An economic evaluation of the Prioritising Responses Of Nurses To deteriorating patient Observations (PRONTO) clinical trial.

Clinical decision-making Hospital cost Medical Emergency Team (MET) Rapid Response System (RRS) cost analysis length of stay nursing care vital signs

Journal

Resuscitation
ISSN: 1873-1570
Titre abrégé: Resuscitation
Pays: Ireland
ID NLM: 0332173

Informations de publication

Date de publication:
10 Jun 2024
Historique:
received: 19 03 2024
revised: 26 05 2024
accepted: 05 06 2024
medline: 13 6 2024
pubmed: 13 6 2024
entrez: 12 6 2024
Statut: aheadofprint

Résumé

Early recognition and response to clinical deterioration reduce the frequency of in-hospital cardiac arrests, mortality, and unplanned intensive care unit (ICU) admissions. This study aimed to investigate the impact of the Prioritising Responses Of Nurses To deteriorating patient Observations (PRONTO) intervention on hospital costs and patient length of stay (LOS). The PRONTO cluster randomised control trial was conducted to improve nurses' responses to patients with abnormal vital signs. Hospital data were collected pre-intervention (T Hospital admission data for 6065 patients (intervention group, 3102; control group, 2963) were collected from four hospitals for T The results of the economic analysis demonstrated that the PRONTO intervention improved nurses' responses to patients with abnormal vital signs and significantly reduced hospital LOS by two days at 12 months in the intervention group compared to baseline. From the hospital's perspective, savings from reduced hospitalisations offset the costs of implementing PRONTO.

Sections du résumé

BACKGROUND BACKGROUND
Early recognition and response to clinical deterioration reduce the frequency of in-hospital cardiac arrests, mortality, and unplanned intensive care unit (ICU) admissions. This study aimed to investigate the impact of the Prioritising Responses Of Nurses To deteriorating patient Observations (PRONTO) intervention on hospital costs and patient length of stay (LOS).
METHOD METHODS
The PRONTO cluster randomised control trial was conducted to improve nurses' responses to patients with abnormal vital signs. Hospital data were collected pre-intervention (T
RESULTS RESULTS
Hospital admission data for 6065 patients (intervention group, 3102; control group, 2963) were collected from four hospitals for T
CONCLUSION CONCLUSIONS
The results of the economic analysis demonstrated that the PRONTO intervention improved nurses' responses to patients with abnormal vital signs and significantly reduced hospital LOS by two days at 12 months in the intervention group compared to baseline. From the hospital's perspective, savings from reduced hospitalisations offset the costs of implementing PRONTO.

Identifiants

pubmed: 38866230
pii: S0300-9572(24)00165-5
doi: 10.1016/j.resuscitation.2024.110272
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

110272

Informations de copyright

Copyright © 2024. Published by Elsevier B.V.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Shalika Bohingamu Mudiyanselage (S)

School of Health and Social Development, Deakin Health Economics, Institute for Health Transformation, Faculty of Health, Deakin University, Geelong, Victoria, Australia. Electronic address: shalika.b@deakin.edu.au.

Julie Considine (J)

School of Nursing and Midwifery, Centre for Quality and Patient Safety Research, Institute for Health Transformation, Faculty of Health, Deakin University, Geelong, Victoria, Australia; Centre for Quality and Patient Safety Research - Eastern Health Partnership, Eastern Health, Box Hill, Victoria, Australia.

Alison M Hutchinson (AM)

School of Nursing and Midwifery, Centre for Quality and Patient Safety Research, Institute for Health Transformation, Faculty of Health, Deakin University, Geelong, Victoria, Australia; Barwon Health, Geelong, Victoria, Australia.

Imogen Mitchell (I)

Australian National University College of Health and Medicine, Canberra, Australian Capital Territory, Australia; Research and Academic Partnerships, Canberra Health Services, Canberra, Australian Capital Territory, Australia.

Mohammadreza Mohebbi (M)

Faculty of Health, Biostatistics Unit, Deakin University, Geelong, Victoria, Australia.

Jennifer J Watts (JJ)

School of Health and Social Development, Deakin Health Economics, Institute for Health Transformation, Faculty of Health, Deakin University, Geelong, Victoria, Australia.

Tracey K Bucknall (TK)

School of Nursing and Midwifery, Centre for Quality and Patient Safety Research, Institute for Health Transformation, Faculty of Health, Deakin University, Geelong, Victoria, Australia; Alfred Health, Melbourne, Victoria, Australia.

Classifications MeSH