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Validation of claims-based algorithms for identification of high-grade cervical dysplasia and cervical cancer

Authors

  • Seoyoung C. Kim,

    Corresponding author
    1. Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women's Hospital/Harvard Medical School, Boston, MA, USA
    2. Division of Rheumatology, Immunology and Allergy, Brigham and Women's Hospital, Boston, MA, USA
    • Correspondence to: S. C. Kim, Brigham and Women's Hospital, 1620 Tremont Street, Suite 3030, Boston, MA 02120, USA. E-mail: skim62@partners.org

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  • Victoria G. Gillet,

    1. Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women's Hospital/Harvard Medical School, Boston, MA, USA
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  • Sarah Feldman,

    1. Gynecologic Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
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  • Huichuan Lii,

    1. Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA
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  • Sengwee Toh,

    1. Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA
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  • Jeffrey S. Brown,

    1. Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA
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  • Jeffrey N. Katz,

    1. Division of Rheumatology, Immunology and Allergy, Brigham and Women's Hospital, Boston, MA, USA
    2. Department of Orthopedic Surgery, Brigham and Women's Hospital/Harvard Medical School, Boston, MA, USA
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  • Daniel H. Solomon,

    1. Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women's Hospital/Harvard Medical School, Boston, MA, USA
    2. Division of Rheumatology, Immunology and Allergy, Brigham and Women's Hospital, Boston, MA, USA
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  • Sebastian Schneeweiss

    1. Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women's Hospital/Harvard Medical School, Boston, MA, USA
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ABSTRACT

Background

High-grade cervical dysplasia or cervical intraepithelial neoplasia grade 2 or worse has been widely used as a surrogate endpoint in cervical cancer screening or prevention trials.

Methods

To identify high-grade cervical dysplasia and cervical cancer, we developed claims-based algorithms that incorporated a combination of diagnosis and procedure codes using the billing data in an electronic medical records database and assessed the validity of the algorithms in an independent administrative claims database. We calculated the positive predictive value (PPV) with the 95% confidence interval (CI) of each algorithm, using new cytologic or pathologic diagnosis of cervical intraepithelial neoplasia 2 or 3, carcinoma in situ, or cervical cancer as the gold standard.

Results

Having ≥1 diagnosis code for high-grade cervical dysplasia or cervical cancer had a PPV of 57.1% (95%CI, 54.7–59.5%). By requiring ≥2 diagnoses for high-grade cervical dysplasia or cervical cancer, separated by 7–30 days, the PPV increased to 60.2% (95%CI, 53.9–66.1%). At least two diagnoses and a procedure code within a month from the first diagnosis date yielded a PPV of 80.7% (95%CI, 73.6–86.2%). The algorithms had greater PPVs in identifying prevalent high-grade cervical dysplasia or cervical cancer. Overall, the PPVs of these algorithms were similar or slightly lower in the external claims data than in the sample used to derive the algorithms.

Conclusions

Use of ≥2 diagnosis codes in combination with a procedure code appears to be a valid tool for studying high-grade cervical dysplasia and cervical cancer in both electronic medical record and administrative claims databases. Copyright © 2013 John Wiley & Sons, Ltd.

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