Journal of Medical Screening > Volume 16, Number 2 > Pp. 67-72

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Original Articles

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

Oscar Lemmers, Biostatistician , Department of Epidemiology, Biostatistics and HTA, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands

Mireille Broeders, Senior Epidemiologist , Department of Epidemiology, Biostatistics and HTA; National Expert and Training Centre for Breast Cancer Screening, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands

André Verbeek, Professor of Clinical Epidemiology , Department of Epidemiology, Biostatistics and HTA, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands

Gerard den Heeten, Professor of Radiology , National Expert and Training Centre for Breast Cancer Screening, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands

Roland Holland, Professor of Pathology , National Expert and Training Centre for Breast Cancer Screening, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands

George F Borm, Associate Professor of Medical Statistics  , Department of Epidemiology, Biostatistics and HTA, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands

Correspondence to: George Borm, Department of Epidemiology, Biostatistics and HTA, 133 Radboud University Nijmegen Medical Centre, PO Box 9101, 6500 HB Nijmegen, The Netherlands; g.borm{at}ebh.umcn.nl

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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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