AMIA Annu Symp Proc - Revisiting the EBM decision model to formalize non-compliance with computerized CPGs: results in the management of breast cancer with OncoDoc2.

Tópicos

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Resumo

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.

Resumo Limpo

hayn et al found prescript model evidencebas medicin base patient clinic state prefer research evid clinic expertis synthes three compon revisit model medic decis make propos descript model introduc clinician prefer formal four reason noncompli clinic practic guidelin cpgs approach appli breast cancer manag decis taken multidisciplinari staff meet msms tenon hospit pari franc use clinic decis support system cdss oncodoc msm decis record februari octob complianc rate cpgs measur noncompli decis main msm choic particular case practic evolut patient choic less frequent even cdss complianc rate reach particular case fall outsid cpgs borderlin case need interpret clinician

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