ReviewPediatrics2014
Building a common pediatric research terminology for accelerating child health research.
Review in Pediatrics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled 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.
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
17 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- External Validation, Recalibration, and Extension of a Prediction Model of Early Acute Kidney Injury in Critically Ill Children Using Multicenter Data.Critical care explorations · 2026Article
- Bridging Data, Semantics, and Clinical Reasoning: A Knowledge Graph Framework for Pediatric Obstructive Sleep Apnea.Children (Basel, Switzerland) · 2026Article
- Visualizing the Complexity of the PCORnet® Infrastructure and Implications for Designing PCORnet® Studies.Medical care · 2026Article
- The state and future of pediatric research-an introductory overview : The state and future of pediatric research series.Pediatric research · 2023Article
- Perspectives from the periphery of Paediatrics.Frontiers in psychology · 2022Article
- Factors Influencing the Adoption of Health Information Standards in Health Care Organizations: A Systematic Review Based on Best Fit Framework Synthesis.JMIR medical informatics · 2020Review
- An Analysis of the Learning Health System in Its First Decade in Practice: Scoping Review.Journal of medical Internet research · 2020Article
- Data Science for Child Health.The Journal of pediatrics · 2019Review
- Accelerating drug development for Alzheimer's disease through the use of data standards.Alzheimer's & dementia (New York, N. Y.) · 2017Article
- Big and disparate data: considerations for pediatric consortia.Current opinion in pediatrics · 2017Review
- What allows a health care system to become a learning health care system: Results from interviews with health system leaders.Learning health systems · 2017Article
- Development of a Pediatric Adverse Events Terminology.Pediatrics · 2017Article
- Adverse drug reactions in neonates and infants: a population-tailored approach is needed.British journal of clinical pharmacology · 2015Article
- NIH/NCATS/GRDR® Common Data Elements: A leading force for standardized data collection.Contemporary clinical trials · 2015Article
- The clinical translation gap in child health exercise research: a call for disruptive innovation.Clinical and translational science · 2015Article
- PEDSnet: a National Pediatric Learning Health System.Journal of the American Medical Informatics Association : JAMIAArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Longitudinal observational clinical data on pediatric patients in electronic format is becoming widely available. A new era of multi-institutional data networks that study pediatric diseases and outcomes across disparate health delivery models and care settings are also enabling an innovative collaborative rapid improvement paradigm called the Learning Health System. However, the potential alignment of routine clinical care, observational clinical research, pragmatic clinical trials, and health systems improvement requires a data infrastructure capable of combining information from systems and workflows that historically have been isolated from each other. Removing barriers to integrating and reusing data collected in different settings will permit new opportunities to develop a more complete picture of a patient's care and to leverage data from related research studies. One key barrier is the lack of a common terminology that provides uniform definitions and descriptions of clinical observations and data. A well-characterized terminology ensures a common meaning and supports data reuse and integration. A common terminology allows studies to build upon previous findings and to reuse data collection tools and data management processes. We present the current state of terminology harmonization and describe a governance structure and mechanism for coordinating the development of a common pediatric research terminology that links to clinical terminologies and can be used to align existing terminologies. By reducing the barriers between clinical care and clinical research, a Learning Health System can leverage and reuse not only its own data resources but also broader extant data resources.
Indexed as
Identifiers
What 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.