Combination Basal Insulin and GLP-1 RA Therapy: A Physiologic Approach to Diabetes Care
Final Live Activities Outcomes Report
January 16, 2019
Sanofi US – Grant ID: IME-2017-11786
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Impact
Pre to Post Test Results By Learning Objectivev +13.51% Improvement: Discuss the benefits of a pathophysiologic vs
algorithmic approach to type 2 diabetes (T2D) managementv +193.65%* Improvement: Utilize effective strategies to overcome barriers
to therapeutic intensification and clinical inertia in T2D managementv +98.04%* Improvement: Realize the limits of basal insulin therapy in
clinical practice and when there is a greater need to address post-prandial hyperglycemia
v +27.95%* Improvement: Identify patients who are most likely to benefit from combined basal insulin-GLP-1RA therapy as an effective means of combining endogenous/exogenous insulin therapy
v 2,365 attendees were reached via both online and live formats, with gains observed across cohorts and modalities from Pre-Test to Post-Test.
v Despite substantial improvements, learners showed persistently low scores on questions assessing their ability to effectively include A1C levels, glucose levels, and the mechanism of hyperglycemia into their treatment selection. They also had low Post-Test scores on a question addressing the impact of A1C and glucose levels on hyperglycemia.
v Although learners demonstrated net increases in Knowledge, Confidence, and practice strategy questions on the follow-up assessment, consistently low scores across domains and a net decrease in Competence highlight the need for ongoing reinforcement.
Executive Summary2,365*Total Attendees
9 Cities
1,288*On Site
1,077*Simulcast / Virtual Symposium
0%20%40%60%80%
100%
LO 1 LO 2 LO 3 LO 4
Pre-Test Post-Test+193.65%*+13.51% +98.04%*
(N = 440–550)
v This curriculum focused on the use of combination basal insulin/GLP-1 therapy in the management of type 2 diabetic patients.
v Substantial improvements and comparatively high scores were measured in learners’ ability to utilize strategies to overcome barriers to treatment intensification and clinical inertia.
*These numbers represent the total number of attendees, irrespective of assessment participation
+27.95%*
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Curriculum Patient Impact
23,650–28,380 patients on a weekly basis
The findings reveal that this education has the potential to impact
1,352,780patients on an annual basis.
23,650–28,380
In the evaluation, learners (N = 2,365) were asked to report how many patients with type 2 diabetes they see in any clinical setting per week by selecting a range. The resulting distribution of learner responses was then extrapolated to reflect the total number of learners who have attended the onsite and online meetings.
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Faculty
Activity Planning CommitteeGregg Sherman, MDMichelle Frisch, MPH, CCMEPStephen WebberSandy Bihlmeyer M.EdAlan Goodstat, LCSWDaniela HiedraDeborah Paschal, ARNP
Robert S. Busch, MD, FACEDirector of Clinical ResearchAlbany Medical Faculty: Community Endocrine GroupAlbany, NY
Davida F. Kruger, MSN, APN-BC, BC-ADM Certified Nurse Practitioner Henry Ford Health System Divisionof Endocrinology, Diabetes, Bone and Mineral Disease Detroit, MI
Donna L. Jornsay, MS, BSN, RN, CPNP, CDE, CDTC, BC-ADM
Diabetes Educator and Nurse ConsultantSan Bruno, CA
Lucia M. Novak, MSN, ANP-BC, BC-ADM, CDTCDirector, Riverside Diabetes CenterRiverside Medical AssociatesAdjunct Assistant ProfessorUniformed ServicesUniversity of the Health SciencesBethesda, MD
Ashlyn Smith, MMS PA-CEndocrinology Associates, P.A.Secretary, American Society of Endocrine Physician Assistants Adjunct Assistant Professor, Midwestern UniversityScottsdale, AZ
Mark Stolar, MDAssociate Professor of Clinical MedicineNorthwestern University Medical SchoolChicago, IL
Jeff Unger, MD, ABFM, FACEDirector, Unger Primary Care Medical GroupRancho Cucamonga, CA
Course Directors
Mark Stolar, MDAssociate Professor of Clinical MedicineNorthwestern University Medical SchoolChicago, IL
Faculty
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Overview
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Commercial Support
The Clinical Updates for Nurse Practitioners and Physician Assistants: 2018 series of CME activities were supported through educational grants or donations from the following companies:
vActelion Pharmaceuticals US, Inc
vSanofi US
vGrifols
vNovartis Pharmaceuticals Corporation
vGlaxoSmithKline
vFerring Pharmaceuticals, Inc.
vMerck Sharp & Dohme Corp.
