Prescribing Feedback for Reducing Prescribing Errors

Overseen By Jennifer Arango, MPH

Age: Any Age

Sex: Any

Trial Phase: Academic

Sponsor: Yale University

Disqualifiers: Failure to meet inclusion criteria

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

Compensation: Varies

Number of Visits: Unknown

What You Need to Know Before You Apply

What is the purpose of this trial?

This trial aims to determine if feedback can help emergency department doctors prescribe medications more safely for older adults. It will test two feedback types: one from an anonymous system and another from a peer doctor. The goal is to reduce the use of potentially inappropriate medications for patients aged 65 and older. Doctors who prescribe medications and have treated at least 30 older patients in the past year may be suitable for this study. As an unphased study, this trial allows participants to contribute to research that could improve medication safety for older adults.

Will I have to stop taking my current medications?

The trial information does not specify whether participants need to stop taking their current medications.

What prior data suggests that this prescribing feedback method is safe for reducing prescribing errors?

Research shows that feedback interventions, like those in this trial, are generally safe. These interventions provide doctors with feedback on their medication prescribing practices, aiming to reduce risky prescriptions for older adults in emergency departments.

Studies have found that feedback based on the Geriatric Emergency Medication Safety Recommendations (GEMS-Rx) can enhance prescription safety. Specifically, doctors become more aware of potentially inappropriate medications (PIMs) and can avoid them. This feedback helps them make safer choices, reducing the chance of negative side effects.

Since this trial involves giving feedback to doctors rather than testing a new drug on patients, the safety risk remains very low. The focus is on changing how doctors prescribe medications to ensure they are safer for older adults. ^{1 2 3 4 5}

Why are researchers excited about this trial?

Researchers are excited about the trial of prescribing feedback systems because these methods aim to reduce prescribing errors through innovative communication strategies. Unlike traditional approaches where providers rely on personal judgment or standard protocols, these systems offer automated feedback messages. One system uses an anonymous messenger that compares individual prescribing habits against aspirational norms. Another leverages a credible peer messenger, offering benchmark comparisons based on Geriatric Emergency Medication Safety Recommendations (GEMS-Rx). These interventions are designed to foster safer prescribing practices by providing real-time insights and comparisons, potentially leading to better patient outcomes.

What evidence suggests that prescribing feedback is effective for reducing prescribing errors?

Research has shown that giving feedback can help reduce mistakes in prescribing medication. In one study, feedback from pharmacists lowered prescribing mistakes from 19 to 11.7 errors each day. Another study found that feedback programs cut narcotic prescribing mistakes by 83%. Digital health tools, including feedback systems, reduced medication errors by up to 54%. In this trial, participants will receive feedback messages either from an anonymous messenger or a credible peer messenger. These findings suggest that feedback messages, whether from an anonymous source or a colleague, can encourage safer prescribing in emergency departments. ^{6 7 8 9 10}

Who Is on the Research Team?

Daniella Meeker, PhD

Principal Investigator

Yale University

Are You a Good Fit for This Trial?

This trial is for healthcare professionals in Emergency Departments who prescribe medications to older adults. The goal is to improve prescribing practices and reduce errors, specifically the use of potentially inappropriate medications (PIMs) upon discharge.

Inclusion Criteria

Practicing in one of the participating Yale New Haven Health System emergency departments

Provides digital affirmative consent to participate

I am a licensed clinician with the authority to prescribe medications.

Exclusion Criteria

Failure to meet inclusion criteria

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Intervention

Providers receive automated prescribing feedback messages from either a credible peer messenger or an anonymous system to promote safer prescribing practices

12 months

Monthly feedback sessions

Follow-up

Participants are monitored for changes in prescribing rates and safety outcomes after the intervention

6 months

What Are the Treatments Tested in This Trial?

Interventions

• Prescribing Feedback

Trial Overview The study tests whether feedback messages about PIMs can help doctors prescribe more safely. It compares peer clinician prescriber feedback with anonymous system feedback against the usual care without such interventions in a randomized setting.

How Is the Trial Designed?

Group I: Credible Peer Messenger Experimental Treatment 1 Intervention

Providers receive automated prescribing feedback messages from a credible peer messenger, including aspirational norms and benchmark comparisons based on Geriatric Emergency Medication Safety Recommendations (GEMS-Rx) recommendations, to promote safer prescribing practices.

Group II: Anonymous Messenger Experimental Treatment 1 Intervention

Providers receive automated prescribing feedback messages from an anonymous messenger system, including aspirational norms and benchmark comparisons based on Geriatric Emergency Medication Safety Recommendations (GEMS-Rx) recommendations, to promote safer prescribing practices.

Group III: Control group Active Control 1 Intervention

Providers continue with standard of care. No feedback messages are sent.

Who Is Running the Clinical Trial?

Yale University

Lead Sponsor

Trials

1,963

Recruited

3,046,000+

National Institute on Aging (NIA)

Collaborator

Trials

1,841

Recruited

28,150,000+

Citations

1. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC6783579/

Pharmacist‐led, video‐stimulated feedback to reduce ... Implementation of this feedback approach was associated with a statistically significant reduction in the mean number of prescribing errors, from 19.0/d to 11.7 ...

2. sciencedirect.com sciencedirect.com/science/article/pii/S2352013224000577

The effectiveness of checklists and error reporting systems ... The review highlights evidence supporting the efficacy of checklists in reducing medication errors, surgical complications, and other adverse events.

3. qualitysafety.bmj.com qualitysafety.bmj.com/content/22/3/256

Personalised performance feedback reduces narcotic ... Initiation of a prescriber-directed error feedback programme was associated with an 83% reduction in narcotic prescribing errors, an elimination of ...

4. jmir.org jmir.org/2025/1/e65546/

Digital Health Technology Interventions for Improving ... On average, DHT interventions reduced ADEs by 37.12% (range 8.2%-66.5%) and medication errors by 54.38% (range 24%-83%). The key drivers of cost ...

5. onlinelibrary.wiley.com onlinelibrary.wiley.com/doi/10.1111/jcpt.13491

Pharmacist‐led, prescription intervention system‐assisted ... The pharmacist-led prescribing feedback intervention led to a significant reduction in prescribing errors. With calls for prescribing feedback ...

6. annemergmed.com annemergmed.com/article/S0196-0644(24)00071-4/fulltext

Modified Delphi Development of a High-Risk Prescription ... The GEMS-Rx list will be used to update a novel geriatric prescription safety quality measure developed by ACEP for use by emergency clinicians ...

7. sciencedirect.com sciencedirect.com/science/article/abs/pii/S0196064424000714

Geriatric Emergency Medication Safety Recommendations ... We present the first expert consensus-based list of high-risk prescriptions for older ED patients (GEMS-Rx) to improve safety among older ED patients.

8. clinicaltrials.gov clinicaltrials.gov/study/NCT07146763

A Trial to Reduce Inappropriate Prescribing to Older Adults ... The study compares the effectiveness of feedback messages about potentially inappropriate medications (PIMs) delivered by peer clinician prescribers or ...

9. pubmed.ncbi.nlm.nih.gov pubmed.ncbi.nlm.nih.gov/38483427/

Modified Delphi Development of a High-Risk Prescription List ... We present the first expert consensus-based list of high-risk prescriptions for older ED patients (GEMS-Rx) to improve safety among older ED patients.

10. jamanetwork.com jamanetwork.com/journals/jamanetworkopen/fullarticle/2831215

Emergency Department Programs to Support Medication ... Geriatric medication programs based in the emergency department (ED) associated with reduced potentially inappropriate medications (PIMs) and adverse events ...