An expert-guided machine-learning approach to estimate the incidence, risk and harms associated with diagnostic delays for infectious diseases.

项目摘要/摘要 诊断错误越来越被认为是疼痛、痛苦和增加的原因 医疗保健成本。诊断延迟是一类重要的诊断错误。虽然很多人 诊断错误发生在医院设置中，急诊科就诊可能特别 重要的是要考虑，因为他们治疗危重病人，因为大多数决定 入院的病人都是在急诊科做的。因此，要实现更多 完全了解诊断延迟需要考虑跨 一系列医疗保健设置，包括诊所就诊、急诊科就诊和 住院治疗。 在诊断传染病方面的延误是值得考虑的重要问题。对于传染性传染病来说 疾病、诊断延迟增加了额外暴露的风险，潜在地 更多的案子。第二，许多传染病是可以有效治疗的，但即使是短暂的延误 在治疗中会导致更差的临床结果。然而，除了少数传染性疾病外， 对疾病(如结核病)、传染病诊断延误的研究不足。因此， 迫切需要调查发病率、危险因素和临床影响以进行诊断。 传染病延误。 我们研究的主要目标是调查与以下相关的诊断延迟 使用现有数据和来自计算机科学领域的方法的传染病 和统计数据。在我们的研究依赖于“大数据”的同时，我们还将利用临床专家 回顾我们的所有结果，并为其做出贡献。我们的主题专家将专业知识融入到 传染病、急诊医学、急诊护理、医学教育、诊断推理、 医疗保健流行病学、公共卫生、工业和专业传染病学会。 具体地说，我们将1)确定大范围诊断延迟的发生率 传染病；2)确定与传染性疾病诊断延误相关的风险因素 经常延误或后果严重的疾病；以及3)估计 在医疗成本和死亡率方面的诊断延误。用我们的数据、方法和临床 专家们，我们将能够将我们的结果转化为未来旨在减少 诊断延迟和改善医疗保健结果。此外，虽然我们的提案侧重于 传染病，我们将发展的方法和途径可以通过 调查非传染性疾病和状况。

Project Summary / Abstract Diagnostic errors are increasingly recognized as a cause of pain, suffering and increased healthcare costs. Diagnostic delays are an important class of diagnostic errors. While many diagnostic errors occur in hospital settings, emergency departments visits may be especially important to consider because they treat critically ill patients and because most decisions to admit patients to the hospital are made in emergency departments. Thus, to enable a more complete understanding of diagnostic delays requires consideration of healthcare visits across a range of healthcare settings including clinic visits, emergency department visits and hospitalizations. Delays in diagnosing infectious diseases are important to consider. For contagious infectious diseases, diagnostic delays increase the risk of additional exposures, potentially generating more cases. Second, many infectious diseases can be effectively treated, but even short delays in treatment lead to worse clinical outcomes. However, with the exception of a few infectious diseases (e.g., tuberculosis), diagnostic delays for infectious diseases are understudied. Thus, there is a critical need to investigate the incidence, risk factors and clinical impact for diagnostic delays for infectious diseases. The overarching goal of our research is to investigate diagnostic delays associated with infectious diseases using existing data along with methods from the fields of computer science and statistics. While our research relies upon “big data”, we will also use clinical experts to review and contribute to all of our results. Our subject matter experts incorporate expertise in infectious diseases, emergency medicine, acute care, medical education, diagnostic reasoning, healthcare epidemiology, public health, industry, and professional infectious disease societies. Specifically, we will 1) determine the incidence of diagnostic delays for a wide range of infectious diseases; 2) identify the risk factors associated with diagnostic delays for infectious diseases that are frequently delayed or have serious outcomes; and 3) estimate the impact of diagnostic delays in terms of healthcare costs and mortality. With our data, methods and clinical experts, we will be able to translate our results into future interventions designed to decrease diagnostic delays and improve healthcare outcomes. In addition, while our proposal focuses on infectious diseases, the methods and approaches that we will develop can be adopted to investigate non-infectious diseases and conditions.