Acute Care Learning Laboratory-Reducing Threats to Diagnostic Fidelity in Critical Illness
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
- 否
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
Brian W. Pickering, M.B., B.Ch.
Pricinple Investigator
Mayo Clinic
