The effectiveness of diagnosing oral mucosal diseases using a clinical decision support system

Oral mucosal diseases pose a significant diagnostic challenge due to the similarity of clinical presentations across different pathologies. The integration of Clinical Decision Support Systems (CDSS) represents a promising approach in dentistry to improve diagnostic accuracy. Objective. This study aimed to evaluate the effectiveness of diagnosing oral mucosal diseases with and without the use of a CDSS. Materials and Methods . The study utilized:UMKB (United Medical Knowledge Base) – a unified medical knowledge base, CDSS (Clinical Decision Support System) and an electronic physician assistant,patients and expert dentists. A comparative prospective study was conducted involving 102 patients with oral mucosal diseases. Diagnostic accuracy was assessed with and without CDSS assistance. Patient satisfaction with the diagnostic process was evaluated via digital questionnaires (Google Forms). Results. The use of CDSS by dentists: increased the frequency of preliminary diagnoses (92% with CDSS vs. 78.8% without),iImproved diagnostic correctness (86.5% with CDSS vs. 51.9% without), enhanced final diagnosis completeness (90% with CDSS), increased preventive care recommendations (94% with CDSS vs. 73% without). Conclusions. The CDSS significantly improved: diagnostic accuracy (p = 0.002), data completeness (p < 0.001 for general and oral mucosal examinations), reduced the need for external consultations (p = 0.003), expanded preventive care coverage (p = 0.004). Patient satisfaction was higher with CDSS use (p = 0.003), though this correlation weakened with age (p = 0.047).

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Published
2025-09-24
DOI
https://doi.org/10.33667/2078-5631-2025-20-94-99
Primary Topic
Electronic Health Records Systems
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article
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article

The effectiveness of diagnosing oral mucosal diseases using a clinical decision support system

Huiping Tan, E. G. Margaryan, Astrid Turner, Shuang Pan et al.
Medical alphabet
Electronic Health Records Systems
article

The effectiveness of diagnosing oral mucosal diseases using a clinical decision support system

Huiping Tan, E. G. Margaryan, Astrid Turner, Shuang Pan, A. G. Kadzhoian, G. A. Bledzhyants, Yu. S. Kurenkova, M. T. Abdelrakhim, D. K. Dlyaverovna
article en

Abstract

Oral mucosal diseases pose a significant diagnostic challenge due to the similarity of clinical presentations across different pathologies. The integration of Clinical Decision Support Systems (CDSS) represents a promising approach in dentistry to improve diagnostic accuracy. Objective. This study aimed to evaluate the effectiveness of diagnosing oral mucosal diseases with and without the use of a CDSS. Materials and Methods . The study utilized:UMKB (United Medical Knowledge Base) – a unified medical knowledge base, CDSS (Clinical Decision Support System) and an electronic physician assistant,patients and expert dentists. A comparative prospective study was conducted involving 102 patients with oral mucosal diseases. Diagnostic accuracy was assessed with and without CDSS assistance. Patient satisfaction with the diagnostic process was evaluated via digital questionnaires (Google Forms). Results. The use of CDSS by dentists: increased the frequency of preliminary diagnoses (92% with CDSS vs. 78.8% without),iImproved diagnostic correctness (86.5% with CDSS vs. 51.9% without), enhanced final diagnosis completeness (90% with CDSS), increased preventive care recommendations (94% with CDSS vs. 73% without). Conclusions. The CDSS significantly improved: diagnostic accuracy (p = 0.002), data completeness (p < 0.001 for general and oral mucosal examinations), reduced the need for external consultations (p = 0.003), expanded preventive care coverage (p = 0.004). Patient satisfaction was higher with CDSS use (p = 0.003), though this correlation weakened with age (p = 0.047).

Medical alphabet(20)
Cairo University (EG), Harbin Medical University (CN), Sechenov University (RU), Bakulev Scientific Center for Cardiovascular Surgery Russian Academy of Medical Sciences (RU)
Openalex Percentile: Top 71%
Electronic Health Records Systems
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