Department of Public Health, Experimental and Forensic Medicine, University of Pavia, Pavia, Italy.
Health Direction, IRCCS Fondazione Istituto Neurologico C. Mondino, Pavia, Italy.
Ann Ig. 2024 Mar-Apr;36(2):256-260. doi: 10.7416/ai.2024.2603. Epub 2024 Jan 18.
Healthcare-Associated-Infections are a critical concern in healthcare settings, posing serious threats to patient safety and causing significant morbidity, mortality, and financial strain. This study aims to calculate healthcare-associated-infections trends in the hospital setting through an automatic reporting system.
The study is a descriptive analysis of automatically generated trends of an innovative digital tool based on existing hospital information flows.
An algorithm was developed within a Clinical Information System to create a suite of quality indicators for monitoring healthcare-associated-infections trends. The algorithm used criteria related to admission, laboratory tests and antimicrobial administrations. A descriptive analysis was conducted for patients aged 18 or older, admitted to a neurological or to a neuro-rehabilitation department of a neurologic hospital from 2019 to 2022.
The results showed fluctuations in healthcare-associated-infections prevalence from 2.9% to 5.6% and hospital infec-tions prevalence from 4.5% to 10.9%, with notable increases in 2020 and 2021. The majority (70.3%) of healthcare associated infections identified by the tool were confirmed to be potentially hospital-acquired, according to the European Centre of Disease Prevention and Control's definition.
The study posits the algorithm as a vital tool for automatically monitoring hospital infections, providing valuable preliminary results for improving care quality and guiding the infections' prevention and control strategies, with plans to benchmark the algorithm against a gold standard in the future.
在医疗环境中，医院获得性感染是一个至关重要的关注点，对患者安全构成严重威胁，并导致发病率、死亡率和财务负担显著增加。本研究旨在通过自动报告系统计算医院环境中的医院获得性感染趋势。
该研究是对基于现有医院信息流的创新数字工具的自动生成趋势的描述性分析。
在临床信息系统中开发了一种算法，以创建一套用于监测医院获得性感染趋势的质量指标。该算法使用了与入院、实验室检查和抗菌药物管理相关的标准。对 2019 年至 2022 年期间入住神经病学或神经康复科的 18 岁或以上的患者进行了描述性分析。
结果显示，医院获得性感染的患病率从 2.9%波动到 5.6%，医院感染的患病率从 4.5%波动到 10.9%，2020 年和 2021 年显著增加。根据欧洲疾病预防控制中心的定义，该工具确定的大多数（70.3%）医院获得性感染被确认为潜在的医院获得性感染。
该研究提出了一种算法，将其作为自动监测医院感染的重要工具，为提高护理质量和指导感染预防和控制策略提供了有价值的初步结果，并计划在未来将该算法与黄金标准进行基准测试。
