Computer Simulation of Acute Coronary Syndrome Care in the Emergency Department

急诊科急性冠脉综合征护理的计算机模拟

基本信息

批准号：
7800874
负责人：
DANIEL Joseph FRANCE
金额：
$ 19.73万
依托单位：
VANDERBILT UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2009
资助国家：
美国
起止时间：
2009-04-10 至 2012-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7800874
关键词：
Academy Accident and Emergency department Acute Acute myocardial infarction Adult Affect American American Heart Association Beds Biochemistry Biological Markers Cardiac Cardiology Caring Cause of Death Characteristics Chest Pain Clinical Clinical Data Clinical Research Cohort Studies Complement Complex Computer Simulation Consult Coupling Cox Models Critical Care Crowding Data Development Diagnosis Dimensions Electrocardiogram Emergency Situation Engineering Event Future Guidelines Healthcare Hospital Information Systems Hospitalization Hospitals Informatics Information Systems Institution Knowledge Laboratories Lead Link Logic Methodology Methods Metric Modeling Myocardial Infarction Myocardial Ischemia Nature Operating Rooms Outcome Pathway interactions Patient Care Patients Performance Practice Guidelines Process Provider Public Health Quality Indicator Quality of Care Queuing Theory Radiology Specialty Research Research Design Research Methodology Resources Risk Roentgen Rays Safety Services Statistical Methods Statistical Models Stratification Stroke System Testing Time Uncertainty Visit Work acute coronary syndrome base care delivery care systems college computerized data processing evidence base evidence based guidelines hazard improved innovation meetings microsystems models and simulation operation patient safety prevent programs public health relevance service utilization simulation therapy design tool

项目摘要

DESCRIPTION (provided by applicant): The primary objective of this study is to use queuing theory - the study of waiting lines - and computer simulation, to determine how tight coupling between hospitals and emergency departments (ED) affects time-critical cardiac care in the ED. The study aims to explain how variability in the demand for ED and hospital resources creates service delays (radiology, laboratory, and consults) and bottlenecks in patient flow, and how these factors lead to performance errors in the diagnosis and treatment of patients suspected of having acute coronary syndrome (ACS). ACS is an umbrella term that includes all clinical findings consistent with acute myocardial ischemia. Because delays in delivery of evidence-based care affects outcome in ACS, this study will define performance errors as avoidable delays in care delivery. Chest pain prompts over 5.3 million ED visits and more than 1 million hospitalizations annually for acute myocardial infarction (AMI), the leading cause of death in the U.S., often occurring before the patient is admitted to the hospital. ACS is a strong predictor of future AMI, and clinical research has shown that rapid risk stratification and timely treatment are critical to favorable outcomes in ACS patients. The American College of Cardiology (ACC), the American Heart Association (AHA), and others have developed and endorsed practice guidelines for ACS, many of which emphasize the temporal dimension of care. Despite growing clinical evidence supporting these guidelines, many EDs fail to meet these evidence-based standards. [The study hypothesis is that wait time distributions associated with ACS quality indicators (QI) are influenced more by artificial (i.e., man-made) variability in ED and hospital work processes than by natural variability in ED patient arrivals and clinical factors. This project will use a retrospective cohort study of adult patients admitted to the ED with suspected ACS. The specific aims are to: 1) Recreate the time-course of ED care for all suspected ACS patients during a 35-month period; 2) Use system queuing metrics to characterize concurrent demands placed on ED and hospital system resources during each discrete episode of ACS patient care; 3) Use Cox proportional hazards regression to model the effects of patient characteristics (i.e., clinical and demographic), ancillary service utilization (e.g., ECG), staffing provisions, and system queuing metrics characterizing ED and hospital patient flow on time-dependent ACS QIs; 4) Develop and validate an evidence-based discrete-event simulation (DES) model of the hospital cardiac care system to advance our understanding of ACS performance errors and to facilitate predictive (i.e., "what if") analyses of clinical improvements aimed at eliminating errors and delays. A Cox model will be developed for each ACS process interval (i.e., time to event). These models will be programmed as functions into the applicable DES entity (i.e., patient, lab, X-ray, etc) flow logic to compute wait-time distributions for each care process interval (ED arrival-to-ECG, etc). The simulation methodology will be used to prospectively test system interventions designed to improve the timeliness of cardiac care in the ED]. Public Health Relevance: This project is relevant to public health because it aims to identify hospital system barriers that hinder or prevent emergency department (ED) clinicians from adhering to evidence-based practice guidelines for acute coronary syndrome. A major component of the research will focus on the impact of ED crowding, a national but understudied problem, on emergency cardiac care. The research is innovative because it will use system engineering tools to complement conventional statistical methods in modeling complex dynamic interactions between patients and the healthcare care system.

