Background: Noise pollution in intensive care units is a relevant problem, associated with psychological and physiological consequences for patients and healthcare staff. Sources of noise pollution include medical equipment, alarms, communication tools, staff activities, and conversations. Aim: To explore the cumulative effects of noise caused by an increasing number and type of medical devices in an intensive care setting on simulated patients with increasing clinical complexity. Secondly, to measure medical device alarms and nursing activities' sound levels, evaluating their role as potentially disruptive noises. Study Design: Observational simulation study (reported according to the STROBE checklist). Using an electronic sound meter, the sound levels of an intensive care room in seven simulated clinical scenarios were measured on a single day (09 March 2022), each featuring increasing numbers of devices, hypothetically corresponding to augmented patients' clinical complexity. Secondly, noise levels of medical device alarms and specific nursing activities performed at a distance of three meters from the sound meter were analysed. Results: The empty room's mean baseline noise level was 37.8 (±0.7) dBA; among the simulated scenarios, noise ranged between 45.3 (±1.0) and 53.5 (±1.5) dBA. Alarms ranged between 76.4 and 81.3 dBA, while nursing tasks (closing a drawer, opening a saline bag overwrap, or sterile packages) and speaking were all over 80 dBA. The noisiest activity was opening a sterile package (98 dBA). Conclusion: An increased number of medical devices, an expression of patients' higher clinical complexity, is not a significant cause of increased noise. Some specific nursing activities and conversations produce higher noise levels than medical devices and alarms. This study's findings suggest further research to assess the relationships between these factors and to encourage adequate noise reduction strategies.

Relationship between noise levels and intensive care patients' clinical complexity: An observational simulation study

Imbriaco, Guglielmo
Primo
Writing – Review & Editing
;
Capitano, Martina
Investigation
;
Monesi, Alessandro
Investigation
;
Sebastiani, Stefano
Penultimo
Writing – Review & Editing
;
Samolsky Dekel, Boaz Gedaliahu
Ultimo
Writing – Review & Editing
2023

Abstract

Background: Noise pollution in intensive care units is a relevant problem, associated with psychological and physiological consequences for patients and healthcare staff. Sources of noise pollution include medical equipment, alarms, communication tools, staff activities, and conversations. Aim: To explore the cumulative effects of noise caused by an increasing number and type of medical devices in an intensive care setting on simulated patients with increasing clinical complexity. Secondly, to measure medical device alarms and nursing activities' sound levels, evaluating their role as potentially disruptive noises. Study Design: Observational simulation study (reported according to the STROBE checklist). Using an electronic sound meter, the sound levels of an intensive care room in seven simulated clinical scenarios were measured on a single day (09 March 2022), each featuring increasing numbers of devices, hypothetically corresponding to augmented patients' clinical complexity. Secondly, noise levels of medical device alarms and specific nursing activities performed at a distance of three meters from the sound meter were analysed. Results: The empty room's mean baseline noise level was 37.8 (±0.7) dBA; among the simulated scenarios, noise ranged between 45.3 (±1.0) and 53.5 (±1.5) dBA. Alarms ranged between 76.4 and 81.3 dBA, while nursing tasks (closing a drawer, opening a saline bag overwrap, or sterile packages) and speaking were all over 80 dBA. The noisiest activity was opening a sterile package (98 dBA). Conclusion: An increased number of medical devices, an expression of patients' higher clinical complexity, is not a significant cause of increased noise. Some specific nursing activities and conversations produce higher noise levels than medical devices and alarms. This study's findings suggest further research to assess the relationships between these factors and to encourage adequate noise reduction strategies.
2023
Imbriaco, Guglielmo; Capitano, Martina; Rocchi, Margherita; Suhan, Aglaia; Tacci, Alice; Monesi, Alessandro; Sebastiani, Stefano; Samolsky Dekel, Boaz Gedaliahu
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/928122
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