Developing Clinical Decision Support Systems Adaptive to Clinicians' Fatigue (Cessation Fatigue)

开发适应临床医生疲劳（戒断疲劳）的临床决策支持系统

• 批准号: 10655627
• 负责人: Mustafa Ozkaynak
• 金额: $ 16.91万
• 依托单位: UNIVERSITY OF COLORADO DENVER
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-07-01 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10655627
• 关键词: Accident and Emergency department; Adverse event; Affect; Antibiotics; Automation; Caring; Characteristics; Clinical; Clinical Decision Support Systems; Cognitive; Complex; Data; Decision Making; Development; Educational workshop; Electronic Health Record; Emergency medical service; Environment; Evaluation; Fatigue; Foundations; Frequencies; Future; Goals; Graph; Guidelines; Health system; Healthcare; Healthcare Systems; Hour; Impairment; Individual; Intelligence; Intercept; Interruption; Intervention; Interview; Intuition; Judgment; Knowledge; Literature; Medical Errors; Methods; Modeling; Occupational Safety; Occupations; Outcome; Outpatients; Patient-Focused Outcomes; Patients; Pattern; Performance; Personal Satisfaction; Population; Predisposition; Process; Provider; Public Health; Qualitative Evaluations; Quality of Care; Quantitative Evaluations; Reporting; Resources; Schedule; System; Techniques; Testing; Time; Trust; Underinsured; Uninsured; Variant; Work; alertness; biomedical informatics; burnout; clinical decision support; clinical decision-making; clinically relevant; design; experience; hazard; health information technology; human error; improved; innovation; literacy; multitask; negative affect; novel; patient safety; pediatric emergency; pressure; recruit; response; risk mitigation; success; support tools; theories; time use

Abstract: Fatigue is a latent hazard in health care, (particularly in emergency departments-ED), leading to poor judgement and increased medical errors. Fatigue-induced adverse events have negative financial and patient/occupational safety impact in EDs and other settings. Commonly used time- and task-management strategies (e.g., multitasking), are much less effective in clinicians with fatigue. Potential causes, consequences, and fatigue-induced adverse events, have been studied, however interventions to mitigate risks is limited. Currently proposed solutions to obviate fatigue (e.g., limit working hours, decreased patient load) can be helpful, but fatigue is a complex construct, making it less feasible to develop uncomplicated solutions. Decades of adaptive automation literature suggest that clinical decision support (CDS) systems that can adapt to in-the-moment variations in clinician’s fatigue, have potential to intercept fatigue-induced human errors and preclude potential adverse events. A criticism of CDS, is that it only provides decontextualized decision support when it has potential to be adapted to its users (i.e., frontline clinicians). Users with different fatigue level have different needs. When CDS support is decontextualized, it becomes part of the background that actually contribute to clinician fatigue. Clinicians not welcoming CDS prompts, develop strategies to avoid interacting with the CDS, which can lead to negative outcomes. Adaptive CDS would configure itself based on a clinician’s fatigue level to provide the right level of information, to the right user, at the right time. The primary objective of this study is to develop the foundation for adaptive CDS in EDs, that is sensitive to a user’s fatigue and adapts to the user’s fatigue level. A mixed method design will be used to achieve our objective through two aims: (1) Examine the impact of ED clinician fatigue on (a) clinical decision making and (b) the use of the CDS for antibiotic prescription; (2) Develop and evaluate CDS design and implementation guidelines for a CDS that adapts to ED clinician fatigue. The unique contribution of this study lies in (1) creating a foundation for a novel health information technology (HIT), adaptable CDS; (2) integrating cognitive decision-making theories into the CDS design; (3) developing a CDS to accommodate the prevalent negative work condition, fatigue. Three main deliverables will be disseminated comprehensively. First, we will provide a detailed description of impact of fatigue on clinical decision making. Second, we will provide a detailed description of impact of fatigue on the use of clinical decision support systems in EDs. Third, we will report on design guidelines for adaptive CDS, thereby supporting replicability by other scholars and designers. Eventually, this proposal will improve clinician’s performance under challenging work conditions, hence patient outcomes.

摘要：疲劳是医疗保健（尤其是在急诊部门）的懒散，导致 判断力不佳和医疗错误增加。 患者/职业安全性IMP和其他常用时间和任务管理 策略（例如，多任务）在疲劳的临床医生中有效得多。 已经研究了后果和疲劳引起的不良事件，但是干预以减轻风险 是有限的。 请帮助，但疲劳是一个复杂的辅助结构，使开发未识别的解决方案变得不太可能。 几十年的自适应自动化文献表明，临床决策支持（CD）系统可以适应 在临床医生疲劳的瞬间变化中，有可能拦截幕僚引起的人类错误和 排除潜在的不利事件。 对CD的批评是，在此之前，只有在有可能成为可能的情况下提供否定的决策支持。 适应其用户（即前线临床医生）。 支持是脱皮的，它是背景的一部分，这是临床医生疲劳的作用。 临床医生不欢迎CD提示，制定策略以避免与CD互动，这可能导致 负面结果。 在正确的时间向正确的用户提供信息级别。 这是为ED中自适应CD基础发展基础的主要目的，这对 用户的疲劳和适应用户的疲劳水平。 通过两个目的目标：（1）检查ED临床医生疲劳对（a）临床决策和和和和 （b）使用CD用于抗生素处方； 适应ED临床医生疲劳的CD指南。 这项研究的独特贡献在于（1）为Noalth信息技术创造基础 （命中），适应性CD；（2）将认知决策理论整合到CDS设计中； CD适应普遍的负面工作状况，疲劳。 三个主要的交付成果将全面传播。 疲劳对临床决策的影响。 关于临床决策支持系统的使用 CD，从而支持其他学者和设计师的可复制性。 临床医生的表演在挑战工作条件下，患者的结果。