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）： 为了确定医院中的一系列感染是否代表疫情，医院感染控制专业人员必须首先认识到一​​种新的感染模式，然后确定该模式是否足够关注优秀干预。认可和调查过程中的问题会导致延迟，随着延迟的增加，医院的成本增加了，住院病的发病率和死亡率以及经济上 - 有时超过100万美元。关于爆发警报的最新学术研究集中在综合症监测算法上，该算法利用临床前数据（例如，急诊药品购买的记录和急诊室就诊中的主要投诉记录），试图检测大地理位置的疫情。基于这样的观察，即适用于医院数据的简单检测方法已经显示出令人鼓舞的结果，目前的项目始于这样的假设：新的，更高级的计算机辅助医院感染控制方法可以潜在地改善全国患者的结果。这项研究旨在开发MIASMA，这是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）派生的培养数据以及特定于患者的位置和订购数据，该位置和订购数据被抽象为与机构无关的标准格式作为输入。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需要调查警报所需的数据，包括由医院位置的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具有必要数据源的机构。 公共卫生相关性： 该疾病预防控制中心论文研究项目介绍了计划的MIASMA的构建和评估，Miasma是一种计算机化系统，用于向医院工作人员发出潜在的细菌暴发。 MIASMA将帮助医院感染控制人员更快地检测和调查暴发，如果成功，则会减少爆发进一步传播给其他患者。 MIASMA将使用开源软件灵活设计，并且在评估其功效后，我们将通过免费软件许可证发布Miasma软件，其目标是允许医院提供必要的数据源，以便能够使用该系统。