Aging
Conditions
Keywords
Medication optimization, High-risk medications
Brief summary
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. 70 PCPs will be randomized (i.e., 35 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.
Interventions
BEHAVIORALReinforcement learning
The intervention is a reinforcement learning program that personalizes EHR-based tools for PCPs to promote deprescribing high-risk medications over follow-up. The reinforcement learning intervention selects a tool for each provider based on an algorithm from an inventory of EHR tools and chooses tools that are predicted to motivate action for the individual provider. The inventory of EHR tools from which the algorithm will choose include the following potential factors: open encounter, order entry, cold-state outreach, simplification, and risk framing.
Sponsors
Brigham and Women's Hospital
National Institute on Aging (NIA)
Atrius Health
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
HEALTH_SERVICES_RESEARCH
Masking
DOUBLE (Investigator, Outcomes Assessor)
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
The trial will intervene upon primary care providers (including physicians and PCP-designated nurse practitioners and physician assistants) at Atrius Health. Patients of the PCPs will be included in the intervention and analysis if they are \>/=65 years of age and have been prescribed \>/= 90 pills of high-risk medications in the prior 180 days based on EHR data.
Exclusion criteria
• Not a primary care provider at Atrius Health
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Discontinuation or taper for high-risk medication | Through trial completion, up to 7 months | Deprescribing will be assessed using routinely collected data from the EHR system for eligible patients flagged as in need of deprescribing. The deprescribing outcome will be a "reduction" in inappropriate prescribing, defined as either discontinuation of one the the medication classes of interest or ordering a dose taper. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Discontinuation of high-risk medication | Through trial completion, up to 7 months | Discontinuation of medication assessed using routinely-collected data from the EHR system for eligible patients flagged as in need of deprescribing. |
Countries
United States
Outcome results
None listed