McDaniel Corrie E, White Andrew A, Bradford Miranda C, Sy Carolyn D, Chen Tiffany, Brock Doug, Foti Jeffrey, Beck Jimmy B
C.E. McDaniel is clinical assistant professor, Department of Pediatrics, University of Washington, Seattle, Washington. A.A. White is associate professor, Department of Medicine, University of Washington, Seattle, Washington. M.C. Bradford is a biostatistician, Center for Clinical and Translational Research, Seattle Children's Research Institute, Seattle, Washington. C.D. Sy is clinical instructor, Department of Medicine, University of Washington, Seattle, Washington. T. Chen is clinical instructor, Department of Medicine, University of Washington, Seattle, Washington. D. Brock is associate professor, Department of Family Medicine, University of Washington, Seattle, Washington. J. Foti is clinical associate professor, Department of Pediatrics, University of Washington, Seattle, Washington. J.B. Beck is assistant professor, Department of Pediatrics, University of Washington, Seattle, Washington.
Acad Med. 2018 Feb;93(2):199-206. doi: 10.1097/ACM.0000000000001873.
Little is known about current practices in high-value care (HVC) bedside teaching. A lack of instruments for measuring bedside HVC behaviors confounds efforts to assess the impact of curricular interventions. The authors aimed to define observable HVC concepts by developing an instrument to measure the content and frequency of HVC discussions.The authors developed the HVC Rounding Tool in four iterative phases, using Messick's validity framework. Phases 1 and 2 were designed to collect evidence of content validity, Phases 3 and 4 to collect evidence of response process and internal structure. Phase 1 identified HVC topics within the literature. Phase 2 used a modified Delphi approach for construct definition and tool development. Through two rounds, the Delphi panel narrowed 16 HVC topics to 11 observable items, categorized into three domains (quality, cost, and patient values). Phase 3 involved rater training and creation of a codebook. Phase 4 involved three iterations of instrument piloting. Six trained raters, in pairs, observed bedside rounds during 148 patient encounters in 2016. Weighted kappas for each domain demonstrated improvement from the first to third iteration: Quality increased from 0.65 (95% CI 0.55-0.79) to 1.00, cost from 0.58 (95% CI 0.4-0.75) to 0.96 (95% CI 0.80-1.00), and patient values from 0.41 (95% CI 0.19-0.68) to 1.00. Percent positive agreement for all domains improved from 65.3% to 98.1%. This tool, the first with established validity evidence, addresses an important educational gap for measuring the translation of HVC from theoretical knowledge to bedside practice.
关于高价值医疗（HVC）床边教学的当前实践，人们了解甚少。缺乏用于衡量床边HVC行为的工具，这使得评估课程干预措施的影响变得困难。作者旨在通过开发一种工具来衡量HVC讨论的内容和频率，从而定义可观察到的HVC概念。作者使用梅西克的效度框架，分四个迭代阶段开发了HVC查房工具。第1阶段和第2阶段旨在收集内容效度的证据，第3阶段和第4阶段旨在收集反应过程和内部结构的证据。第1阶段在文献中确定了HVC主题。第2阶段采用改进的德尔菲法进行结构定义和工具开发。经过两轮，德尔菲小组将16个HVC主题缩小到11个可观察项目，分为三个领域（质量、成本和患者价值观）。第3阶段涉及评分员培训和编码手册的创建。第4阶段涉及对该工具进行三次试点迭代。2016年，六名经过培训的评分员成对观察了148次患者查房。每个领域的加权卡帕值从第一次迭代到第三次迭代都有提高：质量从0.65（95%CI 0.55 - 0.79）提高到1.00，成本从0.58（95%CI 0.4 - 0.75）提高到0.96（95%CI 0.80 - 1.00），患者价值观从0.41（95%CI 0.19 - 0.68）提高到1.00。所有领域的阳性一致率从65.3%提高到98.1%。这个工具是第一个具有既定效度证据的工具，解决了衡量HVC从理论知识到床边实践转化的一个重要教育差距问题。
