ArticleStudies in health technology and informatics2019
Extending Achilles Heel Data Quality Tool with New Rules Informed by Multi-Site Data Quality Comparison.
Article in Studies in health technology and informatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed.
- A Practical Approach to Assessing the Completeness of Electronic Health Records for Medical Research: Data Quality Study.JMIR medical informatics · 2026Article
- Beyond Missingness: Systematizing Methods for Comprehensive Data Fitness Assessment in Clinical Research.Journal of medical Internet research · 2026Article
- Data Quality in Health Research: Integrative Literature Review.Journal of medical Internet research · 2023Review
- Privacy-Preserving Federated Model Predicting Bipolar Transition in Patients With Depression: Prediction Model Development Study.Journal of medical Internet research · 2023Article
- Automating Electronic Health Record Data Quality Assessment.Journal of medical systems · 2023Review
- The IeDEA harmonist data toolkit: A data quality and data sharing solution for a global HIV research consortium.Journal of biomedical informatics · 2022Article
- Quality assessment of real-world data repositories across the data life cycle: A literature review.Journal of the American Medical Informatics Association : JAMIA · 2021Review
- A Systematic Framework for Analyzing Observation Data in Patient-Centered Registries: Case Study for Patients With Depression.JMIR research protocols · 2020Article
- Leveraging healthcare professionals' insights to enhance data quality in medical big data platforms: A qualitative study.Digital healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
Large healthcare datasets of Electronic Health Record data became indispensable in clinical research. Data quality in such datasets recently became a focus of many distributed research networks. Despite the fact that data quality is specific to a given research question, many existing data quality platform prove that general data quality assessment on dataset level (given a spectrum of research questions) is possible and highly requested by researchers. We present comparison of 12 datasets and extension of Achilles Heel data quality software tool with new rules and data characterization measures.
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.