Accepted for/Published in: JMIR Medical Informatics
Date Submitted: Jun 10, 2024
Date Accepted: Dec 1, 2024
Diagnostic Decision-Making Variability in Glaucoma: Comparative Analysis of Novice and Expert Optometrists to Inform AI System Design
ABSTRACT
Background:
This study examines the diagnostic decision-making differences between novice and expert optometrists in glaucoma diagnosis.
Objective:
The objective of this study is to identify and analyze the variations in diagnostic decision-making approaches between novice and expert optometrists, with the aim of informing the development of AI systems that can enhance diagnostic accuracy and consistency across different levels of expertise.
Methods:
We conducted in-depth interviews with 14 optometrists including both novices and experts, focusing on their approaches to glaucoma diagnosis. Responses were coded and analyzed qualitatively and quantitatively, and themes were extracted to understand their decision-making patterns and find out variations in their decision-making approaches
Results:
Experts showed higher concordance rates with clinical decisions with limited data, highlighting the impact of experience and data availability on clinical judgment. The accuracy gap narrowed with patient data access to complete historical data. Approaches to the exams assessment and decision differed significantly: experts emphasized comprehensive risk assessments and progression analysis, demonstrating cognitive efficiency and intuitive decision-making, while novices relied more on structured, analytical methods and external references.
Conclusions:
Understanding these differences can inform the future design of AI systems to enhance diagnostic accuracy and consistency across different expertise levels, improving patient outcomes in optometric practice.
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.