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Victor M. Montori, MD, MSc KER UNIT, Mayo Clinic Challenging myths: Empathic decision making in usual clinical settings.

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Presentation on theme: "Victor M. Montori, MD, MSc KER UNIT, Mayo Clinic Challenging myths: Empathic decision making in usual clinical settings."— Presentation transcript:

1 Victor M. Montori, MD, MSc KER UNIT, Mayo Clinic Challenging myths: Empathic decision making in usual clinical settings

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3 Decision making models Modified from Charles C et al ApproachesParental Clinician-as-perfect agent Shared decision-makingInformed Direction and amount of information flow about options Clinician Patient Direction of information flow about values and preferences Clinician Patient DeliberationClinician Clinician, PatientPatient DeciderClinician Clinician, PatientPatient Consistent with EBM principles No when decision is not purely technical and there are options Yes

4 Desired clinical behavior EMPATHIC DECISION MAKING 1.Partnership 2.Dance across models

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6 Wiser Choices Program at Mayo Clinic’s KER UNIT

7 Settings (bold = RCT) WorkSettingPolicyEvaluation Statin ChoicePrimary + specialty care Effective careFeasible, effective, implemented in EHR, multicenter trial DM2 Med ChoicePrimary care“Technical” careFeasible, effective, multicenter trial Aspirin ChoicePrimary care (group)Effective care (but changed)Not evaluated Depression ChoicePrimary careMarketingDesign phase Genomic ChoiceExperimentalSilentDesign phase Osteoporosis ChoicePrimary careEffective careFeasible, effective ICD ChoiceSpecialty carePreference sensitiveDesign phase Smoking choicePrimary careEffective careDesign phase Chest Pain ChoiceEmergencyEffective careFeasible, effective, multicenter trial AMI ChoiceHospital wardEffective careFeasible, effective, multicenter trial Hypertensione-primary careEffective careDesign phase RosiglitazoneGeneralEffective careNot evaluated ProstateGeneral (tablet)Preference sensitiveDesign phase

8 Weymiller et al. Arch Intern Med 2007 Statin Choice

9 Osteoporosis Choice Montori et al, AJM 2011

10 Mullan et al, Arch Intern Med 2009 Diabetes Medication Choice

11 AMI Choice

12 Chest Pain Choice

13 Participants WorkAge, mean (range) IllnessClinician satisfaction (%)* Incremental time investment, median Statin Choice65 (55-80)Chronic, asymptomatic 74%3.8 minutes (-2.9, 10.5) Diabetes Medication Choice 62 (40-92)Chronic asymptomatic 90%2.5 minutes Osteoporosis Choice 67 (51-84)Chronic asymptomatic 75%3.0 minutes (-56, 25) Chest Pain Choice 54 (32-76)Acute, symptomatic 64%1.6 minutes AMI Choice64 (40-85)Acute, symptomatic NA * Would like to use it again with other patients considering the same decision?

14 Success of the decision aid EthicalLegal EconomicEffectiveness Knowledge transfer Creates a conversation Fit

15 Implementation Understandable Doable Favorable Fit for purpose, users, setting

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17 Statin Decision Aid

18 Lessons learnt User-centered design happens in the field, takes multiple iterations and expertise. Testing decision aids in usual clinical settings is tough: decision moments are unpredictable. Repeated use for chronic decisions has been difficult to study in efficacy trials.

19 Myths Goal and settings 1.Decision aids have no role in evidence-based care 2.Decision aids support shared decision making 3.Valid decision aids cannot be used in busy clinical settings, such as primary care Participants 1.Clinicians would not want to use decision aids – they are barriers to adoption of SDM 2.Acutely ill patients are not good targets for SDM 3.Elderly chronically ill patients cannot participate in SDM

20 Summary of 5 years of work 13 wiser choices decision aids Chronic and acute care Primary and specialty care Rural, urban, and academic 50+ sites 200+ clinicians 600+ patients In trials!

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