospitals depend on time-consuming manual audits to monitor clinicians’ prescribing. But much of the information needed could be sourced from electronic health records (EHRs). To develop an informatics methodology to analyse characteristics of hospital AMS practice using routine electronic prescribing and laboratory records. Feasibility study using electronic prescribing, laboratory and clinical coding records from adult patients admitted to six specialities at Queen Elizabeth Hospital, Birmingham, UK (September 2017–August 2018). The study involved: (i) a review of AMS standards of care; (ii) their translation into concepts measurable from commonly available EHRs; and (iii) a pilot application in an EHR cohort study (n = 61679 admissions). We developed data modelling methods to characterize antimicrobial use (antimicrobial therapy episode linkage methods, therapy table, therapy changes). Prescriptions were linked into antimicrobial therapy episodes (mean 2.4 prescriptions/episode; mean length of therapy 5.8 days), enabling several actionable findings. For example, 22% of therapy episodes for low-severity community-acquired pneumonia were congruent with prescribing guidelines, with a tendency to use broader-spectrum antibiotics. Analysis of therapy changes revealed IV to oral therapy switching was delayed by an average 3.6 days (95% CI: 3.4–3.7). Microbial cultures were performed prior to treatment initiation in just 22% of antibacterial prescriptions. The proposed methods enabled fine-grained monitoring of AMS practice down to specialities, wards and individual clinical teams by case mix, enabling more meaningful peer comparison. It is feasible to use hospital EHRs to construct rapid, meaningful measures of prescribing quality with potential to support quality improvement interventions (audit/feedback to prescribers), engagement with front-line clinicians on optimizing prescribing, and AMS impact evaluation studies.