Center for Biomedical Informatics Research, School of Medicine, School of Medicine, Stanford University, Stanford, California, USA.
Department of Computer Science, Georgia State University, Atlanta, Georgia, USA.
J Am Med Inform Assoc. 2021 Jul 14;28(7):1468-1479. doi: 10.1093/jamia/ocab027.
To propose a paradigm for a scalable time-aware clinical data search, and to describe the design, implementation and use of a search engine realizing this paradigm.
The Advanced Cohort Engine (ACE) uses a temporal query language and in-memory datastore of patient objects to provide a fast, scalable, and expressive time-aware search. ACE accepts data in the Observational Medicine Outcomes Partnership Common Data Model, and is configurable to balance performance with compute cost. ACE's temporal query language supports automatic query expansion using clinical knowledge graphs. The ACE API can be used with R, Python, Java, HTTP, and a Web UI.
ACE offers an expressive query language for complex temporal search across many clinical data types with multiple output options. ACE enables electronic phenotyping and cohort-building with subsecond response times in searching the data of millions of patients for a variety of use cases.
ACE enables fast, time-aware search using a patient object-centric datastore, thereby overcoming many technical and design shortcomings of relational algebra-based querying. Integrating electronic phenotype development with cohort-building enables a variety of high-value uses for a learning health system. Tradeoffs include the need to learn a new query language and the technical setup burden.
ACE is a tool that combines a unique query language for time-aware search of longitudinal patient records with a patient object datastore for rapid electronic phenotyping, cohort extraction, and exploratory data analyses.
提出一种可扩展的时间感知临床数据搜索模式，并描述实现该模式的搜索引擎的设计、实现和使用。
高级队列引擎（ACE）使用时间查询语言和内存中的患者对象数据存储来提供快速、可扩展和表达性强的时间感知搜索。ACE 接受观察医学结局伙伴关系通用数据模型中的数据，并可配置为在性能和计算成本之间取得平衡。ACE 的时间查询语言支持使用临床知识图谱自动进行查询扩展。ACE API 可与 R、Python、Java、HTTP 和 Web UI 一起使用。
ACE 提供了一种用于在多种临床数据类型中进行复杂时间搜索的表达性查询语言，并具有多种输出选项。ACE 能够在搜索数百万患者的数据时实现电子表型和队列构建，响应时间在亚秒级，适用于各种用例。
ACE 使用以患者对象为中心的数据存储来实现快速的时间感知搜索，从而克服了基于关系代数查询的许多技术和设计缺陷。将电子表型开发与队列构建集成在一起，为学习型健康系统提供了各种高价值的用途。权衡取舍包括需要学习新的查询语言和技术设置负担。
ACE 是一种工具，它将用于时间感知搜索的纵向患者记录的独特查询语言与用于快速电子表型、队列提取和探索性数据分析的患者对象数据存储相结合。
