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Not yet recruiting NCT05747755

Achieving Diagnostic Excellence Through Prevention and Teamwork

No phase Interventional Diagnostic Errors

For patients and families

In plain language

An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.

What is being studied
The protocol lists: ADEPT Program.
Who it may be relevant to
Registry conditions: Diagnostic Errors. Basic parameters: from 18 years · All.
What needs checking
Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
Where it takes place
United States
Next step
Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
Official title

Achieving Diagnostic Excellence Through Prevention and Teamwork (ADEPT)

Overview

This study seeks to link a group of hospitals to measure and share the rates of diagnostic errors, to understand underlying causes of diagnostic errors, and develop ways that hospitals, clinicians, and patients can work together to avoid diagnostic errors and harms due to those errors. The investigators will test how data sharing and collaboration improve diagnostic processes and develop approaches which can be sustained into the future. The approach represents a novel application of rigorous outcome adjudication to the problem of inpatient diagnostic errors using a learning health system model.

Detailed description

Many factors contribute to diagnostic errors, but key among them are foundational issues in healthcare: complex and fragmented care systems, the limited time available to providers trying to ascertain a firm diagnosis, and the work systems and cultures that support or impede improvements in diagnostic performance. While approaches to identifying diagnostic errors exist, few studies have linked identification of underlying systemic and structural causes of errors to existing quality improvement programs in hospitals. Even fewer have applied resilience theories or positive deviance approaches to characterize the features of cases where the diagnostic process is optimal and then use those findings to frame health system improvement.

This application builds directly on the investigators' currently funded study - Utility of Predictive Systems in Diagnostic Errors (UPSIDE) - which is defining risk factors, underlying causes, and prevalence of diagnostic errors among patients admitted to hospitals participating in a 55-hospital research collaborative, the Hospital Medicine Reengineering Network (HOMERuN). UPSIDE has developed reference standard approaches to adjudication of diagnostic errors, defined factors associated with errors, and created collaborations with participating sites and national organizations, providing a uniquely powerful opportunity to transform how diagnostic process evaluation programs can be used to improve patient safety.

The overall goal of this Center is to turn the investigators' highly successful multicenter network into a diagnostic error learning health system that will integrate diagnostic error assessments into existing quality and safety programs, provide support and expertise needed to reduce diagnostic errors, and catalyze scientific, personnel, and infrastructure changes which will last beyond the duration of this grant.

To achieve the study's overall goals, the investigators will: 1) Implement a case review infrastructure which can accurately identify diagnostic errors and characterize diagnostic processes among patients suffering inpatient deaths, ICU transfers, or rapid-response team calls taking place at hospitals associated the Hospital Medicine Reengineering Network; 2) Develop site-level audit and feedback and group-wide benchmarking reports of error rates, diagnostic process faults, diagnostic process resilience features and use these data to frame collaboration between existing safety and quality programs at participating sites; 3) Use the data and collaborative model to develop and pilot test interventions based on highest priority findings; and 4) Develop understanding of the program's reach, adoption, implementation, and maintenance, as well feasibility and initial experience with pilot interventions. This project will establish a learning health system which can achieve excellence in diagnosis as an ongoing part of care, a system which can be a model for others as well.

Interventions

  • Behavioral ADEPT Program
    Integration of surveillance for diagnostic errors into usual care, benchmarking and sharing of results across hospitals, expert mentoring of quality and safety personnel in change management, pilot testing and refinement of Safety I and Safety II interventions to reduce systemic causes of diagnostic errors and to increase resilience, thus promoting diagnostic excellence.

Primary outcome measures

  • Diagnostic Errors [Time frame: Through hospital discharge, an average of 10 days]
Secondary outcome measures (2)
  • Harmful Diagnostic Errors [Time frame: Through hospital discharge, an average of 10 days]
  • Diagnostic process faults [Time frame: Through hospital discharge, an average of 10 days]

Eligibility criteria

Inclusion criteria

  • Adult patients admitted to general medicine services at one of the participating hospitals and who either died during the hospitalization, were transferred to the ICU >= 48 hours after admission, or had a rapid response.

Exclusion criteria

  • Admitted for a non-medical reason
  • Patients coded in the field who are moribund on arrival to the hospital

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: No

Study design

Allocation
Non-randomized
Model
Single group
Masking
Open label
Primary purpose
Diagnostic

Study locations

United States · 2 centers
  • University of California San Francisco — San Francisco
  • Brigham & Women's Hospital — Boston

Identifiers

NCT: NCT05747755 · 2023P000031 · R18HS029366 · 355948

Primary sources (government registries)

View this study on ClinicalTrials.gov ↗