Identifying the predictors of time to diagnosis and treatment for people with cancer: a protocol for a cross-sectional survey supported by linked cancer registry data
10 affiliations
- 1Institute for Health Transformation, Quality and Patient Safety, School of Nursing and Midwifery, Faculty of Health, Deakin University, Geelong, Victoria, Australia
- 2Victorian Cancer Registry, Cancer Council Victoria, Melbourne, Victoria, Australia
- 3Biostatistics Unit, Faculty of Health, Deakin University, Geelong 3220, Victoria, Australia
- 4Equitable Cancer Outcomes across Rural and Remote Australia (ECORRA) Consumer Advisory Committee, Deakin University, Geelong, Victoria, Australia
- 5Research Unit, Colac Area Health, Colac, Victoria, Australia
- 6Deakin Rural Health, Deakin University, Geelong, Victoria, Australia
- 7Grampians Health, Ballarat, Victoria, Australia
- 8Faculty of Health, Deakin University, Geelong, Victoria, Australia
- 9School of Psychology, Faculty of Health, Deakin University, Geelong, Victoria, Australia
- 10Institute for Health Transformation, Deakin Health Economics, Deakin University, Geelong, Victoria, Australia
Abstract
Introduction: People from rural and remote communities experience poorer cancer outcomes compared with their urban counterparts. In Australia, the Optimal Care Pathways provide guidance for best practice cancer care and outline optimal processes and time frames for diagnosis and treatment. Evidence indicates that survival is improved when care is aligned to these time frames. Understanding the predictors of delays in meeting these benchmarks is therefore critical to improving equity in cancer outcomes. However, the predictors of such delays, particularly in rural and remote areas, remain poorly understood.
This paper describes the protocol of a study that aims to identify predictors of diagnostic and treatment time frame alignment and unwarranted delays according to the Optimal Care Pathways for people with cancer in rural compared with urban areas.
Methods and analysis: This cross-sectional study uses a statewide survey supported by linked Victorian Cancer Registry data. Participants are identified via the Victoria Cancer Registry and are eligible if ≥18 years and diagnosed with head or neck, colorectal, lung, melanoma, prostate or oesophageal cancer in the past 12 months. The survey is disseminated via mail and collects self-report data on cancer diagnostics, treatments and experiences. Respondents’ data are linked with Victorian Cancer Registry data elements, including hospital, pathology and demographic information. One thousand completed surveys are anticipated (500 rural; 500 urban). The primary outcomes are time to diagnosis and time to treatment commencement. Regression models will be used to assess the effect of rurality status and selected predictors. Interaction terms between rurality status and key predictors will also be included. For each outcome, models will initially incorporate all six cancer types. This project will move beyond describing inequities to identifying the key factors associated with time to diagnosis and treatment, informing the generation of targeted solutions to optimise cancer outcomes, regardless of where people live.
Ethics and dissemination: This study was reviewed and approved by the Cancer Council Victoria Human Research Ethics Committee (ref: HREC #2416). Findings will be disseminated through peer-reviewed publications and scientific conference presentations.
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BibTeX
@article{jongebloed2026identifying,
title = {{Identifying the predictors of time to diagnosis and treatment for people with cancer: a protocol for a cross-sectional survey supported by linked cancer registry data}},
author = {Hannah Jongebloed and Sharina Riva and Maria Bechelli and Sue Evans and Rebecca J Bergin and Anna Chapman and Tanita Botha and Helena Rodi and Sophie Boffa and Charlene Wright and Michele Conlin and Emily Lavcanski and Luc te Marvelde and Laura Alston and Anna Wong Shee and Patricia M Livingston and Victoria M White and Lan Gao and Skye Marshall and Anna Ugalde},
journal = {BMJ Open},
year = {2026},
month = oct,
doi = {10.1136/bmjopen-2026-123201},
url = {https://bmjopen.bmj.com/lookup/doi/10.1136/bmjopen-2026-123201},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Identifying the predictors of time to diagnosis and treatment for people with cancer: a protocol for a cross-sectional survey supported by linked cancer registry data
AU - Hannah Jongebloed
AU - Sharina Riva
AU - Maria Bechelli
AU - Sue Evans
AU - Rebecca J Bergin
AU - Anna Chapman
AU - Tanita Botha
AU - Helena Rodi
AU - Sophie Boffa
AU - Charlene Wright
AU - Michele Conlin
AU - Emily Lavcanski
AU - Luc te Marvelde
AU - Laura Alston
AU - Anna Wong Shee
AU - Patricia M Livingston
AU - Victoria M White
AU - Lan Gao
AU - Skye Marshall
AU - Anna Ugalde
PY - 2026
DA - 2026/10/28
JO - BMJ Open
DO - 10.1136/bmjopen-2026-123201
UR - https://bmjopen.bmj.com/lookup/doi/10.1136/bmjopen-2026-123201
AB - Introduction: People from rural and remote communities experience poorer cancer outcomes compared with their urban counterparts. In Australia, the Optimal Care Pathways provide guidance for best practice cancer care and outline optimal processes and time frames for diagnosis and treatment. Evidence indicates that survival is improved when care is aligned to these time frames. Understanding the predictors of delays in meeting these benchmarks is therefore critical to improving equity in cancer outcomes. However, the predictors of such delays, particularly in rural and remote areas, remain poorly understood. This paper describes the protocol of a study that aims to identify predictors of diagnostic and treatment time frame alignment and unwarranted delays according to the Optimal Care Pathways for people with cancer in rural compared with urban areas. Methods and analysis: This cross-sectional study uses a statewide survey supported by linked Victorian Cancer Registry data. Participants are identified via the Victoria Cancer Registry and are eligible if ≥18 years and diagnosed with head or neck, colorectal, lung, melanoma, prostate or oesophageal cancer in the past 12 months. The survey is disseminated via mail and collects self-report data on cancer diagnostics, treatments and experiences. Respondents’ data are linked with Victorian Cancer Registry data elements, including hospital, pathology and demographic information. One thousand completed surveys are anticipated (500 rural; 500 urban). The primary outcomes are time to diagnosis and time to treatment commencement. Regression models will be used to assess the effect of rurality status and selected predictors. Interaction terms between rurality status and key predictors will also be included. For each outcome, models will initially incorporate all six cancer types. This project will move beyond describing inequities to identifying the key factors associated with time to diagnosis and treatment, informing the generation of targeted solutions to optimise cancer outcomes, regardless of where people live. Ethics and dissemination: This study was reviewed and approved by the Cancer Council Victoria Human Research Ethics Committee (ref: HREC #2416). Findings will be disseminated through peer-reviewed publications and scientific conference presentations.
SN - 2044-6055
SN - 2044-6055
ER -