Suppr超能文献

一种用于简化多学科肿瘤委员会工作流程的病例复杂性衡量标准:MeDiC 工具的混合方法开发和早期验证。

A measure of case complexity for streamlining workflow in multidisciplinary tumor boards: Mixed methods development and early validation of the MeDiC tool.

机构信息

Centre for Implementation Science, Health Service and Population Research Department, King's College London, London, UK.

Department of Surgery, University College London Hospitals NHS Foundation Trust, London, UK.

出版信息

Cancer Med. 2020 Jul;9(14):5143-5154. doi: 10.1002/cam4.3026. Epub 2020 May 31.

Abstract

BACKGROUND AND OBJECTIVE

There is increasing emphasis in cancer care globally for care to be reviewed and managed by multidisciplinary teams (ie, in tumor boards). Evidence and recommendations suggest that the complexity of each patient case needs to be considered as care is planned; however, no tool currently exists for cancer teams to do so. We report the development and early validation of such a tool.

METHODS

We used a mixed-methods approach involving psychometric evaluation and expert review to develop the Measure of case-Discussion Complexity (MeDiC) between May 2014 and November 2016. The study ran in six phases and included ethnographic interviews, observations, surveys, feasibility and reliability testing, expert consensus, and multiple expert-team reviews.

RESULTS

Phase-1: case complexity factors identified through literature review and expert interviews; Phase-2: 51 factors subjected to iterative review and content validation by nine cancer teams across four England Trusts with nine further items identified; Phase 3: 60 items subjected to expert review distilled to the most relevant; Phase 4: item weighing and further content validation through a national UK survey; Phases 5 and 6: excellent interassessor reliability between clinical and nonclinical observers, and adequate validity on 903 video case discussions achieved. A final set of 27 factors, measuring clinical and logistical complexities were integrated into MeDiC.

CONCLUSIONS

MeDiC is an evidence-based and expert-driven tool that gauges the complexity of cancer cases. MeDiC may be used as a clinical quality assurance and screening tool for tumor board consideration through case selection and prioritization.

摘要

背景与目的

在全球范围内,癌症治疗越来越强调由多学科团队(即肿瘤委员会)来审查和管理护理。有证据和建议表明,在规划护理时需要考虑每个患者病例的复杂性;然而,目前还没有癌症团队可以使用的工具。我们报告了这种工具的开发和早期验证。

方法

我们使用了一种混合方法,包括心理测量评估和专家审查,以开发用于评估病例讨论复杂性的测量工具(MeDiC)。该研究在 2014 年 5 月至 2016 年 11 月期间分六个阶段进行,包括民族志访谈、观察、调查、可行性和可靠性测试、专家共识以及多次专家团队审查。

结果

第 1 阶段:通过文献回顾和专家访谈确定病例复杂性因素;第 2 阶段:9 个英格兰信托机构的 9 个癌症团队对 51 个因素进行了迭代审查和内容验证,并确定了另外 9 个因素;第 3 阶段:对 60 个因素进行专家审查,以确定最相关的因素;第 4 阶段:通过英国全国性调查对项目进行加权和进一步内容验证;第 5 阶段和第 6 阶段:临床和非临床观察员之间的评估者间信度极好,在 903 个视频病例讨论中达到了足够的有效性。一套最终的 27 个因素,用于衡量临床和后勤复杂性,被整合到 MeDiC 中。

结论

MeDiC 是一种基于证据和专家驱动的工具,用于衡量癌症病例的复杂性。MeDiC 可以作为一种临床质量保证和筛选工具,通过病例选择和优先级确定来考虑肿瘤委员会。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2cbb/7367630/5e662d9f4b34/CAM4-9-5143-g001.jpg

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

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验