谷歌浏览器插件
订阅小程序
在清言上使用

Partnership As a Pathway to Diagnostic Excellence: the Challenges and Successes of Implementing the Safer Dx Learning Lab

The Joint Commission Journal on Quality and Patient Safety(2024)

引用 0|浏览4
暂无评分
摘要
BackgroundLearning health system (LHS) approaches could potentially help health care organizations (HCOs) identify and address diagnostic errors. However, few such programs exist, and their implementation is poorly understood.MethodsWe conducted a qualitative evaluation of the Safer Dx Learning Lab, a partnership between a health system and a research team, to identify and learn from diagnostic errors and improve diagnostic safety at an organizational level. We conducted virtual interviews to solicit participant feedback regarding experiences with the lab, focusing specifically on implementation and sustainment issues.ResultsInterviews of 25 members associated with the lab identified the following successes: learning and professional growth, improved workflow related to streamlining the process of reporting error cases, and a psychologically safe culture for identifying and reporting diagnostic errors. However, multiple barriers also emerged: competing priorities between clinical responsibilities and research, time-management issues related to a lack of protected time, and inadequate guidance to disseminate findings. Lessons learned included understanding the importance of obtaining buy-in from leadership and interested stakeholders, creating a psychologically safe environment for reporting cases, and the need for more protected time for clinicians to review and learn from cases.ConclusionsFindings suggest that a learning health systems approach using partnerships between researchers and a health system impacted organizational culture by prioritizing learning from diagnostic errors and encouraging clinicians to be more open to reporting. The study findings can help organizations overcome barriers to engage clinicians and inform future implementation and sustainment of similar initiatives.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要