Healthcare-Associated-Infections: preliminary results from a real-time reporting system of an Italian neurologic research hospital.

IF 1.5 Q3 HEALTH CARE SCIENCES & SERVICES
Lorenzo Blandi, Vittorio Bolcato, Alessandro Meloni, Daniele Bosone, Anna Odone
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引用次数: 0

Abstract

Background: 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.

Study design: The study is a descriptive analysis of automatically generated trends of an innovative digital tool based on existing hospital information flows.

Methods: 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.

Results: 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.

Discussion and conclusions: 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.

医疗保健相关感染:意大利一家神经病学研究医院实时报告系统的初步结果。
背景:医疗保健相关感染是医疗保健环境中的一个重要问题,对患者安全构成严重威胁,并导致严重的发病率、死亡率和经济压力。本研究旨在通过自动报告系统计算医院环境中的医疗相关感染趋势:研究设计:本研究是对基于现有医院信息流的创新数字工具自动生成的趋势进行描述性分析:方法:在临床信息系统中开发了一种算法,用于创建一套质量指标,监测医疗相关感染趋势。该算法采用了与入院、实验室检测和抗菌药物使用相关的标准。对2019年至2022年期间神经病医院神经科或神经康复科收治的18岁及以上患者进行了描述性分析:结果显示,医疗相关感染率从2.9%到5.6%不等,医院感染率从4.5%到10.9%不等,2020年和2021年明显上升。根据欧洲疾病预防与控制中心的定义,该工具确定的大多数(70.3%)医疗相关感染被证实可能是医院感染:该研究认为该算法是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与控制策略提供了宝贵的初步结果,并计划在未来将该算法与黄金标准进行比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Annali di igiene : medicina preventiva e di comunita
Annali di igiene : medicina preventiva e di comunita HEALTH CARE SCIENCES & SERVICES-
CiteScore
3.40
自引率
0.00%
发文量
69
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