The 10 Essential Features of a Dermatological AI for Public Health Systems
The increasing demand for dermatological services, coupled with a global shortage of specialists, necessitates innovative solutions. Artificial Intelligence (AI) in dermatology holds immense promise, but for public health systems to realize its full potential, the technology must meet stringent clinical and technical criteria. This document outlines these critical needs and illustrates how Legit.Health's platform is engineered to address them comprehensively.Table of contents
Key Elements
1. Differential Diagnosis for +200 Conditions
Why It Matters
Skin conditions are diverse, ranging from common inflammatory disorders and infections to rare diseases and malignancies. Primary care physicians (PCPs) and other non-specialist clinicians are often the first point of contact. An AI tool with a narrow diagnostic scope fails to support these frontline clinicians adequately. For example, an AI focused only on melanoma detection or a handful of common rashes cannot perform effective patient triage—the process of sorting patients based on the urgency.
Without a broad diagnostic range, the AI cannot reliably determine if a patient can be managed in primary care, needs routine referral, or requires urgent specialist attention. This limitation perpetuates existing bottlenecks, delays care for those who need it most, and can lead to suboptimal patient outcomes due to misdiagnosis or delayed appropriate intervention.
Solution
Legit.Health addresses this fundamental need by providing differential diagnosis capabilities for approximately 300 distinct skin conditions. This extensive range covers the majority of dermatological cases encountered in both primary and secondary care settings.
Legit.Health includes the following disease categories:
- Malignant diseases: pigmented lesions and tumoral diseases, such as melanoma, basal cell carcinoma, and cutaneous squamous cell carcinoma.
- Inflammatory diseases: including, among others, psoriasis, hidradenitis, and atopic dermatitis.
- Infectious diseases: viral infections such as herpes zoster and genital warts, bacterial infections such as impetigo, and fungal infections such as candidiasis.
- Autoimmune diseases: covering the entire spectrum, including bullous diseases, cutaneous lupus, and dermatomyositis, among others.
- Genodermatoses: detecting rare genetic skin disorders.
- Vascular diseases: such as hemangiomas and vascular malformations.
- Other conditions: including urticaria, various types of alopecia, and many other processes encompassed within such a complex specialty as dermatology
The system does not merely provide a single label; instead, it generates a ranked list of potential diagnoses, each with an associated confidence level. This augments the clinician's decision-making process, rather than attempting to replace it.
Crucially, Legit.Health incorporates specific indices, such as a malignancy suspicion score and an urgency indicator. These quantitative outputs enable the creation of intelligent, automated workflows. For instance, a high malignancy suspicion can trigger an automatic alert and fast-track referral to a dermatologist, while a low-urgency condition with a clear management plan might empower the PCP to treat the patient directly, thereby optimizing specialist resources and improving the speed and quality of care delivery.
2. Objective and Automated Severity Measure
Why It Matters
Diagnosing a condition is only the first step; quantifying its severity is equally crucial for effective patient management. Disease severity directly influences therapeutic choices (e.g., topical treatments vs. systemic medications vs. biologics), determines the urgency of intervention, and serves as the primary metric for monitoring treatment efficacy and disease progression over time.
Traditional severity assessment often relies on subjective clinical judgment, which can lead to inter-observer and intra-observer variability. This inconsistency can compromise treatment decisions and make it difficult to compare outcomes across different settings or clinicians. Standardized, validated scoring systems (e.g., PASI for psoriasis, SCORAD for atopic dermatitis) exist, but manual calculation is time-consuming and prone to error, making their consistent use in busy clinical practice challenging. For PCPs to confidently manage certain dermatological conditions, they require reliable tools to assess severity accurately.
Solution
Legit.Health incorporates sophisticated algorithms capable of automatically analyzing clinical images to quantify objective parameters of skin disease. From these parameters, the system calculates a wide array of internationally recognized and validated dermatological scoring systems. These include, but are not limited to:
- PASI (Psoriasis Area and Severity Index)
- SCORAD (SCORing Atopic Dermatitis)
- EASI (Eczema Area and Severity Index)
- IHS4 (International Hidradenitis Suppurativa Severity Score System)
- GAGS (Global Acne Grading System)
- UAS7 (Urticaria Activity Score over 7 days)
- SALT (Severity of Alopecia Tool)
- LUDWIG Scale (for female pattern hair loss)
- GPPGA (Global Psoriasis Physician Global Assessment)
- VASI (Vitiligo Area Scoring Index)
This automated assessment, derived directly from patient images, minimizes subjectivity and clinician burden. It provides a consistent, reproducible, and guideline-compliant measure of severity, essential for tailoring treatment, tracking patient progress longitudinally, and making informed referral decisions. This capability is particularly valuable for empowering PCPs and for facilitating value-based healthcare models where objective outcome measurement is paramount.
