Application of visually based, computerised diagnostic decision support system in dermatological medical education: a pilot study

Abstract

This study demonstrated that VCDDSS increases diagnostic accuracy by 18.75%, which means we can avoid possible misdiagnosis, provide better treatment, and avoid waste of medical resources. The user satisfaction is high. We expect wider application of this kind of decision support system in clinical practice, medical education, residency training, and patient education in the future. Further large-scale studies should be planned to confirm its application.

Effect of a clinical evidence technology on patient skin disease outcomes in primary care: a cluster-randomized controlled trial

“…In a pilot study by Chou, clinical diagnoses of 13 patients were made by 13 dermatology residents and 51 medical students before and after using VisualDx. Diagnostic accuracy increased from 63% to 81% ( p <0.01) as judged by a consultant dermatologist [21]. Despite these positive intermediate effects, the published literature, including the study reported here, provides no evidence of better patient outcomes.…”

“…In one study, its use improved the differential diagnosis of cellulitis by emergency room physicians [20]. In a pilot study, diagnostic accuracy of dermatology residents and medical students increased after using VisualDx, as judged by a consultant dermatologist [21].…”

Diagnostic error: incidence, impacts, causes and preventive strategies

“…47 A digital image library of skin eruptions increased diagnostic accuracy of dermatology residents by 19% in a randomised trial. 48 An interactive computed decision support system achieved up to 75% reduction in diagnostic errors relating to vignettes of neurological disorders. 49 A web-based system that facilitated internet crowdsourcing of multiple opinions improved diagnostic accuracy among junior physicians.…”

“…Computed decision support systems that generate differential diagnoses using inputted clinical data yield small improvements in diagnostic accuracy when clinicians revisit their diagnoses following a differential diagnosis generator consultation 47. A digital image library of skin eruptions increased diagnostic accuracy of dermatology residents by 19% in a randomised trial 48. An interactive computed decision support system achieved up to 75% reduction in diagnostic errors relating to vignettes of neurological disorders 49.…”

A Data Driven Educational Decision Support System

“…The system did not specifically describe data modeling, nor is it a model centered on the learner's learning performance. For the most essential DDEDSS research, it was of little reference [3]. Hernes and Sobieska-Karpińska proposed the data modeling of talent quality evaluation [4].…”