Advancing stated-preference methods for measuring the preferences of patients with type 2 diabetes

Transcription

1 Advancing stated-preference methods for measuring the preferences of patients with type 2 diabetes 1

2 WELCOME John F. P. Bridges, Ph. D. Principal investigator Center for Health Services and Outcomes Research Department of Health Policy and Management Johns Hopkins Bloomberg School of Public Health Project supported by the Patient-Centered Outcomes Research Institute (PCORI) Johns Hopkins Bloomberg School of Public Health 2

3 Overview of this meeting Session 1: Preferences and priori1es of pa1ents with type 2 diabetes 1:00-1:15pm Welcome and introduc6on 1:15-2:00pm Barriers and facilitators to self-management of type 2 diabetes 2:00-2:45pm Treatment preferences of pa6ents with type 2 diabetes Session 2: Other applica1ons of stated-preference studies 3:00-4:00pm Examples of stated-preference studies in health 4:00-4:30pm Current and proposed stated-preference studies in health 4:30-5:00pm Wrap up and Discussion 5:00-6:30pm Recep6on (Carpenter room, School of Nursing) 2014, Johns Hopkins University. All rights reserved. 3

4 Welcome and Overview of the PCORI Project 4

5 Overview This project is funded by the Patient-Centered Outcomes Research Institute Methods Program Award (ME ). It aims to promote, advance and apply statedpreference methods to measure the priorities and preferences of patients and other stakeholders in medicine The project is funded for three years at $750,000 direct costs. Deemed exempt of review by JHSPH Institutional Review Board (IRB 6001) 5

6 Acknowledgements Management team: John F P Bridges (PI), Albert Wu Patient/stakeholder engagement team: Daniel Longo, Lee Bone Stated-preference evaluation team: Karen Bandeen-Roche, Jodi Segal, Tanjala Purnell Project manager Karen Edwards Student investigators Ellen Janssen, Allison Oakes, Mo Zhou Diabetes action board members 6

7 Diabetes action board (DAB) The diabetes action board (DAB) is a group of local and national stakeholders that has played and will continue to play a role in: Developing this study to measure the preference of patients in type 2 diabetes Assisting in the broad dissemination of the research findings and in leverage further applications and action in type 2 diabetes Building personal and professional relationships to enrich our work 7

8 Objectives of the PCORI study 1. Demonstrate and disseminate good practices for patient and community involvement in patient centered outcomes research projects by applying principles of community-based participatory research 2. Address several key methodological questions pertaining to the use of stated-preference methods 3. Demonstrate and disseminate good practices for the application of stated-preference methods in patient centered outcomes research 8

9 Aims of the PCORI study 1. Compare two survey methods for assessing the priorities of patients with type 2 diabetes (rating/ ranking vs. best-worst scaling) 2. Compare two survey methods for measuring the preferences of patients with type 2 diabetes (choice based conjoint/discrete choice experiment vs. best-worst scaling) 3. Compare stratification and segmentation methods for analyzing preference heterogeneity 4. Assess patients and stakeholders beliefs about the relevance of our methods and results 9

10 PCORI Diabetes Preferences Study Study Overview - Progress Progress First DAB mee6ng Second DAB mee6ng Third DAB mee6ng Fourth DAB mee6ng FiVh DAB mee6ng Final DAB mee6ng White paper Report: focus groups Report: aggregate findings Report: heterogeneity Report: follow up findings Systema6c Review Focus groups (n=25) Pretest (n=25) Pilot test (n=50) Na6onal (n=1000) Follow up survey (n=600) Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Completed 2014, Johns Hopkins University. All rights reserved. 10

11 National Survey - Overview 1103 people participants with self-reported type 2 diabetes. Survey was administered through GfK Knowledge Panel, a nationally representative online panel. The survey was in the field for 16 days from October 10 to October 25, 2015 Collected preference data as well as self-reported demographic, personality, and clinical information 11

12 Survey structure A 2X2 randomized design was utilized Participants were randomized to: A prioritization method to measure barriers and facilitators to diabetes self-management Likert vs. BWS Case 1 A preference method to measure treatment preferences for hypothetical diabetes medications DCE vs. BWS Case 2 12

