Literature DB >> 30100161

Linkage of the ACR National Mammography Database to the Network of State Cancer Registries: Proof of Concept Evaluation by the ACR National Mammography Database Committee.

Margarita L Zuley1, Robert M Nishikawa2, Cindy S Lee3, Elizabeth Burnside4, Robert Rosenberg5, Edward A Sickles6, Wendie Berg7, Jessica Leung8, Jennifer Harvey9, Debapriya Sengupta10, David Gur2.   

Abstract

PURPOSE: The National Mammography Database (NMD) contains nearly 20 million examinations from 693 facilities; it is the largest information source for use and effectiveness of breast imaging in the United States. NMD collects demographic, imaging, interpretation, biopsy, and basic pathology results, enabling facility and physician comparison for quality improvement. However, NMD lacks treatment and clinical outcomes data. The network of state cancer registries (CRs) contains detailed pathologic, treatment, and clinical outcomes data. This pilot study assessed electronic linkage of NMD and CR data at a multicenter institution as proof of concept.
MATERIALS AND METHODS: We obtained Quality Oversight Committee approval for this retrospective study. Data of patients diagnosed with breast cancer in 2014 and 2015 were retrieved from our NMD-approved radiology information system (RIS) and matched with reportable patients in our CR using social security number (SSN), first name (fname), last name (lname), and date of birth (DOB). Matching was repeated without SSN. Percentage and reasons for mismatch were evaluated.
RESULTS: The RIS query identified 1,316 patients. CR linkage was 99.2% successful (n = 1,305 of 1,316) using SSN, fname, lname, and DOB. Eleven mismatches included four CR case-finding failures, one NMD fname error, five nonreportable in the CR, and one with correct identifiers in both databases. Without SSN, linkage was 97.3% successful (n = 1,281 of 1,316); name errors accounted for 19 and DOB accounted for 5 additional mismatches.
CONCLUSION: Using common data elements, linkage between the NMD and state CRs may be feasible and could provide critical outcomes information to advance accurate assessment of breast imaging in the United States.
Copyright © 2018 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Breast; data linkage; medical; record linkage

Mesh:

Year:  2018        PMID: 30100161      PMCID: PMC6371782          DOI: 10.1016/j.jacr.2018.06.027

Source DB:  PubMed          Journal:  J Am Coll Radiol        ISSN: 1546-1440            Impact factor:   5.532


  6 in total

1.  Collaborative Modeling of the Benefits and Harms Associated With Different U.S. Breast Cancer Screening Strategies.

Authors:  Jeanne S Mandelblatt; Natasha K Stout; Clyde B Schechter; Jeroen J van den Broek; Diana L Miglioretti; Martin Krapcho; Amy Trentham-Dietz; Diego Munoz; Sandra J Lee; Donald A Berry; Nicolien T van Ravesteyn; Oguzhan Alagoz; Karla Kerlikowske; Anna N A Tosteson; Aimee M Near; Amanda Hoeffken; Yaojen Chang; Eveline A Heijnsdijk; Gary Chisholm; Xuelin Huang; Hui Huang; Mehmet Ali Ergun; Ronald Gangnon; Brian L Sprague; Sylvia Plevritis; Eric Feuer; Harry J de Koning; Kathleen A Cronin
Journal:  Ann Intern Med       Date:  2016-01-12       Impact factor: 25.391

2.  The National Mammography Database: Preliminary Data.

Authors:  Cindy S Lee; Mythreyi Bhargavan-Chatfield; Elizabeth S Burnside; Paul Nagy; Edward A Sickles
Journal:  AJR Am J Roentgenol       Date:  2016-02-11       Impact factor: 3.959

3.  Breast Cancer Surveillance Consortium: a national mammography screening and outcomes database.

Authors:  R Ballard-Barbash; S H Taplin; B C Yankaskas; V L Ernster; R D Rosenberg; P A Carney; W E Barlow; B M Geller; K Kerlikowske; B K Edwards; C F Lynch; N Urban; C A Chrvala; C R Key; S P Poplack; J K Worden; L G Kessler
Journal:  AJR Am J Roentgenol       Date:  1997-10       Impact factor: 3.959

4.  Trends and Patterns of Disparities in Cancer Mortality Among US Counties, 1980-2014.

Authors:  Ali H Mokdad; Laura Dwyer-Lindgren; Christina Fitzmaurice; Rebecca W Stubbs; Amelia Bertozzi-Villa; Chloe Morozoff; Raghid Charara; Christine Allen; Mohsen Naghavi; Christopher J L Murray
Journal:  JAMA       Date:  2017-01-24       Impact factor: 56.272

5.  Effects of mammography screening under different screening schedules: model estimates of potential benefits and harms.

Authors:  Jeanne S Mandelblatt; Kathleen A Cronin; Stephanie Bailey; Donald A Berry; Harry J de Koning; Gerrit Draisma; Hui Huang; Sandra J Lee; Mark Munsell; Sylvia K Plevritis; Peter Ravdin; Clyde B Schechter; Bronislava Sigal; Michael A Stoto; Natasha K Stout; Nicolien T van Ravesteyn; John Venier; Marvin Zelen; Eric J Feuer
Journal:  Ann Intern Med       Date:  2009-11-17       Impact factor: 25.391

6.  Benefits, harms, and costs for breast cancer screening after US implementation of digital mammography.

Authors:  Natasha K Stout; Sandra J Lee; Clyde B Schechter; Karla Kerlikowske; Oguzhan Alagoz; Donald Berry; Diana S M Buist; Mucahit Cevik; Gary Chisholm; Harry J de Koning; Hui Huang; Rebecca A Hubbard; Diana L Miglioretti; Mark F Munsell; Amy Trentham-Dietz; Nicolien T van Ravesteyn; Anna N A Tosteson; Jeanne S Mandelblatt
Journal:  J Natl Cancer Inst       Date:  2014-05-28       Impact factor: 13.506

  6 in total
  2 in total

Review 1.  Common data elements of breast cancer for research databases: A systematic review.

Authors:  Esmat Mirbagheri; Maryam Ahmadi; Soraya Salmanian
Journal:  J Family Med Prim Care       Date:  2020-03-26

Review 2.  Cancer Informatics in 2019: Deep Learning Takes Center Stage.

Authors:  Jeremy L Warner; Debra Patt
Journal:  Yearb Med Inform       Date:  2020-08-21
  2 in total

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