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Curriculum Overview9 Accredited Live Regional Symposia with 1 simulcast
Sep 8, 2018 – Nov 17, 20181 Accredited Live Virtual Symposium:
Nov 17, 2018
Online Enduring CME Monograph:
vLaunch Date: Oct 31, 2018
vEnd Date: Oct 30, 2019
vHosted at http://naceonline.com/CME-
Courses/course_info.php?course_id=1053
Clinical Highlights eMonograph -
eMonograph containing key teaching points
from the CME Activity was distributed 1 week
after the meeting to all attendees.
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Learning Objectives
v Discuss the benefits of a pathophysiologic vs algorithmic approach to type 2 diabetes (T2D) management
v Utilize effective strategies to overcome barriers to therapeutic intensification and clinical inertia in T2D management
v Realize the limits of basal insulin therapy in clinical practice and when there is a greater need to address post-prandial hyperglycemia
v Identify patients who are most likely to benefit from combined basal insulin-GLP-1RA therapy as an effective means of combining endogenous/exogenous insulin therapy
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Learning outcomes were measured using matched Pre-Test and Post-Test scores for Knowledge, Performance, Confidence, and practice strategy and across all of the curriculum’s Learning Objectives.
Outcomes Metric Definition Application
Percentage change This is how the score changes resulting from the education are measured. The change is analyzed as a relative percentage difference by taking into account the magnitude of the Pre-Test average.
Differences between Pre-Test, Post-Test, and PCA score averages
P value (p) This is the measure of the statistical significance of a difference in scores. It is calculated using dependent or independent samples t-tests to assess the difference between scores, taking into account sample size and score dispersion. Differences are considered significant for when p ≤ .05.
Significance of differences between Pre-Test, Post-Test, and PCA scores and among cohorts
Effect size (d) This is a measure of the strength/magnitude of the change in scores (irrespective of sample size). It is calculated using Cohen's d formula, with the most common ranges of d from 0-1: d < .2 is a small effect, d=.2-.8 is a medium effect, and d > .8 is a large effect.
Differences between Pre-Test and Post-Test score averages
Power This is the probability (from 0 to 1) that the “null hypothesis” (no change) will be appropriately rejected. It is the probability of detecting a difference (not seeing a false negative) when there is an effect that is dependent on the significance (p), effect size (d), and sample size (N).
Differences between Pre-Test and Post-Test score averages
Percentage non-overlap This is the percentage of data points at the end of an intervention that surpass the highest scores prior to the intervention. In this report, it will reflect the percentage of learners at Post-Test who exceed the highest Pre-Test scores.
Differences between Pre-Test and Post-Test score averages
Outcomes Methodology
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2018 Clinical Updates Participation
2018 Symposium/Simulcast Date Attendees
White Plains, NY 9/8/18 189Orlando, FL 9/15/18 199Seattle, WA 9/22/18 103
Philadelphia, PA (King of Prussia) 10/6/18 79Anaheim, CA 10/13/18 98Charlotte, NC 10/20/18 115Phoenix, AZ 10/27/18 116
Phoenix, AZ simulcast 10/27/18 550Dallas, TX 11/3/18 260Miami, FL 11/10/18 129
Virtual 11/17/18 527Total 2,365
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Level 1 Participation
Demographics Patient Reach
2,365* Total Attendees
9 Cities
1,288* On Site
1,077*Simulcast / Virtual Symposium
Participation
*These numbers represent the total number of attendees, irrespective of assessment participation
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73.60%
9.97% 9.79%3.32% 2.80% 0.52%
NP PA MD RN Other DO
Profession Years in Practice
Patient Care Focus: 95%
36.99%
21.79%19.59%
21.62%
< 5 5–10 11–20 > 20
Level 1: Demographics and Patient Reach
74.66%
6.90% 6.03% 4.31% 8.10%
Primary Care-Family Practice,Internal Medicine
Other Cardiology EmergencyMedicine/ Critical
Care
Specialty above
Specialists:Hospitalist 3.62%Endocrinology 2.41%Psychiatry/Neurology 0.69%Pulmonology 0.69%Gastroenterology 0.52%Rheumatology 0.17%
