ArticleJournal of the American Medical Informatics Association : JAMIA2021
ACE: the Advanced Cohort Engine for searching longitudinal patient records.
Article in Journal of the American Medical Informatics Association : JAMIA, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- VIEWER: an extensible visual analytics framework for enhancing mental healthcare.Journal of the American Medical Informatics Association : JAMIA · 2026Article
- Leveraging data-driven insights for esophageal and gastric cancer diagnosis.BMC medical informatics and decision making · 2025Article
- Improving Phenotyping of Patients With Immune-Mediated Inflammatory Diseases Through Automated Processing of Discharge Summaries: Multicenter Cohort Study.JMIR medical informatics · 2025Article
- An Interactive Information Visualization System for Temporal Queries in a Large-scale COVID-19 EHR Dataset (COVID-SPHERE): development and qualitative evaluation.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024Article
- The Stanford Medicine data science ecosystem for clinical and translational research.JAMIA open · 2023Article
- A pandemic preparedness network for individuals living with compromised immune systems.Blood advances · 2023Article
- Representing and utilizing clinical textual data for real world studies: An OHDSI approach.Journal of biomedical informatics · 2023Article
- Trends and opportunities in computable clinical phenotyping: A scoping review.Journal of biomedical informatics · 2023Article
- Construction of Cohorts of Similar Patients From Automatic Extraction of Medical Concepts: Phenotype Extraction Study.JMIR medical informatics · 2022Article
- Design and validation of a FHIR-based EHR-driven phenotyping toolbox.Journal of the American Medical Informatics Association : JAMIA · 2022Article
- Clinical Informatics Approaches to Understand and Address Cancer Disparities.Yearbook of medical informatics · 2022Review
- Temporal Cohort Logic.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2022Article
- Treatment and Monitoring Variability in US Metastatic Breast Cancer Care.JCO clinical cancer informatics · 2021Article
- Answering real-world clinical questions using large language model, retrieval-augmented generation, and agentic systems.Digital healthArticle
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
objectiveTo 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. MATERIALS AND
methodsThe 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.
resultsACE 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. DISCUSSION: 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.
conclusionACE 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.