Evidence map›Paper›PMID 42184213›Full record

Observational studyJournal of nursing management2026

Topic Modeling of Nursing Documentation in Hemodialysis Units: A Mixed-Methods Study of Nursing Surveillance Activities.

Mi-Kyoung Cho, Hye-Young Kim, Hyohjung Lee, Yoon Hee Cho

Abstract readObservational Study
In one paragraph

Observational study in Journal of nursing management, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Observational
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Mi-Kyoung ChoDepartment of Nursing Science, Research Institute of Nursing Science, College of Nursing, Chungbuk National University, Cheongju, South Korea, chungbuk.ac.kr.ORCID https://orcid.org/0000-0003-1406-1149
Hye-Young KimDepartment of Internal Medicine, Chungbuk National University Hospital, College of Medicine, Chungbuk National University, Cheongju, South Korea, chungbuk.ac.kr.ORCID https://orcid.org/0000-0003-4102-5135
Hyohjung LeeDepartment of Nursing Science, Research Institute of Nursing Science, College of Nursing, Chungbuk National University, Cheongju, South Korea, chungbuk.ac.kr.ORCID https://orcid.org/0009-0008-9063-4694
Yoon Hee ChoDepartment of Nursing, College of Nursing, Dankook University, Cheonan, South Korea, dankook.ac.kr.ORCID https://orcid.org/0000-0002-5555-6650

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

AIM AND

objectivesThis study aimed to characterize documentation patterns in hemodialysis nursing records using integrated text mining and nursing surveillance analysis, focusing on surveillance priorities and documentation imbalances.

backgroundHemodialysis patients require continuous nursing surveillance due to frequent intradialytic complications; however, systematic analyses of nursing documentation in this setting remain limited.

designA mixed-methods study integrating quantitative text mining and structured analysis of nursing surveillance activities.

methodsFree-text nursing records (300,321 entries) generated during maintenance hemodialysis sessions for 188 adult patients at a tertiary hospital in South Korea (July 2020-June 2025) were analyzed. Keyword frequency analysis and latent Dirichlet allocation topic modeling were performed after preprocessing, resulting in an eight-topic model. Nursing surveillance activities were mapped to the 16-item Korean Nursing Surveillance Scale through sentence-level classification by two independent researchers.

resultsThe top 30 keywords accounted for 75.3% of all extracted terms, indicating highly repetitive documentation. Terms related to dialysis procedures, vascular access, blood pressure, vital signs, bleeding, falls, pain, dizziness, and hypotension were frequently documented, whereas education-related terms were less frequently documented. Topic modeling identified three overarching domains: the hemodialysis treatment process, clinical assessment and monitoring, and safety and risk management. Surveillance item analysis demonstrated high documentation frequencies for vascular access, vital signs, bleeding, and hypotension or dizziness, with low documentation of patient self-management and education.

conclusionHemodialysis nursing documentation primarily emphasizes physiological surveillance and safety management, with relatively limited documentation of patient education and self-management support. IMPLICATIONS FOR NURSE LEADERS: These findings suggest that optimizing electronic nursing record templates, along with incorporating structured prompts and natural language processing approaches, may support more balanced documentation and data-driven decision-making.

Indexed as

Data MiningDocumentationHemodialysis Units, HospitalNursing RecordsRenal DialysisAdultFemaleHumansMaleRepublic of Koreamachinenatural language processingnursing recordspatient safetypattern analysisrenal dialysis

Identifiers

PMID42184213
PMCPMC13200736

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LicenceCC BY
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Registered trials

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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.