13 2. Barriers and facilitators to diabetes self-management 13

14 Topic identification The proposal called for a comparison of two methods for prioritization The topic was to be chosen through community engagement DAB members were: Informed about various prioritization methods Engaged in a topic selection deliberative process involving Brain storming about possible topics Dot voting to identify most important topics 2014, Johns Hopkins University. All rights reserved. 14

15 Brainstorming and voting results Daily choices Lifestyle Family/support person involvement Things that ma^er to me (health) Things that impact my decisions Sources & methods of informa6on Educa6on techniques Diet & exercise/weight control Barriers to treatment Things I understand Barriers to lifestyle changes (# of votes)

16 Diabetes self-management The ability to manage the symptoms, treatment, physical and psychosocial consequences and lifestyle changes inherent in living with a chronic condition. Intended to curb the worsening of the disease and its associated complications. Given the complex and chronic nature of diabetes, effective and comprehensive self-management is key to the well-being of the patient and often cannot be substituted by additional medical interventions. 16

17 Barriers and facilitators Barriers and facilitators to self-management can be both personal and socio-environmental. Personal factors include an individual s disease-related beliefs, understanding, and experiences. Key socio-environmental factors include geography, socioeconomic status, family, culture, religion, work, and access to health care. Although much literature exists to identify key barriers and facilitators to the self-management of type 2 diabetes, there has not yet been an attempt to prioritize and weight each of the barriers and facilitators from the perspective of the patient. 17

18 Identifying barriers and facilitators 1. Literature review 12 studies that examined priorities in type 2 diabetes 2. Focus groups Three focus groups with patients with type 2 diabetes in Baltimore (n=24) 3. DAB meetings Presented factors to DAB members for comment 4. Pretest interviews Patients with type 2 diabetes (n=25) in Baltimore 5. Pilot Testing Patients with type 2 diabetes from a national online panel (n=50) 2014, Johns Hopkins University. All rights reserved. 18

19 Hypothesized facilitators Factors My own knowledge (++) Healthcare providers (+) Support from others (+) Description Do you feel you know enough about diabetes to self-manage your diabetes? Do your healthcare providers have a positive or negative impact on your ability to self-manage you diabetes? Do you have enough support from friends, co-workers, support groups or others in your community? 19

20 Hypothesized neutral factors Factors Access to healthy food (+/ ) Staying motivated (+/ ) My ability to pay (+/ ) Physical environment (+/ ) Local events (+/ ) Description Do you have regular access to healthy food that will support your ability for diabetes self-management? Do you usually have the self-control to make the best choices for managing your diabetes? Do you have enough money to successfully self-manage your diabetes? Does the place/location where you live and work provide you with the resources to manage your diabetes? Do your local events (e.g. cultural, community, or religious) impact your ability for diabetes self-management? 20

21 Hypothesized barriers Factors Family commitments ( ) Work commitments ( ) Other health conditions ( ) Description Does your family have a positive or negative impact on your ability to selfmanage your diabetes? Does your work (or other responsibilities) affect your ability to self-manage your diabetes? Do you have other health conditions (mental and physical) that affect how you manage your diabetes? 21

22 Prioritization methods Likert Item Best Worst Scaling A quantified response to a statement on a symmetric, balanced scale according to objective/subjective criteria Strengths: simple, intuitive appeal, frequent use Limitations: central tendency bias, social desirability bias, acquiescence bias, ceiling/ floor effect 2014, Johns Hopkins University. All rights reserved. A repeated discretechoice response assessing the best/worst statement according to objective/subjective criteria Strengths: simple design and analysis Limitations: possible floor and ceiling effects Limited evidence on strengths and limitations, needs to be further studied 22

23 Prioritization tasks Likert Item 11 items Rank each item on a 5 point scale from strong nega6ve impact (-2) to strong posi6ve impact (+2) on capacity for diabetes self-management. Best Worst Scaling Case 1 11 items Par6cipant presented with 11 sets of 5 items according to a BIB Design From each set, asked to select the best and the worst in terms of impact on diabetes selfmanagement 2014, Johns Hopkins University. All rights reserved. 23

