ArticleJAMIA open2026
Expanding the OMOP common data model to support extracorporeal life support research.
Article in JAMIA open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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
1 citing paper in PubMed.
- Challenges and opportunities in ECMO monitoring: A mixed-methods appraisal.The journal of extra-corporeal technology · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors.
Funding
Abstract
Objective: Despite the increased availability of electronic health records, open-source standardized data collection to facilitate high-resolution data during extracorporeal life support (ECLS) is lacking. This project aimed to assess the Observational Medical Outcomes Partnership Common Data Model (OMOP CDM) for interoperability to store data sufficiently generated in the context of ECLS and to develop a custom data model expansion in case the OMOP CDM proved insufficient. Design and Setting: The OMOP CDM was analyzed qualitatively by expert consensus for its capability to capture data relative to ECLS as well as the presence of fitting ECLS-related concepts. Database entries necessary to store information about primary ECLS components were compared using the OMOP CDM versus the custom data model expansion. Main Results: Analysis of data elements required to capture ECLS data within the OMOP CDM revealed a paucity of suitable concepts within the OHDSI Standardized Vocabularies, limiting capture of ECLS circuit-derived data. Custom ECLS-specific database tables and novel concepts were introduced as part of a custom expansion, the ECLS Common Data Model (ECLS CDM). The number of database entries necessary to store ECLS use cases was reduced by up to 90%. The ECLS CDM was released as an open-source project on GitHub and placed in the public domain. Conclusions: With the first iteration of the ECLS CDM, we introduce a data model to improve interoperability for data describing ECLS and elevate data quality, enabling multi-center research and quality initiatives.
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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.