Akademik Veri Yönetim Sistemi
Journal of Multi-Criteria Decision Analysis, cilt.31, sa.5-6, 2024 (ESCI)
In clinical consultation, Shared Decision Making (SDM) between the patient and clinician can inform the patient about available treatment options, likely harms and benefits in order to reach a joint decision that accommodates the patient's preferences. Multi-Criteria Decision Analysis (MCDA) can be beneficial for this complex problem by offering systematic approaches to elicit preferences for multiple conflicting criteria and evaluate alternatives accordingly. We propose an online SDM tool based on MCDA to guide decisions in clinical consultation where there are multiple treatment options whose outcomes in different factors vary according to the patient. The tool was designed with a panel of domain experts and it enables rapid elicitation of patient preferences and clinician judgements. It is based on Preference Ranking Organization Method for Enrichment Evaluations II (PROMETHEE II) to produce a comprehensive evaluation of the options. The patient-specific outcomes used in the SDM tool are derived from predictive machine learning models or published evidence. The tool was firstly qualitatively evaluated using a fictitious shoulder pain scenario with three focus groups of consultant and specialist physiotherapists. It was evaluated further with patients via structured interview format. The general response was positive; stating that the tool was informative about options and their performance in multiple criteria, and also useful in making a joint decision. The tool is ready to be incorporated into clinical care and evaluated by clinicians and patients in parallel with existing processes.