Precision Feedback for Anesthesia Care

Overseen By Zach Landis-Lewis

Age: 18+

Sex: Any

Trial Phase: Academic

Sponsor: University of Michigan

Disqualifiers: Ended participation, Changed roles, Changed institutions, others

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

Compensation: Varies

Number of Visits: Unknown

3500 Participants Needed

Trial Summary

Do I need to stop my current medications for this trial?

The protocol does not specify whether you need to stop taking your current medications.

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 data supports the idea that Precision Feedback for Anesthesia Care is an effective treatment?

The available research shows that Precision Feedback for Anesthesia Care can improve clinical practice by providing personalized performance summaries to healthcare providers. This approach highlights specific areas where performance can be improved, making it more effective than standard feedback methods. By focusing on the most relevant information for each provider, Precision Feedback helps them understand and act on performance gaps, potentially leading to better patient care. ^{1 2 3 4 5}

What data supports the effectiveness of the treatment Precision Feedback for Anesthesia Care?

Research shows that Audit and Feedback (A&F), which involves giving healthcare providers summaries of their clinical performance, can significantly improve clinical practice. Precision Feedback, a more tailored version of A&F, uses personalized metrics and optimal message formats to enhance its impact, suggesting it could be effective in improving anesthesia care. ^{1 2 3 4 5}

What safety data is available for Precision Feedback in anesthesia care?

The provided research does not directly address safety data for Precision Feedback in anesthesia care. It focuses on the effectiveness, design, and implementation of Audit and Feedback (A&F) systems, including electronic versions, but does not specifically mention safety outcomes or data related to anesthesia care. ^{1 2 4 6 7}

Is Precision Feedback for Anesthesia Care safe for humans?

The research articles reviewed do not provide specific safety data for Precision Feedback or its related names. They focus on the effectiveness and design of audit and feedback systems rather than safety outcomes. ^{1 2 4 6 7}

Is the treatment in the trial 'Precision Feedback for Anesthesia Care' a promising treatment?

Yes, the treatment is promising because it uses precision feedback to improve anesthesia care by focusing on the most important performance gaps for each provider, making it easier for them to understand and act on the feedback. ^{1 2 3 4 8}

How does the Precision Feedback for Anesthesia Care treatment differ from other treatments?

Precision Feedback for Anesthesia Care is unique because it uses a tailored approach to provide feedback to healthcare providers, focusing on the most relevant performance metrics for each individual. This personalized feedback aims to improve clinical practice by highlighting specific areas for improvement, unlike traditional methods that use a one-size-fits-all approach. ^{1 2 3 4 8}

What is the purpose of this trial?

This cluster-randomized trial will assess the effectiveness of a precision feedback service on anesthesia provider performance. The precision feedback service enhances a standard audit and feedback (A\&F) email with a brief message and visual display about high-value performance information. The control arm will receive a standard "one size fits most" A\&F email that is currently sent to anesthesia providers each month. Hypothesis: Providers receiving precision feedback will increase a) care quality for improvable measures and b) email engagement (click-through and dashboard login rates) when compared with providers receiving standard A\&F emails. The study investigators will assess unintended consequences in a mixed-methods process evaluation.

Research Team

Zach Landis-Lewis

Principal Investigator

University of Michigan

Eligibility Criteria

This trial is for anesthesia providers who are already part of the MPOG provider feedback email program. It's designed to see if a more personalized feedback method can improve their performance in providing care.

Inclusion Criteria

Participation in the Multicenter Perioperative Outcomes Group (MPOG) provider feedback email program.

Timeline

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Pre-intervention

Providers' baseline performance is measured for 6 months before the intervention

6 months

Intervention

Providers receive either precision-enhanced feedback or standard feedback emails monthly

6 months

Follow-up

Participants are monitored for email engagement and performance improvements

6 months

Treatment Details

Interventions

• Precision Feedback
• Standard Feedback

Trial Overview The study compares two types of email messages: precision-enhanced feedback emails with tailored content and visuals, versus standard 'one size fits most' audit and feedback emails currently used.

Participant Groups

Group I: precision-enhanced feedback email messages Experimental Treatment 1 Intervention

Providers receive an enhanced monthly email containing precision audit and feedback (A\&F).

Group II: standard feedback email messages Active Control 1 Intervention

Providers receive the standard "one size fits most" A\&F monthly email.

Who Is Running the Clinical Trial?

University of Michigan

Lead Sponsor

Trials

1,891

Recruited

6,458,000+

National Library of Medicine (NLM)

Collaborator

Trials

42

Recruited

108,000+

Findings from Research

The development of a web-based audit and feedback (A&F) dashboard for primary care was informed by user-centered design and A&F theory, incorporating input from family physicians to ensure it meets their needs.

User interviews revealed that while physicians are interested in peer comparisons, high burnout levels and a lack of motivation to improve performance were significant barriers, highlighting the need for dashboards to present data effectively and support physicians in quality improvement efforts.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Developing an Audit and Feedback Dashboard for Family Physicians: User-Centered Design Process. Shuldiner, J., Kiran, T., Agarwal, P., et al.[2023]

In a review of 146 randomized trials on audit and feedback (A&F) interventions, it was found that most feedback compared performance against benchmarks (60.3%), but only a small percentage (5.5%) provided a rationale for the chosen comparators, indicating a lack of theoretical grounding in their design.

