ArticleStudies in health technology and informatics2019
Rule-Based Data Quality Assessment and Monitoring System in Healthcare Facilities.
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 10 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
10 citing papers in PubMed.
- Process for Quality Management of Electronic Medical Records-Based Data: Case Study Using Real Colorectal Cancer Data.JMIR medical informatics · 2025Article
- Automating Electronic Health Record Data Quality Assessment.Journal of medical systems · 2023Review
- Electronic health record data quality variability across a multistate clinical research network.Journal of clinical and translational science · 2023Article
- Standardized Description of the Feature Extraction Process to Transform Raw Data Into Meaningful Information for Enhancing Data Reuse: Consensus Study.JMIR medical informatics · 2022Article
- Developing a systematic approach to assessing data quality in secondary use of clinical data based on intended use.Learning health systems · 2022Article
- Tailoring Rule-Based Data Quality Assessment to the Patient-Centered Outcomes Research Network (PCORnet) Common Data Model (CDM).AMIA ... Annual Symposium proceedings. AMIA Symposium · 2022Article
- Development of a data utility framework to support effective health data curation.BMJ health & care informatics · 2021Article
- Application of openEHR archetypes to automate data quality rules for electronic health records: a case study.BMC medical informatics and decision making · 2021Article
- Rules Based Data Quality Assessment on Claims Database.Studies in health technology and informatics · 2020Article
- Analysis of Anesthesia Screens for Rule-Based Data Quality Assessment Opportunities.Studies in health technology and informatics · 2019Article
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
Measuring and managing data quality in healthcare has remained largely uncharted territory with few notable exceptions. A rules-based approach to data error identification was explored through compilation of over 6,000 data quality rules used with healthcare data. The rules were categorized based on topic and logic yielding twenty-two rule templates and associated knowledge tables used by the rule templates. This work provides a scalable framework with which data quality rules can be organized, shared among facilities and reused. The ten most frequent data quality problems based on the initial rules results are identified. While there is significant additional work to be done in this area, the exploration of the rule template and associated knowledge tables approach here shows rules-based data quality assessment and monitoring to be possible and scalable.
Indexed as
Identifiers
30741240PMC6692115What 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.