Literature DB >> 19564518

League tables of breast cancer screening units: worst-case and best-case scenario ratings helped in exposing real differences between performance ratings.

Oscar Lemmers1, Mireille Broeders, André Verbeek, Gerard den Heeten, Roland Holland, George F Borm.   

Abstract

OBJECTIVES: Data on the performance of health boards, hospitals and medical specialists, etc., are being collected at various levels in the health-care system and are often presented as league tables. These tables ignore natural variation and/or confounders, and this introduces uncertainty about their interpretation. The purpose of this study was to devise and illustrate a method to expose the real difference between the ratings in league tables.
METHODS: Two values per rating were added to the league tables: the best-case scenario and the worst-case scenario. True performance will lie somewhere between these two values. The method is illustrated using data from the Dutch breast cancer screening programme.
RESULTS: By focusing on one performance indicator and one confounder, it was possible to show shifts in the rating order of breast cancer screening units and thus expose the uncertainty about the true performance of each screening unit.
CONCLUSIONS: The worst-case and best-case scenario ratings demonstrated the uncertainty within the ratings of a league table. League tables should therefore only be used with great caution and after providing the public with sufficient information.

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Year:  2009        PMID: 19564518     DOI: 10.1258/jms.2009.008093

Source DB:  PubMed          Journal:  J Med Screen        ISSN: 0969-1413            Impact factor:   2.136


  3 in total

1.  Diagnostic mammography: identifying minimally acceptable interpretive performance criteria.

Authors:  Patricia A Carney; Jay Parikh; Edward A Sickles; Stephen A Feig; Barbara Monsees; Lawrence W Bassett; Robert A Smith; Robert Rosenberg; Laura Ichikawa; James Wallace; Khai Tran; Diana L Miglioretti
Journal:  Radiology       Date:  2013-01-07       Impact factor: 11.105

2.  Identifying minimally acceptable interpretive performance criteria for screening mammography.

Authors:  Patricia A Carney; Edward A Sickles; Barbara S Monsees; Lawrence W Bassett; R James Brenner; Stephen A Feig; Robert A Smith; Robert D Rosenberg; T Andrew Bogart; Sally Browning; Jane W Barry; Mary M Kelly; Khai A Tran; Diana L Miglioretti
Journal:  Radiology       Date:  2010-05       Impact factor: 11.105

3.  Understanding and benchmarking health service achievement of policy goals for chronic disease.

Authors:  Erica Bell; Bastian Seidel
Journal:  BMC Health Serv Res       Date:  2012-09-29       Impact factor: 2.655

  3 in total

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