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Successfully Achieving and Maintaining Euglycemia During Pregnancy for Type 2 Diabetes Through Technology and Coaching

The Ohio State University logo

The Ohio State University

Status

Enrolling

Conditions

Type2diabetes
Pregnancy in Diabetic
Pregnancy, High Risk
Pre-Gestational Diabetes

Treatments

Device: DEXCOM G7 PRO Continuous Glucose Monitor
Device: Patient mHealth app linked to a provider dashboard
Behavioral: Care team coaching for medical and social needs (HUB)
Device: Provider dashboard

Study type

Interventional

Funder types

Other
Industry
Other U.S. Federal agency

Identifiers

NCT05662462
2022H0399

Details and patient eligibility

About

The ACHIEVE RCT will measure the effect of the intervention (mHealth app with CGM, provider dashboard, and care team coaching) compared to current standard care (prenatal visits, self-monitored blood glucose, and certified diabetes care and education specialist) on achieving glycemic control (hemoglobin A1c <6.5% in the third trimester). We hypothesize a 25% absolute increase in the proportion of participants in the intervention group who will meet the target hemoglobin A1c <6.5% in the third trimester compared to the standard care group

Full description

Type 2 diabetes (T2D) in pregnancy increases the risk of adverse outcomes for both the mother and infant. Over 1 in 3 infants born to individuals with T2D will experience an adverse outcome, including large for gestational age at birth, preterm birth, birth trauma, neonatal hypoglycemia, and stillbirth. Strict maternal glycemic control throughout pregnancy is key to optimizing perinatal outcomes. This is possible with insulin pharmacotherapy, vigilant glucose monitoring, lifestyle modifications including diet and exercise, and team-based prenatal care. Medicaid-enrolled pregnant individuals with T2D experience non-medical social needs that limit their ability to achieve glycemic control, including lack of reliable transportation to attend prenatal visits, access to resources to engage in diet and exercise changes, and convenient methods to log self-monitored glucose values and adjust insulin dosing.

A multi-faceted provider-patient based approach is needed with proven strategies to improve glycemic control. We propose "ACHIEVE: Successfully achieving and maintaining euglycemia during pregnancy for type 2 diabetes through technology and coaching." Our intervention is multi-component, including a mobile health (mHealth) application (app), provider dashboard, DEXCOM continuous glucose monitoring (CGM), and care team coaching for medical and social needs. This intervention empowers Medicaid-enrolled pregnant individuals with T2D and their healthcare providers to achieve and maintain glycemic control, improve access to care, and provide patient education and support. Each sub-component of the proposed intervention is grounded in Social Cognitive Theory (SCT), and emphasizes on individuals' skills, knowledge and beliefs, and self-efficacy to achieve glycemic control.

We propose three aims: AIM 1: Develop the tailored ACHIEVE mHealth app and provider dashboard for Medicaid-enrolled pregnant individuals with T2D and their healthcare team through active stakeholder engagement; AIM 2: Conduct an RCT and measure the effect of the intervention (mHealth app with CGM, provider dashboard, and care team coaching) compared to current standard care (prenatal visits, self-monitored blood glucose, and certified diabetes care and education specialist) on achieving glycemic control (hemoglobin A1c <6.5% in the third trimester). We hypothesize a 25% absolute increase in the proportion of participants in the intervention group who will meet the target hemoglobin A1c <6.5% in the third trimester compared to the standard care group; and AIM 3: Identify multi-level patient and provider barriers and facilitators to satisfaction, engagement, and use of the intervention and its subcomponents.

Enrollment

124 estimated patients

Sex

Female

Ages

18+ years old

Volunteers

No Healthy Volunteers

Inclusion and exclusion criteria

Inclusion Criteria:

  1. pregnant individuals age ≥18 years;
  2. ≤20 weeks of gestation;
  3. diagnosis of pregestational T2D and A1c ≥6.5% at the time of study enrollment;
  4. Medicaid insurance;
  5. English or Spanish speaking;
  6. cognitively able to complete the study requirements;
  7. consent to all study activities;
  8. accessible for participation in study activities;
  9. use a smartphone with internet access;
  10. not currently using a CGM device.

Participants must also consent to the study team abstracting information from their electronic health records (EHRs), using CGM for glucose monitoring if randomized to the intervention group, tracking the participants' clinic, hospital, and emergency room visits during the study period, as well as tracking the number of times the participants use the ACHIEVE mobile health (mHealth) application (app), including what activities are used in the mobile application (e.g., recording blood glucose, scheduling appointments, messaging their healthcare providers, accessing educational resources).

Trial design

Primary purpose

Treatment

Allocation

Randomized

Interventional model

Parallel Assignment

Masking

Single Blind

124 participants in 2 patient groups

ACHIEVE Intervention
Active Comparator group
Description:
The intervention includes a multi-component, including a mobile health (mHealth) application (app), provider dashboard, DEXCOM continuous glucose monitoring (CGM), and care team coaching for medical and social needs. The intervention group will also receive standard of care as described below.
Treatment:
Device: Provider dashboard
Behavioral: Care team coaching for medical and social needs (HUB)
Device: Patient mHealth app linked to a provider dashboard
Device: DEXCOM G7 PRO Continuous Glucose Monitor
Standard of care
No Intervention group
Description:
Standard of care includes prenatal visits, self-monitored blood glucose, and certified diabetes care and education specialist support.

Trial contacts and locations

1

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Central trial contact

Kartik Venkatesh, MD, PhD

Data sourced from clinicaltrials.gov

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