ArticleAMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science2019
Making sense of abbreviations in nursing notes: A case study on mortality prediction.
Article in AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Article
- Natural Language Processing of Nursing Notes: An Integrative Review.Computers, informatics, nursing : CIN · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Unstructured data from electronic health records hold potential for improving predictive models for health outcomes. Efforts to extract structured information from the unstructured data used text mining methodologies, such as topic modeling and sentiment analysis. However, such methods do not account for abbreviations. Nursing notes have valuable information about nurses' assessments and interventions, and the abbreviation use is common. Thus, abbreviation disambiguation may add more insight when using unstructured text for predictive modeling. We present a new process to extract structured information from nursing notes through abbreviation normalization, lemmatization, and stop word removal. Our study found that abbreviation disambiguation in nursing notes for subsequent topic modeling and sentiment analysis improved prediction of in-hospital and 30-day mortality while controlling for comorbidity.
Identifiers
31258980PMC6568120What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.