Patients with T2D seen each week, in any clinical setting:
17.67%9.02%
14.23%14.95%
18.86%16.61%
8.66%
0% 5% 10% 15% 20%
> 25
21–25
16–20
11–15
6–10
1–5
None
Specialty
Average number of patients seen each week with T2D per clinician: 11
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Level 2-5:Outcomes Metrics
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42.05%(49.36%)
25.35%(43.50%) 19.28%
(39.45%)
41.64%(49.30%)
47.73%(49.95%)
74.45%(43.62%)
38.19%(48.58%)
53.27%(49.89%)
Discuss the benefits of apathophysiologic vs algorithmic approach
to type 2 diabetes (T2D) management
Utilize effective strategies to overcomebarriers to therapeutic intensification and
clinical inertia in T2D management
Realize the limits of basal insulin therapyin clinical practice and when there is agreater need to address post-prandial
hyperglycemia
Identify patients who are most likely tobenefit from combined basal insulin-GLP-
1RA therapy as an effective means ofcombining endogenous/exogenous
insulin therapy
Learning Objectives Analysis
Learning Objective 1 Learning Objective 2 Learning Objective 3 Learning Objective 4
v Moderate to substantial gains (ranging from 14% to 194%) from low Pre-Test averages were achieved on all Learning Objectives.
• All score increases were significant except for the the 14% increase on the Learning Objective related to pathophysiologic and algorithmic approaches to T2D management.
v Post-Test averages remained especially low (<53%) on three of the four Learning Objectives; a comparatively high Post-Test score (74%) was achieved on the Learning Objective on strategies to overcome barriers to therapeutic intensification and clinical inertia in T2D management.
(N = 440–550)
Pre-Test Post-Test
+13.51% +193.65%* +98.04%* +27.95%*
*significant at the p ≤ 0.05 level
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Learning Domain Analysis(N = 477–818)
Pre-Test Post-Test
v Significant gains (ranging from 28% to 88%) were achieved in all learning domains.
v Even after substantial and significant improvements, Post-Test averages for the scored Knowledge and Competence domains remained low (both 53%).
v The substantial 88% increase in Knowledge was driven by a score increase of 194% on an item about clinician misperceptions regarding the use of injectable agents in patients with T2D.
v The 51% gain in Confidence was due to the increase in reported Confidence to identify patients for whom fixed-ratio basal insulin/GLP-1 RAs may be appropriate. Confidence levels, however, remained low.
v Learners substantially increased their reported intent to use a physiologic approach to selecting therapy for T2D, resulting in a high Post-Test practice strategy rating (4.0).
28.20%(36.75%)
41.64%(49.30%)
53.00%(40.67%)
53.27%(49.89%)
Knowledge Competence
*significant at the p ≤ 0.05 level, matched data
+87.93%* +27.95%*
2.07(1.00)
2.80(1.18)
3.12(0.92)
3.98(0.94)
Confidence Practice
+50.54%* +42.22%*
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Curriculum/Activity Intervention Effect
Learning Domain Effect Size* % Non-OverlapKnowledge 0.639 44.63%
Competence 0.234 20.85%
Effect Size Definition: This is a standardized measure of the strength/magnitude of the change in scores, irrespective of sample size. This metric quantifies the association between outcome and exposure to education, in a way which makes meta-analysis possible. There exist many types of effect size measures, each appropriate in different situations. We select Cohen’s d for this analysis, which is a standardized difference in mean. Most commonly, d ranges from 0–1: d < 0.2 is a small effect, d = 0.2–0.8 is a medium effect, and d > 0.8 is a large effect.
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Learning Domain by Professional Cohort
v Nurse practitioners (NPs) and physicians demonstrated statistically significant gains in all learning domains, with the except of Competence, in which non-significant gains were measured.
v In the scored Knowledge and Competence domains, NPs had modestly higher Post-Test scores, while physicians had higher Post-Test scores in Confidence and practice strategy.
v NPs and physicians both showed consistently low Post-Test scores (ranging from 44% to 55%) in the scored Knowledge and Competence domains.
