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Related Experiment Video

Updated: Feb 12, 2026

Pattern-based Search of Epigenomic Data Using GeNemo
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Improving Vital Status Data Using Text Searches.

Lindsey M Hutchison, Francis P Boscoe

    Journal of Registry Management
    |March 30, 2018
    PubMed
    Summary
    This summary is machine-generated.

    This study improved New York State Cancer Registry data accuracy by identifying and correcting miscoded vital status deaths. This enhances the reliability of cancer survival statistics for New York.

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    Area of Science:

    • Oncology
    • Biostatistics
    • Public Health

    Background:

    • The New York State Cancer Registry database is crucial for cancer surveillance and research.
    • Accurate vital status coding is essential for reliable cancer survival analysis.

    Purpose of the Study:

    • To identify and correct missed deaths and miscoded vital status in the New York State Cancer Registry.
    • To improve the overall quality of cancer registry data for New York.

    Main Methods:

    • Utilized the SEER*DMS SQL data search feature.
    • Identified potentially miscoded cases by analyzing keywords in pathology and remarks text.
    • Reviewed and corrected vital status codes within the database.

    Main Results:

    • The SEER*DMS tool effectively identified miscoded vital status cases.
    • A significant number of vital status codes were corrected, enhancing data accuracy.

    Conclusions:

    • Improving data quality, even with numerous corrections, leads to more accurate cancer survival statistics.
    • Enhanced data integrity will support more reliable epidemiological studies and public health initiatives in New York.