ArticleJAMIA open2024
Establishing data elements and exchange standards to support long COVID healthcare and research.
Article in JAMIA open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- Pathways to Real World Evidence From the Real World of School-Based Physical Fitness Testing (SB-PFT).Learning health systems · 2026Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: The Multiple Chronic Conditions (MCCs) Electronic Care (e-Care) Plan project aims to establish care planning data standards for individuals living with MCCs. This article reports on the portion of the project focused on long COVID and presents the process of identifying and modeling data elements using the HL7 Fast Healthcare Interoperability Resources (FHIR) standard. Materials and Methods: Critical data elements for managing long COVID were defined through a consensus-driven approach involving a Technical Expert Panel (TEP). This involved 2 stages: identifying data concepts and establishing electronic exchange standards. Results: The TEP-identified and -approved long COVID data elements were mapped to the HL7 US Core FHIR profiles for syntactic representation, and value sets from standard code systems were developed for semantic representation of the long COVID concepts. Discussion: Establishing common long COVID data standards through this process, and representing them with the HL7 FHIR standard, facilitates interoperable data collection, benefiting care delivery and patient-centered outcomes research (PCOR) for long COVID. These standards may support initiatives including clinical and pragmatic trials, quality improvement, epidemiologic research, and clinical and social interventions.By building standards-based data collection, this effort accelerates the development of evidence to better understand and deliver effective long COVID interventions and patient and caregiver priorities within the context of MCCs and to advance the delivery of coordinated, person-centered care. Conclusion: The open, collaborative, and consensus-based approach used in this project will enable the sharing of long COVID-related health concerns, interventions, and outcomes for patient-centered care coordination across diverse clinical settings and will facilitate the use of real-world data for long COVID research.
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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.