Teledermatology as a Solution: How AI is Transforming the Evaluation of Skin Lesions and Cancer Detection

Many healthcare centers in the U.S. have long delays when scheduling dermatology visits. Patients with common skin problems or suspected lesions often wait weeks or months before seeing a specialist. This wait can cause serious problems, especially with conditions like melanoma, where finding it early is important for survival.

For example, Ashford & St. Peter’s Hospitals NHS Foundation Trust (ASPH) in the UK had wait times up to one year for routine skin lesion checks before using an AI system. Although this example is from outside the U.S., similar problems happen in American healthcare, especially in rural areas with few dermatologists.

Long wait times put stress on doctors and lower patient satisfaction. Also, urgent referral routes meant for suspected skin cancer can get used wrongly because routine appointments are not available quickly.

Teledermatology and AI: How They Work Together

Teledermatology means checking skin problems from a distance using digital pictures or live video. Patients can have pictures taken at a clinic or at home with special devices. These images are sent electronically to dermatologists or AI systems for checking.

Artificial intelligence helps teledermatology by using computer programs to study the pictures of skin lesions. AI often uses convolutional neural networks (CNN) that look for patterns in images. The systems decide if lesions are likely harmless, maybe dangerous, or cancerous.

There are AI tools for doctors in clinics and smartphone apps for people to check their own skin. But AI systems used by doctors usually work better, especially when experts also review the results.

Real-World Example: AI Implementation at Ashford & St. Peter’s Hospitals

ASPH partnered with Skin Analytics, a company that makes AI teledermatology tools, to fix their long waiting list. Before using AI, 396 patients were waiting for routine skin lesion checks, causing delays and wrong use of referral routes.

In July 2023, the hospital started using an AI system called DERM from Skin Analytics. Healthcare assistants took pictures of patients’ skin lesions using an iPhone with a dermatoscope. These pictures were then uploaded for AI review. Patients got text messages with health questions and appointment info before the picture taking. This made the process smoother.

With AI screening, the hospital quickly looked at over 2,400 patients on their Urgent Suspected Skin Cancer (USSC) list. The system re-examined each lesion to find patients who needed to be seen in person first. This led to:

• The number of patients waiting over 18 weeks dropped from 71 to just 1.
• The routine waitlist shrank from 396 patients to 33.
• 21% of patients were sent home without more in-person visits.
• 14% were sent to other specialists.
• 14% were changed to routine appointments instead of urgent ones.

The system helped use appointments better by giving priority to patients needing face-to-face visits. This saved time and resources.

AI Diagnostic Accuracy in Skin Cancer Detection

Research shows AI can be very good at diagnosing skin cancers by looking at images. This is especially true when AI works together with dermatologists. A study published in the Journal of Investigative Dermatology shows that AI, especially CNN algorithms, can classify skin images well on their own.

Many studies tested AI in lab settings, but recent progress focuses on real-world use that helps healthcare delivery.

The article points out that AI looks promising, but figuring out the best way to use it in clinics is still ongoing. It is important that AI supports what doctors do to keep patient care safe and reliable.

Benefits of AI Teledermatology for U.S. Medical Practices

For medical practice leaders in the U.S., using AI teledermatology can offer many advantages:

• Improved Patient Access and Reduced Wait Times
  AI can quickly screen skin lesions. Patients get assessments faster, which can cut the time between referral and treatment and improve outcomes, especially for risky cases like melanoma.
• Optimized Use of Specialist Resources
  AI can spot low-risk cases that don’t need urgent care. This lets dermatologists focus on patients who really need help, making the workflow better and cutting unneeded visits.
• Enhanced Data Management and Documentation
  Digital images and AI reports can be added to electronic health records (EHRs). This gives a full record and helps keep care consistent.
• Support for Primary Care Providers
  Many patients first see their primary care doctor about skin concerns. AI tools can help decide which lesions need dermatologist referrals and which can be handled by the primary care provider.
• Reduced Costs and Health Economic Benefits
  Better patient paths and fewer unneeded visits lower costs and help healthcare finances.

AI and Workflow Automation in Skin Lesion Evaluation

AI not only helps with diagnosis but also improves workflow in dermatology services. It can solve several problems U.S. medical centers face.

Pre-Visit Preparation and Scheduling:
AI systems can contact patients through text or online portals before visits. Sending questions and instructions helps patients come ready, cutting delays during imaging. Staff can gather important data ahead of time.

Image Capture and Management:
Healthcare staff can use smartphones with dermatoscopes to quickly take good images. AI automatically uploads and analyzes the pictures, lowering data errors and reducing manual work.

Triage and Prioritization:
AI sorts images by risk level. It schedules urgent live visits for high-risk lesions and routine checks for low-risk cases. This shortens waiting lists and prevents backups.

Communication and Follow-Up:
Automated messages tell patients about their next steps, like scheduling a specialist visit or safely ending care. This keeps patients informed.

Integration with Electronic Health Records:
AI results can fill out standard reports in EHRs in real time, helping keep consistent records and supporting teamwork among care providers.

Analytics and Performance Monitoring:
Automatic data tracking lets administrators watch key measures like wait times, triage accuracy, and patient volume. This helps improve processes and use resources better.

These workflow improvements reduce workload for clinical and office staff and make dermatology care better overall.

Additional Considerations for U.S. Healthcare Organizations

Medical practices in the U.S. thinking about adding AI teledermatology should consider several points:

• Regulatory Compliance and Data Privacy:
  Make sure systems meet HIPAA rules for safe data handling and storage.
• Technology Infrastructure:
  Practices need good internet and devices that work for taking images and telehealth visits.
• Training and Change Management:
  Staff including healthcare assistants and doctors need training to use AI tools well.
• Patient Education:
  Explain clearly how AI helps with diagnosis and treatment to set correct expectations and encourage cooperation.
• Collaboration Among Specialties:
  AI may suggest cases that need other specialists. Having good care coordination helps patient paths.
• Reimbursement Models:
  Knowing billing codes and insurance coverage for teledermatology is key to keeping programs running.

Future Directions in AI-Driven Dermatology Care

The use of AI in dermatology, including teledermatology, is expected to grow fast. New imaging tools like 3D imaging, reflectance confocal microscopy, and optical coherence tomography combined with AI may improve diagnosis further.

In the U.S., these tools can help overcome lack of specialists or long travel distances by allowing remote skin checks. Adding AI to primary care can help find skin cancer earlier and lower pressure on dermatology clinics.

Research continues to test AI tools in real clinics and improve workflows so they fit well with how doctors and patients work.

Medical practice leaders and IT managers have an important role in checking these new technologies. Using AI teledermatology carefully can improve patient access, use resources better, and raise the quality of dermatology care.

With smart AI use and workflow automation, dermatology services in the U.S. can reduce wait times, find more malignant lesions, and give better results for patients in many different groups.