Development and Feasibility Testing of DM-BOOST Intervention. (DM-BOOST)

Development and Feasibility Testing of a Diabetes Mellitus Program Using Behavioral Economics to Optimize Outreach and Self-management Support With Technology.

DM-BOOST uses clinical informatics tools to identify types of patients with gaps in diabetes care and deploy tailored, proactive outreach methods rooted in behavioral economics to nudge them towards increased engagement with diabetes self-management training and leverage patient-facing technologies to enhance longitudinal patient self-management support.

Study Overview

• Status: Completed
• Conditions: Diabetes Mellitus, Type 2
• Intervention / Treatment: Behavioral: Diabetes BOOST; Behavioral: Usual Care

Detailed Description

In DM-BOOST, the Principal investigator will deploy a mixed-methods, patient-centered approach to intervention development and initiate a multiphase optimization strategy (MOST) to learn how to maximize patient engagement and support of self-management training. In this pilot, study team will complete the first phase (Preparation), and initiate feasibility piloting of the second phase (Optimization). Completion of optimization and MOST's final phase (Evaluation), will occur in a subsequent project.

In the preparation phase, Principal investigator will first analyze EHR and claims data in the UMCCTS data lake to identify sociodemographic characteristics associated with gaps in diabetes care to develop patient persona archetypes (Aim 1). Next, Principal investigator will selectively recruit patients of identified persona types as consultants, elicit stakeholder feedback during community engagement studios and conduct usability testing to iteratively design the intervention (Aim 2). Study team will then conduct a feasibility pilot (Aim 3) to assess user experience of the intervention implementation and collect exploratory outcome data to be used to inform a subsequent, complete optimization trial.

• Study Type: Interventional
• Enrollment (Actual): 66
• Phase: Not Applicable

Contacts and Locations

Study Locations

• United States
  • Massachusetts
    • Worcester, Massachusetts, United States, 01655
      • University of Massachusetts Medical School

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: Yes

Description

Inclusion Criteria:

• Adults (age 18+)
• Cognitively able to consent (Aims 2 and 3)
• Diagnosed with type 2 diabetes (Aims 1-3)
• Receive primary care at UMMHC in past 12 months at time of initial analysis (Aims 1-3)
• English speaking (Aims 2 and 3)
• Have access to patient portal or a smart phone (Aim 3)

Exclusion Criteria:

• Adults unable to consent (lacking cognitive capacity) (Aims 2 and 3)
• Individuals who are not yet adults (infants, children, teenagers) (Aims 1-3)
• Pregnant women (Aims 1-3)
• Prisoners (Aims 1-3)
• Non-English speaking (Aims 2 and 3)

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Supportive Care
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: Double

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Active Comparator: Usual Care; Comparison Group participants will complete a baseline survey, receive a DSMT referral request from research team to their primary care provider and a mailed welcome letter. The mailed letter will welcome the participant to the study and contain general information about diabetes self-care behaviors and goal setting. They will complete a DSMT session. They will then complete a 3-month follow-up survey and qualitative interview.	Behavioral: Usual Care; Participants will receive usual care for DSMT.
Experimental: Intervention - Diabetes BOOST; Intervention group participants will complete a baseline survey, receive a referral to DSMT from the research team, a mailed welcome letter and self-care education sent via a series of personalized patient portal secure messages, text messages, and video call. They will be sent text messages with information about one of the American Association of Diabetes Educators 7 self-care behaviors and will receive encouragement to author their own self-management behavioral goals. Participants will also complete a telehealth training video call with research staff and review the goals that the participant replied with. The participant will then be encouraged to send a patient portal message to their DSMT CDCES that includes their personalized goals prior to their scheduled DSMT session. They will then complete a 3-month follow-up survey and qualitative interview.	Behavioral: Diabetes BOOST; Participants will receive supportive care using technology for DSMT in addition to usual care.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Intervention Acceptability (Aim 2)	Patient-reported assessment of intervention acceptability via usability testing. Qualitative data collection informed by the Technology Acceptance Model with assessment of perceived usefulness, ease of use, behavioral intention to use and external factors. No quantitative data measured.	1 month
Completion of diabetes self-management training (Aim 3)	Completion of diabetes self-management training.	9 months