3. Real-Time Image Quality Assessment
Why It Matters
The adage "garbage in, garbage out" is acutely relevant in AI-assisted medical imaging. The diagnostic and assessment accuracy of any dermatological AI system is fundamentally dependent on the quality of the input images. Suboptimal images—those that are out of focus, poorly illuminated, incorrectly framed, or taken at an inappropriate distance—can lead to erroneous AI outputs, potentially resulting in misdiagnosis, delayed treatment, or unnecessary anxiety for patients. If image quality issues are only detected retrospectively (e.g., by a specialist reviewing images from a teledermatology consultation, or by the AI system after the patient has left the clinic), it necessitates patient recalls for re-imaging. This is inefficient, costly, frustrating for patients and clinicians alike, and delays the care pathway.
Solution
Legit.Health proactively addresses this challenge with its integrated DIQA (Dermatology Image Quality Assessment) algorithm. DIQA operates in real-time, at the moment the image is being captured. If the image quality does not meet predefined standards for dermatological assessment (e.g., issues with focus, lighting, field of view), the system immediately prompts the user (whether a clinician, nurse, or even a patient using a home-monitoring application) to retake the photograph, providing guidance on how to improve it. This ensures that only images of sufficient diagnostic quality are accepted and processed by the AI. The efficacy and methodology of DIQA have been validated and published in a high-impact, peer-reviewed medical journal, underscoring its scientific rigor. This real-time quality control mechanism is critical for minimizing diagnostic errors, optimizing workflow efficiency, and ensuring the reliability of the entire teledermatology process. Dermatology Image Quality Assessment (DIQA). Journal of the American Academy
of Dermatology https://doi.org/10.1016/j.jaad.2022.11.002
4. Regulatory Certification
Why It Matters
Software intended for diagnosing, treating, or monitoring medical conditions is classified as a medical device and is subject to stringent regulatory oversight. This is essential to protect patient safety and ensure that such tools are clinically effective and perform as claimed by the manufacturer. Healthcare institutions and clinicians have a legal and ethical obligation to use medical devices that have undergone appropriate conformity assessments and bear the requisite certifications (e.g., CE marking in Europe). Using uncertified or inappropriately certified software exposes patients to potential risks and healthcare providers to significant legal and reputational liabilities. For public health tenders, robust regulatory compliance is a non-negotiable prerequisite.
Solution
Legit.Health is developed and maintained under a rigorous Quality Management System compliant with ISO 13485 (Medical devices - Quality management systems - Requirements for regulatory purposes). The platform is:
- Certified as a Class I medical device under the EU Medical Device Directive (MDD 93/42/EEC).
- Certified as a Class IIb medical device under the EU Medical Device Regulation (MDR 2017/745).
This dual certification, particularly the higher-risk Class IIb designation, underscores the critical nature of Legit.Health's intended use in supporting clinical decision-making for diagnosis and severity assessment. This commitment to regulatory excellence ensures patient safety, legal compliance for deploying institutions, and a foundation of trust for clinicians and patients. ISO 13485:2016 certificate issued by BSI.
The formal publication of the MDR Class IIb certificate is pending, a situation reflective of the current transitional pressures and limited Notified Body capacity within the European regulatory system, not any deficiency in the product's compliance or technical documentation.
Additional Features
5. Support for Rare Diseases
Why It Matters
While common diseases constitute the bulk of dermatological caseloads, rare diseases often present significant diagnostic challenges due to their infrequent occurrence and clinicians' limited exposure. Patients with rare dermatological conditions frequently experience diagnostic delays, leading to prolonged suffering, increased morbidity, and higher healthcare costs. AI systems that can recognize patterns associated with rare diseases can be invaluable decision-support tools, particularly for non-specialists.
Solution
Legit.Health's diagnostic algorithms have been trained on diverse datasets that include a range of rare dermatological conditions, such as Generalized Pustular Psoriasis (GPP). By incorporating these conditions, the platform provides crucial support to clinicians when faced with unusual presentations, helping to shorten the diagnostic odyssey for affected patients and facilitate timely access to appropriate care.
6. Scientific Validation and Peer-Reviewed Publications
Why It Matters
Regulatory certification attests to safety and conformity with stated intended purposes. However, discerning healthcare providers and systems also seek independent, peer-reviewed evidence of a medical device's clinical performance, accuracy, and real-world utility. Scientific publications in reputable journals and presentations at established medical congresses provide this transparency and allow for critical appraisal by the medical community.
