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The influence of patient characteristics on the alarm rate in intensive care units: a retrospective cohort study.
Sinno, Zeena-Carola; Shay, Denys; Kruppa, Jochen; Klopfenstein, Sophie A I; Giesa, Niklas; Flint, Anne Rike; Herren, Patrick; Scheibe, Franziska; Spies, Claudia; Hinrichs, Carl; Winter, Axel; Balzer, Felix; Poncette, Akira-Sebastian.
Afiliação
  • Sinno ZC; Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Medical Informatics, Charitéplatz 1, 10117, Berlin, Germany.
  • Shay D; Harvard T.H. Chan School of Public Health, Department of Epidemiology, Boston, MA, USA.
  • Kruppa J; Hochschule Osnabrück, University of Applied Sciences, Osnabrück, Germany.
  • Klopfenstein SAI; Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Medical Informatics, Charitéplatz 1, 10117, Berlin, Germany.
  • Giesa N; Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Core Facility Digital Medicine and Interoperability, Charitéplatz 1, 10117, Berlin, Germany.
  • Flint AR; Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Medical Informatics, Charitéplatz 1, 10117, Berlin, Germany.
  • Herren P; Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Medical Informatics, Charitéplatz 1, 10117, Berlin, Germany.
  • Scheibe F; Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Medical Informatics, Charitéplatz 1, 10117, Berlin, Germany.
  • Spies C; Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neurology, Charitéplatz 1, 10117, Berlin, Germany.
  • Hinrichs C; NeuroCure Clinical Research Center, Charitéplatz 1, 10117, Berlin, Germany.
  • Winter A; Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Anesthesiology and Intensive Care Medicine, Charitéplatz 1, 10117, Berlin, Germany.
  • Balzer F; Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Nephrology and Medical Intensive Care, Charitéplatz 1, 10117, Berlin, Germany.
  • Poncette AS; Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Surgery, Charitéplatz 1, 10117, Berlin, Germany.
Sci Rep ; 12(1): 21801, 2022 12 16.
Article em En | MEDLINE | ID: mdl-36526892
Intensive care units (ICU) are often overflooded with alarms from monitoring devices which constitutes a hazard to both staff and patients. To date, the suggested solutions to excessive monitoring alarms have remained on a research level. We aimed to identify patient characteristics that affect the ICU alarm rate with the goal of proposing a straightforward solution that can easily be implemented in ICUs. Alarm logs from eight adult ICUs of a tertiary care university-hospital in Berlin, Germany were retrospectively collected between September 2019 and March 2021. Adult patients admitted to the ICU with at least 24 h of continuous alarm logs were included in the study. The sum of alarms per patient per day was calculated. The median was 119. A total of 26,890 observations from 3205 patients were included. 23 variables were extracted from patients' electronic health records (EHR) and a multivariable logistic regression was performed to evaluate the association of patient characteristics and alarm rates. Invasive blood pressure monitoring (adjusted odds ratio (aOR) 4.68, 95%CI 4.15-5.29, p < 0.001), invasive mechanical ventilation (aOR 1.24, 95%CI 1.16-1.32, p < 0.001), heart failure (aOR 1.26, 95%CI 1.19-1.35, p < 0.001), chronic renal failure (aOR 1.18, 95%CI 1.10-1.27, p < 0.001), hypertension (aOR 1.19, 95%CI 1.13-1.26, p < 0.001), high RASS (aOR 1.22, 95%CI 1.18-1.25, p < 0.001) and scheduled surgical admission (aOR 1.22, 95%CI 1.13-1.32, p < 0.001) were significantly associated with a high alarm rate. Our study suggests that patient-specific alarm management should be integrated in the clinical routine of ICUs. To reduce the overall alarm load, particular attention regarding alarm management should be paid to patients with invasive blood pressure monitoring, invasive mechanical ventilation, heart failure, chronic renal failure, hypertension, high RASS or scheduled surgical admission since they are more likely to have a high contribution to noise pollution, alarm fatigue and hence compromised patient safety in ICUs.
Assuntos

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Alarmes Clínicos / Insuficiência Cardíaca / Hipertensão / Falência Renal Crônica Tipo de estudo: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Adult / Humans Idioma: En Revista: Sci Rep Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Alemanha

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Alarmes Clínicos / Insuficiência Cardíaca / Hipertensão / Falência Renal Crônica Tipo de estudo: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Adult / Humans Idioma: En Revista: Sci Rep Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Alemanha