The Value of VisualDx

Improve diagnostic accuracy, save time, and reduce patient harm.

Diagnostic errors cost our healthcare system $1.6 billion annually in malpractice payments. These errors harm patients and lead to other indirect costs and a considerable drain on healthcare resources.

VisualDx aims to reduce diagnostic errors by augmenting a clinician’s thinking. We help establish a logical method of clinical reasoning to avert common diagnostic pitfalls. This leads to evidence-based decision making.

Increase in Accuracy
when primary care doctors use VisualDx to diagnose skin conditions1
Minutes Saved
each day when using VisualDx2
Medical Image Resource
for representation of dark skin, as published by JAAD3

Evidence-Based Infographics

VisualDx Plus DermExpert Improves Diagnostic Accuracy Among Non-Dermatology Clinicians

Proven Benefits of Using VisualDx

JAAD Study: Diversity in the VisualDx Image Collection

The Value of VisualDx: Quality care begins with an accurate diagnosis

A Medical Crisis Below the Surface: Nearly every person will experience a diagnostic error in their lifetime

Diagnostic Error: Medicine’s silent emergency

Time Savings: See how much time physicians save while using VisualDx

Visualize Complexity: Technology can increase diagnostic accuracy

The Financial Risk of Diagnostic Errors: Diagnostic errors are one of the most serious problems plaguing healthcare systems today

Diagnostic Accuracy: Room for improvement

Improving Diagnosis of Skin Conditions by Using VisualDx

Cellulitis Safety Program: One diagnosis costs one billion in wasted healthcare dollars

Diagnostic Visual Decision Support

VisualDx assists diagnostic decision making in areas where physicians and other providers have expressed a consistent need—those areas requiring pattern-recognition expertise. We help physicians recognize and diagnose by leveraging the innate human ability to pattern match. Simply search by patient factors to see a visual differential diagnosis. VisualDx combines the best medical images in the world—reviewed and confirmed by leading physician experts—with a unique and powerful search engine to give you patient-specific answers in seconds. Serious infectious, immunologic, metabolic, nutritional, psychiatric, and genetic diseases often present visually.

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Proven to Increase Diagnostic Accuracy

Use of VisualDx early in the diagnostic workflow may reduce misdiagnosis for more efficient healthcare management.

  • In a published study of medical educational resources, researchers found VisualDx to have the most diverse images; 28.5% of all images in VisualDx are of dark skin4. For more than 20 years, VisualDx has been committed to providing a comprehensive resource for medical images across all skin types.
  • In a randomized, blinded study of emergency physicians, internists, family physicians, and dermatologists conducted at the University of Rochester, VisualDx improved diagnostic accuracy over 120% for complex medical cases compared with standard textbooks and atlases5. This improved outcome was achieved after only 5 minutes of training using VisualDx.
  • In a published study conducted at UCLA-Harbor Medical Center and University of Rochester Strong Memorial Hospital, physicians using VisualDx were over 4 times more likely to suggest the correct diagnosis for patients admitted to the hospital for serious infections. Without VisualDx, admitting physicians made diagnostic errors 28% of the time. These errors can lead to overprescribing of antibiotics and increased patient risk of hospital-acquired infections6.

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1. Breitbart EW, Choudhury K, Andersen AD, et al. Improved patient satisfaction and diagnostic accuracy in skin diseases with a Visual Clinical Decision Support System-A feasibility study with general practitioners. PLOS One. https://doi. org/10.1371/journal.pone.0235410. Published July 29, 2020. Accessed August 13, 2020.

2. Based on a 2013 survey of 468 VisualDx users.

3. Alvarado SM, Feng H, Representation of dark skin images of common dermatologic conditions in educational resources: a cross-sectional analysis, JAAD (2020),  Published June 10, 2020. Accessed June 18, 2020.

4. Alvarado SM, Feng H, Representation of dark skin images of common dermatologic conditions in educational resources: a cross-sectional analysis, JAAD (2020), Published June 10, 2020.

5. Papier A, Allen E, McDermott M. Visual informatics: real-time visual decision support. Poster presented at: American Medical Informatics Association 2001 Annual Symposium; November 3-7, 2001; Washington, DC.

6. David CV, Chira S, Eells SJ, et al. Diagnostic accuracy in patients admitted to hospitals with cellulitis. Dermatol Online J. 2011;17(3):1. Published 2011 Mar 15.