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Clinical utilization (Aim 3)	Rate of clinical utilization as measured by number of visits per participant to primary, specialty care, and emergency/hospital care visits measured 6-months after follow-up visit.	9 months
Diabetes self-efficacy (Aim 3)	Diabetes self efficacy will be measured at baseline and 3 months after enrolling in the study using the Diabetes Management Self-Efficacy Scale. Participants will provide feedback on set of questions, using a 5-point Likert scale( with 1=Strong Disagree, 2=Somewhat Disagree, 3= Neutral, 4=Somewhat Agree, 5= Strongly Agree)	3 months
Diabetes treatment satisfaction (Aim 3)	Diabetes Treatment Satisfaction will be measured at 3 months after enrolling in the study using the Diabetes Treatment Satisfaction Questionnaire Change tool. Participants will be asked to share how their experience of current treatment has changed from their experience of treatment before the study began. They will answer each question by choosing 3 for Much More Satisfied Now up to -3 for Much Less Satisfied Now. (3,2,1,0,-1,-2,-3)	3 months
Diabetes self-management skills (Aim 3)	Self-management skills will be measured at 3 months after enrolling in the study. Participant will be asked questions about their diabetes self-care activities during the past seven days using the Summary of Diabetes Self-Care Activities Measure	3 months
Patient engagement with Diabetes Self-Management Training (Aim 3)	Engagement data will be collected by research staff. It will be measured by the numbers of patients who request contact, are reached, enrolled in the study and scheduled DSMT appointment.	9 months
Hemoglobin A1C (HbA1C) (Aim 3)	Measurement of HbA1c values to determine impact of intervention. HbA1c values at baseline visit will be compared with values at 3-6 months after participant's enrollment. These data will be obtained through EHR chart review.	6 months

Other Outcome Measures

Outcome Measure	Measure Description	Time Frame
Predictors of guideline-concordant diabetes care (sociodemographic predictors) (Aim 1)	Retrospective analysis of EHR data to identify clusters of sociodemographic predictors of guideline-concordant of diabetes care will be identified. Retrospective data will be requested from UMMS Data Lake through the Data Science Core. Data requested for adult patients with T2D since Epic EHR roll-out in October 2017 will include: • Sociodemographic characteristics (gender, date of birth, race/ethnicity, zip code, language, marital status, insurance type)	Assessed at baseline
Predictors of guideline-concordant diabetes care (HbA1c level) (Aim 1)	Retrospective analysis of EHR data to identify clusters of clinical predictors of guideline-concordant of diabetes care will be identified. Retrospective data will be requested from UMMS Data Lake through the Data Science Core. Data requested for adult patients with T2D since Epic EHR roll-out in October 2017 will include: • Clinical characteristics as measured by the level of HbA1c	Assessed at baseline
Predictors of guideline-concordant diabetes care (BMI) (Aim 1)	Retrospective analysis of EHR data to identify clusters of clinical predictors of guideline-concordant of diabetes care will be identified. Retrospective data will be requested from UMMS Data Lake through the Data Science Core. Data requested for adult patients with T2D since Epic EHR roll-out in October 2017 will include: • Clinical characteristics as measured by the level of BMI. Weight and height will be combined to report BMI in kg/m^2	Assessed at baseline
Predictors of guideline-concordant diabetes care (Smoking Status) (Aim 1)	Retrospective analysis of EHR data to identify clusters of clinical predictors of guideline-concordant of diabetes care will be identified. Retrospective data will be requested from UMMS Data Lake through the Data Science Core. Data requested for adult patients with T2D since Epic EHR roll-out in October 2017 will include: • Clinical characteristics as measured by the smoking status	Assessed at baseline
Predictors of guideline-concordant diabetes care (Cholesterol level) (Aim 1)	Retrospective analysis of EHR data to identify clusters of clinical predictors of guideline-concordant of diabetes care will be identified. Retrospective data will be requested from UMMS Data Lake through the Data Science Core. Data requested for adult patients with T2D since Epic EHR roll-out in October 2017 will include: • Clinical characteristics as measured by the the level of cholesterol	Assessed at baseline
Predictors of guideline-concordant diabetes care (Clinical utilization) (Aim 1)	Retrospective analysis of EHR data to identify clusters of clinical predictors of guideline-concordant of diabetes care will be identified. Retrospective data will be requested from UMMS Data Lake through the Data Science Core. Data requested for adult patients with T2D will include: • Clinical utilization as measured by number of visits per participant to primary care, specialty visits, emergency room, hospitalizations, education/training, patient portal use, care management engagement since Epic EHR roll-out in October 2017	Assessed at baseline

Collaborators and Investigators

• Sponsor: Daniel Amante
• Collaborators: Worcester Polytechnic Institute
• Investigators: Principal Investigator: Daniel J Amante, PhD, MPH, UMass Medical School

Study record dates

Study Major Dates

• Study Start (Actual): January 13, 2021
• Primary Completion (Actual): November 1, 2022
• Study Completion (Actual): January 1, 2024

Study Registration Dates

• First Submitted: December 29, 2020
• First Submitted That Met QC Criteria: January 12, 2021
• First Posted (Actual): January 15, 2021

Study Record Updates

• Last Update Posted (Actual): February 22, 2024
• Last Update Submitted That Met QC Criteria: February 20, 2024
• Last Verified: February 1, 2024

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Glucose Metabolism Disorders; Metabolic Diseases; Endocrine System Diseases; Diabetes Mellitus; Diabetes Mellitus, Type 2
• Other Study ID Numbers: H00017902

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No