Reis Ben Y, Kirby Chaim, Hadden Lucy E, Olson Karen, McMurry Andrew J, Daniel James B, Mandl Kenneth D
Children's Hospital Informatics Program at the Harvard-MIT Division of Health Sciences and Technology, Harvard Medical School, Boston, MA 02115, USA.
J Am Med Inform Assoc. 2007 Sep-Oct;14(5):581-8. doi: 10.1197/jamia.M2342. Epub 2007 Jun 28.
In this report, we describe the Automated Epidemiological Geotemporal Integrated Surveillance system (AEGIS), developed for real-time population health monitoring in the state of Massachusetts. AEGIS provides public health personnel with automated near-real-time situational awareness of utilization patterns at participating healthcare institutions, supporting surveillance of bioterrorism and naturally occurring outbreaks. As real-time public health surveillance systems become integrated into regional and national surveillance initiatives, the challenges of scalability, robustness, and data security become increasingly prominent. A modular and fault tolerant design helps AEGIS achieve scalability and robustness, while a distributed storage model with local autonomy helps to minimize risk of unauthorized disclosure. The report includes a description of the evolution of the design over time in response to the challenges of a regional and national integration environment.
在本报告中，我们描述了为马萨诸塞州的实时人群健康监测而开发的自动流行病学地理时间综合监测系统（AEGIS）。AEGIS为公共卫生人员提供参与的医疗机构利用模式的自动近实时态势感知，支持生物恐怖主义和自然发生疫情的监测。随着实时公共卫生监测系统融入区域和国家监测计划，可扩展性、稳健性和数据安全等挑战日益突出。模块化和容错设计有助于AEGIS实现可扩展性和稳健性，而具有本地自主性的分布式存储模型有助于将未经授权披露的风险降至最低。该报告包括为应对区域和国家整合环境的挑战而随时间推移对设计演变的描述。
