EHR Nudges for Overmedication

(HRPP Trial)

Recruiting at 1 trial location

Overseen By Stephen D Persell, MD, MPH

Age: 18+

Sex: Any

Trial Phase: Academic

Sponsor: Northwestern University

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Compensation: Varies

Number of Visits: Unknown

786 Participants Needed

Trial Summary

Will I have to stop taking my current medications?

The trial information does not specify whether you need to stop taking your current medications. It focuses on helping doctors reduce high-risk medication use, so it's best to discuss your specific situation with the trial team.

What data supports the effectiveness of this treatment?

Research shows that using nudges in electronic health records can help guide doctors to make better decisions, like reducing unnecessary tests or medications. These nudges can improve how doctors follow treatment guidelines, potentially leading to better patient outcomes. ^{1 2 3 4 5}

Is the EHR nudge system safe for humans?

The research on EHR nudge systems, which are designed to help doctors make better decisions, does not report any safety concerns for humans. These systems aim to improve healthcare practices by gently guiding clinicians towards better choices without adding much mental strain. ^{1 2 4 6 7}

How does the EHR nudge treatment for overmedication differ from other treatments?

The EHR nudge treatment is unique because it uses behavioral economics principles integrated into electronic health records to subtly guide doctors towards better prescribing practices, reducing overmedication without adding extra mental workload. This approach is novel compared to traditional methods, as it focuses on changing clinician behavior through decision support systems rather than directly altering patient medication regimens. ^{1 2 4 6 8}

What is the purpose of this trial?

High-risk polypharmacy is common among older adults in the United States, is particularly dangerous for individuals with dementia or cognitive impairment, and is associated with harms such as adverse drug reactions, falls, and higher costs of care. This project aims to test in a pragmatic clinic-randomized controlled trial two electronic health record-based behavioral economic nudges to help clinicians reduce high-risk polypharmacy among their older adult patients and in the subgroup with dementia or cognitive impairment. The main questions this trial aims to answer are: Aim 1: To evaluate the effects of an EHR-based commitment nudge, a justification nudge, and the combination of both nudges on a composite measure of high-risk polypharmacy via a pragmatic randomized controlled trial. The investigators will use cluster randomization in which primary care clinics are randomized to receive 0, 1, or 2 nudges using a factorial design. The nudges will run for 18 months, followed by 12 months of observation to assess persistence of effects. Aim 2: To qualitatively and quantitatively assess clinician experiences with the EHR-based nudges, including their acceptability and effects on workflow. At the conclusion of the intervention period, the investigators will perform semi-structured interviews and field a clinician survey.

Eligibility Criteria

This trial is for older adults at high risk of polypharmacy, especially those with dementia or cognitive impairment. It's being conducted in Northwestern Medicine or UPMC primary care clinics that specialize in Internal Medicine, Family Medicine, General Practice, or Geriatrics.

Inclusion Criteria

Patients must be affiliated with Northwestern Medicine or UPMC primary care clinic in Internal Medicine, Family Medicine, General Practice, or Geriatrics.

Exclusion Criteria

Not applicable.

Timeline

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Intervention

Implementation of EHR-based commitment and justification nudges to reduce high-risk polypharmacy

18 months

Ongoing EHR interactions

Observation

Observation period to assess persistence of effects from the intervention

12 months

Follow-up

Participants are monitored for safety and effectiveness after the intervention

4-8 weeks

Treatment Details

Interventions

• Clinical decision support (CDS)-Commitment nudge
• Clinical decision support (CDS)-Justification nudge
• Clinician education

Trial Overview The trial tests two EHR-based nudges designed to help doctors reduce risky multiple medication use among elderly patients. Clinics are randomly chosen to receive either no nudges, one type of nudge (commitment or justification), or both for 18 months and then observed for another year.

Participant Groups

Group I: Justification nudge Experimental Treatment 2 Interventions

The justification nudge will be an EHR alert triggered for patients with high-risk polypharmacy when a clinician begins to renew or newly prescribe a medication that causes a high-risk criterion to be fulfilled (i.e., a medication meeting causing 1 of the 7 high-risk polypharmacy criteria/primary study measures to be met). This alert will inform the clinician of the high-risk nature of the prescription and request a free-text justification for starting or renewing the medication. This written justification will appear in the EHR in a section of that encounter that other EHR users can see.

