Towards a National Diagnostic Excellence Dashboard - Partnering with Stakeholders to Construct Evidence-Based Operational Measures of Misdiagnosis-Related Harms

迈向国家卓越诊断仪表板 - 与利益相关者合作，构建基于证据的误诊相关危害的操作措施

• 批准号: 10388199
• 负责人: DAVID NEWMAN-TOKER
• 金额: $ 38.66万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2024-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10388199
• 关键词: Towards; National; Diagnostic; Excellence; Dashboard

Project Summary (Abstract) This four-year project combines the assets of a leading academic medical center (Johns Hopkins Medicine) with those of a recognized international leader in diagnostic excellence (Society to Improve Diagnosis in Medicine [SIDM]) and a major physician specialty society (American College of Emergency Physicians [ACEP]) to break new ground in operational measurement of patient harms linked to diagnostic error. To achieve the goal of improved patient outcomes through diagnostic excellence, it is essential to be able to measure diagnostic performance. Diagnostic errors are the largest cause of preventable harms in US medical care, affecting an estimated 12 million people each year, causing permanent disability or death in at least 0.5 million. Diagnostic safety is a priority research area for AHRQ and the National Academy of Medicine (NAM). A key impediment to “moving the needle” on reducing harms from diagnostic error is the lack of measures that matter to both patients and clinicians, yet can be fully operationalized (i.e., routinely monitored in the existing workflow). Impactful diagnostic outcome measures would assess serious morbidity and mortality in clinical contexts where diagnostic errors are known to occur. Ideal measures would be specific, valid, precise, and comparable across institutions to facilitate benchmarking that identifies both low and high outlier performers. This proposal uses a novel approach to constructing evidence-based diagnostic outcome measures with readily-available administrative and claims data sets. The Symptom-disease Pair Analysis of Diagnostic Error (“SPADE”) method first identifies a clinically-plausible relationship between a common presenting symptom and a dangerous underlying disease (e.g., chest pain-heart attack, fever-sepsis, dizziness-stroke). It then searches for a statistically-valid pattern of unexpected adverse events (e.g., observed greater than expected short-term inpatient hospitalization following a treat-and-release emergency department [ED] visit). Once such patterns are confirmed, they can be monitored to assess the impact of interventions to improve diagnosis. This proposal seeks to mature a partially-developed SPADE measure (for dizziness-stroke, a frequent cause of serious misdiagnosis-related harms) to the point of readiness for use in national benchmarking of hospital-level diagnostic performance for quality improvement. This SPADE pair has been validated through detailed chart review and statistical testing using data from four Johns Hopkins hospitals, and the National Quality Forum (NQF) has named this measure as a top priority for immediate development. This project will advance the measure towards broad adoption with two Specific Aims: (1) engage key national stakeholders to optimize attributes of the missed stroke measure (via expert panel and emergency physician survey) and (2) measure diagnostic performance of US hospital EDs using the refined missed stroke measure (via Medicare data analysis). These Aims will address stroke misdiagnosis now and, also, yield generalizable scientific insights. This will streamline future development of new measures of harm for other important symptom-disease pairs.

项目摘要（摘要） 这个为期四年的项目结合了领先的学术医疗中心（约翰霍普金斯医学）的资产 与那些公认的国际领先的诊断卓越（社会改善诊断， 医学[SIDM]）和一个主要的医师专业协会（美国急诊医师学会 [ACEP]）在与诊断错误相关的患者伤害的操作测量方面开辟了新天地。 为了通过卓越的诊断实现改善患者预后的目标，必须能够 测量诊断性能。诊断错误是美国医疗保健中可预防伤害的最大原因 据估计，每年有1200万人受到影响，造成至少0.5%的人永久残疾或死亡。 万诊断安全性是AHRQ和美国国家医学科学院（NAM）的优先研究领域。 在减少诊断错误造成的伤害方面，“移动针头”的一个关键障碍是缺乏措施， 对患者和临床医生都很重要，但可以完全操作（即，定期监测现有的 工作流）。有影响力的诊断结果指标将评估临床中的严重发病率和死亡率 已知发生诊断错误的上下文。理想的衡量标准应该是具体的、有效的、精确的， 各机构之间的可比性，以便于确定低和高离群表现的基准。 该提案使用了一种新的方法来构建基于证据的诊断结果测量， 随时可用的行政和索赔数据集。误诊的症病配对分析 SPADE（“SPADE”）方法首先鉴定常见的呈现症状与临床上合理的关系。 和危险的潜在疾病（例如，胸痛-心脏病发作、发热-败血症、头晕-中风）。然后它 搜索意外不良事件的治疗有效模式（例如，观察值大于预期值 急诊科[艾德]就诊后短期住院）。一旦这样 如果模式得到确认，则可以对其进行监测，以评估干预措施的影响，从而改善诊断。 该提案旨在使部分开发的SPADE措施成熟（针对头晕-中风，这是一种常见的原因， 严重误诊相关的伤害），以准备用于国家医院级基准 质量改进的诊断性能。该SPADE对已通过详细图表进行验证 使用来自四家约翰霍普金斯医院和国家质量论坛的数据进行审查和统计检验 (NQF)已将这项措施列为当务之急。该项目将推动 为广泛采用而采取的措施，有两个具体目标：（1）使主要的国家利益攸关方参与， 漏诊卒中测量的属性（通过专家小组和急诊医生调查）和（2）测量 使用精确的漏诊卒中测量（通过Medicare数据）的美国医院ED的诊断性能 分析）。这些目标将解决中风误诊现在，也产生普遍的科学见解。 这将简化未来对其他重要疾病-疾病对的新危害措施的开发。