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利用仪表板支持本科和研究生医学教育中的持续质量改进。

Using Dashboards to Support Continuous Quality Improvement in Undergraduate and Graduate Medical Education.

作者信息

Dufault Carolyn L, Colson Eve R, Dallaghan Gary L Beck, Buchanan April O, Aagaard Eva M, Blaylock Leslie, Wroblewski Matthew, Osterberg Lars, Roman Brenda J B, Coplit Lisa

机构信息

Washington University School of Medicine, St. Louis, MO, USA.

Carle Illinois College of Medicine, Urbana, IL, USA.

出版信息

J Gen Intern Med. 2025 Jan;40(1):171-176. doi: 10.1007/s11606-024-09011-2. Epub 2024 Sep 4.

DOI:10.1007/s11606-024-09011-2
PMID:39230808
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11780057/
Abstract

Like other complex systems, medical education programs require a systematic continuous quality improvement (CQI) approach to drive effective improvement. Accreditation bodies in both undergraduate medical education (UME) and graduate medical education (GME) require programs to have effective CQI processes. Dashboards facilitate visualization and tracking of key metrics that impact medical education programming, thus driving excellence. Keys to developing useful dashboards include using existing program evaluation frameworks to identify desired outputs, determine acceptable evidence, and identify key data sources. In developing dashboards, it is important to consider data management including oversight and appropriate sharing of reports. When effectively developed and delivered to key parties, data dashboards serve as valuable tools to drive improvement of medical education programing. The purpose of this paper is to provide guidance for dashboard implementation and use in medical education, with a focus on UME and GME, based on available literature and experiences in our own institutions.

摘要

与其他复杂系统一样,医学教育项目需要采用系统的持续质量改进(CQI)方法来推动有效的改进。本科医学教育(UME)和研究生医学教育(GME)的认证机构都要求项目具备有效的CQI流程。仪表盘有助于可视化和跟踪影响医学教育规划的关键指标,从而推动卓越发展。开发有用仪表盘的关键包括使用现有的项目评估框架来确定期望的产出、确定可接受的证据以及识别关键数据源。在开发仪表盘时,重要的是要考虑数据管理,包括报告的监督和适当共享。当有效开发并提供给关键方时,数据仪表盘可作为推动医学教育规划改进的宝贵工具。本文的目的是根据现有文献和我们自己机构的经验,为医学教育中仪表盘的实施和使用提供指导,重点是UME和GME。

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本文引用的文献

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Competency-Based Assessments: Leveraging Artificial Intelligence to Predict Subcompetency Content.基于能力的评估:利用人工智能预测亚能力内容。
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Drivers of Dashboard Development (3-D): A Curricular Continuous Quality Improvement Approach.仪表盘开发的驱动因素(3-D):一种课程持续质量改进方法。
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