Revisiting the EBM decision model to formalize non-compliance with computerized CPGs: results in the management of breast cancer with OncoDoc2 - Bouaud, Jacques (American Medical Informatics Association, 2011)
In 2002, Haynes et al. founded a prescriptive model of evidence-based medicine based on the patient’s clinical state, her preferences, and research evidence, clinical expertise synthesizing the other three components. Revisiting this model of medical decision making, we propose a descriptive model introducing clinicians’ preferences and formalize four reasons of non-compliance with clinical practice guidelines (CPGs). The approach has been applied to breast cancer management decisions taken by multidisciplinary staff meetings (MSMs) at the Tenon hospital, Paris, France, while using a clinical decision support system (CDSS): OncoDoc2. 1,889 MSM decisions have been recorded [February 2007–October 2009]. The compliance rate with CPGs was measured at 91.0%. Non-compliant decisions are mainly “MSM choices” (39.1%) and “particular cases” (34.9%). “Practice evolution” and “patient choices” are less frequent (12.4% and 11.2%). Even with a CDSS, a 100% compliance rate cannot be reached because particular cases fall outside CPGs and borderline cases need to be interpreted by clinicians.