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Data Duplication and Errors in Large Medical Data Sets: A Case Study in the IRIS® Registry
Eric A Goldberg1, Connor J Ross1, Vivian Paraskevi Douglas1
1Massachusetts Eye and Ear, Department of Ophthalmology, Harvard Medical School, Boston, Massachusetts.
Data errors like duplication are common in the American Academy of Ophthalmology IRIS Registry. The study found a link between the first practice record and these data errors, suggesting areas for improvement.
Area of Science:
- Ophthalmology
- Health Informatics
- Data Science
Background:
- The American Academy of Ophthalmology IRIS Registry (Intelligent Research in Sight) is a valuable source of real-world data for ophthalmology research.
- However, large datasets can contain entry errors and data duplication, potentially impacting research accuracy.
- Understanding these data quality issues is crucial for reliable analysis of conditions like cataract surgery, diabetic retinopathy, and age-related macular degeneration.
Purpose of the Study:
- To investigate the prevalence and nature of entry errors and data duplication within the IRIS Registry.
- Specifically examining records related to cataract surgery (CS), neodymium-doped: yttrium aluminum garnet (YAG) capsulotomy, age-related macular degeneration (AMD), and diabetic retinopathy (DR).
Main Methods:
- A retrospective cohort study design was employed, analyzing IRIS Registry data from 2013-2023.
- Identified duplicate records for CS and YAG capsulotomy based on multiple entries for the same eye, including those on different dates (Dd).
- Assessed transition errors in AMD and DR records, defined as incorrect staging of disease severity over time. Investigated predictors using permutation feature importance (PFI).
Main Results:
- Significant data duplication was found: 30.9% of CS eyes and 29.1% of YAG capsulotomy eyes had duplicates, with 5.5% and 4.1% exhibiting Dd, respectively.
- Transition errors were observed in 13.6% of AMD eyes and 12.7% of DR eyes.
- Analysis revealed a relationship between the eye's first recorded practice and the occurrence of data errors (Dd and transition errors).
Conclusions:
- Data duplication and entry errors are present in the IRIS Registry, necessitating careful consideration during analysis of repeated procedures or chronic conditions.
- The findings highlight an association between the originating practice of the first record and data errors.
- Transparency and collaboration among stakeholders are essential to address these data quality challenges and improve data stewardship.
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