Reinforcement Learning in Diabetes Mellitus Trial (REINFORCE)

Mass General Brigham

Status: Completed

Conditions: Medication Adherence; Diabetes Mellitus, Type 2

Treatments: Behavioral: Reinforcement Learning

Study type: Interventional

Funder types: Other; NIH

Identifiers

NCT04473326

P30AG064199-01 (U.S. NIH Grant/Contract)

2020P000846

Details and patient eligibility

About

Reinforcement learning is an advanced analytic method that discovers each individual's pattern of responsiveness by observing their actions and then implements a personalized strategy to optimize individuals' behaviors using trial and error. The goal of this pilot study is to develop and test a novel reinforcement learning-enhanced text messaging program to support medication adherence in patients with type 2 diabetes. Type 2 diabetes is an optimal condition in which to test this program, as it is one of the most prevalent chronic conditions in the US adult population and requires most patients to be on daily or twice daily doses of medications. This pilot study will be a parallel randomized pragmatic trial comparing medication adherence and clinical outcomes for adults aged 18-84 with type 2 diabetes who are prescribed 1-3 daily oral medications for this disease. Participants will be randomized to one of two arms for the duration of the study period: (1) a reinforcement learning intervention arm with up to daily, tailored text messages based on time-varying treatment-response patterns; or (2) a control arm with up to daily, un-tailored text messages. Our outcomes of interest will be medication adherence, as measured by electronic pill bottles, and HbA1c levels.

Full description

The goal of this pilot study is to develop and test a novel reinforcement learning-enhanced text messaging program to support medication adherence in patients with type 2 diabetes. This pilot study will be a parallel randomized pragmatic trial comparing medication adherence and clinical outcomes for adults aged 18-84 with type 2 diabetes who are prescribed 1-3 daily oral medications for this disease. Participants will be randomized to one of two arms for the duration of the study period: 1) a reinforcement learning intervention arm with up to daily, tailored text messages based on time-varying treatment response patterns, or 2) a control arm with up to daily, untailored text messages. Our outcomes of interest will be medication adherence, as measured by electronic pill bottles, and HbA1c levels.

Enrollment: 60 patients

Sex: All

Ages: 18 to 84 years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• Age between 18-84 years
• Diagnosed with type 2 diabetes mellitus (T2DM) and are prescribed between 1-3 daily oral medications for this disease
• Currently have a smartphone with a data plan or WiFi at home
• HbA1c level ≥7.5%
• Basic working knowledge of English
• Willing and able to set up the platform and adhere to study procedures
• Either not currently using a pillbox or willing to use electronic pill bottles (EDMs) for diabetes medications for the duration of the study

Exclusion criteria

• Patients with active enrollment in another diabetes trial within Mass General Brigham
• Patients who receive daily assistance with taking their medications at home
• Patients who are unable to receive text messages for more than 3 days in a row during the study period

Trial design

Primary purpose: Health Services Research

Allocation: Randomized

Interventional model: Parallel Assignment

Masking: Double Blind

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60 participants in 2 patient groups

Reinforcement Learning Intervention Arm

Experimental group

Description:

Up to daily, tailored text messages.

Treatment:

Behavioral: Reinforcement Learning

Control Arm

No Intervention group

Description:

Up to daily, untailored text messages.