ArticleMedical care2012
A pragmatic framework for single-site and multisite data quality assessment in electronic health record-based clinical research.
Article in Medical care, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 142 papers, 4 of them syntheses 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
142 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Data quality assessment in healthcare, dimensions, methods and tools: a systematic review.BMC medical informatics and decision making · 2025Pooled it
- Challenges for Data Quality in the Clinical Data Life Cycle: Systematic Review.Journal of medical Internet research · 2025Pooled it
- Digital Health Data Quality Issues: Systematic Review.Journal of medical Internet research · 2023Pooled it
- Data Quality Issues With Physician-Rating Websites: Systematic Review.Journal of medical Internet research · 2020Pooled it
- Data Quality of Longitudinally Collected Patient-Reported Outcomes After Thoracic Surgery: Comparison of Paper- and Web-Based Assessments.Journal of medical Internet research · 2021Trial
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- Application Progress of Machine Learning in Prognostic Prediction of Percutaneous Coronary Intervention: A Systematic Review.Journal of clinical medicine research · 2026Review
- Accuracy of Electronic Medical Records for Quantifying Rates of Sedative and Analgesic Infusions for Acute Disorders of Consciousness in Big Data Research.Neurocritical care · 2026Article
- Approaches to Collect Comprehensive Electronic Patient Data Across Multiple Providers and Payers for Research: Landscape Analysis.Journal of medical Internet research · 2026Article
- Implementation of a pragmatic pathway to ensure high-quality processing of heterogeneous remote health sensing data.Smart health (Amsterdam, Netherlands) · 2026Article
- Retrospective Cohort Study on Racial and Ethnic Disparities in Cesarean Birth in a Midwifery-Integrated Health System.Journal of obstetric, gynecologic, and neonatal nursing : JOGNN · 2026Article
- Accuracy of electronic medical records to quantify rates of sedative and analgesic infusions for acute disorders of consciousness big data research.medRxiv : the preprint server for health sciences · 2025Article
- Process for Quality Management of Electronic Medical Records-Based Data: Case Study Using Real Colorectal Cancer Data.JMIR medical informatics · 2025Article
- A Physician-Driven Patient Safety Paradigm: The "Pitfall Bank" as a Translational Mechanism for Medical Error Prevention.Healthcare (Basel, Switzerland) · 2025Article
- A cohort study of engagement in telehealth psychotherapy versus in-person services.Psychotherapy research : journal of the Society for Psychotherapy Research · 2025Article
- Optimizing the efficiency and effectiveness of data quality assurance in a multicenter clinical dataset.Journal of the American Medical Informatics Association : JAMIA · 2025Article
- Assessing the harmonization of structured electronic health record data to reference terminologies and data completeness through data provenance.Learning health systems · 2025Article
- The BMIgap tool to quantify transdiagnostic brain signatures of current and future weight.Nature. Mental health · 2025Article
- Navigating electronic health record accuracy by examination of sex incongruent conditions.Journal of the American Medical Informatics Association : JAMIA · 2024Article
82 more citing papers are in PubMed but not listed here.
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5 authors.
Funding
Abstract
introductionAnswers to clinical and public health research questions increasingly require aggregated data from multiple sites. Data from electronic health records and other clinical sources are useful for such studies, but require stringent quality assessment. Data quality assessment is particularly important in multisite studies to distinguish true variations in care from data quality problems.
methodsWe propose a "fit-for-use" conceptual model for data quality assessment and a process model for planning and conducting single-site and multisite data quality assessments. These approaches are illustrated using examples from prior multisite studies. APPROACH: Critical components of multisite data quality assessment include: thoughtful prioritization of variables and data quality dimensions for assessment; development and use of standardized approaches to data quality assessment that can improve data utility over time; iterative cycles of assessment within and between sites; targeting assessment toward data domains known to be vulnerable to quality problems; and detailed documentation of the rationale and outcomes of data quality assessments to inform data users. The assessment process requires constant communication between site-level data providers, data coordinating centers, and principal investigators. DISCUSSION: A conceptually based and systematically executed approach to data quality assessment is essential to achieve the potential of the electronic revolution in health care. High-quality data allow "learning health care organizations" to analyze and act on their own information, to compare their outcomes to peers, and to address critical scientific questions from the population perspective.
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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.