Literature DB >> 9973074

Patients with newly diagnosed carcinoma of the breast: validation of a claim-based identification algorithm.

K M Leung1, A G Hasan, K S Rees, R G Parker, A P Legorreta.   

Abstract

The objectives of this study were to validate a claims-based algorithm for identification of patients with newly diagnosed carcinoma of the breast and to optimize the algorithm. Claims data from all females aged 21 years or older who enrolled in a large California health maintenance organization during the study period from October 1, 1994 through March 31, 1996 were analyzed. Medical records of the patients identified through the claims-based algorithm were reviewed to determine whether the patients were correctly identified. The initial algorithm had a positive predictive value of 84% which was similar to the previous study. The percentages of correct identification significantly increased with the patient's age at diagnosis. Other patient demographic characteristics and facility characteristics were not related to the accuracy of the identification. Using a classification tree procedure and additional information from the false-positive cases, the initial algorithm was modified for improvement. The best-modified algorithm had a positive predictive value of 92% while only 0.5% (4/837) of the true-positive cases were excluded. The results once again demonstrated that patients with newly diagnosed carcinomas of the breast can be identified using claims data. These databases provide an efficient and effective tool for performing health services studies on large patient populations.

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Year:  1999        PMID: 9973074     DOI: 10.1016/s0895-4356(98)00143-7

Source DB:  PubMed          Journal:  J Clin Epidemiol        ISSN: 0895-4356            Impact factor:   6.437


  13 in total

1.  French claims data as a source of information to describe cancer incidence: predictive values of two identification methods of incident prostate cancers.

Authors:  Chantal Marie Couris; Arnaud Seigneurin; Sabiha Bouzbid; Muriel Rabilloud; Paul Perrin; Xavier Martin; Cyrille Colin; Anne-Marie Schott
Journal:  J Med Syst       Date:  2006-12       Impact factor: 4.460

2.  Identification of patients with nonmelanoma skin cancer using health maintenance organization claims data.

Authors:  Melody J Eide; Richard Krajenta; Dayna Johnson; Jordan J Long; Gordon Jacobsen; Maryam M Asgari; Henry W Lim; Christine C Johnson
Journal:  Am J Epidemiol       Date:  2009-12-06       Impact factor: 4.897

3.  Leveraging Linkage of Cohort Studies With Administrative Claims Data to Identify Individuals With Cancer.

Authors:  Mackenzie R Bronson; Nirav S Kapadia; Andrea M Austin; Qianfei Wang; Diane Feskanich; Julie P W Bynum; Francine Grodstein; Anna N A Tosteson
Journal:  Med Care       Date:  2018-12       Impact factor: 2.983

4.  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

5.  In the absence of cancer registry data, is it sensible to assess incidence using hospital separation records?

Authors:  Moyra E Brackley; Margaret J Penning; Mary L Lesperance
Journal:  Int J Equity Health       Date:  2006-10-06

6.  National trends in oropharyngeal cancer incidence and survival within the Veterans Affairs Health Care System.

Authors:  Jose P Zevallos; Jennifer R Kramer; Vlad C Sandulache; Sean T Massa; Christine M Hartman; Angela L Mazul; Benjamin M Wahle; Sophie P Gerndt; Erich M Sturgis; Elizabeth Y Chiao
Journal:  Head Neck       Date:  2020-09-12       Impact factor: 3.821

7.  Validation of Claims Algorithms for Progression to Metastatic Cancer in Patients with Breast, Non-small Cell Lung, and Colorectal Cancer.

Authors:  Beth L Nordstrom; Jason C Simeone; Karen G Malley; Kathy H Fraeman; Zandra Klippel; Mark Durst; John H Page; Hairong Xu
Journal:  Front Oncol       Date:  2016-02-01       Impact factor: 6.244

8.  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

9.  Estimation of national colorectal-cancer incidence using claims databases.

Authors:  C Quantin; E Benzenine; M Hägi; B Auverlot; M Abrahamowicz; J Cottenet; E Fournier; C Binquet; D Compain; E Monnet; A M Bouvier; A Danzon
Journal:  J Cancer Epidemiol       Date:  2012-06-26

10.  Cancer incidence estimation method: an Apulian experience.

Authors:  Anna M Nannavecchia; Ivan Rashid; Francesco Cuccaro; Antonio Chieti; Danila Bruno; Maria G Burgio Lo Monaco; Cinzia Tanzarella; Lucia Bisceglia
Journal:  Eur J Cancer Prev       Date:  2017-09       Impact factor: 2.497

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