This trial evaluates whether providing physicians with access to Prof. Valmed, a clinical decision support medical product, improves identification of rheumatic diseases and formulation of differential diagnoses compared with conventional decision support.
Advanced AI, particularly large language models, shows promise for enhancing clinical reasoning, yet most systems such as ChatGPT are not certified as medical products. Prof. Valmed is a clinical decision support medical product designed to assist physicians in diagnostic decision making. Given frequent referral problems and diagnostic delays in rheumatology, evaluating such support is highly relevant for clinical workflows. This randomized controlled trial will test whether access to Prof. Valmed improves physicians' diagnostic performance in cases of suspected rheumatic disease compared with conventional decision support. Participants will be randomized to either use Prof. Valmed or rely on conventional tools while working through standardized clinical cases. For each case, participants will submit up to three differential diagnoses and a confidence rating. Independent reviewers, blinded to group allocation, will adjudicate accuracy. Findings will clarify the benefits and limitations of integrating Prof. Valmed into routine practice.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
DIAGNOSTIC
Masking
SINGLE
Enrollment
82
Prof Valmed. decision support system.
Institute for Digital Medicine, University Hospital of Giessen and Marburg, Philipps University Marburg
Marburg, Germany
Diagnostic accuracy of top diagnosis
Participants in each group will make at least one disease suggestion (top diagnosis) and up to a total of a maximum of 3 suggestions. Percentage of exact matches of the top suggestion with the actual diagnosis will be analyzed
Time frame: directly (within 10 minutes) after Intervention
Diagnostic accuracy of top 3 suggestions
Participants in each group will make at least one disease suggestion (top diagnosis) and up to a total of a maximum of 3 suggestions. Percentage of exact matches with the actual diagnosis included in the top 3 suggestions will be analyzed
Time frame: directly (within 10 minutes) after Intervention
Diagnostic confidence
For each case participants will be asked for their diagnostic confidence (VAS 0-10). The mean score will be compared between groups.
Time frame: directly (within 10 minutes) after Intervention
Time spent for diagnosis
We will compare how much time (in seconds) participants spend per case between the two study arms.
Time frame: directly (within 10 minutes) after Intervention
Perceived Information Timeliness
Perceived ability to receive the information needed without delay (Likert scale from 1 to 5)
Time frame: directly (within 10 minutes) after Intervention
Perceived diagnostic support quality
Perceived quality of the diagnostic support (Likert scale from 1 to 5)
Time frame: directly (within 10 minutes) after Intervention
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Diagnostic reasoning
For each case, participants will receive 1 point for each plausible diagnosis and 2 points for a completely correct response. The total scores will be compared between the randomized groups.
Time frame: during evaluation