ArticlePloS one2023
Impact of cognitive decline on medical outcomes and nursing workload: A retrospective cohort study.
Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
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Who cites it
1 citing paper in PubMed, 3 citations in OpenAlex.
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Few reports have quantitatively investigated the effect of dementia on medical outcomes and nurse workload. Therefore, we aimed to investigate whether cognitive decline can be identified from a nurse assessment and determined its effect on medical outcomes and nurse workload. This retrospective cohort study used electronic medical record data to investigate whether patients judged by nurses to have cognitive decline were as affected as those with a dementia diagnosis. Further, a model formula was created and validated to predict the probability of needing physical restraint, the nursing care workload, and the record volume. The subjects were 43,330 patients aged ≥40 years who were hospitalized at the study hospital during the four-year study period. Data were analyzed using the chi-square test, Welch's t-test, logistic regression analysis and linear regression analysis. The implementation of physical restraint and a discharge support conference was significantly higher in patients deemed by nurses to have cognitive decline. Nurse-deemed patients with cognitive decline were affected by the outcome and workload as much as those with dementia. The false discovery rate for the Probability model formula of physical restraint and discharge support conference were 0.198 and 0.266. The correlation coefficient of the model formula for predicting nursing care and recording volume was 0.5-0.6. Combining nurse assessment and patient attribute information in a model was useful for predicting nurse workload. These findings may serve as a foundational component for the Clinical Decision Support System, aiding in the evaluation of intervention methods from the early stages of hospital admission and improving care delivery.
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