Institute of Health Informatics, University College London, London, UK.
Research Department of Primary Care & Population Health, University College London, London, UK.
J Antimicrob Chemother. 2021 Jul 15;76(8):1969-1977. doi: 10.1093/jac/dkab125.
In secondary care, antimicrobial use (AMU) must be monitored to reduce the risk of antimicrobial resistance and infection-related complications. However, there is variation in how hospitals address this challenge, partly driven by each site's level of digital maturity, expertise and resources available. This systematic review investigated approaches to measuring AMU to explore how these structural differences may present barriers to engagement with AMU surveillance.
We searched four digital databases and the websites of relevant organizations for studies in high-income, inpatient hospital settings that estimated AMU in adults. Excluded studies focused exclusively on antiviral or antifungal therapies. Data were extracted data on 12 fields (study description, data sources, data extraction methods and professionals involved in surveillance). Proportions were estimated with 95% CIs.
We identified 145 reports of antimicrobial surveillance from Europe (63), North America (53), Oceania (14), Asia (13) and across more than continent (2) between 1977 and 2018. Of 145 studies, 47 carried out surveillance based on digital data sources. In regions with access to electronic patient records, 26/47 studies employed manual methods to extract the data. The majority of identified professionals involved in these studies were clinically trained (87/93).
Even in regions with access to electronic datasets, hospitals rely on manual data extraction for this work. Data extraction is undertaken by healthcare professionals, who may have conflicting priorities. Reducing barriers to engagement in AMU surveillance requires investment in methods, resources and training so that hospitals can extract and analyse data already contained within electronic patient records.
在二级医疗机构中，必须监测抗菌药物的使用（AMU），以降低抗菌药物耐药性和感染相关并发症的风险。然而，医院在应对这一挑战的方式上存在差异，部分原因是每个医院的数字化成熟度、专业知识和可用资源水平不同。本系统评价调查了测量 AMU 的方法，以探讨这些结构差异如何可能成为参与 AMU 监测的障碍。
我们在四个数字数据库和相关组织的网站上搜索了在高收入、住院医院环境中估计成人 AMU 的研究。排除了仅关注抗病毒或抗真菌治疗的研究。数据提取了 12 个领域（研究描述、数据来源、数据提取方法和参与监测的专业人员）的数据。用 95%CI 估计了比例。
我们在 1977 年至 2018 年间，从欧洲（63 项）、北美（53 项）、大洋洲（14 项）、亚洲（13 项）和跨越多个大陆（2 项）的 145 份抗菌药物监测报告中确定了 47 项基于数字数据来源的监测。在有电子病历可访问的地区，47 项研究中有 26 项采用手动方法提取数据。这些研究中涉及的大多数专业人员都具有临床培训背景（87/93）。
即使在有电子数据集可访问的地区，医院也依赖于手动数据提取来进行这项工作。数据提取是由医疗保健专业人员完成的，他们可能有冲突的优先级。要降低参与 AMU 监测的障碍，需要在方法、资源和培训方面进行投资，以便医院可以提取和分析电子病历中已经包含的数据。
