Literature DB >> 12948366

Estimating the sensitivity and specificity of matching name-based with non-name-based case registries.

P Etkind1, Y Tang, M Whelan, S Ratelle, J Murphy, S Sharnprapai, A Demaria.   

Abstract

Because non-name-based case registries have recently been used for reporting human immunodeficiency virus infection, this study attempted to define the sensitivity, specificity and accuracy of case registry matches using non-name-based registries. The AIDS, sexually transmitted disease (STD), and tuberculosis (TB) case registries were matched using all available information to establish the standard. The registries were then matched again using five increasingly less specific criteria to compare sensitivity, specificity and accuracy. The registries were then also transformed into non-name-based codes as if they were the HIV registry and matched again. With name-based registries, sensitivities increased as the matching criteria became less exacting, while the accuracy declined slightly. Specificities remained close to 100% due to the relatively small number of matched cases. Results from matches of non-name-based registry matches were similar to those of the name-based registry matches. Non-name reporting can be used for data matching with acceptable accuracy.

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Year:  2003        PMID: 12948366      PMCID: PMC2870007          DOI: 10.1017/s0950268803008914

Source DB:  PubMed          Journal:  Epidemiol Infect        ISSN: 0950-2688            Impact factor:   2.451


  3 in total

1.  CDC and progress toward integration of HIV, STD, and viral hepatitis prevention.

Authors:  John W Ward; Kevin A Fenton
Journal:  Public Health Rep       Date:  2007       Impact factor: 2.792

2.  The effect of case rate and coinfection rate on the positive predictive value of a registry data-matching algorithm.

Authors:  Qiang Xia; Sarah L Braunstein; Laura E Stadelmann; Preeti Pathela; Lucia V Torian
Journal:  Public Health Rep       Date:  2014 Jan-Feb       Impact factor: 2.792

3.  Practical Considerations for Matching STD and HIV Surveillance Data with Data from Other Sources.

Authors:  Lori M Newman; Michael C Samuel; Mark R Stenger; Todd M Gerber; Kathryn Macomber; Jeffrey A Stover; Wendy Wise
Journal:  Public Health Rep       Date:  2009       Impact factor: 2.792

  3 in total

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