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Pilot study to show the loss of important data in nursing handover

Pothier, David, Monteiro, Pedro, Mooktiar, Mutuzua, Shaw, Alison·2005·British Journal of Nursing

Abstract

A good nursing handover process is a crucial part of providing quality nursing care in a modern healthcare environment. The conservation of patient data during the handover process is vital to ensure good continuity of care and safe practice. Any errors or omissions made during the handover process may have dangerous consequences. The authors observed the handover of 12 simulated patients over five consecutive handover cycles between nurses. Three handover styles were used and the amount of data loss was recorded for each style. A purely verbal handover style resulted in the loss of all data after three cycles. A note-taking style (the traditional style used in most hospital wards) resulted in only 31% of data being transferred correctly after five cycles. When a typed sheet was included with the verbal handover, data loss was minimal. Current handover methods may result in significant loss of important data that may impact on patient care. The authors recommend that prior to handover, a formal handover sheet be constructed that can be transferred as part of the handover process.

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Metadata

Authors
Pothier, D., Monteiro, P., Mooktiar, M., & Shaw, A.
Venue
British Journal of Nursing
Published
2005-11-01
Volume
14
Issue
20
Pages
1090-1093
ISSN
  • 0966-0461 (ISSN-L)
  • 2052-2819
OpenAlex
W2132195419
Cited by
170
References
0
FWCI
2.78
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Pilot study to show the loss of important data in nursing handover. https://app.cochat.ai/papers/10.12968/bjon.2005.14.20.20053
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Pothier, D., Monteiro, P., Mooktiar, M., & Shaw, A. (2005). Pilot study to show the loss of important data in nursing handover. British Journal of Nursing. https://doi.org/10.12968/bjon.2005.14.20.20053

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.