Affiliations 

  • 1 Department of Nursing, The Second Affiliated Hospital Zhejiang University School of Medicine, Hangzhou, China
  • 2 Department of Nursing, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang, Malaysia
  • 3 Department of Community Health, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang, Selangor, Malaysia
  • 4 Department of Medicine, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang, Selangor, Malaysia
  • 5 Department of General Practice and International Medicine, The Second Affiliated Hospital Zhejiang University School of Medicine, Hangzhou, China
J Adv Nurs, 2024 Nov 28.
PMID: 39607180 DOI: 10.1111/jan.16541

Abstract

AIMS: To investigate the prevalence of rapid response team delays, survival distribution of admission to rapid response team delay and its prognostic factors.

DESIGN: A retrospective single-centre study.

METHODS: Data on rapid response team activations from 1 January 2018 to 31 December 2022 were retrieved from electronic medical records at a tertiary hospital in Hangzhou, China. All patients who met the eligibility criteria were included. Multivariable Cox regression analysis was conducted to analyse the data.

RESULTS: Out of 636 patients included, 18.4% (117) experienced a delay, with a median (interquartile range) of 8.5 (12) days from admission to rapid response team activation. Six significant prognostic factors were found to be associated with the higher hazard ratio of rapid response team delay, including call time (05:01 PM and 7:59 AM), emergency admission, a higher Modified Early Warning Score, an admission diagnosis of infection, a comorbidity of respiratory failure/Acute Respiratory Distress Syndrome and the absence of lung infection.

CONCLUSION: The prevalence of rapid response team delays was lower, and the days from admission to rapid response team delay was longer than in previous studies. Healthcare providers are suggested to prioritise the care of high-risk patient groups and provide proactive monitoring to ensure timely identification and management.

IMPLICATIONS FOR PATIENT CARE: Implementing artificial intelligence in continuous monitoring systems for high-risk patients is recommended. The findings help nurses anticipate potential delays in rapid response team activation, enabling better preparedness.

IMPACT: The study highlights the prevalence of rapid response team delays, timing from admission to rapid response team activation and six prognostic factors influencing delays. It could shape patient care and inform future research. Hospital administrators should review staffing, especially during night shifts, to minimise delays. Further qualitative research is needed to explore why nurses may delay rapid response team activation.

REPORTING METHOD: The STROBE checklist was adhered to when reporting this study. 'No patient or public contribution'.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.