Abstract
Clinical guidelines (CPGs) provide evidence-based treatment options based on patient's clinical context. A guideline-based Clinical Decision Support System (DSS) matches a patient's clinical data with the clinical knowledge represented as a computer-interpretable guideline (CIG) to provide patient-specific recommendations. Physicians try to provide personalized treatment recommendations by different methods such as adjusting the recommendations to suit the patient's personal situations, to abide with his personal constraints, such as availability level of family support, and his personal preferences regarding side effects of medications. To support such personalization, CIGs would need to be customized to address not only the clinical context but to include also personal context and preferences. Yet it is important to stress that the (evidence-based) clinical context should remain the primary contextual aspect that determines the treatment options.
Our aim is to develop a decision model that will help physicians define the treatment recommendations based on the specific clinical context and personalize the recommendations, using other contextual aspects.
Our aim is to develop a decision model that will help physicians define the treatment recommendations based on the specific clinical context and personalize the recommendations, using other contextual aspects.
Original language | English |
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State | Published - 2014 |
Event | AMIA 2014, American Medical Informatics Association Annual Symposium - Duration: 1 Jan 2014 → … |
Conference
Conference | AMIA 2014, American Medical Informatics Association Annual Symposium |
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Period | 1/01/14 → … |