Development and evaluation of an ontology-based clinical decision support system for urinary incontinence based on Iranian adapted evidence-based clinical practice guidelines

Abstract

Abstract Introduction: Urinary incontinence is one of the most common complaints and problems, especially among women, in the world. The use of clinical decision support systems based on ontology can be a useful tool for physicians to easily access the recommendations of clinical guidelines, and provide ease and accuracy in the management of urinary incontinence. Objective: To design and evaluate an ontology-based clinical decision support system for urinary incontinence based on an adapted evidence-based clinical guideline in Iran. Methods: This study is a mixed method study. A systematic review was conducted to assess the studies conducted on ontology-based clinical decision support systems and clinical guidelines for diagnosis and treatment. Then, a search was conducted to identify and select up-to-date adapted evidence-based clinical guidelines for urinary incontinence in Iran. An ontology was developed based on the selected adapted clinical guideline. The decision support system for the diagnosis and treatment of urinary incontinence was designed based on the developed ontology. In the final step, the system and ontology were implemented and evaluated. Results: In the systematic review, 24 articles were included. According to the results of the included studies, Protégé and OWL were used in ontology design. Clinical guidelines were used in domain ontology development and rules extraction. In one-third of the studies, the rules were created based on the SWRL language. An adapted clinical guidelines for urinary incontinence was identified; and the ontology was designed based on this guideline and with Protégé software and based on OWL-DL language. A number of 82 SWRL rules were developed for the diagnosis and treatment of urinary incontinence. A decision support system was designed for the diagnosis and treatment of urinary incontinence in Iran. The consistency, accuracy and completeness of the ontology were confirmed. The high level of acceptability of the system was reported by the evaluators. Conclusion: In healthcare, ontology-based decision support systems can play an effective role in helping clinicians and patients. In the long term, these types of systems are useful and effective in producing and expanding sharable knowledge in a clinical field, as well as enriching the terminology related to the clinical field.