24 Prioritization via Likert items Strong negative impact -2 Negative impact -1 Neither a positive nor a negative impact 0 Positive impact +1 Strong positive impact Local events Support from others Access to healthy food Healthcare providers Physical environment Staying motivated My own knowledge Family commitments Work commitments My ability to pay Other health conditions +2 24

25 Prioritization via BWS Things impacting your own diabetes self-management Best Worst Access to healthy food Healthcare providers My ability to pay Local events Family commitments Consider the following things that can have a positive or negative impact on your own diabetes self-management. Which of the following things is the best and which is the worst in terms of impact on your own diabetes self-management? 25

26 Demographic characteristics Likert BWS1 P-value Total (N, prop) Age (mean, range) Gender Male (N, prop) 263 (.48) 290 (.52).140 Race White (N, prop) 287 (.52) 288 (.52) Black (N, prop) 126 (.23) 128 (.23) Hispanic (N, prop) 117 (.21) 119 (.21) Other (N, prop) 19 (.03) 19 (.03) Education.522 No High school degree (N, prop) 44 (.08) 38 (.07) High school degree (N, prop) 189 (.34) 173 (.31) Some college (N, prop) 163 (.30) 175 (.32) Bachelor s or higher (N, prop) 153 (.28) 168 (.30) 2014, Johns Hopkins University. All rights reserved. 26

27 Diabetes related characteristics Likert BWS1 P-value Years of diagnosis (mean, range) Hypoglycemia At least once in past 6 mo (N, prop) 270 (.50) 262 (.47).599 A1c level % (N, prop) 75 (.14) 88 (.16) 7.0%, but < 8.0% (N, prop) 149 (.27) 148 (.27) < 7.0% (N, prop) 242 (.44) 218 (.40) Don t know (N, prop) 79 (.15) 94 (.17) Diabetes medicine.644 No medicine (N, prop) 52 (.09) 47 (.09) Only pills (N, prop) 333 (.61) 333 (.60) Only insulin/injection (N, prop) 48 (.09) 42 (.08) Pills and injections (N, prop) 2014, Johns Hopkins University. All 115 rights reserved. (.21) 131 (.24) 27

28 Self-reported personality Standardized score on a scale from strongly disagree (-2) to strongly agree (+2) I am always op6mis6c about future I have a lot of selfcontrol I am ac6vely working to improve health I consider myself a risk taker 2014, Johns Hopkins University. All rights reserved. I am good with numbers Doctors should always ask pa6ents for preferences. Likert BWS 1 28

29 Time spent per section (minutes) Q1 Min Media n Max Q3 Likert BWS 1 Task N Median (min) Min (min) Q1 Q2 Max (min) Likert BWS

30 Research Question Are priorities estimated using Likert items the same as priorities estimated using Best-Worst scoring? Determine: Correlation between methods Equivalence of the methods Respondent burden of the methods 30

31 Methods Evaluation questions to determine respondent burden using Likert item questions Likert rating results were aggregated into a standardized scores Best-Worst responses were aggregated into BW scores (Times a factor was chosen as best Times it was chosen as worst) / Total number of times it appeared 31

32 Evaluation of prioritization tasks Likert BWS I found it easy to understand the ques6ons I found it easy to complete the ques6ons I answered in a way consistent with my preferences 32

33 Frequency of Likert item responses

34 BWS responses Number of 1mes aoribute was chosen as worst or as best My own knowledge Healthcare providers Access to healthy food Support from others Staying mo1vated Family commitments Physical environment Best Worst My ability to pay Work commitments Local events Other health condi1ons

35 Likert item vs. BWS (rho=0.97) BWS score Likert score 35

36 Likert Scores item vs. BWS scores Score Likert Scale BWS 36

37 BWS 1 results by Gender Best_Worst Score Male Female 37

38 BWS 1 results by A1c Below 7% Above 7%

39 Conclusions Overall, there was a fairly strong consistency (rho >0.9) between the methods Responses to the Likert items demonstrated some of the classical biases of the approach Social desirability bias/acquiescence bias Responses to the BWS were more variable, symmetric, and consistent with hypotheses, but lacked a clear determination neutrality (i.e. had no natural zero) 39

