ArticleAMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science2013
Semantic ETL into i2b2 with Eureka!
Article in AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed.
- I2b2-etl: Python application for importing electronic health data into the informatics for integrating biology and the bedside platform.Bioinformatics (Oxford, England) · 2022Article
- The Collaborative Metadata Repository (CoMetaR) Web App: Quantitative and Qualitative Usability Evaluation.JMIR medical informatics · 2021Article
- The Semantic Data Dictionary - An Approach for Describing and Annotating Data.Data intelligence · 2020Article
- Experiences of Transforming a Complex Nephrologic Care and Research Database into i2b2 Using the IDRT Tools.Journal of healthcare engineering · 2019Article
- Extending i2b2 into a framework for semantic abstraction of EHR to facilitate rapid development and portability of Health IT applications.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2019Article
- Enhancing the Representational Power of i2b2 through Referent Tracking.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2018Article
- Architecting the Data Loading Process for an i2b2 Research Data Warehouse: Full Reload versus Incremental Updating.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2017Article
- Metadata-driven Clinical Data Loading into i2b2 for Clinical and Translational Science Institutes.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2016Article
- Desiderata for computable representations of electronic health records-driven phenotype algorithms.Journal of the American Medical Informatics Association : JAMIA · 2015Article
- Review and evaluation of electronic health records-driven phenotype algorithm authoring tools for clinical and translational research.Journal of the American Medical Informatics Association : JAMIA · 2015Review
- Identifying the Clinical Laboratory Tests from Unspecified "Other Lab Test" Data for Secondary Use.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2015Article
- Temporal abstraction-based clinical phenotyping with Eureka!AMIA ... Annual Symposium proceedings. AMIA Symposium · 2013Article
- WaveformECG: A Platform for Visualizing, Annotating, and Analyzing ECG Data.Computing in science & engineeringArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Clinical phenotyping is an emerging research information systems capability. Research uses of electronic health record (EHR) data may require the ability to identify clinical co-morbidities and complications. Such phenotypes may not be represented directly as discrete data elements, but rather as frequency, sequential and temporal patterns in billing and clinical data. These patterns' complexity suggests the need for a robust yet flexible extract, transform and load (ETL) process that can compute them. This capability should be accessible to investigators with limited ability to engage an IT department in data management. We have developed such a system, Eureka! Clinical Analytics. It extracts data from an Excel spreadsheet, computes a broad set of phenotypes of common interest, and loads both raw and computed data into an i2b2 project. A web-based user interface allows executing and monitoring ETL processes. Eureka! is deployed at our institution and is available for deployment in the cloud.
Identifiers
24303265PMC3845783What OpenQuestion holds
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.