Abstract
Clinical decision-support systems (CDSSs) are systems designed to influence clinician decision making regarding specific patients. They provide information related to a specific clinical situation and produce recommendations. Ambiguities in the cancer screening process and uncertainties in the identification of cancer symptoms, as well as concerns about providing referrals in primary care, lead to a complex cancer detection process for the general practitioner (GP). In addition, there is fragmentation in cancer care between primary and secondary care, which increases patients' feelings of uncertainty. Clinical interoperability guidelines are being used to help general primary care practitioners make appropriate decisions for the given clinical circumstances and improve adherence to paper-based guidelines. In this work, a CDSS is developed based on clinical practice guidelines (CPGs) and using the PROforma methodology, which employs the task network model (TNM). The TNM outperforms other models because it supports the guideline's steps, which are revealed over time, and it can explicitly model sequences of tasks or alternative pathways. CDSSs will assist GPs in challenges associated with detecting cancer in individual patients in a specific clinical situation.