Evidence map›Paper›PMID 41269063›Full record

ArticleCritical care medicine2026

Extending the Observational Medical Outcomes Partnership (OMOP) Common Data Model for Critical Care Medicine: A Framework for Standardizing Complex ICU Data Using the Society of Critical Care Medicine's Critical Care Data Dictionary (C2D2).

Meredith C B Adams, Robert W Hurley, Karsten Bartels, Matthew L Perkins, Cody Hudson, Umit Topaloglu, J Perren Cobb, Karin Reuter-Rice, Jacqueline C Stocking, Ashish K Khanna

Abstract read
In one paragraph

Article in Critical care medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Meredith C B AdamsDepartments of Anesthesiology, Artificial Intelligence, Translational Neuroscience, and Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC.ORCID 0000-0002-3969-4279
Robert W HurleyDepartment of Anesthesiology, Translational Neuroscience, and Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC.ORCID 0000-0001-6591-9390
Karsten BartelsAnesthesiology, Psychiatry, and Learning Health Sciences, University of Michigan, Ann Arbor, MI.
Matthew L PerkinsDepartment of Comprehensive Cancer Center, Wake Forest University School of Medicine, Winston-Salem, NC.
Cody HudsonDepartment of Comprehensive Cancer Center, Wake Forest University School of Medicine, Winston-Salem, NC.
Umit TopalogluDepartment of Cancer Biology, Wake Forest University School of Medicine, Winston-Salem, NC.
J Perren CobbDepartments of Surgery and of Anesthesiology, Keck School of Medicine of USC, Los Angeles, CA.
Karin Reuter-RiceDepartments of Pediatrics and Neurosurgery, Division of Critical Care Medicine, Duke University, School of Nursing, School of Medicine, Durham, NC.
Jacqueline C StockingDepartment of Internal Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, University of California Davis Health, Sacramento, CA.
Ashish K KhannaDepartment of Anesthesiology, Division of Critical Care Medicine, Wake Forest School of Medicine, Atrium Health Wake Forest Baptist Medical Center, Winston-Salem, NC.

Funding

MIRHIQL Resource Center for Improving Quality of Life with Chronic Pain (MRC)R24DA058606 · NIDA · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI ADAMS, MEREDITH C. B., HURLEY, ROBERT WILLSON · 2023 to 2023
$6.0M
WF DISC: Navigating Data Solutions for Chronic Pain and Opioid Use DisorderU24DA057612 · NIDA · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI MEREDITH C. B. ADAMS · 2022 to 2026
$5.6M
Wake Forest IMPOWR Dissemination Education and Coordination Center (IDEA-CC)R24DA055306 · NIDA · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI ADAMS, MEREDITH C. B. · 2021 to 2023
$3.3M
Development of a predictive model and electronic health record-based probability scoring system and dashboard for postoperative respiratory failureK01HL168222 · NHLBI · UNIVERSITY OF CALIFORNIA AT DAVIS · PI Jacqueline C Stocking · 2023 to 2026
$734k
Workforce Innovation in Data Science, Education, and Addiction Research (WISER)R25DA061740 · NIDA · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI MEREDITH C. B. ADAMS, Amber Keller Brooks · 2024 to 2026
$405k
NHLBI NIH HHS K01 HL168222NIDA NIH HHS R24 DA055306NIDA NIH HHS R24 DA058606NIDA NIH HHS R25 DA061740NIDA NIH HHS U24 DA057612
6 · The paper itself

Abstract

objectivesTo evaluate the compatibility of the Society of Critical Care Medicine's (SCCM) Critical Care Data Dictionary (C2D2) with the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) and initiate a set of steps extending OMOP to accommodate specialized critical care data elements.

designSystematic analysis and mapping study using a three-tiered semantic matching approach to demonstrate technical feasibility and identify fundamental challenges in critical care data standardization.

settingCritical care medicine informatics research environment. SUBJECTS: The SCCM's C2D2 elements.

interventionsNone. MEASUREMENTS AND MAIN

resultsWe evaluated the compatibility of C2D2 clinical variables with the OMOP CDM using a three-tier classification system (full match, partial match, and no match). Our analysis of 226 C2D2 elements revealed that 49.6% of concepts had full OMOP equivalents, 46.4% required modification, and 4.0% had no suitable mapping. Key incompatibilities were identified in ventilator parameters, composite scoring systems, and advanced organ support documentation. A large language model-based semantic matching system yielded a precision of 59.5%, recall of 87.0%, and F1 score of 70.7% at an optimized similarity threshold of 0.90. These findings highlight the need to harmonize data standardization approaches within the field of critical care, including how to handle concept stacking within single variables, age-specific criteria, and specialized constructs that were curated through the SCCM Delphi process, but reveal an OMOP mapping incompatibility or missing variables.

conclusionsExtending the OMOP CDM for critical care is technically feasible and requires targeted modifications to accommodate composite scores, temporal precision, and specialized critical care concepts as well as the resources needed to support this build. The community acutely faces crucial decisions about whether to pursue OMOP integration, adapt the C2D2 for version 2.0 compatibility, work toward OMOP vocabulary inclusion through Observational Health Data Sciences and Informatics processes, or collaborate with electronic health record vendors for native critical care standards support. These decisions require balancing technical feasibility with long-term sustainability and maintenance considerations.

Indexed as

Common Data ElementsCritical CareCritical Care OutcomesIntensive Care UnitsHumansSocieties, MedicalCommon Data Modelcritical care medicinedata mappingdata standardsObservational Medical Outcomes Partnership

Identifiers

PMID41269063
PMCPMC12955978

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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 Socratic graph.