The feasibility and validity of using a real time location system (RTLS) to measure bedside contact time.

direct patient contact healthcare resource management nurse staffing requirements nursing time real time location system

Journal

Journal of research in nursing : JRN
ISSN: 1744-988X
Titre abrégé: J Res Nurs
Pays: England
ID NLM: 101234311

Informations de publication

Date de publication:
Aug 2022
Historique:
entrez: 22 9 2022
pubmed: 23 9 2022
medline: 23 9 2022
Statut: ppublish

Résumé

The association between the nurse-to-patient ratio and patient outcomes has been extensively investigated. Real time location systems have the potential capability of measuring the actual amount of bedside contact patients receive. This study aimed to determine the feasibility and accuracy of real time location systems as a measure of the amount of contact time that nurses spent in the patients' bed space. An exploratory, observational, feasibility study was designed to compare the accuracy of data collection between manual observation performed by a researcher and real time location systems data capture capability. Four nurses participated in the study, which took place in 2019 on two hospital wards. They were observed by a researcher while carrying out their work activities for a total of 230 minutes. The amount of time the nurses spent in the patients' bed space was recorded in 10-minute blocks of time and the real time location systems data were extracted for the same nurse at the time of observation. Data were then analysed for the level of agreement between the observed and the real time location systems measured data, descriptively and graphically using a kernel density and a scatter plot. The difference (in minutes) between researcher observed and real time location systems measured data for the 23, 10-minute observation blocks ranged from zero (complete agreement) to 5 minutes. The mean difference between the researcher observed and real time location systems time in the patients' bed space was one minute (10% of the time). On average, real time location systems measured time in the bed space was longer than the researcher observed time. There were good levels of agreement between researcher observation and real time location systems data of the time nurses spend at the bedside. This study confirms that it is feasible to use real time location systems as an accurate measure of the amount of time nurses spend at the patients' bedside.

Sections du résumé

Background UNASSIGNED
The association between the nurse-to-patient ratio and patient outcomes has been extensively investigated. Real time location systems have the potential capability of measuring the actual amount of bedside contact patients receive.
Aims UNASSIGNED
This study aimed to determine the feasibility and accuracy of real time location systems as a measure of the amount of contact time that nurses spent in the patients' bed space.
Methods UNASSIGNED
An exploratory, observational, feasibility study was designed to compare the accuracy of data collection between manual observation performed by a researcher and real time location systems data capture capability. Four nurses participated in the study, which took place in 2019 on two hospital wards. They were observed by a researcher while carrying out their work activities for a total of 230 minutes. The amount of time the nurses spent in the patients' bed space was recorded in 10-minute blocks of time and the real time location systems data were extracted for the same nurse at the time of observation. Data were then analysed for the level of agreement between the observed and the real time location systems measured data, descriptively and graphically using a kernel density and a scatter plot.
Results UNASSIGNED
The difference (in minutes) between researcher observed and real time location systems measured data for the 23, 10-minute observation blocks ranged from zero (complete agreement) to 5 minutes. The mean difference between the researcher observed and real time location systems time in the patients' bed space was one minute (10% of the time). On average, real time location systems measured time in the bed space was longer than the researcher observed time.
Conclusions UNASSIGNED
There were good levels of agreement between researcher observation and real time location systems data of the time nurses spend at the bedside. This study confirms that it is feasible to use real time location systems as an accurate measure of the amount of time nurses spend at the patients' bedside.

Identifiants

pubmed: 36131691
doi: 10.1177/17449871211016169
pii: 10.1177_17449871211016169
pmc: PMC9483226
doi:

Types de publication

Journal Article

Langues

eng

Pagination

421-433

Informations de copyright

© The Author(s) 2021.

Déclaration de conflit d'intérêts

Declaration of conflicting interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

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Auteurs

Ann-Marie Cannaby (AM)

Chief Nurse, The Royal Wolverhampton NHS Trust, New Cross Hospital, Wolverhampton, UK.

Vanda Carter (V)

Practice Education Facilitator for Research, The Royal Wolverhampton NHS Trust, New Cross Hospital, Wolverhampton, UK.

Thomas Hoe (T)

Economist Researcher/ Consultant, The Royal Wolverhampton NHS Trust, New Cross Hospital, Wolverhampton, UK.

Stephenson Strobel (S)

Economics Candidate, Cornell University Department of Policy Analysis and Management, Ithaca, NY.

Elena Ashtari Tafti (EA)

PhD in Economics Candidate, University College London, London, UK; The Royal Wolverhampton NHS Trust, New Cross Hospital, Wolverhampton, UK.

Rephna Baker (R)

Associate Chief Nurse,The Royal Wolverhampton NHS Trust, New Cross Hospital, Wolverhampton, UK.

Clare Nash (C)

Senior Procurement Nurse, The Royal Wolverhampton NHS Trust, New Cross Hospital, Wolverhampton, UK.

Vanessa Whatley (V)

Deputy CNO, The Royal Wolverhampton NHS Trust, New Cross Hospital, Wolverhampton, UK.

Richard Gray (R)

Professor of Clinical Nursing Practice, School of Nursing and Midwifery, College of Science, Health and Engineering, La Trobe University, Bundoora, Australia.

Classifications MeSH