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临床试验/NCT03865303
NCT03865303已完成不适用

Acute Care Learning Laboratory-Reducing Threats to Diagnostic Fidelity in Critical Illness

Mayo Clinic2 个研究点 分布在 1 个国家目标入组 25,551 人开始时间: 2019年4月22日最近更新:
适应症

试验速览

阶段
不适用
状态
已完成
发起方
Mayo Clinic
入组人数
25,551
试验地点
2
主要终点
Validation of automated phenotypes

研究概览

简要总结

Diagnostic error and delay remain a leading cause of preventable harm and death in the United States. Using a learning laboratory structure, researchers will implement mixed-methods research approaches to identify the systemic weaknesses that contribute to diagnostic error and delay in the hospital setting. The knowledge gained from research innovative will allow researchers to design, develop, implement, and refined a suite of human-centered tools that can be deployed to reduce the risk of diagnostic error and delay in both community and academic hospital settings.

详细描述

Despite the recognition that diagnostic errors an delays are a major contributor to preventable deaths in the USA, little progress has been made to reduce mortality outcomes from this known killer. An effective strategy leading to meaningful reduction in diagnostic error and delay rates has not made its way into practice. This proposal is unique and novel and combines mixed-methods research approaches with systems engineering research approaches to understand the interplay of the multiple factors contributing to diagnostic error and delay. The knowledge gained from this holistic approach will then be used within the learning laboratory to inform the design, development, evaluation, and refinement of the solutions to diagnostic error and delay. "Control Tower" will be the staging ground for the in situ learning laboratory and will be built on top of a well-established clinical informatics infrastructure and hospital environment open to innovation and practice change.

研究设计

研究类型
Observational
观察模型
Cohort
时间视角
Prospective

入排标准

年龄范围
18 Years 至 120 Years(Adult, Older Adult)
性别
All
接受健康志愿者

入选标准

  • 未提供

排除标准

  • 未提供

结局指标

主要结局

Validation of automated phenotypes

时间窗: 1 year

Use data from the patient electronic medical record to identify the number of diagnostic error or delay to validate clinical environment automated phenotypes

Adoption (Number of time the Control Tower used during the clinical encounters)

时间窗: 1 year

Standardized process tracking sheets to track each time the control tower system is triggered and used.

Implementation Acceptability

时间窗: 1 year

Focused questions about beliefs, attitudes, usability by healthcare providers

次要结局

未报告次要终点

研究者

发起方
Mayo Clinic
申办方类型
Other
责任方
Principal Investigator
主要研究者

Brian W. Pickering, M.B., B.Ch.

Pricinple Investigator

Mayo Clinic

研究点 (2)

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