Document Details

Document Type : Thesis 
Document Title :
Modeling and Executing a Guideline-Based Clinical Decision Support System Using the PROforma Methodology
تصميم وتنفيذ نظام دعم قرار طبي معتمد على دليل الممارسة الطبية باستخدام منهجية بروفورما
 
Subject : Faculty of Computing and Information Technology 
Document Language : Arabic 
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 and uncertainties in the identification of cancer symptoms, 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 (CIG) are being used to help general primary care practitioners make appropriate decisions for the given clinical circumstances because it contains well-defined medical knowledge that satisfies the quality of knowledge required and improve adherence to paper-based guidelines. We suggest that a CDSS is needed to assist GPs in challenges associated with detecting cancer in individual patients in a specific clinical situation. In this work, a CDSS model is developed based on clinical practice guidelines (CPG) 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. Unified modeling language (UML) activity diagrams were used to make the initial design. The models was then translated into PROforma during system implementation. The developed model was executed in the Tallis tester using 30 real test cases; then, 10 simulated test cases were added to satisfy the branch testing criteria. the simulated case recommendations results were reviewed by the specialist, who approved their correctness. The real case recommendations results were compared with the diagnoses made by the specialist, showing that the CDSS accurately diagnosed most of the cases, with 27 cases out of 30 concordant with the specialist’s recommendations, representing 90% accuracy. 
Supervisor : Prof. Abdullah Saad AL-Malaise AL-Ghamdi 
Thesis Type : Master Thesis 
Publishing Year : 1441 AH
2019 AD 
Added Date : Thursday, October 17, 2019 

Researchers

Researcher Name (Arabic)Researcher Name (English)Researcher TypeDr GradeEmail
شيماء سعود الفليتAlfleit, Shaimaa SaudResearcherMaster 

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