Literature DB >> 12269766

Use of Medicare claims data to measure county-level variation in breast carcinoma incidence and mammography rates.

Gregory S Cooper1, Zhong Yuan, Reena N Jethva, Alfred A Rimm.   

Abstract

BACKGROUND: National-level population-based data about breast carcinoma incidence and its association with screening mammography are currently not available.
METHODS: Inpatient, hospital outpatient and physician/supplier Medicare claims were used to identify incident cases of breast carcinoma in women > or = 65 years from 1996 to 1997 and calculate county-level incidence rates. The 1994-1995 claims data were used to determine county-level rates of mammography, and determine the correlation with incidence.
RESULTS: The median 2-year incidence rate for women > or = 65 was 979/100,000, and substantial variation in incidence between counties was observed. (i.e. 25th percentile 789/100,000, 75th percentile 1186/100,000). Two-year county-level mammography rates also varied among counties (i.e. 25th percentile 30.5%, 75th percentile 40.9%) and were higher in white women than in black women (median 36.8 and 26.3%, respectively). Counties with higher rates of mammography also had higher age-adjusted incidence rates.
CONCLUSIONS: Medicare claims may provide an alternative source of population-based data, particularly for areas in which registry data are not readily available, or are of limited scope. The data highlight the geographic variation in incidence and screening rates that may be useful for targeted interventions, and also suggest that mammography remains in a growth phase.

Entities:  

Mesh:

Year:  2002        PMID: 12269766     DOI: 10.1016/s0361-090x(02)00056-9

Source DB:  PubMed          Journal:  Cancer Detect Prev        ISSN: 0361-090X


  9 in total

1.  Estimation of disease incidence in claims data dependent on the length of follow-up: a methodological approach.

Authors:  Sascha Abbas; Peter Ihle; Ingrid Köster; Ingrid Schubert
Journal:  Health Serv Res       Date:  2012-04       Impact factor: 3.402

2.  Estimation of asthma incidence among low-income children in Texas: a novel approach using Medicaid claims data.

Authors:  Judy K Wendt; Elaine Symanski; Xianglin L Du
Journal:  Am J Epidemiol       Date:  2012-09-28       Impact factor: 4.897

3.  Is it possible to estimate the incidence of breast cancer from medico-administrative databases?

Authors:  L Remontet; N Mitton; C M Couris; J Iwaz; F Gomez; F Olive; S Polazzi; A M Schott; B Trombert; N Bossard; M Colonna
Journal:  Eur J Epidemiol       Date:  2008-08-21       Impact factor: 8.082

4.  The impact of the lookback period and definition of confirmatory events on the identification of incident cancer cases in administrative data.

Authors:  Jonas Czwikla; Kathrin Jobski; Tania Schink
Journal:  BMC Med Res Methodol       Date:  2017-08-14       Impact factor: 4.615

5.  Estimating cancer incidence based on claims data from medical insurance systems in two areas lacking cancer registries in China.

Authors:  Hongrui Tian; Wei Yang; Yanjun Hu; Zhen Liu; Lei Chen; Liang Lei; Fan Zhang; Fen Cai; Huawen Xu; Mengfei Liu; Chuanhai Guo; Yun Chen; Ping Xiao; Junhui Chen; Ping Ji; Zhengyu Fang; Fangfang Liu; Ying Liu; Yaqi Pan; Isabel Dos-Santos-Silva; Zhonghu He; Yang Ke
Journal:  EClinicalMedicine       Date:  2020-03-20

6.  Is hospital discharge administrative data an appropriate source of information for cancer registries purposes? Some insights from four Spanish registries.

Authors:  Enrique E Bernal-Delgado; Carmen Martos; Natalia Martínez; María Dolores Chirlaque; Mirari Márquez; Carmen Navarro; Lauro Hernando; Joaquín Palomar; Isabel Izarzugaza; Nerea Larrañaga; Olatz Mokoroa; M Cres Tobalina; Joseba Bidaurrazaga; María José Sánchez; Carmen Martínez; Miguel Rodríguez; Esther Pérez; Yoe Ling Chang
Journal:  BMC Health Serv Res       Date:  2010-01-08       Impact factor: 2.655

7.  Using small-area estimation to describe county-level disparities in mammography.

Authors:  Karen L Schneider; Kate L Lapane; Melissa A Clark; William Rakowski
Journal:  Prev Chronic Dis       Date:  2009-09-15       Impact factor: 2.830

8.  Validating the use of Medicare Australia billing data to examine trends in skin cancer.

Authors:  Eshini Perera; Neiraja Gnaneswaran; Marlon Perera; Rodney Sinclair
Journal:  F1000Res       Date:  2015-11-24

9.  Assessing and Explaining Geographic Variations in Mammography Screening Participation and Breast Cancer Incidence.

Authors:  Jonas Czwikla; Iris Urbschat; Joachim Kieschke; Frank Schüssler; Ingo Langner; Falk Hoffmann
Journal:  Front Oncol       Date:  2019-09-18       Impact factor: 6.244

  9 in total

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