Solution
Legit.Health is committed to scientific transparency and rigorous validation. The company has an extensive record of over 10 publications in high-impact, peer-reviewed scientific journals and presentations at leading international medical congresses. These publications detail the development, validation, and clinical application of its AI algorithms, including DIQA and various diagnostic and severity assessment modules, providing objective evidence of their performance and clinical value.
7. Proven Implementation Track Record
Why It Matters
A novel technology may perform well in controlled research settings, but its true value is demonstrated through successful implementation and sustained use in real-world clinical practice. Healthcare systems look for solutions with a proven track record, indicating scalability, reliability, interoperability with existing health IT infrastructure, and acceptance by clinical users.
Solution
Legit.Health is not a theoretical concept; it is a market-ready solution with a demonstrated history of successful deployments. Notably, it is implemented within the public health system of Asturias (SESPA) in Spain, showcasing its suitability for large-scale public healthcare environments. Furthermore, leading private healthcare organizations, such as Sanitas, utilize Legit.Health's technology across their hospital networks. These deployments provide tangible proof of the platform's robustness, clinical utility, and ability to integrate effectively into diverse healthcare workflows.
8. Sello SNS de IA
Why It Matters
National health authorities are increasingly establishing frameworks to evaluate and endorse AI solutions that meet high standards of quality, safety, and ethical considerations. Such endorsements provide an additional layer of assurance for healthcare providers and procurement bodies.
Solution
Legit.Health is actively working towards and is well-positioned to obtain the *Sello SNS de IA from the Spanish Ministry of Health. This accreditation ("un distintivo de conformidad y calidad otorgado por el SNS a aquellas soluciones y algoritmos de IA que han superado satisfactoriamente el proceso de evaluación técnica y normativa") will further validate Legit.Health's adherence to the stringent quality and regulatory benchmarks set by the Spanish National Health System.
9. User Interface
Why It Matters
Even the most sophisticated AI engine can fail to deliver its potential if it is difficult to use or integrate. Developing a user-friendly, clinically intuitive, and secure interface for a medical device API requires significant expertise in human-computer interaction, clinical workflows, and data security. If each healthcare institution must develop its own front-end, it leads to duplicated effort, potential inconsistencies, and a suboptimal user experience, hindering adoption.
Solution
Recognizing this challenge, Legit.Health offers more than just an API. It provides a mature, specialized user interface (UI) that has been refined through years of real-world use by thousands of clinicians. This UI is designed for seamless integration into existing hospital systems or mobile health applications, often via a simple iframe. Key benefits include:
- Optimized Clinical Workflows: The interface is designed around the practical needs of dermatological assessment.
- Proven Usability: Years of feedback from a large user base have driven iterative improvements, ensuring an intuitive experience.
- Enhanced Security and Resilience: The UI adheres to high standards for data protection and system stability.
- Accelerated Deployment: Providing a ready-to-use, yet integrable, UI significantly reduces the time and resources healthcare institutions need to invest in front-end development, allowing them to leverage the full power of the AI much faster.
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10. Interoperable and well-documented API
Why It Matters
Healthcare systems require robust, well-documented APIs to ensure seamless integration with existing electronic health record (EHR) systems and other healthcare IT infrastructure. A poorly documented API can lead to implementation challenges, increased costs, and delays in deployment.
Solution
Legit.Health provides comprehensive API documentation, including detailed specifications, use cases, and integration guidelines. This documentation is designed to facilitate smooth interoperability with various EHR systems, ensuring that healthcare providers can easily incorporate Legit.Health's capabilities into their existing workflows.
Likewise, interoperability is essential to ensure that data flows smoothly among different systems and platforms. This not only improves operational efficiency but also guarantees that clinicians have access to accurate, up-to-date information at the right time.
Additionally, Legit.Health adheres to recognized interoperability standards such as HL7 FHIR, ensuring that data can be shared and used effectively across different platforms and systems. This interoperability not only enhances operational efficiency but also ensures that clinicians have access to accurate, up-to-date information at the right time.
Summary
Legit.Health offers a scientifically validated, regulatory-compliant, and clinically proven dermatological AI platform. Its comprehensive diagnostic and severity assessment capabilities, coupled with real-time image quality assurance and a focus on seamless integration, directly address the core needs of modern healthcare systems. By empowering clinicians, optimizing workflows, and improving patient outcomes, Legit.Health is the ideal partner for public health entities in Spain and beyond, seeking to harness the transformative potential of artificial intelligence in dermatology.