Community Surveillance of Coronary Heart Disease

冠心病社区监测

• 批准号: 9395941
• 负责人: ROBERT JOEL GOLDBERG
• 金额: $ 80.34万
• 依托单位: UNIV OF MASSACHUSETTS MED SCH WORCESTER
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-12-15 至 2020-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9395941
• 关键词: Acute; Acute myocardial infarction; Address; Adoption; American; Area; Big Data; Caring; Case Fatality Rates; Cessation of life; Classification; Clinical; Clinical Informatics; Clinical Treatment; Clinical Trials; Code; Collection; Communities; Computerized Medical Record; Coronary; Coronary heart disease; Data; Data Sources; Development; Diagnostic; Disease Surveillance; Epidemiologist; Fostering; Future; Guidelines; Harvest; Health Care Costs; Health Policy; Health Services; Hospital Administration; Hospitals; ICD-9; Impairment; Incidence; Information Technology; Inpatients; International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10); Investigation; Life Expectancy; Manuals; Medical; Medical center; Medicine; Methods; Modeling; Monitor; Morbidity - disease rate; Myocardial Infarction; Myocardial Reperfusion; National Heart, Lung, and Blood Institute; Natural Language Processing; New England; Outcome; Participant; Patients; Periodicity; Physicians; Policy Maker; Population; Population Study; Practice Management; Prevention; Public Health; Quality of life; Recurrence; Research; Research Personnel; Research Support; Rural; Secondary Prevention; Symptoms; System; Technology; Time; Update; Work; base; clinical epidemiology; clinically relevant; cost effective; electronic data; experience; functional disability; health disparity; high risk population; hospital readmission; innovation; insight; metropolitan; mortality; older patient; optimal treatments; outcome forecast; population based; prevent; socioeconomics; surveillance data; treatment guidelines; trend

Project Summary/Abstract Preventing the onset of acute myocardial infarction (AMI) and its recurrence, and reducing the morbidity and mortality associated with AMI, remain of significant public health and clinical concern. Monitoring contemporary trends in AMI incidence, treatment, and in-hospital and long-term outcomes is of considerable importance given periodic national updates of treatment guidelines, emphasis on reducing hospital readmissions, and revised definitions and classifications of AMI. Continuously supported by the NHLBI, we have conducted more than 35 years of population-based surveillance of AMI incidence and attack rates, hospital management practices, and the in-hospital and long-term prognosis associated with AMI among residents of central MA hospitalized at all central MA medical centers. We have a highly experienced team of cardiologists, epidemiologists, clinical informatics, and health services researchers who will build on multi- decade long trends (1975-2011) in our principal study endpoints examined previously in this study to the two new study years of patients hospitalized with AMI at all central MA medical centers in 2014 and 2017. To sustain our efforts into the era of electronic medical records (EMRs), and after implementation of the ICD-10 system in 2015, we will develop a new automated AMI surveillance system that efficiently utilizes EMRs by taking advantage of state-of-art natural language processing (NLP) methods that will be compatible with ICD-10 (Aim 1). We will use the new NLP method to streamline traditional chart review-based collection of socio-demographic, clinical, treatment, and hospital and post-discharge outcomes data in patients hospitalized with AMI at all 11 central MA medical centers in 2014 and 2017. The data extracted from NLP-streamlined chart reviews will be used to validate and refine the NLP system. Issues related to changes from ICD-9 to ICD- 10 will be carefully addressed. The new NLP-enriched EMR-based surveillance system will eventually be implemented in all participating central MA hospitals. Using the NLP-enriched and EMR-based surveillance data, we will monitor the contemporary clinical epidemiology of AMI, and out-of-hospital deaths due to coronary disease, and changing landscape, over a more than 40 year period (1975-2017) (Aim 2). The new EMR-based and NLP-enriched system will enhance the population-based surveillance of acute coronary disease. This new system will be cost-effective, more efficient and near-real time, have greater accuracy and precision, and can be readily updated to accommodate changes in information technologies and broadly applicable to other hospital systems. It will support our continued efforts to provide unique community- based observational data on several populations that are often excluded from clinical trials, and that are increasing in numbers, namely the elderly and patients with multiple morbidities. Furthermore, it will generate critical data to inform more national clinical guidelines on the enhanced prevention and management of AMI. If successful, the system can serve as a model and be implemented statewide in MA and elsewhere in the US.

项目摘要/摘要 防止急性心肌梗塞（AMI）及其复发，并降低发病率 以及与AMI相关的死亡率，仍然存在着重要的公共卫生和临床关注。监视 AMI发病率，治疗以及院内和长期结局的当代趋势是相当大的 考虑到定期的全国治疗指南更新的重要性，强调减少医院 复习和修订的AMI的定义和分类。在NHLBI的不断支持下，我们 已经对AMI发病率和攻击率进行了超过35年的基于人群的监视， 医院管理实践，以及与AMI相关的院内和长期预后 MA中部的居民在所有中央医疗中心住院。我们有一个经验丰富的团队 心脏病专家，流行病学家，临床信息学和卫生服务研究人员将以多种作用为基础 十年漫长趋势（1975-2011）在我们的主要研究终点中，先前在本研究中检查给两个 2014年和2017年，所有中央MA医疗中心在所有中央医疗中心住院的患者的新研究年。 维持我们进入电子病历（EMR）时代的努力，并在执行后 ICD-10系统在2015年，我们将开发一个新的自动化AMI监视系统，该系统有效地利用 通过利用最先进的自然语言处理（NLP）方法，EMR将兼容 与ICD-10（AIM 1）。我们将使用新的NLP方法简化基于传统图表审查的集合 社会人口统计学，临床，治疗以及医院以及入院后的结果数据 在2014年和2017年的所有11个中央医疗中心都有AMI。 图表评论将用于验证和完善NLP系统。与从ICD-9到ICD的变化有关的问题 10将仔细解决。新的基于NLP的EMR监视系统最终将是 在所有参与的中央马医院实施。使用基于NLP富含EMR的监视 数据，我们将监测AMI的当代临床流行病学以及冠状动脉造成的院外死亡 在40多年来（1975-2017）（AIM 2）中，疾病和景观改变了景观。 新的基于EMR和NLP富集的系统将增强基于人群的急性监视 冠状动脉疾病。这个新系统将具有成本效益，更高效且近乎真实的时间，具有更大的 准确性和精确度，可以轻松更新以适应信息技术的变化和 广泛适用于其他医院系统。它将支持我们继续努力提供独特的社区 - 基于临床试验中通常排除的几个人群的基于观察数据，而 人数增加，即老年人和患有多种病毒的患者。此外，它将产生 关键数据可为更多有关增强AMI预防和管理的国家临床指南提供信息。如果 成功，该系统可以用作模型，并在美国和美国其他地方进行全州实施。