Optimizing Electronic Health Record Prompts With Behavioral Economics to Improve Prescribing for Older Adults
NUDGE-EHR
1 other identifier
interventional
216
1 country
1
Brief Summary
Prescribing of potentially unsafe medications for older adults is extremely common; benzodiazepines and sedative hypnotics are, for example, key drug classes frequently implicated in adverse health consequences for vulnerable older adults, such as confusion or sedation, leading to hospitalizations, falls, and fractures. Fortunately, most of these consequences are preventable. Physicians' lack of awareness of alternatives, ambiguous practice guidelines, and perceived pressure from patients or caregivers are among the reasons why these drugs are used more than might be optimal. Reducing inappropriate use of these drugs may be achieved through decision support tools for providers that are embedded in electronic health record (EHR) systems. While EHR strategies are widely used to support the informational needs of providers, these tools have demonstrated only modest effectiveness at improving prescribing. The effectiveness of these tools could be enhanced by leveraging principles of behavioral economics and related sciences.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for not_applicable
Started Oct 2020
Typical duration for not_applicable
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
February 23, 2020
CompletedFirst Posted
Study publicly available on registry
February 26, 2020
CompletedStudy Start
First participant enrolled
October 13, 2020
CompletedPrimary Completion
Last participant's last visit for primary outcome
August 1, 2022
CompletedStudy Completion
Last participant's last visit for all outcomes
August 31, 2022
CompletedResults Posted
Study results publicly available
October 26, 2023
CompletedNovember 7, 2024
October 1, 2024
1.8 years
February 23, 2020
July 6, 2023
October 16, 2024
Conditions
Keywords
Outcome Measures
Primary Outcomes (2)
Change in Inappropriate Prescribing by Study Arm: Descriptive Comparison Across Study Arms
This outcome is measured as a composite of 1) discontinuation of study high-risk medications (i.e., active discontinuation or lack of an order during follow-up) or 2) ordering a dose taper (for benzodiazepine or sedative hypnotics) using EHR data by the primary care provider included in the study arm. If any of these actions occurred by the primary care provider, then the patient was considered to have had a change in prescribing (i.e., a reduction in inappropriate prescribing). This outcome was measured as a binary outcome. As noted in the Outcome Measure Time Frame below, these outcomes were measured and presented across both stages of the adaptive trial at Atrius Health rather than separately, as this was part of the pre-specified analytic plan.
22 months (2 stages)
Change in Inappropriate Prescribing by the Seven Behavioral Intervention Factors (Open Encounter Timing, Boostering, Cold-state Priming, Simplification, Sign-off Approval, Pre-commitment, and Risk Framing): Primary Analysis Approach
This outcome is measured as a binary composite of 1) discontinuation of study high-risk medications (i.e., active discontinuation or lack of an order during follow-up) or 2) ordering a dose taper using EHR data by the primary care provider in the arm. If the provider performed any of these actions, then the patient was considered as having a change in prescribing (i.e., a reduction in inappropriate prescribing). As noted in the Time Frame below, these outcomes were measured and analyzed across both Stages of the trial in the primary analysis. The following outcomes are shown stratified by patients who were in arms containing one of the seven behavioral intervention factors and also among those in arms that did not contain an intervention factor. The primary analysis conducts analyses by intervention factor; the model treats patients in arms that do not contain any of the behavioral factors (i.e., Base Order Entry Alert, Standard Epic Basic Alert, and Usual Care) as the referent.
22 months (2 stages)
Secondary Outcomes (2)
Quantity of Prescribing by Study Arm: Descriptive Comparison Across Study Arms
22 months (2 stages)
Quantity of Prescribing by the Seven Behavioral Intervention Factors (Open Encounter Timing, Boostering, Cold-state Priming, Simplification, Sign-off Approval, Pre-commitment, and Risk Framing): Primary Analysis Approach
22 months (2 stages)
Study Arms (16)
Base Order Entry Alert
EXPERIMENTALBase Open Encounter Alert
EXPERIMENTALOrder Entry + Follow-up booster Alert
EXPERIMENTALOpen Encounter + Follow-up booster Alert
EXPERIMENTALOrder Entry + Cold State outreach
EXPERIMENTALOpen Encounter + Cold State outreach
EXPERIMENTALOrder Entry + Simplified
EXPERIMENTALOpen Encounter + Simplified
EXPERIMENTALOrder Entry + Sign-off alert
EXPERIMENTALOpen Encounter + Sign-off alert
EXPERIMENTALOrder Entry + Pre-commitment
EXPERIMENTALOpen Encounter + Pre-commitment
EXPERIMENTALOrder Entry + Different Risks
EXPERIMENTALOpen Encounter + Different Risks
EXPERIMENTALStandard Epic Basic Alert
EXPERIMENTALNo Alert (Usual Care)
NO INTERVENTIONInterventions
An alert will display in the electronic health record when the provider orders one of the high-risk medications for an eligible patient.