*significant at the p ≤ 0.05 level
Learning DomainNurse Practitioner Physician
N Pre-Test Post-Test % Change N Pre-Test Post-Test % Change
Knowledge 229 29.69%(35.64%)
54.95%(38.59%) +85.05%* 19 21.93%
(34.65%)50.88%
(40.27%) +132.00%*
Competence 156 43.59%(49.59%)
50.64%(50.00%) +16.18% 18 38.89%
(48.75%)44.44%
(49.69%) +14.29%
Confidence 152 1.89(0.94)
2.99(0.92) +58.19%* 12 2.75
(0.92)3.75
(0.60) +36.36%*
Practice 142 2.76(1.21)
3.99(0.99) +44.39%* 13 3.46
(0.63)4.31
(0.61) +24.44%*
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*significant at the p ≤ 0.05 level; unmatched data
At follow-up:
v Statistically significant net gains were measured from Pre-Test to the Post Curriculum Assessment (PCA) in all areas except for Competence.
v In the Competence domain, a net-decrease of 26% was measured between the Pre-Test and PCA, highlighting learner difficulty in the ability to select treatment based on specific A1C, postprandial and fasting glucose levels.
v Low Post-Test averages were measured in the scored Knowledge and Competence domains, in addition to low reported Confidence (2.7 in the PCA).
4-Week Retention Analysis
28.20%(36.75%)
41.64%(49.30%)
53.00%(40.67%)
53.27%(49.89%)40.59%
(49.12%) 31.01%(46.30%)
0%20%40%60%80%
100%
Knowledge CompetencePre-Test Post-Test PCA
-25.53%*
2.07(1.00)
2.80(1.35)
3.12(0.92)
3.98(0.94)
2.71(1.00)
3.51(1.00)
1.00
2.00
3.00
4.00
5.00
Confidence PracticePre-Test Post-Test PCA
+43.94%* +30.80%* +25.40%
(N = 570)
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Disease state awareness Diagnostic evaluation Patient education
Screening protocols Pharmacotherapy
Please select the specific areas of skills, or practice behaviors, you have improved regarding the treatment of patients with type 2 diabetes since this CME activity. (Select all that apply)N=570
(4-week Post Assessment)
82% 74% 88%
75% 90%
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Insurance/financial issues Medication costs Formulary restrictions
Time constraints Patient adherence
What specific barriers have you encountered that may have prevented you from successfully implementing strategies for patients with type 2 diabetes since this CME activity? (Select all that apply) N=570
(4-week Post Assessment)
79%
81%77%
82%84%
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Identified Learning Gaps: Selection of antidiabetic therapy based on the mechanism of hyperglycemia and on A1C, postprandial glucose, and fasting glucose levelsDespite a 14% improvement, learners remained challenged on a Knowledge question that addressed the mechanisms of hyperglycemia that can be targeted by available antidiabetic therapies.
All of the following mechanisms of hyperglycemia in T2D can be targeted by available antidiabetic therapies, EXCEPT:
Results:• At Post-Test, 46% of learners correctly answered: “Decreased lipolysis.”
Despite a 31% improvement, learners also struggled with a Competence question which asked about appropriate changes to basal insulin therapy, given a patient’s A1C, postprandial glucose, and fasting glucose levels.
A 48-year-old obese woman, 11-year history of T2D, A1C 7.5%. SMBG log shows FBG 66-140 mg/dLand PBG 164-230 mg/dL. Antidiabetic mediations: metformin 1000 mg bid, glimepiride 2 mg qd, and insulin glargine U100 46 units qhs. She reports frustration with weight-loss efforts and sometimes skips the insulin because she’s busy and worried about weight gain and hypoglycemia. What might be appropriate at this time?
Results:
• At Post-Test, 53% of learners correctly answered: “Discontinue basal insulin and glimepiride and initiate fixed-ratio basal insulin/GLP-1 RA.”
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Identified Learning Gaps: Impact of postprandial and fasting glucose and A1C levels on hyperglycemia
Despite an 81% improvement, learners remained challenged on a Knowledge question that addressed the relationship between hyperglycemia and the levels of A1C, postprandial glucose, and fasting glucose.
