Literature DB >> 17238759

Assessing the accuracy of diagnostic codes in administrative databases: the impact of the sampling frame on sensitivity and specificity.

Mark G Weiner1, Jennifer H Garvin, Thomas R Ten Have.   

Abstract

The appropriate application of administrative data in clinical research requires an assessment of the accuracy of diagnostic codes against a gold standard of expert review of selected clinical charts. Typically accuracy is related to the degree of correlation between the administrative coding and the expert review. However, the choice of the sampling frame for the chart review can introduce bias that may alter the assessment of sensitivity and specificity of the coding process. This poster will explore advantages and disadvantages of common methods by which sensitivity and specificity are determined, and suggest possible methods of addressing bias.

Mesh:

Year:  2006        PMID: 17238759      PMCID: PMC1839455     

Source DB:  PubMed          Journal:  AMIA Annu Symp Proc        ISSN: 1559-4076


  4 in total

1.  Tradeoffs of using administrative claims and medical records to identify the use of personalized medicine for patients with breast cancer.

Authors:  Su-Ying Liang; Kathryn A Phillips; Grace Wang; Carol Keohane; Joanne Armstrong; William M Morris; Jennifer S Haas
Journal:  Med Care       Date:  2011-06       Impact factor: 2.983

2.  Validation of Diagnostic and Procedural Codes for Identification of Acute Cardiovascular Events in US Veterans with Rheumatoid Arthritis.

Authors:  Lisa A Davis; Alyse Mann; Grant W Cannon; Ted R Mikuls; Andreas M Reimold; Liron Caplan
Journal:  EGEMS (Wash DC)       Date:  2014-01-14

3.  Comparing the validity of different ICD coding abstraction strategies for sepsis case identification in German claims data.

Authors:  Carolin Fleischmann-Struzek; Daniel O Thomas-Rüddel; Anna Schettler; Daniel Schwarzkopf; Angelika Stacke; Christopher W Seymour; Christoph Haas; Ulf Dennler; Konrad Reinhart
Journal:  PLoS One       Date:  2018-07-30       Impact factor: 3.240

4.  Chart validation of an algorithm for identifying hereditary progressive muscular dystrophy in healthcare claims.

Authors:  Xiaoxue Chen; Abiy Agiro; Ann S Martin; Ann M Lucas; Kevin Haynes
Journal:  BMC Med Res Methodol       Date:  2019-08-09       Impact factor: 4.615

  4 in total

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