Influence of service characteristics on high priority performance indicators and standards in the BreastScreen Australia program

Abstract

BACKGROUND: Data from BreastScreen Australia Screening and Assessment Services (SAS) for 2002-2010 were analysed to determine whether some SAS characteristics were more conducive that others to high screening performance, as indicated by high priority performance indicators and standards. MATERIALS AND METHODS: Indicators investigated related to: numbers of benign open biopsies, screen-detected invasive cancers, and interval cancers, and wait times between screening and assessment. Multivariate Poisson regression was undertaken using as candidate predictors of performance, SAS size (screening volume), urban or rural location, year of screening, accreditation status, and percentages of clients from culturally and linguistically diverse backgrounds, rural and remote areas, and socio-economically disadvantaged areas. RESULTS: Performance standards for benign biopsies and invasive cancer detection were uniformly met irrespective of SAS location and size. The interval cancer standard was also met, except in 2003 when the 95% confidence interval of the rate still incorporated the national standard. Performance indicators improved over time for: benign open biopsy for second or subsequent screening rounds; rates of invasive breast cancer detection for second or subsequent screening rounds; and rates of small cancer detection. No differences were found over time in interval cancer rates. Interval cancer rates did not differ between non-metropolitan and metropolitan SAS, although state-wide SAS had lower rates. The standard for wait time between screening and assessment (being assessed <28 days) was mostly unmet and this applied in particular to SAS with high percentages of culturally and linguistically diverse women in their screening populations. CONCLUSIONS: Gains in performance were observed, and all performance standards were met irrespective of SAS characteristics, except wait times to assessment. Additional descriptive data should be collected on SAS characteristics, and their associations with favourable screening performance, as these may be important when deciding on SAS design.