To enhance the effectiveness of A&F, the study suggests using tailored comparisons instead of general benchmarks, limiting the number of comparators shown, and encouraging recipients to set personal targets based on relevant information, which could improve the credibility and actionability of the feedback.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Clinical performance comparators in audit and feedback: a review of theory and evidence. Gude, WT., Brown, B., van der Veer, SN., et al.[2023]

The study aims to implement a precision audit and feedback (A&F) system in anesthesia care, which tailors performance feedback to individual providers based on their specific needs and performance gaps, potentially improving care quality and outcomes.

Conducted with over 60 hospitals in a national consortium, the study will evaluate the effectiveness of this precision A&F approach through a cluster randomized controlled trial, with data collection starting in March 2022 and the intervention phase beginning in March 2024.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

A Scalable Service to Improve Health Care Quality Through Precision Audit and Feedback: Proposal for a Randomized Controlled Trial. Landis-Lewis, Z., Flynn, A., Janda, A., et al.[2022]

The usability evaluation of the Performance Improvement plaN GeneratoR (PINGR) identified 47 usability issues, with the most significant problems related to 'Consistency and standards' and 'Match between system and real world', which could hinder effective use by clinicians.

The recommended actions component of PINGR had the highest number of usability issues, indicating that improvements in this area could enhance the overall effectiveness of computerized Audit and Feedback systems in primary care.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Interface design recommendations for computerised clinical audit and feedback: Hybrid usability evidence from a research-led system. Brown, B., Balatsoukas, P., Williams, R., et al.[2022]

In a study involving 40 internal medicine teams, intensive audit and feedback methods, including daily data dashboards and weekly performance reviews, significantly improved the completion of discharge metrics (79.3% vs. 63.2% in the control group, P<0.0001).

The effectiveness of the intensive feedback diminished after the intervention ended, indicating that continuous and timely feedback is crucial for maintaining improved performance in clinical settings.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Next-generation audit and feedback for inpatient quality improvement using electronic health record data: a cluster randomised controlled trial. Patel, S., Rajkomar, A., Harrison, JD., et al.[2019]

The effectiveness of electronic audit and feedback (e-A&F) interventions in improving quality of care is highly variable, as shown by a meta-analysis of seven studies involving 81,700 patients and 329 healthcare professionals, with many studies exhibiting medium to high risk of bias.

Most e-A&F interventions targeted theoretical domains like 'knowledge', 'social influences', and 'goals', but did not comprehensively address all relevant domains, indicating a need for future research to better understand which theoretical factors are crucial for enhancing the effectiveness of e-A&F interventions.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

A systematic review of electronic audit and feedback: intervention effectiveness and use of behaviour change theory. Tuti, T., Nzinga, J., Njoroge, M., et al.[2023]

A review of 140 trials on audit and feedback (A&F) interventions revealed significant gaps in reporting, with clarity ranging from 56% to 97%, indicating a need for improved standardization in how these interventions are documented.

The study identified 17 modifiable elements of A&F interventions, highlighting considerable variation in their design, with 51% targeting individual providers and 92% aimed at behavior change, which may affect the overall effectiveness of A&F in clinical practice.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Reporting and design elements of audit and feedback interventions: a secondary review. Colquhoun, H., Michie, S., Sales, A., et al.[2018]

The acceptance of clinical performance feedback by physicians is significantly influenced by the characteristics of the feedback itself, such as its content and timeliness, as well as the fairness of the assessment process.

Emotional responses to feedback, often stemming from the assessment process rather than the feedback content, play a crucial role in determining how physicians react and modify their patient-management behaviors.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Model depicting aspects of audit and feedback that impact physicians' acceptance of clinical performance feedback. Payne, VL., Hysong, SJ.[2018]

References

1. Canada pubmed.ncbi.nlm.nih.gov

Developing an Audit and Feedback Dashboard for Family Physicians: User-Centered Design Process. [2023]

2. England pubmed.ncbi.nlm.nih.gov

Clinical performance comparators in audit and feedback: a review of theory and evidence. [2023]

3. Canada pubmed.ncbi.nlm.nih.gov

A Scalable Service to Improve Health Care Quality Through Precision Audit and Feedback: Proposal for a Randomized Controlled Trial. [2022]

4. Ireland pubmed.ncbi.nlm.nih.gov

Interface design recommendations for computerised clinical audit and feedback: Hybrid usability evidence from a research-led system. [2022]

5. England pubmed.ncbi.nlm.nih.gov

Next-generation audit and feedback for inpatient quality improvement using electronic health record data: a cluster randomised controlled trial. [2019]

6. England pubmed.ncbi.nlm.nih.gov

A systematic review of electronic audit and feedback: intervention effectiveness and use of behaviour change theory. [2023]

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

Reporting and design elements of audit and feedback interventions: a secondary review. [2018]

8. England pubmed.ncbi.nlm.nih.gov

Model depicting aspects of audit and feedback that impact physicians' acceptance of clinical performance feedback. [2018]