Evidence map›Paper›PMID 40036488›Full record

ArticleJMIR medical informatics2025

Correlation Between Diagnosis-Related Group Weights and Nursing Time in the Cardiology Department: Cross-Sectional Study.

Chen Lv, Yi-Hong Gong, Xiu-Hua Wang, Jun An, Qian Wang, Jing Han, Xiao-Feng Chen

Abstract read
In one paragraph

Article in JMIR medical informatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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0cells of the map it votes in
2citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Observational
4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Chen LvDepartment of Nursing, Beijing Chest Hospital, Capital Medical University, Beijing, China.
Yi-Hong GongDepartment of Performance and Reform, Beijing Chest Hospital, Capital Medical University, Beijing, China.
Xiu-Hua WangDepartment of Nursing, Beijing Chest Hospital, Capital Medical University, Beijing, China.
Jun AnDepartment of Information Center, Beijing Chest Hospital, Capital Medical University, Beijing, China.
Qian WangDepartment of Orthopaedics, Beijing Chest Hospital, Capital Medical University, Beijing, China.
Jing HanDepartment of Cardiology, Beijing Chest Hospital, Capital Medical University, Beijing, China.
Xiao-Feng ChenDepartment of Intensive Care Unit, Beijing Chest Hospital, Capital Medical University, No.9 Beiguan Street, Area 1, Tongzhou District, Beijing, 101149, China, +86 18210076705.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Diagnosis-related group (DRG) payment has become the main form of medical expense settlements, and its application is becoming increasingly extensive. Objective: This study aimed to explore the correlation between DRG weights and nursing time and to develop a predictive model for nursing time in the cardiology department based on DRG weights and other factors. Methods: A convenience sampling method was used to select patients who were hospitalized in the cardiology ward of Beijing Chest Hospital between April 2023 and April 2024. Nursing time was measured by direct and indirect nursing time. To determine the distributions of nursing time based on different demographics, a Pearson correlation was used to analyze the relationship between DRG weight and nursing time, and a multiple linear regression was used to determine the influencing factors of total nursing time. Results: A total of 103 subjects were included in this study. The DRG weights were positively correlated with direct nursing time (r=0.480; P<.001), indirect nursing time (r=0.394; P<.001), and total nursing time (r=0.448; P<.001). Moreover, age was positively correlated with the 3 nursing times (direct: r=0.235; indirect: r=0.192; total: r=0.235; all P<.001). The activities of daily living (ADL) score on admission was negatively correlated with the 3 nursing times (direct: r=-0.316; indirect: r=-0.252; total: r=-0.301; all P<.001). In addition, the nursing level on the first day of admission was positively correlated with the 3 nursing times (direct: r=0.333; indirect: r=0.332; total: r=0.352; all P<.001). Furthermore, the multivariate analysis found that the nursing level on the first day of admission, complications or comorbidities, DRG weight, and ADL score on admission were the influencing factors of nursing time (R2=0.328; F5,97=69.58; P<.001). Conclusions: DRG weight showed a strong correlation with nursing time and could be used to predict nursing time, which may assist in nursing resource allocation in cardiology departments.

Indexed as

Cardiology Service, HospitalDiagnosis-Related GroupsAdultAgedBeijingCross-Sectional StudiesFemaleHumansMaleMiddle AgedTime Factorsdiagnosis-related groupshuman resourcesnursingnursing timeworkload

Identifiers

PMID40036488
PMCPMC11896087

What Socratic holds

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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 Socratic graph.