MIASMA: A Medical Informatics Application for Systematic Microbiological Alerts

MIASMA：用于系统微生物警报的医学信息学应用程序

• 批准号: 7770216
• 负责人: Randy J. Carnevale
• 金额: $ 3.78万
• 依托单位: VANDERBILT UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-30 至 2011-09-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7770216
• 关键词: MIASMA; Medical; Informatics; Application; Systematic

DESCRIPTION (provided by applicant): To determine whether a cluster of infections in a hospital represents an outbreak, hospital infection control professionals must first recognize a new pattern of infection and then determine whether the pattern is of sufficient concern to merit intervention. Problems during the recognition and investigative processes incur delays, and with delays come increased costs to the hospital, inpatient morbidity and mortality, and in economic terms -- sometimes exceeding $1 million. Recent academic studies of outbreak alerting have focused on syndromic surveillance algorithms, which utilize pre-clinical data (e.g., records of over-the-counter pharmaceutical purchases and of chief complaints from emergency room visits) in an attempt to detect outbreaks in large geographic areas. Based on the observation that simple detection methods applied to hospital data have already shown promising results, the current project begins with the presumption that new, more advanced approaches to computer-assisted hospital infection control can potentially improve patient outcomes nationwide. This study aims to develop MIASMA, a Medical Informatics Application for Systematic Microbiological Alerts. MIASMA will use electronic medical record (EMR) derived culture data and patient-specific location and order data abstracted into an institution-independent standard format as input. It will incorporate statistical and rule-based alerting methods along with novel heuristic detection methods. MIASMA will also collect, organize, and display the data needed by hospital infection staff to investigate alerts, including a visualization component supported by geographic models of hospital locations. It will be deployed and evaluated at Vanderbilt University Hospital, but will be made freely available to any institution with the necessary data sources available. PUBLIC HEALTH RELEVANCE: This CDC dissertation research project describes planned construction and evaluation of MIASMA, a computerized system for alerting hospital staff regarding potential bacterial outbreaks. MIASMA will help hospital infection control staff detect and investigate outbreaks more quickly, and if successful will thus reduce further spread of outbreaks to additional patients. MIASMA will be designed flexibly using open source software, and after an evaluation to document its efficacy, we will release the MIASMA software the general public via a free software license with a goal of allowing hospital with the necessary data sources available to be able to use the system.

描述（由申请人提供）： 为了确定医院中的聚集性感染是否代表爆发，医院感染控制专业人员必须首先识别新的感染模式，然后确定该模式是否值得采取干预措施。识别和调查过程中出现的问题会导致延误，而延误会导致医院成本、住院患者发病率和死亡率以及经济方面的成本增加——有时超过 100 万美元。最近关于疫情警报的学术研究主要集中在症状监测算法上，该算法利用临床前数据（例如非处方药购买记录和急诊室就诊的主诉记录），试图检测大面积地理区域的疫情爆发。基于对医院数据应用简单检测方法已经显示出有希望的结果的观察，当前的项目首先假设新的、更先进的计算机辅助医院感染控制方法有可能改善全国范围内的患者治疗结果。本研究旨在开发 MIASMA，一种用于系统微生物警报的医学信息学应用程序。 MIASMA 将使用电子病历 (EMR) 衍生的培养数据和患者特定位置以及抽象为独立于机构的标准格式的订单数据作为输入。它将结合统计和基于规则的警报方法以及新颖的启发式检测方法。 MIASMA 还将收集、组织和显示医院感染人员调查警报所需的数据，包括由医院位置地理模型支持的可视化组件。它将在范德比尔特大学医院进行部署和评估，但将免费提供给任何拥有必要数据源的机构。 公共卫生相关性： CDC 的这篇论文研究项目描述了 MIASMA 的计划建设和评估，MIASMA 是一个计算机化系统，用于警告医院工作人员潜在的细菌爆发。 MIASMA 将帮助医院感染控制人员更快地发现和调查疫情，如果成功，将减少疫情向更多患者的进一步传播。 MIASMA将使用开源软件进行灵活设计，经过评估记录其功效后，我们将通过免费软件许可证向公众发布MIASMA软件，目的是让拥有必要数据源的医院能够使用系统。