Journal article
Lead-Dx: Development and evaluation of a simulation-based education codesign framework to address diagnostic excellence for all
Clinical simulation in nursing, v 120, 102067
Nov 2026
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Abstract
•Framework to address diagnostic inequity through SP-faculty codesign.•Creates psychologically safe teams and aligns to codesign principles.•Actionable processes result in competency-aligned and valid simulation scenarios.
While accurate diagnoses are fundamental to healthcare, errors affect estimated 12 million people yearly, with harms underestimated among marginalized persons. Codesign offers a promising educational solution.
A simulation codesign framework was developed. Evaluation included team psychological safety, codesign principal alignment, and scenario quality.
Learning equity, addressing disparities in diagnosis (Lead-Dx) is a process-oriented, structured framework in which faculty collaborate with standardized patients with lived experiences of diagnostic inequity. Lead-Dx supports psychologically safe team environments, aligns with codesign principles, and yields valid scenarios.
Lead-Dx is an actionable framework that addresses diagnostic inequity through collaborative SP-faculty simulation codesign.
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Details
- Title
- Lead-Dx: Development and evaluation of a simulation-based education codesign framework to address diagnostic excellence for all
- Creators
- Leah Burt (Corresponding Author) - University of Illinois ChicagoBob Kiser - University of Illinois ChicagoJoy V. Goldsmith - University of MemphisCristina Gonzalez - New York UniversitySusan Corbridge - University of Illinois ChicagoWelcome Jerde - Patient Advocate, Minneapolis, MN 55403, USAKate Morse - Drexel UniversityAndrew Olson - University of MinnesotaLarry Gruppen - University of Michigan
- Publication Details
- Clinical simulation in nursing, v 120, 102067
- Publisher
- Elsevier
- Number of pages
- 7
- Grant note
- Josiah Macy Jr.
This work was supported (in part) by the Josiah Macy Jr. Foundation .
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Nurse Practitioner Master of Science in Nursing (MSN)
- Web of Science ID
- WOS:001883430300001
- Other Identifier
- 991022232715404721