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 infections 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.

Healthcare-Associated-Infections: preliminary results from a real-time reporting system of an Italian neurologic research hospital / Blandi, L.; Bolcato, V.; Meloni, A.; Bosone, D.; Odone, A.. - In: ANNALI DI IGIENE MEDICINA PREVENTIVA E DI COMUNITÀ. - ISSN 1120-9135. - 36:2(2024), pp. 256-260. [Epub ahead of print] [10.7416/ai.2024.2603]

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

Blandi L.
Primo
;
Odone A.
2024-01-01

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 infections 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.
2024
Clinical Information System
Digital Health
Electronic Health Record
Healthcare-Associated-Infection
Infection Prevention and Control Strategies
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11768/170036
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