为组织员工健康倡议制定质量改善实施分类学
Grace Gao1,2,3, Lindsay Vaclavik4, Alvin D Jeffery5,6,7
1Veteran Affairs Quality Scholars Program, Joseph Maxwell Cleland Atlanta VA Medical Center, Atlanta, Georgia, United States.
本研究引入了一种新的质量改进和实施分类法 (QIIT),用于对医疗保健中的证据翻译障碍和促进者进行分类. 该QIIT增强语义互操作性,并支持可持续的,临床知情解决方案.
科学领域:
- 医疗保健服务研究 医疗服务研究
- 信息科学 信息科学 信息科学
- 知识管理知识管理
背景情况:
- 标准化分类学 (STs) 对于知识表示和医疗保健中的语义互操作性至关重要.
- 在对证据和质量改进 (QI) 实施的交叉点的分类和编码方面存在差距.
- 本报告利用一种新的语义和本体学方法来解决这一差距.
研究的目的:
- 利用语义和本体学的方法,从员工健康QI计划中综合实施障碍和促进器数据.
- 引入一个原始的框架,即质量改进和实施分类法 (QIIT),用于分类QI实施障碍和促进者.
主要方法:
- 通过使用定性主题分析和QA因果分析,从实施障碍和促进者数据集中合成术语.
- 开发了质量改进和实施分类学 (QIIT) 分类方案.
- 在现有的条款和模型上构建了QIIT框架,包括QI计划-做-研究-行动阶段,实施研究领域的综合框架和鱼骨类别.
主要成果:
- 该QIIT是一个层次和关系分类方案.
- 该分类学与四个QI阶段,五个实施领域和六个概念决定因素联系在一起.
- 可定制描述符和二进制或利克特属性尺度进一步完善了QIIT.
结论:
- 引入了一种新的方法来标准化用于描述证据翻译到QI实施障碍和促进者的分类学.
- QIIT分类方案减少了冗余,并使语义协议和本体知识表示成为可能.
- 整合现有的分类学提高了效率,促进了可比的QI评估,以实现可持续的实施和创新的解决方案.
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