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The relationship between breast screening readers’ real-life performance and their associated performance on the PERFORMS scheme (Conference Presentation)
Author(s): Leng Dong; Jacquie Jenkins; Eleanor Cornford; Yan Chen

Paper Abstract

Breast Screening Information System (BSIS) records all breast screening personnel’s quality assurance results for England. The PERFORMS self-assessment scheme also invites these individuals to take part annually to report a series of challenging breast screening cases and feedback to them to help them improve their real life screening performance. How PERFORMS data relate to actual screening performance were investigated between these two sets of data. In this study, 582 screeners consented to take part. Their performance over a three-year period were acquired from BSIS database. Also, each individual’s comparative data were extracted from the PERFORMS database over the same time period and the relationship between the two sets of measures were examined. 533 participants’ data were successfully matched and validated. A kendall’s tau-b correlation was run to determine the relationship between the PPV values calculated from real-life data (cancer detected/ total recalls) over the past three years and the PERFORMS average PPV values over the same period. There was a strong, positive correlation between them, which was statistically significant (τb = .141, p <.01) confirming that PERFORMS data accurately reflect real life screening performance. It can be concluded that the PERFORMS scheme could potentially be used to provide early indication of individual performance and helped them improve appropriately. More detailed analysis will also test the cancer detection rate, recall rate and discrepant cancers to see if more measures from real life performance can be reflected by PERFORMS data.

Paper Details

Date Published: 15 March 2019
PDF
Proc. SPIE 10952, Medical Imaging 2019: Image Perception, Observer Performance, and Technology Assessment, 109520S (15 March 2019); doi: 10.1117/12.2512474
Show Author Affiliations
Leng Dong, Loughborough Univ. (United Kingdom)
Jacquie Jenkins, Public Health England (United Kingdom)
Eleanor Cornford, Cheltenham General Hospital (United Kingdom)
Yan Chen, Loughborough Univ. (United Kingdom)


Published in SPIE Proceedings Vol. 10952:
Medical Imaging 2019: Image Perception, Observer Performance, and Technology Assessment
Robert M. Nishikawa; Frank W. Samuelson, Editor(s)

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