Shared Decision Making in Diabetes: What, Why, and How? Nilay D. Shah Mayo Clinic Rochester, Minnesota, USA

Transcription

1 Shared Decision Making in Diabetes: What, Why, and How? Nilay D. Shah Mayo Clinic Rochester, Minnesota, USA

2 Disclosures Funding provided by: AHRQ: R18 HS019214; R18 HS NIDDK: R34 DK84009 Foundation for Informed Medical Decision Making (FIMDM) American Diabetes Association (ADA) Mayo Clinic Foundation for Medical Education and Research Mayo Clinic CCaTS

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4 Decision making models Approaches Parental Clinician-as-perfect agent Shared decision-making Informed Direction and amount of information flow about options Clinician Patient Clinician Patient Clinician Patient Clinician Patient Direction of information flow about values and preferences Clinician Patient Clinician Patient Clinician Patient Clinician Patient Deliberation Clinician Clinician Clinician, Patient Patient Decider Clinician Clinician Clinician, Patient Patient Consistent with EBM principles No when decision is not purely technical and there are options Yes Yes Yes Modified from Charles C et al

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6 Opportunities for SDM in practice When pros and cons are closely balanced When pros>cons only if patients adhere When pros and cons are not well known

7 What if patients drove the process? (1) What are my options? What happens if I do nothing else? (2) What are the risks and benefits of each option? (3) How likely are these risks and benefits to happen? Shepherd HL, et al. Patient Educ Couns (2011), doi: /j.pec

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9 Shared Decision Making Why do it? 1. Payment and policy 2. Efficiency time, cost, utilization 3. Patient Safety misdiagnosis of patient preferences leads to unwanted or unneeded tests and treatments 4. Patient Engagement what would the patient choose if the patient knew what clinician knows 5. Patient Experience satisfaction 6. Ethics right thing to do

10 The body of evidence Systematic review of 115 RCTs Compared to usual care, decision aids: Increase patient involvement by 34% (+++-) Increase patient knowledge of options by 13% (++++) Increase consultation time by ~2.6 minutes Reduce decisional conflict by ~7% Reduce % undecided by 40% No consistent effect on choice, adherence, health outcomes or costs Stacey D et al. Cochrane review 2014

11 EBM KT Glasziou and Haynes ACP JC 2005

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13 There are now 75 trials and 11 systematic reviews of trials, per day Bastian et. al, 2010 PLoS Medicine

14 Source: IOM, Best Care at Lower Costs

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16 Imagine. 62-year old woman. Diabetes: Metformin 2x/day, SU 1x/day Hypertension: Diuretic and ACE-I 1/day Hypercholesterolemia: statin 1/day Osteoporosis: Bisphosphonate 1/week Chronic pain: NSAID 2x/day Asthma: oral leukotriene 1x/day OTC: Aspirin 1x/day Other health care requirements: testing and screening; specialists Caregiver...

17 What should be the A1c goal? Which agents to use?

18 Clinical inertia Quality of care HbA1c Report card Technical decisions

19 Will I live longer? Will I feel better? Will I live unhindered by complications?

20 For HbA1c to work... Is there a strong, consistent, independent association between HbA1c and patient important outcomes? Have RCTs across drug classes shown that improvement in HbA1c has consistently led to improvement in patient important outcomes? Tx CAUSAL PATHWAY HbA1c Patient important outcomes

21 Observational studies Consistent association between a 1% increase in HbA1c and 50% increase in risk of progression of retinopathy 20% increase in risk of macrovascular complications

22 20% diabetes trials in 2003 measured patient important outcomes Montori et al. Diabetes Care 2006

23 18% diabetes trials in future will measure patient important outcomes as primary endpoints Gandhi et al. JAMA 2008

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25 Key problem: Do not follow advice Wasted or misallocated healthcare resources: US$ 290b (100b in avoidable hospitalizations) Poor health despite cost and side effects Complicated patient-clinician relationship Cutler and Everett NEJM /NEJMp

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27 Evidence synthesis Observation clinical encounters Initial prototype Field testing Designers Study team Patient advisory groups Clinicians Stakeholders Modified prototype Final Decision Aid Evaluation (trial)

28 Goal of our encounter tools Create a conversation Patient asks questions + formulates plan Tool must be quiet: share evidence + shut up. Goal for conversation: collaborative deliberation Preferences are constructed through discussion (trying on the options)

29 Diabetes Cards Nature of diabetes medication discussions Summarizing the research evidence Iterative process Choice Architecture

30 Baseball Cards

31 Narrative Cards

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33 Why not a benefits card? The impact of diabetes medications on patient important outcomes is unclear. Insulin and microvascular SU and insulin and macrovascular Glitazones and macrovascular Metformin and macrovascular

34 Incorporate patient preferences and context into clinical decisions

35 Incorporate research evidence and clinician s expertise into patient decisions

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37 More helpful Improved knowledge Increased patient involvement No difference in adherence (perfect adherence in control gr) No significant impact on HbA1c levels Mullan RJ et al. Archives of Internal Medicine 2009

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39 Risk-Treatment Paradox Probability of a statin prescription Low Intermediate High Ko, Mamdani and Alter JAMA 2004

40 ACC/AHA Cholesterol Guidelines

41 ACC/AHA Cholesterol Guidelines Ioannidis JP. JAMA 2014

42 ACC/AHA Cholesterol Guidelines Pencina MJ. NEJM. 2014; March 19 online.

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44 Improved Knowledge Risk estimation Comfort with the decision Total trust Action (70% fewer Rx in low risk patients) Short-term adherence Weymiller et al. Arch Intern Med 2007

45 Web Statin Choice

46 Web Statin Choice

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50 IMPLEMENTATION

51 Implementing Statin Choice EMR Link Web EMR Documentation

52 Engaging the Practices What is SDM? I already do SDM Practice-based research network Clinical champions relationship building

53 Engaging the Practices (2) Demos of the tools Voluntary participation by clinicians Flexible implementation what works best for that clinic? Tie-in to ongoing quality improvement efforts

54 Barriers to Participating PRACTICE Time Value what is the impact? we already do this Competing priorities Beliefs CLINICIAN Initiating this work

55 Participants Work Age, mean (range) Clinician satisfaction (%)* Incremental time investment, median Statin Choice 65 (55-80) 74% 3.8 minutes Diabetes Medication Choice 62 (40-92) 90% 2.5 minutes * Would like to use it again with other patients considering the same decision?

56 Lessons learnt User-centered design happens in the field, takes multiple iterations and expertise Challenges with evidence synthesis and changing evidence 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

57 Lessons learnt Decision aids have increased knowledge and patient involvement in the decision consistently The impact on improving adherence to medications is mixed Clinicians and patients have reported high-levels of satisfaction (in trial settings)

58 Work in progress Better understanding of the level of evidence necessary to embed into practice Challenges of broad implementation into routine practice and repeated use Right place and time to engage patients with chronic conditions

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