Reducing Treatment Risk in Older Patients With Diabetes: Comparative Effectiveness of Academic Detailing With and Without Pre-Visit Patient Preparation
Phase: NA
Conditions: Type 2 Diabetes Treated With Insulin, Hypoglycemia, Primary Health Care, Polypharmacy
Sponsor: Kaiser Permanente

 
 
 
COVER PAGE 
 
Title: Reducing Treatment Risk in Older Patients With Diabetes: Comparative 
Effectiveness of Academic Detailing With and Without Pre-Visit Patient Preparation 
 
ClinicalTrials.Gov Registration: NCT04585191 
 
12/2/2024 (revised 3/6/2025) 
 
 
 
 

RETRO RCT Analytic Plan 
 
Background 
Over one-quarter of people aged 65 and older have type 2 diabetes, and this proportion is expected to 
increase rapidly in coming decades. Glycemic control in older patients must balance the short-term risks of 
treatment (e.g., hypoglycemia and its immediate consequences) with the long-term benefits of reduced 
microvascular complications (e.g., diabetic retinopathy or renal disease). Of increasing concern, 
hypoglycemia has become the leading preventable complication of treatment in this older population and 
increases the risk of cognitive decline, falls, lower health-related quality of life, hospitalization, and death. 
These severe consequences of hypoglycemia begin to change the balance between treatment benefit and 
risk as patients get older and develop increasing frailty and additional co-morbid chronic conditions. As 
patients age, they are less likely to experience the long-delayed benefits associated with tight glycemic 
control and more likely to suffer from the short-term risk of treatment-related hypoglycemia. This changing 
balance creates a critically important decisional dilemma of how best to balance long-term treatment goals 
with short-term treatment risks to optimize current health and well-being. 
 
Design and Methods 
We will conduct a comparative effectiveness randomized clinical trial involving the following two strategies 
for changing clinical management, both of which are transportable to a wide range of clinical settings and 
can be readily adopted into clinical practice: 
1. Academic detailing is a well-validated strategy for changing prescribing practices that employs focused 
and pragmatic education for practicing clinicians. Academic detailing sessions are generally brief (30-45 
minutes), integrated into the usual workday (e.g. during practice weekly meetings or lunches), and 
consist of clearly presented summaries of current evidence and guideline recommendations.  
2. Patient pre-visit preparation is a more patient-centric strategy that has shown efficacy for improving 
clinical interactions and shared decision making. In this strategy, patients are prepared for clinical 
encounters prior to visits. Information exchange is bi-directional (i.e., patients receive information 
about relevant trade-offs and provide information about preferences and other relevant information to 
facilitate collaborative decision making with their provider).  
The study has the following aims and design: 
Aim 1: To compare academic detailing alone (Arm 1) to academic detailing + patient pre-visit 
preparation (Arm 2). We will measures differences in medication de-prescribing rates among well-
controlled older patients with type 2 diabetes at high risk for medication-related hypoglycemia. [primary 
clinical outcome] 
Aim 2: To compare differences between these 2 arms in patient-reported diabetes distress, decisional 
confidence, and perceived quality of care. [primary patient-reported outcomes] 
 
Protocol Summary  
Importance: Medication-related hypoglycemia is the leading cause of iatrogenic complications among older 
adults with type 2 diabetes (T2D).  
Objective: Compare two strategies for insulin and/or sulfonylureas deprescribing in older patients with T2D 
treated in a PCP-randomized clinical trial (RCT).  
Interventions: PCPs will 1+ academic detailing (AD) sessions that provide evidence to support diabetes 
medication reassessment and potential deprescribing strategies in older patients with T2D. Prior to their 
visit with a participating PCP, trial patients will be randomly assigned to receive either a pre-visit 
deprescribing activation handout or an attention control healthy lifestyle handout. 
Main Outcomes and Measures: Primary outcomes (assessed at 6 months) are diabetes medication 
deprescribing (an aggregate measure) and any patient-reported severe hypoglycemia episodes.  

Protocol Details 
1. RCT Eligible Participants– 
a. Kaiser Permanente members aged 75+ years with Diabetes Type 2 
b. Inclusions: 
i. Hemoglobin A1c<=8% (in-control) 
ii. Current use (in prior six months) of insulin and/or sulfonylurea 
iii. Consent to participate in the study 
c. Exclusions: 
i. Deceased 
ii. End of KP Membership 
iii. Does not speak English 
iv. Medical exclusions (Type 1 diabetes, cognitively impaired, palliative care, chemo 
regime) 
 
2. Study period 
a. Patients provisionally enrolled from October 1, 2020-July 31, 2023 
i. Patients provisionally enrolled based on verbal consent 
ii. Enrollment and official consent are upon initial patient encounter with their PCP 
b. Follow-up from October 1, 2020-September 15, 2024 
c. Index Date (T0) 
i. Initial Patient Encounter with their PCP (e.g., visit, secure message) following 
receipt of packet 
d. Follow-up Period – Analyze two time points 
i. 6 months following the index date (T6) 
1. Follow-up survey may be more than six months after the initial visit, 
depending on when the RAs are able to successfully contact the patient 
for the follow-up survey 
ii. 12 months following the index date (T12) 
 
3. Study Arms 
a. Study Arm Assignment 
i. PCPs were randomized upon Academic Detailing session attendance 
ii. Patients were assigned to a study arm based on their PCP on file upon 
enrollment 
b. Arm 1 (Control): Academic Detailing + General Packet 
c. Arm 2 (Intervention): Academic Detailing + Patient Pre-Visit Preparation Packet 
 
 
 

Statistical Analysis Plan (SAP) 
 
We will construct generalized estimating equation (GEE) models to compare changes from baseline in 
clinical and patient-reported outcomes (p < 0.05) between clinical trial arms. All statistical analyses will use 
SAS 9.4 (SAS Institute Inc), and regression models were fit using PROC GENMOD. For each deprescribing, 
patient-reported and hypoglycemia-related outcome, we will construct a regression model with baseline 
measurements of the outcome included as covariates and a repeated statement to account for patient 
clustering within PCP panels. We will also examined heterogeneity of treatment effect (HTE) based on 
demographic and baseline clinical variables by calculating interaction term p-values from the models with 
and without interaction terms at 6 and 12 months for the deprescribing primary outcome.  
 