描述（由申请人提供）：本研究的主要目的是使用排队理论（对排队的研究）和计算机模拟，以确定医院和急诊科 (ED) 之间的紧密耦合如何影响急诊室中时间紧迫的心脏护理。埃德。该研究旨在解释急诊室和医院资源需求的变化如何造成服务延迟（放射科、实验室和咨询）和患者流程的瓶颈，以及这些因素如何导致疑似患有疑似疾病的患者的诊断和治疗中的表现错误。急性冠状动脉综合征（ACS）。 ACS 是一个涵盖性术语，包括与急性心肌缺血一致的所有临床表现。由于循证护理服务的延迟会影响 ACS 的预后，因此本研究将绩效错误定义为可避免的护理服务延迟。胸痛每年会导致超过 530 万人次就诊，并导致超过 100 万人因急性心肌梗塞 (AMI) 住院，AMI 是美国的主要原因，通常发生在患者入院之前。 ACS 是未来 AMI 的有力预测因子，临床研究表明，快速风险分层和及时治疗对于 ACS 患者的良好预后至关重要。美国心脏病学会 (ACC)、美国心脏协会 (AHA) 和其他机构制定并认可了 ACS 实践指南，其中许多指南强调护理的时间维度。尽管越来越多的临床证据支持这些指南，但许多急诊室未能满足这些基于证据的标准。 [研究假设是，与 ACS 质量指标 (QI) 相关的等待时间分布更多地受到 ED 和医院工作流程中人为（即人为）变异的影响，而不是受到 ED 患者到达和临床因素的自然变异的影响。该项目将对急诊科收治的疑似 ACS 成年患者进行回顾性队列研究。具体目标是： 1) 重新创建 35 个月期间所有疑似 ACS 患者的 ED 护理时间进程； 2) 使用系统排队指标来描述 ACS 患者护理的每个离散事件期间对 ED 和医院系统资源的并发需求； 3) 使用 Cox 比例风险回归来模拟患者特征（即临床和人口统计）、辅助服务利用率（例如心电图）、人员配置以及表征 ED 和医院患者流量的系统排队指标对时间依赖性 ACS QI 的影响; 4) 开发和验证医院心脏护理系统的基于证据的离散事件模拟 (DES) 模型，以增进我们对 ACS 性能错误的理解，并促进旨在消除临床改进的预测（即“假设”）分析错误和延误。将为每个 ACS 过程间隔（即事件发生时间）开发 Cox 模型。这些模型将作为函数编程到适用的 DES 实体（即患者、实验室、X 射线等）流程逻辑中，以计算每个护理过程间隔（急诊室到达心电图等）的等待时间分布。模拟方法将用于前瞻性测试旨在提高急诊室心脏护理及时性的系统干预措施]。公共卫生相关性：该项目与公共卫生相关，因为它旨在确定阻碍或阻止急诊科 (ED) 临床医生遵守急性冠脉综合征循证实践指南的医院系统障碍。该研究的一个主要部分将集中于急诊室拥挤对心脏急诊护理的影响，这是一个全国性但尚未得到充分研究的问题。该研究具有创新性，因为它将使用系统工程工具来补充传统统计方法，以建模患者与医疗保健系统之间复杂的动态交互。