如何评估临终阶段的医院护理——用于回顾性病历分析的数据提取工具的开发

How to Evaluate Hospital Care in the Dying Phase-Development of a Data Extraction Tool for Retrospective Medical Record Analysis.

作者信息

Kaur Sukhvir, Meesters Sophie, Schieferdecker Aneta, Dangendorf Annika, Strohbücker Barbara, Oubaid Nikolas, Ullrich Anneke, Milke Viola, Oechsle Karin, Schulz Holger, Voltz Raymond, Kremeike Kerstin

机构信息

Department of Palliative Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.

Palliative Care Unit, Department of Oncology, Hematology and BMT, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.

出版信息

J Eval Clin Pract. 2025 Aug;31(5):e70174. doi: 10.1111/jep.70174.

Abstract

BACKGROUND

Hospitals are the most common place of death in European countries, including Germany, where nearly half of the population dies in hospitals, mostly outside specialised palliative care wards. At the same time, quality of hospital care in the dying phase is reported as poor. Although existing (inter-)national guidelines provide outcome variables, their evaluation of implementation is lacking. This study aims to develop and test a structured tool for data extraction from medical records (MRs) to evaluate hospital care in the dying phase. The provision of such a tool can help to identify needs for improvement of care.

METHODS

We developed a data extraction tool by operationalizing recommendations for the dying phase of the evidenced-based German National Palliative Care Guideline. The tool was used to extract notes from MRs of n = 400 deceased patients of 10 general wards and intensive care units at two University Medical Centres. We analysed the tool's information density and content validity. Descriptive statistics were calculated as frequencies and percentages.

RESULTS

The final tool consists of 39 variables in six domains. Initially, 55 variables were derived from guideline recommendations. With regard to content validity, notes for 37 (67%) variables could be extracted from the MRs, while 16 variables were removed due to poor or unclear documentation. Two additional variables were identified inductively and included in the final tool. Notes could be extracted for all domains, while information density (% of MR with notes) varied: (1) Dying process and death (n = 380, 95.0%), (2) Medication and interventions (N = 323, 80.7%), (3) Information and involvement of patients and informal caregivers (n = 155, 38.8%), (4) Symptom assessment (n = 105, 26.3%), (5) Involvement of specialised palliative care (n = 78, 19.5%), (6) Goals-of-care (n = 76, 19.0%). Variation in documentation can reflect differences in care provision or recording practices, suggesting a need for documentation standards.

CONCLUSION

The tool enables a structured retrospective analysis of guideline-recommended aspects of care in the dying phase in MRs, applicable to both general wards and intensive care units. It can support quality improvement by identifying documentation gaps and areas of care improvement, and can contribute to target interventions in different hospital settings. To obtain a comprehensive understanding of the care provided, MR analysis should be combined with other methods and perspectives and tested in other settings.

TRIAL REGISTRATION

The study is registered in the German Clinical Trials Register (DRKS00025405).

摘要

背景

在包括德国在内的欧洲国家,医院是最常见的死亡场所,在德国,近一半的人口在医院死亡,其中大部分人死于非专门的姑息治疗病房。与此同时,据报道临终阶段的医院护理质量较差。尽管现有的(国际)指南提供了结果变量,但缺乏对其实施情况的评估。本研究旨在开发并测试一种用于从医疗记录(MR)中提取数据的结构化工具,以评估临终阶段的医院护理。提供这样一种工具有助于确定护理改进的需求。

方法

我们通过将基于证据的德国国家姑息治疗指南中关于临终阶段的建议进行操作化,开发了一种数据提取工具。该工具用于从两个大学医学中心的10个普通病房和重症监护病房的n = 400名已故患者的MR中提取记录。我们分析了该工具的信息密度和内容效度。描述性统计以频率和百分比计算。

结果

最终工具由六个领域的39个变量组成。最初,从指南建议中得出了55个变量。关于内容效度,37个(67%)变量的记录可从MR中提取,而16个变量因记录不佳或不明确而被删除。另外归纳确定了两个变量并纳入最终工具。所有领域的记录均可提取,但信息密度(有记录的MR的百分比)有所不同:(1)临终过程和死亡(n = 380,95.0%),(2)药物治疗和干预措施(n = 323,80.7%),(3)患者及非正式照护者的信息与参与情况(n = 155,38.8%),(4)症状评估(n = 105,26.3%),(5)专门姑息治疗的参与情况(n = 78,19.5%),(6)护理目标(n = 76,19.0%)。记录的差异可能反映了护理提供或记录实践的差异,这表明需要记录标准。

结论

该工具能够对MR中临终阶段指南推荐的护理方面进行结构化回顾性分析,适用于普通病房和重症监护病房。它可以通过识别记录差距和护理改进领域来支持质量改进,并有助于在不同医院环境中进行针对性干预。为了全面了解所提供的护理,MR分析应与其他方法和观点相结合,并在其他环境中进行测试。

试验注册

该研究已在德国临床试验注册中心(DRKS00025405)注册。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4857/12344475/fb59efda7a89/JEP-31-0-g001.jpg

本文引用的文献

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索