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Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
Measuring quality in the care of metastatic colorectal cancer utilising available registry data: A modified Delphi
Catherine Dunn1, Jeremy Shapiro2, Margaret Lee3
1Personalised Oncology Division, Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia.
Background And Aims:
The current lack of quality indicators for patients with metastatic colorectal cancer compromises our ability to examine the quality of care delivered, and to ensure optimal patient outcomes. We sought to define a novel set of quality indicators that could be assessed using available data from a prospective comprehensive clinical colorectal cancer registry, ultimately enabling us to explore local practice and benchmark performance between institutions.
Methods:
We performed a systematic review of the literature to review existing quality indicators for metastatic colorectal cancer. We engaged an expert panel of medical oncologists in a two-step modified Delphi analysis, using online questionnaires to rate and refine our initial list of candidate indicators, and to generate potential new ones.
Results:
Thirty-five unique quality indicators for metastatic colorectal cancer were identified from the literature. Nine of these 35 were able to be captured in TRACC, and an additional 3 novel indicators, also captured in TRACC, were added to the list to reflect current practice. After 2 online surveys of eight medical oncologists, a final list of 14 quality indicators were recommended for inclusion.
Conclusion:
A modified Delphi method was used to propose a set of 14 novel quality indicators to be extracted from an existing comprehensive metastatic colorectal cancer clinical registry. The quality indicators intentionally encompassed critical components of modern, multi-disciplinary care, spanning the treatment continuum across diagnosis to end of life. These will be used in work underway utilising TRACC data to identify potential gaps in care and avenues for quality improvement.
