Clinical Decision Support Tool for Early Pancreatic Cancer Detection in Primary Care: Simulation Study
Javiera Martinez-Gutierrez, Kaleswari Somasundaram, Christina Maresch Bernardes, Meena Rafiq, Silja Schrader, Susan Jordan, Sophie Chima, Lucas De Mendonca, Kit Huckvale, Barbara Hunter, Jo-Anne Manski-Nankervis, James Lawson, Katrina Anderson, Vivienne Milch, Rachel E Neale

TL;DR
A simulation study tested a tool to help GPs detect early pancreatic cancer symptoms, finding it useful but highlighting concerns about overtesting and costs.
Contribution
A simulated CDSS for pancreatic cancer detection in primary care was evaluated for acceptability and feasibility.
Findings
GPs found the CDSS easy to use and effective for identifying patients with pancreatic cancer risk factors.
Concerns about overtesting, costs, and patient anxiety were raised by GPs.
A stepwise approach to investigations was preferred over immediate imaging.
Abstract
Early detection in primary care could improve pancreatic cancer survival, but diagnosis is often delayed due to the low prevalence of the disease, the nonspecific nature of early symptoms, and the broad range of conditions and volume of consultations managed by general practitioners (GPs). In Australia, improving pancreatic cancer outcomes, including via earlier diagnosis, is a priority being progressed under the National Pancreatic Cancer Roadmap developed by Cancer Australia. Computerized clinical decision support systems (CDSSs) have shown promise in aiding timely cancer diagnosis; however, barriers to adopting CDSS such as mistrust of the recommendations or not being embedded in the clinical workflow remain. Simulation techniques, which offer flexible and cost-effective ways to evaluate digital health interventions, can be used to test CDSS before real-world implementation. This…
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Taxonomy
TopicsPancreatic and Hepatic Oncology Research · Electronic Health Records Systems · Machine Learning in Healthcare