At what approximate level of A1C does postprandial glucose make a larger contribution to hyperglycemia than fasting glucose?
Results:• At Post-Test, 36% of learners correctly answered: “<7.5%.”
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Overall Educational Impactv Significant improvements (ranging from 28% – 88%) were measured across all learning domains.
• The cohort analysis of professions showed that NPs demonstrated higher Post-Test scores than
physicians in Knowledge and Competence (55% and 51% for NPs vs. 51% and 44% for physicians,
respectively), while physicians demonstrated higher Post-Test averages on the Confidence and practice
strategy ratings (2.99 and 3.99 for NPs vs. 3.75 and 4.31 for physicians, respectively).
• Live onsite learners demonstrated higher Post-Test averages than online learners in all learning domains.
• Analysis of learning retention in the PCA showed that net gains from Pre-Test were measured in all
learning domains except for Competence, in which a decrease was measured.
v Significant improvements (ranging from 28% – 194%) were measured across three of the four Learning
Objectives; on the Learning Objective related to the pathophysiologic and algorithmic approaches to T2D
management, a non-significant 14% score increase was measured.
• Low Post-Test scores, ranging from 38% to 53%, were measured on three Learning Objectives; only the
Learning Objective that addressed strategies to overcome barriers to therapeutic intensification showed a
moderately high score of 74%.
v The analysis of the Knowledge and Competence domains identified two persistent learning gaps related to the selection of optimal therapy and the impact of A1C, postprandial and fasting glucose levels on hyperglycemia.
• Despite an improvement of 14%, learners remained challenged on a Knowledge question addressing the
mechanisms of hyperglycemia that can be targeted by available therapies. Learners also demonstrated a
31% improvement, but remained challenge on a Competence question about selecting therapy based on
specific A1C, postprandial glucose, and fasting glucose levels.
• Learner difficulty on the Competence question was responsible for the low PCA score and net
decrease in this domain, highlighting the need for continued education in this specific area.
• On the Knowledge question that addressed the A1C level in which postprandial glucose makes the
greater contribution to hyperglycemia, an 81% improvement was measured; however, the Post-Test score
remained especially low, with comparable proportions of learners correctly answering <7.5% and
incorrectly answering >8% (36% and 37%, respectively).
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Appendix
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Learning ObjectiveLive Onsite Learners Live Online Learners
N Pre-Test Post-Test % Change N Pre-Test Post-Test % Change
Discuss the benefits of a pathophysiologic vs algorithmic approach to type 2 diabetes (T2D) management
326 43.25%(49.54%)
47.85%(49.95%) +10.64% 114 38.60%
(48.68%)47.37%
(49.93%) +22.73%
Utilize effective strategies to overcome barriers to therapeutic intensification and clinical inertia in T2D management
379 24.54%(43.03%)
77.31%(41.88%) +215.05%* 118 27.97%
(44.88%)65.25%
(47.62%) +133.33%*
Realize the limits of basal insulin therapy in clinical practice and when there is a greater need to address post-prandial hyperglycemia
370 18.11%(38.51%)
41.62%(49.29%) +129.85%* 159 22.01%
(41.43%)30.19%
(45.91%) +37.14%
Identify patients who are most likely to benefit from combined basal insulin-GLP-1RA therapy as an effective means of combining endogenous/exogenous insulin therapy
393 42.24%(49.39%)
55.73%(49.67%) +31.93%* 157 40.13%
(49.02%)47.13%
(49.92%) +17.46%
Learning Objectives Analysis – Live Onsite vs. Live Online Audience• “Live onsite learners” include only those attending in-person meetings.
• ”Live online learners” include those from both the Simulcast and Virtual Symposium.
*significant at the p ≤ 0.05 level
v Average score increases were achieved independently by live onsite and live online learners for all Learning Objectives.
v Onsite learners demonstrated higher Post-Test averages on three of the four Learning Objectives. Comparably low Post-Test scores (47% and 48%) were measured on the Learning Objective on discussing the benefits of pathophysiologic and algorithmic approaches to T2D management.
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*significant at the p ≤ 0.05 level
• “Live onsite learners” include only those attending in-person meetings.
