Optimizing clinical decisions: integrating side effect implications into support systems

Given the paramount importance of treatment plan side effects to patients, they should be at the core of clinical decision-making. Traditional clinical decision support systems (CDSS) often rely on clinical guidelines for their knowledge bases, causing them to overlook the significance of side effects. Current research has shown limited examples of effectively integrating treatment plan side effects with clinical guideline knowledge. To address this deficiency, we can extract relevant knowledge by mining information about side effects from literature resources. This process involves analyzing literature abstracts and identifying matching literature knowledge based on the patient's specific symptoms, which is then integrated with the knowledge in clinical guidelines. By doing so, we establish a chain of associations linking the patient, treatment plan, and side effects. Clinicians can evaluate this chain of associations and reevaluate guideline-based decisions to optimize the clinical decision-making process. In order to validate the effectiveness of this approach, we have designed and implemented a prototype system for breast cancer patients. This system showcases the importance of combining side effect information with clinical guideline knowledge and demonstrates its potential in optimizing clinical decision making through weight reassessment. Through practical application, this system can provide more comprehensive and personalized treatment recommendations, thereby enhancing overall treatment program quality.