ArticleAMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science2019
Extending i2b2 into a framework for semantic abstraction of EHR to facilitate rapid development and portability of Health IT applications.
Article in AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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.
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Who cites it
5 citing papers in PubMed.
- i2b2-ML: module to facilitate machine learning in the informatics for integrating biology and the bedside platform.JAMIA open · 2026Article
- Use of automatic SQL generation interface to enhance transparency and validity of health-data analysis.Informatics in medicine unlocked · 2022Article
- A Patient-Screening Tool for Clinical Research Based on Electronic Health Records Using OpenEHR: Development Study.JMIR medical informatics · 2021Article
- Deep phenotyping: Embracing complexity and temporality-Towards scalability, portability, and interoperability.Journal of biomedical informatics · 2020Article
- Cloud Services for Patient Cohort Identification Using the Informatics for Integrating Biology and the Bedside Platform.BioMed research international · 2020Article
Corrections and comments
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Authors and funding
21 authors.
Funding
Abstract
The wide gap between a care provider's conceptualization of electronic health record (EHR) and the structures for electronic health record (EHR) data storage and transmission, presents a multitude of obstacles for development of innovative Health IT applications. While developers model the EHR view of the clinicians at one end, they work with a different data view to construct health IT applications. Although there has been considerable progress to bridge this gap by evolution of developer friendly standards and tools for terminology mapping and data warehousing, there is a need for a simplified framework to facilitate development of interoperable applications. To this end, we propose a framework for creating a layer of semantic abstraction on the EHR and describe preliminary work on the implementation of this framework for management of hyperlipidemia and hypertension. Our goal is to facilitate the rapid development and portability of Health IT applications.
Identifiers
31258990PMC6568124What 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.