• ”Live online learners” include those from both the Simulcast and Virtual Symposium.
Learning Domain Analysis – Live Onsite vs. Live Online Audience
v Live onsite and live online learners independently demonstrated average score increases in all learning domains.
v Live onsite learners demonstrated greater score increases from comparable Pre-Test scores, which resulted in higher Post-Test scores in all learning domains.
Learning DomainLive Onsite Learners Live Online Learners
N Pre-Test Post-Test % Change N Pre-Test Post-Test % Change
Knowledge 604 27.95%(36.46%)
56.02%(40.22%) +100.39%* 214 28.89%
(37.54%)44.47%
(40.72%) +53.91%*
Competence 393 42.24%(49.39%)
55.73%(49.67%) +31.93%* 157 40.13%
(49.02%)47.13%
(49.92%) +17.46%
Confidence 387 2.09(1.03)
3.16(0.93) +50.74%* 101 1.99
(0.86)2.98
(0.88) +49.75%*
Practice 374 2.77(1.19)
4.03(0.93) +45.80%* 103 2.92
(1.15)3.80
(0.96) +29.90%*
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12.14%
36.53%
36.20%
15.12%
18.50%
45.14%
19.95%
12.86%
4. >8.5%
3. >8%
2. <7.5%
1. <7%
At what approximate level of A1C does postprandial glucose make a larger contribution to hyperglycemia than fasting glucose?
All of the following mechanisms of hyperglycemia in T2D can be targeted by available antidiabetic therapies, EXCEPT:
18.96%
15.8%
19.47%
45.76%
20.99%
14.23%
24.59%
40.19%
4. Increased hepatic glucose production
3. Increased glucose reabsorption
2. Decreased incretin ef fect
1. Decreased lipolysis
Knowledge Questions:
+81.49%
+13.86%
✓
✓
N = (724–906)
Pre-Test Post-TestNote: Data is unmatched
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12.62%
6.73%
9.86%
70.79%
30.41%
27.99%
17.56%
24.05%
4. Hypoglycemia is a major patient concernwith insulin use
3. Cost of injectable agents is an issue forsome patients
2. Clinicians have lit tle t ime to provideinstruction
1. The need to advance therapy is never-ending
Which of the following is a common clinician misperception regarding the use of injectable agents in patients with T2D?
Knowledge Questions, continued:
+194.41%✓
N = (786–832)
Pre-Test Post-TestNote: Data is unmatched
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53.10%
38.53%
2.98%
5.39%
40.52%
47.13%
5.36%
6.98%
4. Discont inue basal insulin andglimepiride and init iate fixed-ratio
basal insulin/GLP-1 RA
3. Discont inue basal insulin andglimepiride and init iate GLP-1 RA
and SGLT-2 inhibitor
2. Discont inue glimepiride andinitiate full basal-bolus insulin
1. Increase dose of basal insulin andadd DPP-4 inhibitor
A 48-year-old obese woman, 11-year history of T2D, A1C 7.5%. SMBG log shows FBG 66-140 mg/dL and PBG 164-230 mg/dL. Antidiabetic mediations: metformin 1000 mg bid, glimepiride 2 mg qd, and insulin glargine U100 46 units qhs. She reports frustration with weight-loss efforts and sometimes skips the insulin because she’s busy and worried about weight gain and hypoglycemia. What might be appropriate at this time?
Competence Questions
+31.03%
N = (802–872)
Note: Data is unmatchedPre-Test Post-Test
✓
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Confidence Question:Please rate your confidence in your ability to identify patients for whom fixed-ratio basal insulin/GLP-1 RAs may be appropriate:
Confidence & Practice QuestionsN = (730–746)
Practice Question:How often do you use a physiologic approach to selecting therapy for T2D?
Pre-Test Post-Test Note: Data is unmatched
6.99%
26.48%
39.25%
24.6%
2.69%
1.78%
6.99%
22.19%
35.07%
33.97%
5. Very confident
4. Pretty much confident
3. Moderately confident
2. Slightly confident
1. Not at all confident
31.5%
43.3%
18.1%
5.5%
1.61%
7.81%
21.9%
32.65%
20.87%
16.77%
5. Always
4. Often
3. Sometimes
2. Rarely
1. Never