ArticleNursing open2023
Developing and testing inter-rater reliability of a data collection tool for patient health records on end-of-life care of neurological patients in an acute hospital ward.
Article in Nursing open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed, 7 citations in OpenAlex.
- optRF: Optimising random forest stability by determining the optimal number of trees.BMC bioinformatics · 2025Article
- Nursing contribution to end-of-life care decision-making in patients with neurological diseases on an acute hospital ward: documentation of signs and symptoms.BMC nursing · 2025Article
- Transition to end-of-life care in patients with neurological diseases in an acute hospital ward.BMC neurology · 2024Article
- Developing and testing inter-rater reliability of a data collection tool for patient health records on end-of-life care of neurological patients in an acute hospital ward.Nursing open · 2023Article
- End-of-Life Care in an Acute Neurological Ward: A Retrospective Analysis of Clinical Practices During the Last Week of Life.The Journal of neuroscience nursing : journal of the American Association of Neuroscience NursesObservational
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aimDevelop and test a data collection tool-Neurological End-Of-Life Care Assessment Tool (NEOLCAT)-for extracting data from patient health records (PHRs) on end-of-life care of neurological patients in an acute hospital ward.
designInstrument development and inter-rater reliability (IRR) assessment.
methodNEOLCAT was constructed from patient care items obtained from clinical guidelines and literature on end-of-life care. Expert clinicians reviewed the items. Using percentage agreement and Fleiss' kappa we calculated IRR on 32 nominal items, out of 76 items.
resultsIRR of NEOLCAT showed 89% (range 83%-95%) overall categorical percentage agreement. The Fleiss' kappa categorical coefficient was 0.84 (range 0.71-0.91). There was fair or moderate agreement on six items, and moderate or almost perfect agreement on 26 items.
conclusionThe NEOLCAT shows promising psychometric properties for studying clinical components of care of neurological patients at the end-of-life on an acute hospital ward but could be further developed in future studies.
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Registered trials
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