40 Questions? Thank You! 2015, Johns Hopkins University. All rights reserved. 40

41 3. Patient preferences for diabetes medications 41

42 Preference methods Discrete Choice Best Worst Scaling A repeated discretechoice response indicating preference between two or more profiles according to objective/subjective criteria Strengths: most frequently used and studied statedpreference method Limitations: complicated design and analysis 2014, Johns Hopkins University. All rights reserved. A repeated discretechoice response assessing the best/worst aspect of a profile according to objective/ subjective criteria Strengths: simple design and analysis Limitations: possible floor and ceiling effects 42

43 Instrument development Evidence synthesis Expert consultation Stakeholder engagement Pretest interviews 2014, Johns Hopkins University. All rights reserved. Pilot testing 43

44 The diabetes preference literature 10 a^ributes extracted from 12 DCEs CVD"risk"(3)" Monitoring"(2)" Quality"of"Life"(2)" Side"effects"(5)" Burden"(15)" Hypoglycemia"(12)" Nausea"(7)" Weight"(8)" Glucose"(14)" Cost"(5)" 0" 5" 10" 15" 20" 25" 30" 35" 40" 45" 50" 2014, Johns Hopkins University. All rights reserved. Max" Median" Min" 44

45 Decision Framework Suppose that your doctor says that your current diabetes medicine is not working to keep your blood sugar controlled. Your doctor recommends that you add another diabetes medicine to lower your A1c. 2014, Johns Hopkins University. All rights reserved. 45

46 Attributes Attributes A1c levels go down Stable blood glucose Low blood glucose Nausea Additional medicine Additional outof-pocket costs Highest benefit/ Lowest risk Medium benefit and risk Lowest benefit/ Highest risk 1% 0.5% 0% 6 days per week None None 4 days per week During the day only 30 minutes per day 1 pill per day 2 pills per day 2 days per week During the day and/or night 90 minutes per day 1 pill and 1 injection per day $10 per month $30 per month $50 per month 46

47 Preference elicitation Best-Worst Scaling (BWS) Attributes A1c levels go down Stable blood sugar Low blood glucose Medicine A Best Worst 1% 4 days/wk During the day Nausea None Additional medicine Additional out-ofpocket costs 2 pills/day $50/mo Attributes A1c levels go down Stable blood sugar Low blood glucose Nausea Additional medicine Additional outof-pocket costs Which medicine would you choose? 2014, Johns Hopkins University. All rights reserved. Discrete Choice Experiment (DCE) Medicine A Medicine B 1% 0.5% 2 days/wk 4 days/wk During the day None None 90 min/ day 2 pills/day 1 pill/day $50/mo Medicine A $30/mo Medicine B 2015, 2014, 2014, Johns Johns Hopkins Hopkins University. University. All All rights All rights reserved. reserved. 47

48 Preference tasks DCE 6 attributes at 3 levels each Bayesian efficient design: 48 profile pairs divided into 4 blocks Added 2 holdout tasks to each block 18 profile pairs per participant Prompt: Consider the following two diabetes medicines. Which medicine would you prefer? Best Worst Scaling Case 2 6 attributes at 3 levels each Orthogonal design: 18 profiles per participant Prompt: Which of this medicine s characteristics is the best and which is the 2014, Johns Hopkins University. All rights reserved. worst? 48

49 Research Question Are treatment preferences estimated using BWS Case 2 the same as treatment preferences estimated using DCE? Determine: Correlation between methods Equivalence of the methods Respondent burden of the methods 49

50 Methods Estimated mixed logit models for both the BWS and DCE Mixed logit models can account for preference heterogeneity between individuals 50

