在同一个 (评估) 页面上:一种新的方法来增强混合方法的实施评估.
Laura Ellen Ashcraft1,2, Amanda D Peeples3, Daniel Hall4,5
1Center for Healthcare Evaluation, Resaerch, and Promotion (CHERP), VA Medical Center Corporal Michael J Crescenz, Philadelphia, Pennsylvania, USA lauraellen.ashcraft@pennmedicine.upenn.edu.
BMJ open quality
|September 23, 2025
概括
本研究提出了一种新的七步过程,用于制定复杂的质量改进和实施科学项目的严格评估计划. 这种方法提高了远程工作的跨学科团队的协调和严格性.
科学领域:
- 医疗保健服务研究 医疗服务研究
- 实施科学 实施科学
- 混合方法 研究 研究 研究 混合方法
背景情况:
- 质量改进和实施科学评估经常使用复杂的混合方法方法,涉及跨学科团队.
- 随着COVID-19大流行和远程工作的转变,这些评估面临重大挑战.
- 现有的工具不足以严格规划地理分布的远程工作团队的评估.
研究的目的:
- 创建一个新的,可复制的七步过程,为大型混合实施评估试验制定严格的评估计划.
- 解决与远程工作,跨学科团队进行复杂评估的挑战.
主要方法:
- 开发了一个七步的过程: 1) 选择模板和指定人, 2) 初始开发, 3) 异步反, 4) 差距分析, 5) 虚拟同步讨论, 6) 完成文档, 7) 申请和征求反.
- 该过程应用于九个医疗中心的大型混合型III实施评估试验.
- 纳入团队科学方法来增强评估计划的开发.
主要成果:
- 新的七步评估计划工具提高了大型计划评估的严格性和执行力.
- 该过程促进了清晰的沟通,有序的工作流程和严格的评估目标的运作.
- 评估计划开发过程充当了召集功能,加强了远程团队成员之间的协调.
结论:
- 结构化的七步过程可以提高跨学科团队的混合方法评估的严谨性和凝聚力,特别是远程工作的团队.
- 这种新的方法为在复杂的实施科学项目中制定强有力的评估计划提供了可复制的框架.
- 开发的过程支持团队协调和在具有挑战性的研究环境中有效运行评估目标.
更多相关视频
05:26Enactive Phenomenological Approach to the Trier Social Stress Test: A Mixed Methods Point of View
Published on: January 7, 2019
7.2K
06:05The Participant-Reported Implementation Update and Score PRIUS: A Novel Method for Capturing Implementation-Related Data Over Time
Published on: February 19, 2021
1.6K
相关概念视频
02:01Group Design
The most basic experimental design involves two groups: the experimental group and the control group. The two groups are designed to be the same except for one difference— experimental manipulation. The experimental group gets the experimental manipulation—that is, the treatment or variable being tested—and the control group does not. Since experimental manipulation is the only difference between the experimental and control groups, we can be sure that any differences between the two are due to...
03:00Self-Evaluation: Self-Enhancement and Self-Verification
Social psychologists have documented that feeling good about ourselves and maintaining positive self-esteem is a powerful motivator of human behavior (Tavris & Aronson, 2008). In the United States, members of the predominant culture typically think very highly of themselves and view themselves as good people who are above average on many desirable traits (Ehrlinger, Gilovich, & Ross, 2005). Often, our behavior, attitudes, and beliefs are affected when we experience a threat to our...
01:15Nursing Evaluation
The evaluation stage signals the end of the nursing process. The nurse gathers evaluative data to assess whether or not the patient has attained the expected results. Whereas the nurse collects data in the nursing assessment to identify the patient's health concerns, the evaluation stage data determines if the indicated health issues are resolved. Evaluative data collection includes two sections: the data acquired to evaluate patient outcomes and the time criteria for data collection.
Section...
Section...
01:15Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs
Bioequivalence experimental study designs play a pivotal role in testing the effectiveness of various treatments. Key among these are the repeated measures, cross-over, carry-over, and Latin square designs. In the repeated measures design, each subject receives all treatments, allowing for temporal comparisons. This type of design is useful in reducing variability but requires careful planning to avoid bias.The cross-over design, an economical method, involves sequential administration of...
01:29Self-Evaluation Maintenance Model
The Self-Evaluation Maintenance (SEM) model offers a psychological framework to understand how individuals’ self-esteem is influenced by the achievements of others, particularly those with whom they share close personal bonds. The SEM model operates when personal rather than social identity guides individuals. Central to this model is the notion that individuals have an inherent desire to preserve a favorable self-image, which is continuously shaped by interpersonal comparisons and...
01:28Methods of Medium Optimization
Optimizing growth media enhances microbial proliferation and maximizes product yield. Statistical experimental design methodologies provide structured and reproducible approaches, offering progressively higher levels of robustness and efficiency.The One-Factor-at-a-Time (OFAT) MethodThe One-Factor-at-a-Time (OFAT) method involves adjusting a single variable while keeping all others constant. However, it cannot detect interactions between variables, often leading to suboptimal outcomes when...