Reinforcement Learning for Aging
(REINFORCE-EHR Trial)
Trial Summary
What is the purpose of this trial?
The overall goal of the proposed research is to refine and adapt and perform efficacy testing of a novel reinforcement learning-based approach to personalizing EHR-based tools for PCPs on deprescribing of high-risk medications for older adults. The trial will be conducted at Atrius Health, an integrated delivery network in Massachusetts, and will intervene upon primary care providers. The investigators will conduct a cluster randomized trial using reinforcement learning to adapt electronic health record (EHR) tools for deprescribing high-risk medications versus usual care. 60 PCPs will be randomized (i.e., 30 each to the reinforcement learning intervention and usual care \[no EHR tool\] in each arm) to the trial and follow them for approximately 30 weeks. The primary outcome will be discontinuation or ordering a dose taper for the high-risk medications for eligible patients by included primary care providers, using EHR data at Atrius. The primary hypothesis is that the personalized intervention using reinforcement learning will improve deprescribing compared with usual care.
Will I have to stop taking my current medications?
The trial does not specify if participants must stop taking their current medications. However, it focuses on helping doctors reduce or stop high-risk medications for older adults, so your doctor might discuss changes to your medication.
What data supports the effectiveness of the treatment Reinforcement Learning for aging?
Is Reinforcement Learning for Aging safe for humans?
How does the treatment Reinforcement Learning for Aging differ from other treatments for aging?
Reinforcement Learning for Aging is unique because it uses a learning-based approach to adapt behaviors based on rewards, which may help older adults improve their ability to adjust to new situations despite age-related declines in explicit knowledge and attention. Unlike traditional treatments that might focus on medication or physical interventions, this approach leverages cognitive processes to enhance adaptation and decision-making.1112131415
Eligibility Criteria
This trial is for primary care providers (PCPs) at Atrius Health in Massachusetts. It's focused on helping them to safely reduce or stop prescribing high-risk medications for older adults. The PCPs will be part of a study that uses a new method within their electronic health records.Inclusion Criteria
Exclusion Criteria
Timeline
Screening
Participants are screened for eligibility to participate in the trial
Treatment
Primary care providers are randomized to either a reinforcement learning intervention or usual care for deprescribing high-risk medications
Follow-up
Participants are monitored for safety and effectiveness after treatment
Treatment Details
Interventions
- Reinforcement Learning
Find a Clinic Near You
Who Is Running the Clinical Trial?
Brigham and Women's Hospital
Lead Sponsor
National Institute on Aging (NIA)
Collaborator
Atrius Health
Collaborator