Abstract

IntroductionA long breast cancer diagnostic process can affect patient anxiety and survival. Variations in the length of the diagnostic interval for similar patient presentations can indicate health system inequities and/or inefficiencies.
 Objectives and ApproachWe describe the breast cancer diagnostic interval across Canada and factors associated with its length.
 We studied breast cancer patients diagnosed from 2004/7 to 2010/11/12 in the Canadian provinces: British Columbia, Alberta, Manitoba, Ontario, and Nova Scotia. Using administrative data, we created parallel population-based, provincial-level datasets and ran common analyses. The diagnostic interval was defined from the screening mammogram to the diagnosis for screen-led and from the first referral/test ordering date to the diagnosis for diagnostic-led patients. Stratified by these two diagnostic routes, we describe the variation in the interval across provinces and report on the province-specific associations between the diagnostic interval and: patient age, comorbid disease burden, socioeconomic status combined with rural residence, and continuity of primary care while controlling for cancer stage.
 ResultsThe median diagnostic interval varied by 6 days (29 to 35 days) across provinces. Screen-led patients were diagnosed more quickly (median 2-12 days quicker). The 90th percentile diagnostic interval was 84-126 days longer in diagnostic-led patients. In the diagnostic-led group, increasing comorbid burden was consistently associated with longer diagnostic intervals and being >70 was associated with a shorter interval at the 90th percentile in Manitoba and Ontario. There was no evidence of a clear rural or low socioeconomic status effect and patients without a primary care physician had shorter intervals. In the screen-led group, patients age 40-49 and those in the medium or low income rural areas waited longer for a diagnosis.
 Conclusion/ImplicationsDiagnostic wait times differ across Canada and are variably associated with comorbidity, age, area-level socioeconomic status and rural residence. These results point to practice and system-level effects that warrant further study.

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