Group II: Commitment nudge + Justification nudge Experimental Treatment 3 Interventions

This study arm will receive both the commitment nudge and the justification nudge.

Group III: Commitment nudge Experimental Treatment 2 Interventions

The commitment nudge will be an EHR alert that is triggered when a clinician renews or orders a qualifying medication in any Epic encounter (including non-face-to-face encounters) for a patient aged 65 or greater who meets criteria for high-risk polypharmacy. When triggered, the commitment nudge will offer the clinician a choice option that sets a reminder to discuss polypharmacy at the patient's next visit date.

Group IV: Clinician education only Experimental Treatment 1 Intervention

Online clinician education

Who Is Running the Clinical Trial?

Northwestern University

Lead Sponsor

Trials

1,674

Recruited

989,000+

National Institute on Aging (NIA)

Collaborator

Trials

1,841

Recruited

28,150,000+

University of Pittsburgh Medical Center

Collaborator

Trials

78

Recruited

77,600+

University of Southern California

Collaborator

Trials

956

Recruited

1,609,000+

University of California, Los Angeles

Collaborator

Trials

1,594

Recruited

10,430,000+

Findings from Research

The use of nudge theory in clinical decision support systems (CDSS) could help bridge the gap between existing healthcare evidence and actual clinical practice, potentially improving patient outcomes.

Integrating nudges with electronic health records and artificial intelligence may enhance clinician adherence to guidelines, especially in areas lacking robust evidence, by standardizing behavior in uncertain clinical situations.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Nudging within learning health systems: next generation decision support to improve cardiovascular care. Chen, Y., Harris, S., Rogers, Y., et al.[2022]

A systematic review of 39 studies found that nudges, particularly those that frame information, change default options, or enable choice, can effectively improve clinical decision-making among healthcare providers.

Most studies were conducted in the USA, with 36% being randomized controlled trials, indicating a need for more rigorous research to confirm the effectiveness of nudges compared to other interventions.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Systematic review of clinician-directed nudges in healthcare contexts. Last, BS., Buttenheim, AM., Timon, CE., et al.[2022]

A targeted educational intervention was effective in improving the adoption of clinical decision support (CDS) systems among 478 healthcare providers who were previously overriding these systems, with 34% of them starting to review prescription drug monitoring programs (PDMP) after receiving educational messages.

This study highlights that low-resource strategies, like sending educational messages via email or EHR chat, can significantly enhance the effectiveness of CDS in preventing medical errors and improving patient outcomes.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Targeted messaging to improve the adoption of clinical decision support for prescription drug monitoring program use. Sommers, S., Tolle, H., Napier, C., et al.[2023]

References

1. England pubmed.ncbi.nlm.nih.gov

Nudging within learning health systems: next generation decision support to improve cardiovascular care. [2022]

2. Netherlands pubmed.ncbi.nlm.nih.gov

User-Centered Development of a Behavioral Economics Inspired Electronic Health Record Clinical Decision Support Module. [2020]

3. England pubmed.ncbi.nlm.nih.gov

Systematic review of clinician-directed nudges in healthcare contexts. [2022]

4. England pubmed.ncbi.nlm.nih.gov

Behavioral "nudges" in the electronic health record to reduce waste and misuse: 3 interventions. [2023]

5. Switzerland pubmed.ncbi.nlm.nih.gov

Implementation and Evaluation of Two Nudges in a Hospital's Electronic Prescribing System to Optimise Cost-Effective Prescribing. [2022]

6. Canada pubmed.ncbi.nlm.nih.gov

A Behavioral Economics-Electronic Health Record Module to Promote Appropriate Diabetes Management in Older Adults: Protocol for a Pragmatic Cluster Randomized Controlled Trial. [2022]

7. England pubmed.ncbi.nlm.nih.gov

Targeted messaging to improve the adoption of clinical decision support for prescription drug monitoring program use. [2023]

8. United States pubmed.ncbi.nlm.nih.gov

Design of Behavioral Economic Applications to Geriatrics Leveraging Electronic Health Records (BEAGLE): A pragmatic cluster randomized controlled trial. [2023]