Correlation between Diagnosis-related Group Weights and Nursing Time in the Cardiology Department: A Cross-sectional Study.

IF 3.1 3区医学 Q2 MEDICAL INFORMATICS

JMIR Medical Informatics Pub Date : 2024-11-20 DOI:10.2196/65549

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

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Abstract

Background: Diagnosis-related group (DRG) payment has become the main way of medical expenses settlement, and its application is more and more 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: The convenience sampling method was used to select patients who were hospitalised in the cardiology ward of our hospital between April 2023 and April 2024 as the study participants. Nursing time was measured by direct and indirect nursing time. For the distribution of nursing time with different demographic characteristics, Pearson correlation was used to analyse the relationship between DRG weights and nursing time and multiple linear regression was used to analyse 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 ln(direct nursing time), ln(indirect nursing time) and ln(total nursing time) (r = 0.480, r = 0.394, r = 0.448, all P < .001). Moreover, age was positively correlated with the three nursing times (r = 0.235, r = 0.192, r = 0.235, all P < .001); activities of daily living (ADL) on admission was negatively correlated with the three nursing times (r = -0.316, r = -0.252, r = -0.301, all P < .001); and nursing level on the first day of admission was positively correlated with the three nursing times (r = 0.333, r = 0.332, r = 0.352, all P < .001). Furthermore, the multivariate analysis found that nursing levels on the first day of admission, complications or comorbidities, DRG weights and ADL on admission were the influencing factors of the nursing time of patients (R2 = 0.328, F = 69.58, P < .001).

Conclusions: Diagnosis-related group weights showed a strong correlation with nursing time and can be used to predict nursing time, which may assist in nursing resource allocation in cardiology departments.

Clinicaltrial:

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心脏病科诊断相关组权重与护理时间之间的相关性：一项横断面研究。

背景：诊断相关分组（DRG）付费已成为医疗费用结算的主要方式，其应用范围越来越广：本研究旨在探讨 DRG 权重与护理时间之间的相关性，并根据 DRG 权重和其他因素建立心内科护理时间预测模型：采用方便抽样法，选取 2023 年 4 月至 2024 年 4 月期间在我院心内科病房住院的患者作为研究对象。护理时间通过直接护理时间和间接护理时间进行测量。针对不同人口统计学特征的护理时间分布，采用皮尔逊相关分析 DRGs 权重与护理时间的关系，采用多元线性回归分析总护理时间的影响因素：结果：本研究共纳入 103 名受试者。DRG 权重与 ln（直接护理时间）、ln（间接护理时间）和 ln（总护理时间）呈正相关（r = 0.480、r = 0.394、r = 0.448，均 P <.001）。此外，年龄与三种护理时间呈正相关（r = 0.235、r = 0.192、r = 0.235，均 P < .001）；入院时的日常生活活动（ADL）与三种护理时间呈负相关（r = -0.316、r = -0.252、r = -0.301，所有 P < .001）；入院第一天的护理水平与三个护理时间呈正相关（r = 0.333、r = 0.332、r = 0.352，所有 P < .001）。此外，多变量分析发现，入院第一天的护理水平、并发症或合并症、DRGs 权重和入院时的 ADL 是患者护理时间的影响因素（R2 = 0.328，F = 69.58，P < .001）：诊断相关组权重与护理时间密切相关，可用于预测护理时间，有助于心内科护理资源分配：

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

JMIR Medical Informatics Medicine-Health Informatics

CiteScore

7.90

自引率

3.10%

发文量

173

审稿时长

12 weeks

期刊介绍： JMIR Medical Informatics (JMI, ISSN 2291-9694) is a top-rated, tier A journal which focuses on clinical informatics, big data in health and health care, decision support for health professionals, electronic health records, ehealth infrastructures and implementation. It has a focus on applied, translational research, with a broad readership including clinicians, CIOs, engineers, industry and health informatics professionals. Published by JMIR Publications, publisher of the Journal of Medical Internet Research (JMIR), the leading eHealth/mHealth journal (Impact Factor 2016: 5.175), JMIR Med Inform has a slightly different scope (emphasizing more on applications for clinicians and health professionals rather than consumers/citizens, which is the focus of JMIR), publishes even faster, and also allows papers which are more technical or more formative than what would be published in the Journal of Medical Internet Research.