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Learning Lab for Diagnostic Fidelity

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ClinicalTrials.gov Identifier: NCT03865303
Recruitment Status : Recruiting
First Posted : March 6, 2019
Last Update Posted : October 19, 2020
Sponsor:
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
Change History
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

*   Includes publications given by the data provider as well as publications identified by ClinicalTrials.gov Identifier (NCT Number) in Medline.
 
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
Removed Location Countries  
 
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