ArticleJCO clinical cancer informatics2019
Determining the Cancer Diagnostic Interval Using Administrative Health Care Data in a Breast Cancer Cohort.
Article in JCO clinical cancer informatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 22 citations in OpenAlex.
- Mammographic screening and time to breast cancer diagnosis among immigrants and long-term residents in Ontario.BMC cancer · 2026Article
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- Emergency department use before cancer diagnosis in Ontario, Canada: a population-based study.CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne · 2024Article
- Income differences in time to colon cancer diagnosis.Cancer medicine · 2024Article
- Factors associated with diagnostic and pre-treatment intervals among breast cancer patients attending care at the Uganda Cancer Institute: A cross-sectional study.Cancer medicine · 2023Article
- Analysis of Time to Treatment and Survival Among Adults Younger Than 50 Years of Age With Colorectal Cancer in Canada.JAMA network open · 2023Article
- Measurement of clinical delay intervals among younger adults with colorectal cancer using health administrative data: a population-based analysis.BMJ open gastroenterology · 2022Article
- Explaining regional variations in colon cancer survival in Ontario, Canada: a population-based retrospective cohort study.BMJ open · 2022Article
- Does changing healthcare use signal opportunities for earlier detection of cancer? A review of studies using information from electronic patient records.Cancer epidemiology · 2022Review
- Diagnostic interval for non-screening patients undergoing mammography during the COVID-19 pandemic.European radiology · 2022Article
- Diagnostics in Patients Suspect for Breast Cancer in The Netherlands.Current oncology (Toronto, Ont.) · 2021Article
- Factors associated with waiting time to breast cancer diagnosis among symptomatic breast cancer patients: a population-based study from Ontario, Canada.Breast cancer research and treatment · 2021Article
- Consolidation of Cancer Registry and Administrative Claims Data on Cancer Diagnosis and Treatment in the US Military Health System.JCO clinical cancer informatics · 2020Article
- Breast cancer diagnosis and treatment wait times in specialized diagnostic units compared with usual care: a population-based study.Current oncology (Toronto, Ont.) · 2020Article
- Article
Corrections and comments
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Authors and funding
10 authors at 6 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposePopulation-based administrative health care data could be a valuable resource with which to study the cancer diagnostic interval. The objective of the current study was to determine the first encounter in the diagnostic interval and compute that interval in a cohort of patients with breast cancer using an empirical approach.
methodsThis is a retrospective cohort study of patients with breast cancer diagnosed in Ontario, Canada, between 2007 and 2015. We used cancer registry, physician claims, hospital discharge, and emergency department visit data to identify and categorize cancer-related encounters that were more common in the three months before diagnosis. We used statistical control charts to define lookback periods for each encounter category. We identified the earliest cancer-related encounter that marked the start of the diagnostic interval. The end of the interval was the cancer diagnosis date.
resultsThe final cohort included 69,717 patients with breast cancer. We identified an initial encounter in 97.8% of patients. Median diagnostic interval was 36 days (interquartile range [IQR], 19 to 71 days). Median interval decreased with increasing stage at diagnosis and varied across initial encounter categories, from 9 days (IQR, 1 to 35 days) for encounters with other cancer as the diagnosis to 231 days (IQR 77 to 311 days) for encounters with cyst aspiration or drainage as the procedure.
conclusionDiagnostic interval research can inform early detection guidelines and assess the success of diagnostic assessment programs. Use of administrative data for this purpose is a powerful tool for improving diagnostic processes at the population level.
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