Learning Lab for Diagnostic Fidelity

• ClinicalTrials.gov Identifier: NCT03865303
• Recruitment Status: Recruiting
• First Posted: March 6, 2019
• Last Update Posted: October 19, 2020
• Sponsor: Mayo Clinic
• Collaborator: Agency for Healthcare Research and Quality (AHRQ)
• Information provided by (Responsible Party): Brian W. Pickering, M.B., B.Ch., Mayo Clinic

Tracking Information

• First Submitted Date: January 4, 2019
• First Posted Date: March 6, 2019
• Last Update Posted Date: October 19, 2020
• Actual Study Start Date: April 22, 2019
• Estimated Primary Completion Date: July 31, 2022 (Final data collection date for primary outcome measure)

Current Primary Outcome Measures (submitted: March 5, 2019)

• Validation of automated phenotypes [ Time Frame: 1 year ]
  Use data from the patient electronic medical record to identify the number of diagnostic error or delay to validate clinical environment automated phenotypes
• Adoption (Number of time the Control Tower used during the clinical encounters) [ Time Frame: 1 year ]
  Standardized process tracking sheets to track each time the control tower system is triggered and used.
• Implementation Acceptability [ Time Frame: 1 year ]
  Focused questions about beliefs, attitudes, usability by healthcare providers

• Original Primary Outcome Measures: Same as current
• Current Secondary Outcome Measures: Not Provided
• Original Secondary Outcome Measures: Not Provided
• Current Other Pre-specified Outcome Measures: Not Provided
• Original Other Pre-specified Outcome Measures: Not Provided

Descriptive Information

• Brief Title: Learning Lab for Diagnostic Fidelity
• Official Title: Acute Care Learning Laboratory-Reducing Threats to Diagnostic Fidelity in Critical Illness
• Brief Summary: Diagnostic error and delay remain a leading cause of preventable harm and death in the United States. Using a learning laboratory structure, researchers will implement mixed-methods research approaches to identify the systemic weaknesses that contribute to diagnostic error and delay in the hospital setting. The knowledge gained from research innovative will allow researchers to design, develop, implement, and refined a suite of human-centered tools that can be deployed to reduce the risk of diagnostic error and delay in both community and academic hospital settings.
• Detailed Description: Despite the recognition that diagnostic errors an delays are a major contributor to preventable deaths in the USA, little progress has been made to reduce mortality outcomes from this known killer. An effective strategy leading to meaningful reduction in diagnostic error and delay rates has not made its way into practice. This proposal is unique and novel and combines mixed-methods research approaches with systems engineering research approaches to understand the interplay of the multiple factors contributing to diagnostic error and delay. The knowledge gained from this holistic approach will then be used within the learning laboratory to inform the design, development, evaluation, and refinement of the solutions to diagnostic error and delay. "Control Tower" will be the staging ground for the in situ learning laboratory and will be built on top of a well-established clinical informatics infrastructure and hospital environment open to innovation and practice change.
• Study Type: Observational
• Study Design: Observational Model: Cohort; Time Perspective: Prospective
• Target Follow-Up Duration: Not Provided
• Biospecimen: Not Provided
• Sampling Method: Non-Probability Sample

Study Population

1. All patients at risk of diagnostic error will be eligible for the study.
2. We will include both sexes and all genders and all minority populations as they present with the risk of diagnostic error in the hospitals.

Given the nature of the study, which focuses on patients with or at risk of diagnostic error, outreach efforts to underrepresented populations or individuals would not be possible.

• Condition: Critical Illness
• Intervention: Not Provided
• Study Groups/Cohorts: Not Provided
• Publications *: Not Provided

Recruitment Information

• Recruitment Status: Recruiting
• Estimated Enrollment (submitted: March 5, 2019): 100000
• Original Estimated Enrollment: Same as current
• Estimated Study Completion Date: July 31, 2022
• Estimated Primary Completion Date: July 31, 2022 (Final data collection date for primary outcome measure)

Eligibility Criteria

Inclusion Criteria

• For EMR review all adults admitted to the hospital ages 18 and older with research authorization
• For survey-clinicians including physicians, advanced care practitioners
• For focus groups and interviews-clinicians including physicians, advanced care practitioners

Exclusion Criteria

• Age <18 years old
• No research authorization
• Refusal to give consent

Sex/Gender

• Sexes Eligible for Study: All

• Ages: 18 Years to 120 Years (Adult, Older Adult)
• Accepts Healthy Volunteers: No

Contacts

Contact: Yue Dong, MD; 5072556149; dong.yue@mayo.edu

Contact: Ann Johnson; 5072556149; ajohnson@mayo.edu

• Listed Location Countries: United States

Administrative Information

• NCT Number: NCT03865303
• Other Study ID Numbers: 18-007115; R18HS026609 ( U.S. AHRQ Grant/Contract )
• Has Data Monitoring Committee: No

U.S. FDA-regulated Product

• Studies a U.S. FDA-regulated Drug Product: No
• Studies a U.S. FDA-regulated Device Product: No

• IPD Sharing Statement: Not Provided
• Responsible Party: Brian W. Pickering, M.B., B.Ch., Mayo Clinic
• Study Sponsor: Mayo Clinic
• Collaborators: Agency for Healthcare Research and Quality (AHRQ)

Investigators

• Principal Investigator: Brian W Pickering, M.B., B.Ch.; Mayo Clinic

• PRS Account: Mayo Clinic
• Verification Date: October 2020