The Table lists each baseline covariate that will be used in each outcome model. 
Outcome Model 
Baseline Covariate(s) Included 
Any deprescribing (T6 and T12 models) 
On insulin at T0 – y/n and on sulf at T0 – y/n 
Self-reported severe hypoglycemia event from T6 
patient survey  
Self-reported severe hypoglycemia event from T0 
patient survey 
Hypoglycemia-related ED or IP diagnosis (T6 and 
T12 models) 
Hypoglycemia-related ED or IP diagnosis in 1 year 
prior to T0  
HbA1c lab result (T6 and T12 models) 
Latest HbA1c lab result prior to T0 >8% 
 
 

4. Outcomes 
Outcome 
Timepoints 
Summary Statistic in 
Each Arm and At 
Each Timepoint 
Effect Estimate,  
Difference in: 
Initial  
Statistical Test 
HbA1c Value 
Baseline, Follow-up 
Mean and CI 
Means 
T-test 
HbA1c <=8 
Baseline, Follow-up 
% of Arm 
Proportions 
Chi-sq 
Hypo IP 
Baseline, Follow-up 
% of Arm 
Proportions 
Chi-sq 
Hypo ED 
Baseline, Follow-up 
% of Arm 
Proportions 
Chi-sq 
ED 
Baseline, Follow-up 
% of Arm 
Proportions 
Chi-sq 
IP 
Baseline, Follow-up 
% of Arm 
Proportions 
Chi-sq 
PCP Visits 
Baseline, Follow-up 
% of Arm 
Proportions 
Chi-sq 
Survey 
Responses 
Baseline, Follow-up 
% of Arm 
Proportions 
Chi-sq 
PEPPI Scores 
Baseline, Follow-up 
Mean and CI 
Means 
T-test 
PAID5 Scores 
Baseline, Follow-up 
Mean and CI 
Means 
T-test 
RAND PSQ 
Follow-up 
% of Arm 
Proportions 
Chi-sq 
 
a. Primary Outcomes 
i. Deprescribing of either insulin or SU 
1. Discontinuation of either insulin or SU 
2. Reduction in dose of insulin or SU 
3. Switch from a higher risk to lower risk version of insulin 
ii. Timeframe for determining baseline and follow-up medication regimen 
1. Single-date regimen at T0, T6, and T12 
 
b. Secondary Outcomes 
i. Changes in HbA1c levels 
1. Baseline HbA1c: Use most recent prior to T0 in the year prior to T0; if no 
HbA1c in year prior to T0, pull forward eligibility HbA1c 
2. Follow-up T6: in this timeframe, pick the HbA1c closest to T6 
3. Follow-up T12: in this timeframe, pick the HbA1c closest to T12? 
ii. Hypoglycemic-related hospitalizations 
iii. Hypoglycemic-related ED visits 
1. Number of hypoglycemic-related ED visits between T0-T6 
 
c. Patient-reported outcomes (Change between baseline and follow-up questionnaires) 
i. Incidence of patient-reported moderate and severe hypoglycemic events 
ii. Less diabetes-related stress 
iii. Perceived quality of care

 
5. Baseline data 
a. PCP Data 
b. Patient Data 
i. Demographics: Race, Ethnicity, Age, Gender, Language 
ii. Patient Engagement: Kp.org status, Kp.org usage 
iii. Comorbidities Data lookback: 1 year before study visit date 
iv. Clinical Characteristics 
1. Medications: Diabetes Medication Regime (Insulin, Sulfonylurea), 
Medication Count (All Medications) 
2. Labs: HbA1c 
a. Data lookback: 1 year before study visit date 
b. HbA1c Selection: most recent one prior to T0 
3. Hypoglycemic-related hospitalizations 
4. Hypoglycemic-related ED Visits 
v. Membership/Insurance 
vi. Baseline Survey Responses 
 
6. Lost to Follow-up 
a. Reasons 
i. Loss of membership during study period 
ii. Death 
iii. PCP Switches 
 
7. Analyses 
a. Comparison of baseline characteristics between intervention and control 
b. Comparison of consented vs declined 
i. Characteristics as of Eligibility Date: 
1. Demographics: gender, age, race, ethnicity, language 
2. Study eligibility data: HbA1c, INS/SU Y/N 
c. Flow through the study 
i. Time from provisional enrollment to actual enrollment 
ii. Reasons for drop out and missing data 
d. Comparison of outcomes between intervention and control 
i. Analysis of subsets of patients based on specific characteristics 
 
8. Final Analytic Tables 
a. Enrolled vs Declined 
b. Table 1-Intervention vs Control 
c. PCP Table 
d. Outcomes table 
 
9. Sensitivity Analysis 
a. Sensitivity analyses to assess the impact of missing data 
b. Sensitivity analyses based on modality of visit (virtual vs. in-person) 
c. Strata of people who had prior hypoglycemic events