Reinforcement Learning for Aging
(REINFORCE-EHR Trial)
What You Need to Know Before You Apply
What is the purpose of this trial?
This trial aims to test a smart computer program designed to help doctors stop or reduce risky medications for older adults. The program uses reinforcement learning, a type of artificial intelligence, to select the best tools for doctors based on their past actions. Researchers will compare the program against regular care without these tools to determine which is more effective. Patients aged 65 or older who have frequently been prescribed high-risk medications in the last six months are a good fit for this trial. As an unphased trial, this study offers an opportunity to contribute to innovative research that could enhance medication safety for older adults.
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 prior data suggests that this reinforcement learning approach is safe for primary care providers?
Research has shown that using reinforcement learning in healthcare is generally safe for people. This method involves computer programs that assist doctors in making better decisions, such as when to stop or reduce high-risk medications for older adults. It has not shown any direct harm to patients because it focuses on enhancing doctors' actions rather than altering medications directly.
Studies have found that these tools can identify high-risk patients early and assist doctors in making safer medication choices. While researchers continue to study the use of reinforcement learning in medicine, no evidence suggests it causes negative effects on patients. Instead, it aims to improve how doctors prescribe or stop medications, leading to safer outcomes for patients.12345Why are researchers excited about this trial?
Researchers are excited about the use of reinforcement learning in healthcare because it offers a personalized approach to medication management for aging patients. Unlike traditional methods that rely on fixed protocols, this reinforcement learning program adapts to each primary care provider by selecting electronic health record (EHR) tools tailored to encourage deprescribing of risky medications. The program's unique algorithm learns and improves its recommendations over time, aiming to optimize patient outcomes by promoting safer prescribing habits. This dynamic and personalized strategy could lead to more effective and safer medication use in older adults.
What evidence suggests that this reinforcement learning intervention is effective for deprescribing high-risk medications?
Research has shown that reinforcement learning can aid in deprescribing, which involves reducing or stopping medications that might be unhelpful or harmful. A review of studies found that deprescribing reduces unnecessary medications for older adults. In this trial, one group of participants will receive a reinforcement learning intervention that personalizes electronic health records (EHR) tools for primary care providers (PCPs) to promote deprescribing high-risk medications. This method uses adaptive computer programs to encourage doctors to make better medication choices for their patients over time. Another group will receive usual care, without additional EHR-based tools beyond those used in regular clinical practice. Studies have also shown that educational tools in healthcare improve medication management, enhancing patient safety.678910
Are You a Good Fit for This Trial?
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 for a Trial Participant
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
What Are the Treatments Tested in This Trial?
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