51 Demographic characteristics BWS 2 DCE P-value Total (N, prop) 551 (0.50) 552 (0.50) Age (mean, range) 63 (25, 89) 61 (24, 91).082 Gender Male (N, prop) 274 (0.49) 279 (0.51).787 Race.985 White (N, prop) 286 (0.51) 289 (0.52) Black (N, prop) 128 (0.23) 126 (0.23) Hispanic (N, prop) 117 (0.21) 119 (0.22) Other (N, prop) 20 (0.04) 18 (0.03) Education.393 No HS degree (N, prop) 39 (0.07) 43 (0.08) HS degree (N, prop) 174 (0.32) 188 (0.34) Some college (N, prop) 182 (0.33) 156 (0.28) 2014, Johns Hopkins University. All rights reserved. Bachelor s or higher (N, prop) 156 (0.28) 165 (0.30) 51

52 Diabetes Related Characteristics Years of diagnosis (mean, range) BWS 2 DCE P-value 13.2 (11.9, 14.5) 12.6 (11.4, 13.7) 2014, Johns Hopkins University. All rights reserved. Pills and injections (N, prop) 119 (0.22) 127 (0.23).645 Hypoglycemia At least once in past 6 mo (N, prop) 273 (0.50) 259 (0.47).820 A1c level % (N, prop) 83 (0.15) 80 (0.15) 7.0%, but < 8.0% (N, prop) 144 (0.27) 153 (0.28) < 7.0% (N, prop) 232 (0.43) 228 (0.41) Don t know (N, prop) 84 (0.15) 89 (0.16) Diabetes medicine.049 No medicine (N, prop) 62 (0.11) 37 (0.07) Only pills (N, prop) 321 (0.58) 345 (0.63) Only insulin/injection (N, prop) 48 (0.09) 42 (0.08) 52

53 Self-reported personality Standardized score on a scale from strongly disagree (-2) to strongly agree (+2) I am always op6mis6c about future I have a lot of selfcontrol I am ac6vely working to improve health I consider myself a risk taker 2014, Johns Hopkins University. All rights reserved. I am good with numbers Doctors should always ask pa6ents for preferences. BWS 2 DCE 53

54 Time spend per Section (minutes) Q1 Min Median Max Q3 DCE BWS 2 Task N Median Min Q1 Q3 Max (minutes) (minutes) (minutes) (minutes) (minutes) DCE BWS

55 Evaluation of preference tasks Standardized score on a scale from strongly disagree (-2) to strongly agree (+2) DCE BWS I found it easy to understand the ques6ons I found it easy to complete the ques6ons I answered in a way consistent with my preferences 55

56 Likert rating of the attributes Standardized score on a scale from not important at all (-2) to very important (+2) Importance score 56

57 BWS 2: Results vs. priors (rho=0.93) A1c decrease Stable blood glucose Low blood glucose Nausea Treatment burden Out-ofpocket cost 1% 0.50% 0% 6 days/week 4 days/week Analyzed using condi6onal logit and effects coding 2 days/week None Day Day and/or night Final results None 30 minutes 90 minutes Design priors 1 pill 2 pills 1 pill and 1 injec6on $10 $30 $50 57

58 DCE: Results vs. priors (rho=0.92) A1c decrease 1% 0.50% 0% Stable blood glucose 6 days/week 4 days/week Analyzed using condi6onal logit and effects coding 2 days/week Low blood glucose None Day Day and/or night Final results None Nausea 30 minutes 90 minutes Design priors Treatment burden 1 pill 2 pills 1 pill and 1 injec6on Out-ofpocket cost $10 $30 $50 58

59 DCE: Lexicographic Preferences Took differences between attributes for the two treatment alternatives Participants were recorded if they always chose the alternative with the better level for a particular attribute Final survey (n=552) Pilot survey (n=27) Attribute N Proportion N Proportion Total 70 13% 11 41% A1c decrease 6 1% 1 4% Stable blood sugar 2 0.4% 3 11% Low blood glucose Nausea 21 4% 2 7% Treatment burden 1 0.2% 1 4% Out-of-pocket cost 46 8% 3 11% 59

