SynthesisJournal of medical Internet research2025
Challenges for Data Quality in the Clinical Data Life Cycle: Systematic Review.
Synthesis in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Predictive Value of Machine Learning for Poststroke Mortality Risk: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2026Pooled it
- Where is the patient in the records? Evaluating physiotherapists' first visit in occupational health primary care pathway for low back pain.BMJ open quality · 2026Trial
- Clinical Laboratory Terminology Standardization for Semantic Interoperability Using a Large Language Model-Based Agent: Methodological Study.Journal of medical Internet research · 2026Article
- Assessment of Electronic Clinical Monitoring Systems in the Pediatric Intensive Care Unit: Prospective Concordance Study.JMIR formative research · 2026Article
- Global, multilingual, physician-invited, patient-completed digital registry enabling pre-consultation engagement and supporting more efficient care pathways in venous disease.Scientific reports · 2026Observational
- Health Data Quality Skill Gaps and Training Needs Among European Health Data Stakeholders: Cross-Sectional Survey.Journal of medical Internet research · 2026Article
- Validation is not enough: Longitudinal evidence of post-deployment fragility in clinical AI systems.PLOS digital health · 2026Article
- Measuring the Quality of Datasets: Development of the IDEFIM Indicator Set for Empirical Health Research.Journal of medical Internet research · 2026Article
- A Practical Approach to Assessing the Completeness of Electronic Health Records for Medical Research: Data Quality Study.JMIR medical informatics · 2026Article
- Harmonizing Logical Observation Identifiers Names and Codes (LOINC) Codes and Units in Real-World Oncology Data: Method Development and Evaluation.JMIR medical informatics · 2026Article
- Artificial Intelligence in Adult Cardiovascular Medicine and Surgery: Real-World Deployments and Outcomes.Journal of personalized medicine · 2026Review
- Multi-center disease-specific management system: toward standardized and harmonized clinical pathways in integrated care networks.Frontiers in public health · 2026Article
- A data navigation model to improve access to research data resources in clinical and translational science.Journal of clinical and translational science · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundElectronic health record (EHR) data are anticipated to inform the development of health policy systems across countries and furnish valuable insights for the advancement of health and medical technology. As the current paradigm of clinical research is shifting toward data centricity, the utilization of health care data is increasingly emphasized.
objectiveWe aimed to review the literature on clinical data quality management and define a process for ensuring the quality management of clinical data, especially in the secondary utilization of data.
methodsA systematic review of PubMed articles from 2010 to October 2023 was conducted. A total of 82,346 articles were retrieved and screened based on the inclusion and exclusion criteria, narrowing the number of articles to 851 after title and abstract review. Articles focusing on clinical data quality management life cycles, assessment methods, and tools were selected.
resultsWe reviewed 105 papers describing the clinical data quality management process. This process is based on a 4-stage life cycle: planning, construction, operation, and utilization. The most frequently used dimensions were completeness, plausibility, concordance, security, currency, and interoperability.
conclusionsGiven the importance of the secondary use of EHR data, standardized quality control methods and automation are necessary. This study proposes a process to standardize data quality management and develop a data quality assessment system.
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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.