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

Jónsdóttir, Guðrún R.; Haraldsdottir, Erna; Sigurðardóttir, Valgerður; Thoroddsen, Ásta; Vilhjálmsson, Rúnar; Tryggvadóttir, Guðný Bergþóra; Jónsdóttir, Helga

doi:10.1002/nop2.1789

Cited by 3 publications

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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

et al. 2023

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Aim Develop 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. Design Instrument development and inter‐rater reliability (IRR) assessment. Method NEOLCAT 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. Results IRR 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. Conclusion The 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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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

et al. 2023

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Transition to end-of-life care in patients with neurological diseases in an acute hospital ward

Jonsdottir,

Haraldsdottir,

Vilhjalmsson

et al. 2024

BMC Neurol

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Background Transitioning to end-of-life care and thereby changing the focus of treatment directives from life-sustaining treatment to comfort care is important for neurological patients in advanced stages. Late transition to end-of-life care for neurological patients has been described previously. Objective To investigate whether previous treatment directives, primary medical diagnoses, and demographic factors predict the transition to end-of-life care and time to eventual death in patients with neurological diseases in an acute hospital setting. Method All consecutive health records of patients diagnosed with stroke, amyotrophic lateral sclerosis (ALS), and Parkinson’s disease or other extrapyramidal diseases (PDoed), who died in an acute neurological ward between January 2011 and August 2020 were retrieved retrospectively. Descriptive statistics and multivariate Cox regression were used to examine the timing of treatment directives and death in relation to medical diagnosis, age, gender, and marital status. Results A total of 271 records were involved in the analysis. Patients in all diagnostic categories had a treatment directive for end-of-life care, with patients with haemorrhagic stroke having the highest (92%) and patients with PDoed the lowest (73%) proportion. Cox regression identified that the likelihood of end-of-life care decision-making was related to advancing age (HR = 1.02, 95% CI: 1.007–1.039, P = 0.005), ischaemic stroke (HR = 1.64, 95% CI: 1.034–2.618, P = 0.036) and haemorrhagic stroke (HR = 2.04, 95% CI: 1.219–3.423, P = 0.007) diagnoses. End-of-life care decision occurred from four to twenty-two days after hospital admission. The time from end-of-life care decision to death was a median of two days. Treatment directives, demographic factors, and diagnostic categories did not increase the likelihood of death following an end-of-life care decision. Conclusions Results show not only that neurological patients transit late to end-of-life care but that the timeframe of the decision differs between patients with acute neurological diseases and those with progressive neurological diseases, highlighting the particular significance of the short timeframe of patients with the progressive neurological diseases ALS and PDoed. Different trajectories of patients with neurological diseases at end-of-life should be further explored and clinical guidelines expanded to embrace the high diversity in neurological patients.

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optRF: Optimising random forest stability by determining the optimal number of trees

Lange,

Heinrich,

Gültas

et al. 2024

Preprint

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Machine learning is frequently used to make decisions based on big data. Among these techniques, random forest is particularly prominent in genomic research, where it is used for selecting the best individuals within a test population or for identifying the most important genomic markers. Although random forest is known to have many advantages, one aspect that is often overseen is that it is a non-deterministic method that can produce different models using the same input data. This can have severe consequences on decision-making processes. In this study, we introduce a method to quantify the impact of non-determinism on predictions, variable importance estimates, and the selection process. Our findings demonstrate that increasing the number of trees in random forests enhances the stability in a non-linear way while computation time increases linearly. Consequently, we conclude that there exists an optimal number of trees for any given data set that maximises the stability without unnecessarily extending the computation time. Based on these results, we have developed the R package optRF which models the relationship between the number of trees and the stability of random forest, providing recommendations for the optimal number of trees for any given data set.

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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

Cited by 3 publications

References 50 publications

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

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

Transition to end-of-life care in patients with neurological diseases in an acute hospital ward

optRF: Optimising random forest stability by determining the optimal number of trees

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