60 DCE vs. BWS Case 2 (rho = 0.91) A1c decrease 1% 0.50% 0% Stable blood glucose 6 days/week 4 days/week Analyzed using mixed logit and effects coding 2 days/week Low blood glucose None Day Day and/or night DCE None Nausea 30 minutes BWS 90 minutes Treatment burden 1 pill 2 pills 1 pill and 1 injec6on Out-ofpocket cost $10 $30 $50 60

61 MXL: Individual coefficients (DCE) 1% A1c decrease Stable 6 dy/wk No hypoglycemia No nausea 1 pill % A1c decrease Stable 4 dy/wk Daytime hypoglycemia minutes Nausea 2 pills Density y 61

62 Relative attribute importance DCE BWS 17% 16% 18% 22% 18% 12% 12% 10% 17% 27% 20% 11% 62

63 Standardized attribute importance DCE BWS 0 63

64 Comparing results with the literature A(ributes CVD risk (3) Monitoring Quality of Life Side effects Treatment Hypoglycemia Nausea (7) Weight (8) Glucose (14) Cost (5) Rela%ve a(ribute importance (%) BWS RESULTS DCE RESULTS Max 2014, Johns Hopkins University. All rights reserved. Median Min 64

65 BWS score by Gender A1c decrease Stable blood glucose Low blood glucose Nausea Treatment burden Out-ofpocket cost % 0.50% 0% 6 days/week Analyzed using condi6onal logit and effects coding 4 days/week 2 days/week None Day Day and/or night Male None 30 minutes Female 90 minutes 1 pill 2 pills 1 pill and 1 injec6on $10 $30 $50 65

66 A1c decrease BWS score by A1c level Stable blood glucose Low blood glucose Nausea Treatment burden Out-ofpocket cost % 0.50% 0% Analyzed using condi6onal logit and effects coding 6 days/week 4 days/week 2 days/week None Day Day and/or night None 30 minutes <7.0% >8.0% 90 minutes 1 pill 2 pills 1 pill and 1 injec6on $10 $30 $50 66

67 Conclusion Participants did not express a strong preference towards BWS or DCE. The proportion of individuals with Lexicographic preferences was much lower in the final survey (Bayesian D-efficient design) than in the pilot survey (orthogonal design) Preference weights obtained from BWS or DCE had high correlation, but were on a different scale. 2014, Johns Hopkins University. All rights reserved. 67

68 Questions? Thank You! 2015, Johns Hopkins University. All rights reserved. 68

69 Protecting Health, Saving Lives Millions at a Time 69

70 Barriers and Facilitators Factor Access to healthy food Healthcare providers My own knowledge Staying motivated Description Do you have regular access to healthy food that will support your ability for diabetes self-management? Do your healthcare providers have a positive or negative impact on your ability to self-manage you diabetes? Do you feel you know enough about diabetes to self-manage your diabetes? Do you usually have the self-control to make the best choices for managing your diabetes? My ability to pay Do you have enough money to successfully self-manage your diabetes? Other health conditions Family commitments Physical environment Local events Work commitments Support from others Do you have other health conditions (mental and physical) that affect how you manage your diabetes? Does your family have a positive or negative impact on your ability to selfmanage your diabetes? Does the place/location where you live and work provide you with the resources to manage your diabetes? Do your local events (e.g. cultural, community, or religious) impact your ability for diabetes self-management? Does your work (or other responsibilities) affect your ability to self-manage your diabetes? Do you have enough support from friends, co-workers, support groups or others in your community? 70

71 BWS 1 results by Education Best_Worst Score Less than high school High school degree Some college Bachelor degree 71

72 BWS 1 results by Race Best_Worst Score White Black Hispanic

73 BWS results by Income Best_Worst Score < 25,000 25,000-49,

74 A1c levels A1c levels Doctors prescribe diabetes medicines to help lower your A1c, or average blood glucose level during the past three months. Keeping your A1c at the recommended level may decrease your risk for serious health problems such as heart attack, blindness, amputation, and kidney failure. When taking the new medicine your A1c level might go down by: 1% this is a large decrease 0.5% this is a moderate decrease 0% this is no decrease 74