An alert will display in the electronic health record when the provider opens the chart of an eligible patient.
Once the order entry or open encounter alert displays, the provider will have the option to schedule a follow-up message that will be sent 4 weeks after the alert is triggered
An in-basket message will be sent to the eligible provider 2 days before the eligible patient is scheduled for an in-person visit.
The alert language itself will be simplified.
An alert will display in the electronic health record when the medication is sent to sign-off for providers.
A two-staged pre-commitment electronic health record alert will be used. In the 1st alert, the providers will be prompted to discuss risks of these high-risk medications and share a handout about the risks with their patients, at their own discretion. The second alert will be either an order entry or open encounter alert, depending on the arm the provider is assigned to.
Risks of the high-risk medications will be framed differently.
This alert will be representative of the alerts currently firing in the Atrius system and not incorporate any functionality.
An enhanced alert (known as a Best Practice Advisory \[BPA\]) will appear on the provider's electronic health record screen and will contain several standard components such as information about why the medication is dangerous for their patient and an order set that will allow providers to order a gradual dose taper for their patient, order alternative medications, place a referral to a behavioral health specialist, provide instructions on how to make lifestyle modifications to improve patient symptoms, and add patient instructions for how to gradually taper off benzodiazepines and sedative hypnotics, as applicable.
Eligibility Criteria
You may qualify if:
- Primary care provider at Atrius Health
- Providers will receive these EHR tools for their patients who meet the following criteria:
- older adults (aged 65 years or more)
- who have been prescribed at least 90 pills of benzodiazepine or sedative hypnotic in the last 180 days.
Contact the study team to confirm eligibility.
Sponsors & Collaborators
- Brigham and Women's Hospitallead
- Atrius Healthcollaborator
- National Institutes of Health (NIH)collaborator
Study Sites (1)
Atrius Health
Braintree, Massachusetts, 02184, United States
Related Publications (2)
Lauffenburger JC, Isaac T, Trippa L, Glynn RJ, Russo M, Keller P, Robertson T, Kim DH, Bhatkhande G, Hanken KE, Haff N, Jungo KT, Crum KL, Blair MS, Brill G, Choudhry NK. Comparing Fourteen Behavioral Science Electronic Health Record Deprescribing Tools in Older Adults: NUDGE-EHR Adaptive Trial. J Am Geriatr Soc. 2025 Oct;73(10):3031-3043. doi: 10.1111/jgs.19609. Epub 2025 Jul 4.
PMID: 40614073DERIVEDLauffenburger JC, Isaac T, Trippa L, Keller P, Robertson T, Glynn RJ, Sequist TD, Kim DH, Fontanet CP, Castonguay EWB, Haff N, Barlev RA, Mahesri M, Gopalakrishnan C, Choudhry NK. Rationale and design of the Novel Uses of adaptive Designs to Guide provider Engagement in Electronic Health Records (NUDGE-EHR) pragmatic adaptive randomized trial: a trial protocol. Implement Sci. 2021 Jan 7;16(1):9. doi: 10.1186/s13012-020-01078-9.
PMID: 33413494DERIVED
MeSH Terms
Conditions
Interventions
Condition Hierarchy (Ancestors)
Intervention Hierarchy (Ancestors)
Results Point of Contact
- Title
- Niteesh Choudhry, MD, PhD
- Organization
- Brigham and Women's Hospital
Publication Agreements
- PI is Sponsor Employee
- Yes
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- RANDOMIZED
- Masking
- NONE
- Purpose
- HEALTH SERVICES RESEARCH
- Intervention Model
- PARALLEL
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Niteesh K. Choudhry, MD, PhD, Professor, Harvard Medical School
Study Record Dates
First Submitted
February 23, 2020
First Posted
February 26, 2020
Study Start
October 13, 2020
Primary Completion
August 1, 2022
Study Completion
August 31, 2022
Last Updated
November 7, 2024
Results First Posted
October 26, 2023
Record last verified: 2024-10