Literature DB >> 15017130

The sensitivity of Medicare data for identifying incident cases of invasive melanoma (United States).

David A Barzilai1, Siran M Koroukian, Duncan Neuhauser, Kevin D Cooper, Alfred A Rimm, Gregory S Cooper.   

Abstract

BACKGROUND: The completeness of Medicare claims for identifying patients with melanoma for purposes of conducting population-based studies of melanoma is unknown.
METHODS: Using a linked Surveillance, Epidemiology, and End Result (SEER) tumor registry-Medicare database, the sensitivity of Medicare claims for identifying 5372 patients age > or =65 years diagnosed with invasive melanoma between 1992 and 1996 was determined. Sensitivity was calculated as the proportion of incident cases of melanoma reported by SEER that was also captured by Medicare claim diagnostic codes.
RESULTS: The overall sensitivity of combined Part A and Part B Medicare for incident cases of melanoma was 90.1%. Part B Medicare and Part A Medicare alone had 89.5% and 16.5% sensitivity respectively. Sensitivity was lower for patients with unrecorded Breslow depth and for patients with unstaged or distant stage melanoma.
CONCLUSIONS: Medicare Part B claims have a high sensitivity for detecting melanoma incidence; Medicare Part A has low sensitivity. This sharply contrasts with published studies of other cancers, for whom Part A rather than Part B Medicare captures the predominant portion of incident cases. Medicare Part B or combined Part A and Part B administrative data is a potentially valuable resource for population-based melanoma research in the elderly. Further research characterizing the specificity and predictive value of Medicare data is needed to assess the potential implications of false positive melanoma diagnostic codes.

Entities:  

Mesh:

Year:  2004        PMID: 15017130     DOI: 10.1023/B:CACO.0000019504.74553.32

Source DB:  PubMed          Journal:  Cancer Causes Control        ISSN: 0957-5243            Impact factor:   2.506


  8 in total

1.  Confirmation of family cancer history reported in a population-based survey.

Authors:  Phuong L Mai; Anne O Garceau; Barry I Graubard; Marsha Dunn; Timothy S McNeel; Lou Gonsalves; Mitchell H Gail; Mark H Greene; Gordon B Willis; Louise Wideroff
Journal:  J Natl Cancer Inst       Date:  2011-05-11       Impact factor: 13.506

2.  Socioeconomic status and chemotherapy use for melanoma in older people.

Authors:  Carlos A Reyes-Ortiz; James S Goodwin; Dong D Zhang; Jean L Freeman
Journal:  Can J Aging       Date:  2011-03-01

3.  Socioeconomic status and survival in older patients with melanoma.

Authors:  Carlos A Reyes-Ortiz; James S Goodwin; Jean L Freeman; Yong-Fang Kuo
Journal:  J Am Geriatr Soc       Date:  2006-11       Impact factor: 5.562

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

Authors:  Darcey D Terris; David G Litaker; Siran M Koroukian
Journal:  J Clin Epidemiol       Date:  2007-04-08       Impact factor: 6.437

5.  Risk of melanoma and nonmelanoma skin cancer among patients with inflammatory bowel disease.

Authors:  Millie D Long; Christopher F Martin; Clare A Pipkin; Hans H Herfarth; Robert S Sandler; Michael D Kappelman
Journal:  Gastroenterology       Date:  2012-05-11       Impact factor: 22.682

6.  Validating malignant melanoma ICD-9-CM codes in Umbria, ASL Napoli 3 Sud and Friuli Venezia Giulia administrative healthcare databases: a diagnostic accuracy study.

Authors:  Massimiliano Orso; Diego Serraino; Iosief Abraha; Mario Fusco; Gianni Giovannini; Paola Casucci; Francesco Cozzolino; Annalisa Granata; Michele Gobbato; Fabrizio Stracci; Valerio Ciullo; Maria Francesca Vitale; Paolo Eusebi; Walter Orlandi; Alessandro Montedori; Ettore Bidoli
Journal:  BMJ Open       Date:  2018-04-20       Impact factor: 2.692

7.  Development of query strategies to identify a histologic lymphoma subtype in a large linked database system.

Authors:  Michael Graiser; Susan G Moore; Rochelle Victor; Ashley Hilliard; Leroy Hill; Michael S Keehan; Christopher R Flowers
Journal:  Cancer Inform       Date:  2007-05-04

8.  Estimating the economic costs of skin cancer in New South Wales, Australia.

Authors:  Christopher M Doran; Rod Ling; Joshua Byrnes; Melanie Crane; Andrew Searles; Donna Perez; Anthony Shakeshaft
Journal:  BMC Public Health       Date:  2015-09-23       Impact factor: 3.295

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.