Literature DB >> 25521706

Using administrative data to estimate time to breast cancer diagnosis and percent of screen-detected breast cancers – a validation study in Alberta, Canada.

Y Yuan1, M Li, J Yang, M Winget.   

Abstract

Appropriate use of administrative data enables the assessment of care quality at the population level. Our objective was to develop/validate methods for assessing quality of breast cancer diagnostic care using administrative data, specifically by identifying relevant medical tests to estimate the percentage screen/symptom-detected cancers and time to diagnosis. Two databases were created for all women diagnosed with a first-ever breast cancer in years 2007-2010 in Alberta, Canada, with dates of medical tests received in years 2006-2010. One purchased database had test results and was used to determine the 'true' first relevant test of a cancer diagnosis. The other free administrative database had test types but no test results. Receiver operating characteristic curves and concordance rates were used to assess estimates of percent screen/symptom-detected breast cancers; Log-rank test was used to assess time to diagnosis obtained from the two databases. Using a look-back period of 4-6 months from cancer diagnosis to identify relevant tests resulted in over 94% concordance, sensitivity and specificity for classifying patients into screen/symptom-detected group; good agreement between the distributions of time to diagnosis was also achieved. Our findings support the use of administrative data to accurately identify relevant tests for assessing the quality of breast cancer diagnostic care.
© 2014 John Wiley & Sons Ltd.

Entities:  

Keywords:  administrative data; breast cancer; first relevant test; healthcare system; screen-detected; symptom-detected; time to diagnosis

Mesh:

Year:  2014        PMID: 25521706     DOI: 10.1111/ecc.12277

Source DB:  PubMed          Journal:  Eur J Cancer Care (Engl)        ISSN: 0961-5423            Impact factor:   2.520


  8 in total

1.  Inter- and intra-provincial variation in screen-detected breast cancer across five Canadian provinces: a CanIMPACT study.

Authors:  Marcy Winget; Yan Yuan; Mary L McBride; Cynthia Kendell; Kathleen M Decker; Eva Grunfeld; Patti A Groome
Journal:  Can J Public Health       Date:  2020-02-04

2.  Breast cancer detection method, diagnostic interval and use of specialized diagnostic assessment units across Ontario, Canada.

Authors:  Li Jiang; Julie Gilbert; Hugh Langley; Rahim Moineddin; Patti A Groome
Journal:  Health Promot Chronic Dis Prev Can       Date:  2018-10       Impact factor: 3.240

3.  Validity of ICD-9-CM codes for breast, lung and colorectal cancers in three Italian administrative healthcare databases: a diagnostic accuracy study protocol.

Authors:  Iosief Abraha; Diego Serraino; Gianni Giovannini; Fabrizio Stracci; Paola Casucci; Giuliana Alessandrini; Ettore Bidoli; Rita Chiari; Roberto Cirocchi; Marcello De Giorgi; David Franchini; Maria Francesca Vitale; Mario Fusco; Alessandro Montedori
Journal:  BMJ Open       Date:  2016-03-25       Impact factor: 2.692

4.  Factors related to breast cancer detection mode and time to diagnosis in Alberta, Canada: a population-based retrospective cohort study.

Authors:  Yan Yuan; Maoji Li; Jing Yang; Tracy Elliot; Kelly Dabbs; James A Dickinson; Stacey Fisher; Marcy Winget
Journal:  BMC Health Serv Res       Date:  2016-02-19       Impact factor: 2.655

5.  Determining the Cancer Diagnostic Interval Using Administrative Health Care Data in a Breast Cancer Cohort.

Authors:  Patti A Groome; Colleen Webber; Marlo Whitehead; Rahim Moineddin; Eva Grunfeld; Andrea Eisen; Julie Gilbert; Claire Holloway; Jonathan C Irish; Hugh Langley
Journal:  JCO Clin Cancer Inform       Date:  2019-05

6.  Importance of quality in breast cancer screening practice - a natural experiment in Alberta, Canada.

Authors:  Yan Yuan; Khanh Vu; Ye Shen; James Dickinson; Marcy Winget
Journal:  BMJ Open       Date:  2020-01-06       Impact factor: 2.692

7.  Sensitivity and specificity of breast cancer ICD-9-CM codes in three Italian administrative healthcare databases: a diagnostic accuracy study.

Authors:  Iosief Abraha; Diego Serraino; Alessandro Montedori; Mario Fusco; Gianni Giovannini; Paola Casucci; Francesco Cozzolino; Massimiliano Orso; Annalisa Granata; Marcello De Giorgi; Paolo Collarile; Rita Chiari; Jennifer Foglietta; Maria Francesca Vitale; Fabrizio Stracci; Walter Orlandi; Ettore Bidoli
Journal:  BMJ Open       Date:  2018-07-23       Impact factor: 2.692

8.  Lessons Learned: It Takes a Village to Understand Inter-Sectoral Care Using Administrative Data across Jurisdictions.

Authors:  Patti Ann Groome; Mary L McBride; Li Jiang; Cynthia Kendell; Kathleen M Decker; Eva Grunfeld; Monika K Krzyzanowska; Marcy Winget
Journal:  Int J Popul Data Sci       Date:  2018-11-12
  8 in total

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