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 HS018339
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

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
Direction of information flow about values and preferences
Clinician Patient
Clinician Patient
Deliberation
Clinician
Clinician, Patient
Patient
Decider
Consistent with EBM principles
No when decision is not purely technical and there are options
Yes
empathic
Modified from Charles C et al

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

9. Shared Decision Making
Why do it?
Payment and policy
Efficiency – time, cost, utilization
Patient Safety – misdiagnosis of patient preferences leads to unwanted or unneeded tests and treatments
Patient Engagement – what would the patient choose if the patient knew what clinician knows
Patient Experience – satisfaction
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
A) Criteria involving decision attributes:
Decision aids performed better than usual care interventions by increasing knowledge (MD out of 100; 95% confidence interval (CI) to 16.15; n = 26). When more detailed decision aids were compared to simpler decision aids, the relative improvement in knowledge was significant (MD 4.97 out of 100; 95% CI 3.22 to 6.72; n = 15). Exposure to a decision aid with expressed probabilities resulted in a higher proportion of people with accurate risk perceptions (RR 1.74; 95% CI 1.46 to 2.08; n = 14). The effect was stronger when probabilities were expressed in numbers (RR 1.93; 95% CI 1.58 to 2.37; n = 11) rather than words (RR 1.27; 95% CI 1.09 to 1.48; n = 3). Exposure to a decision aid with explicit values clarification compared to those without explicit values clarification resulted in a higher proportion of patients achieving decisions that were informed and consistent with their values (RR 1.25; 95% CI 1.03 to 1.52; n = 8).
B) Criteria involving decision process attributes:
Decision aids compared to usual care interventions resulted in: a) lower decisional conflict related to feeling uninformed (MD of 100; 95% CI to -3.70; n = 17); b) lower decisional conflict related to feeling unclear about personal values (MD -4.81; 95% CI to -2.40; n = 14); c) reduced the proportions of people who were passive in decision making (RR 0.61; 95% CI 0.49 to 0.77; n = 11); and d) reduced proportions of people who remained undecided post-intervention (RR 0.57; 95% CI 0.44 to 0.74; n = 9). Decision aids appear to have a positive effect on patient-practitioner communication in the four studies that measured this outcome. For satisfaction with the decision (n = 12) and/or the decision making process (n = 12), those exposed to a decision aid were either more satisfied or there was no difference between the decision aid versus comparison interventions. There were no studies evaluating the decision process attributes relating to helping patients to recognize that a decision needs to be made or understand that values affect the choice.
C) Secondary outcomes
Exposure to decision aids compared to usual care continued to demonstrate reduced choice of: major elective invasive surgery in favour of conservative options (RR 0.80; 95% CI 0.64 to 1.00; n = 11). Exposure to decision aids compared to usual care also resulted in reduced choice of PSA screening (RR 0.85; 95% CI 0.74 to 0.98; n = 7). When detailed compared to simple decision aids were used, there was reduced choice of menopausal hormones (RR 0.73; 95% CI 0.55 to 0.98; n = 3). For other decisions, the effect on choices was variable. The effect of decision aids on length of consultation varied from -8 minutes to +23 minutes (median 2.5 minutes). Decision aids do not appear to be different from comparisons in terms of anxiety (n = 20), and general health outcomes (n = 7), and condition specific health outcomes (n = 9). The effects of decision aids on other outcomes (adherence to the decision, costs/resource use) were inconclusive.
Stacey D et al. Cochrane review 2014

11. Glasziou and Haynes ACP JC 2005
EBM KT
Glasziou and Haynes ACP JC 2005

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

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. Quality of care
HbA1c
Clinical
inertia
Technical
decisions
Report card

19. Will I live unhindered by complications?
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?
CAUSAL PATHWAY
Patient
important
outcomes Tx
HbA1c

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

25. Wasted or misallocated healthcare resources:
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

27. Patient advisory groups
Evidence
synthesis
Observation
clinical encounters
Initial prototype
Designers
Study team
Patient advisory groups
Clinicians
Stakeholders
Modified
prototype
Field
testing
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”

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

37. Increased patient involvement
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

39. Risk-Treatment Paradox
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.

44. Improved Knowledge Risk estimation Comfort with the decision
Total trust
Action (70% fewer Rx in low risk patients)
Short-term adherence
First one to be developed.
In endocrinology. Diabetes patients.
Now in the EMR system at Mayo. Used more than 500 times..
Weymiller et al. Arch Intern Med 2007

45. Web
Statin Choice

46. Web
Statin Choice

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. Clinician satisfaction (%)* Incremental time investment, median
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. Challenges with evidence synthesis and changing evidence
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. The impact on improving adherence to medications is mixed
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