75 Stable Blood Sugar Stable blood sugar The new medicine might help keep your blood glucose levels stable on a daily basis. Your blood glucose levels are stable for the day if they stay in a range of mg/dl. When taking this new medicine your blood glucose levels might be stable for: 6 days per week 4 days per week 2 days per week 75

76 Low Blood Sugar Low blood sugar You might experience low blood glucose, also known as hypoglycemia. This may make you feel shaky/drowsy and have blurred vision or difficulty walking/talking. You might pass out (if you don t eat or drink). Low blood glucose can also happen at night while you sleep. Then you won t know about it and you might be more likely to pass out. You might experience low blood glucose: None During the day only During the day and/or at night 76

77 Nausea Nausea The new medicine may cause moderate nausea. This means you feel sick to your stomach and like you need to vomit. When taking this new medicine you might experience nausea for a total of: None 30 minutes per day 90 minutes per day 77

78 Treatment Burden Treatment burden You will have to take the new medicine daily. You need to take this medicine in addition to the medicines you already take. We will consider three different ways of taking the medicine. You might have to take an additional: 1 pill per day 2 pills per day 1 pill and 1 injection per day 78

79 Medication Costs Medication costs The medicine will require out-of-pocket costs in addition to what you already pay for other medicines. The money you spend on this medicine cannot be spent on other things. Your additional costs might be: $10 per month $30 per month $50 per month 79

80 DCE results by Education A1c decrease 1% 0.50% 0% 6 days/week Analyzed using condi6onal logit and effects coding Stable blood glucose 4 days/week 2 days/week Low blood glucose None HS or less Day Day and/or night None Nausea 30 minutes 90 minutes Some college or more Treatment burden 1 pill 2 pills 1 pill and 1 injec6on Out-ofpocket cost $10 $30 $50 80

81 DCE results by Race A1c decrease Stable blood glucose Low blood glucose Nausea Treatment burden Out-ofpocket cost % 0.50% 0% Analyzed using condi6onal logit and effects coding 6 days/week 4 days/week 2 days/week None Day Day and/or night None 30 minutes 90 minutes 1 pill White Black Hispanic 2 pills 1 pill and 1 injection $10 $30 $50 81

82 DCE results by Language A1c decrease Stable blood glucose Low blood glucose Nausea Treatment burden Out-ofpocket cost % 0.50% 0% 6 days/week Analyzed using condi6onal logit and effects coding 4 days/week 2 days/week None Day Day and/or night Spanish None 30 minutes English 90 minutes 1 pill 2 pills 1 pill and 1 injection $10 $30 $50 82

83 Scale differences Estimated preference weights are inversely related to error variances. Therefore estimated preference weights from groups with different variances can differ even if the true weights are the same. These are called scale differences. Can be tested for using Swait-Louviere scale test No scale differences were found based self-reported Skill with numbers Ease of understanding the choice tasks Ease of answering the choice tasks Consistency in answers 83

84 DCE results by Ease of Answering A1c decrease Stable blood glucose Low blood glucose Nausea Treatment burden Out-ofpocket cost % 0.50% 0% 6 days/week 4 days/week 2 days/week None Day Day and/or night Not easy to answer None 30 minutes 90 minutes 1 pill Easy to answer 2 pills 1 pill and 1 injection $10 $30 $50 84

85 DCE: MXL vs. MNL (Rho>0.99) A1c decrease Stable blood glucose Low blood glucose Nausea Treatment burden Out-ofpocket cost % 0.50% 0% 6 days/week 4 days/week 2 days/week None Day MXL Day and/or night None 30 minutes MNL 90 minutes 1 pill 2 pills 1 pill and 1 injec6on $10 $30 $50 85

86 BWS: MXL vs. MNL(Rho>0.99) A1c decrease Stable blood glucose Low blood glucose Nausea Treatment burden Out-ofpocket cost 1% 0.50% 0% 6 days/week 4 days/week 2 days/week None Day Day and/or night MXL None 30 minutes MNL 90 minutes 1 pill 2 pills 1 pill and 1 injec6on $10 $30 $50 86