Literature DB >> 12512248

Use of ICD-9 coding as a proxy for stage of disease in lung cancer.

Simu K Thomas1, Sandra E Brooks, C Daniel Mullins, Claudia R Baquet, Sanjay Merchant.   

Abstract

OBJECTIVE: To determine the validity of using ICD-9-CM codes indicating metastases as a proxy to classify lung cancer patients by stage of disease. RESEARCH
DESIGN: This retrospective database analysis used diagnosis codes to classify subjects to either localized or advanced-stage disease and then compared this classification to the tumor registry staging, which was considered as the 'gold standard.' SUBJECTS AND MEASURES: Study subjects included all lung cancer patients treated at our academic institution during 1996-1997, who were also members of a large insurance company. Data were derived from inpatient cancer-related claims linked with our institution's tumor registry data. Advanced-stage disease (stages II to IV) was defined by claims indicating lymph node involvement or metastases (ICD-9 codes 196-199.1). The tumor registry stagings of the disease for these patients were clustered into two groupings, stages 0-I (localized) and stages II-IV (advanced).
RESULTS: Tumor registry entries were identified for 66/77 (85.7%) patients. A total of 19 out of 22 local disease patients (sensitivity of 86.4%) and 30 out of 44 advanced disease patients (sensitivity of 68.2%) were classified correctly by ICD-9 code. A total of 19 out of 33 patients with local disease codes (PPV of 57.6%) and 30 out of 33 patients with advanced disease codes (PPV = 90.9%) were properly identified.
CONCLUSIONS: For a population of lung cancer patients in an academic institution who were under a private insurance plan, the ICD-9 coding was associated with a sensitivity and positive predictive values that were consistent with previously reported estimates using Medicare-SEER data. The use of such data to classify patients to disease stages should be executed with caution as under-reporting might exist. Continued attention to discharge abstracting will be needed to improve the validity of this technique.

Entities:  

Mesh:

Year:  2002        PMID: 12512248     DOI: 10.1002/pds.759

Source DB:  PubMed          Journal:  Pharmacoepidemiol Drug Saf        ISSN: 1053-8569            Impact factor:   2.890


  11 in total

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3.  Health state information derived from secondary databases is affected by multiple sources of bias.

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8.  Concordance between administrative claims and registry data for identifying metastasis to the bone: an exploratory analysis in prostate cancer.

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Journal:  BMC Res Notes       Date:  2014-09-01

10.  Accuracy of administrative databases in detecting primary breast cancer diagnoses: a systematic review.

Authors:  Iosief Abraha; Alessandro Montedori; Diego Serraino; Massimiliano Orso; Gianni Giovannini; Valeria Scotti; Annalisa Granata; Francesco Cozzolino; Mario Fusco; Ettore Bidoli
Journal:  BMJ Open       Date:  2018-07-23       Impact factor: 2.692

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