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APASI: The bright future of Psoriasis severity assessment has arrived

· 8 min de lectura
Taig Mac Carthy
Co-founder at Legit.Health
Alfonso Medela
CAIO at Legit.Health

Introduction

The future of dermatology has arrived thanks to Legit.Health's revolutionary application of the PASI system: APASI (Automatic Psoriasis Area and Severity Index). Using computer vision algorithms, the researchers have created a tool that processes smartphone images and automatically translates them into the domain of the PASI.

It is widely known that objective, reliable, and precise outcome measures are key to evidence-based medicine. When considering psoriasis, the PASI has the best measurement properties and is the most recommended for clinical trials. That is why we automated the PASI to help patients and doctors achieve better health outcomes.

Automatic PASI for psoriasis

The origins of the PASI

This scoring system for psoriasis was first published in a paper by T. Fredericksson and U. Pettersson in 1978, where they explored the validity of a new treatment for the disease.

Their formula for assessing the severity of the condition would go on to become the gold standard for dermatologists around the globe and is still widely used to this day.

In order to calculate the PASI, the sum of the severity of these three main changes was multiplied with the numerical value of the areas involved and with the various percentages of the four body areas. These values were then added in order to obtain the PASI.

Fredriksson, T., & Pettersson, U. (1978). Severe Psoriasis -- Oral Therapy with a New Retinoid. Dermatology, 157(4), 238--244. doi:10.1159/000250839

PASI score sheet by British Columbia Ministry of Health

The shortfalls of the pen-and-paper PASI

The main goal of PASI is to provide a tool to record data precisely and consistently for routine evaluations and clinical studies. However, it carries a set of problems and limitations.

We found substantial variation [in the results] between experienced and inexperienced physicians using PASI

Richard G. Langley, MD,a and Charles N. Ellis, MDb Halifax, Nova Scotia, and Ann Arbor. Michigan Evaluating psoriasis with Psoriasis Area and Severity Index, Psoriasis Global Assessment, and Lattice System Physician's Global Assessment

In other words, there is a high inter-observer variability, that is most pronounced when compared between experienced and inexperienced practitioners.

Aside from the inter-observer variation, many physicians have reported that filling up the paper sheet is too tedious and time-consuming and that they don't really use it on a day-to-day basis.

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Digital calculators: A half-baked solution to the problem

With the advent of basic computation, several digitalized versions of the PASI scoring system were developed, in an attempt to reduce the time wasted in calculations. These online calculators tackle, although inefficiently, just one of the issues the traditional PASI has. While the formula is calculated automatically, the doctor still has to fill in the value for each parameter.

This not only still requires the time and attention of the physician, but does nothing to address the multiple issues of lack of objectivity and reproducibility within the PASI system.

¿Cómo sabemos si un sistema de puntuación es bueno?

Cuando se trata de evaluaciones dermatológicas, la efectividad de un sistema de puntuación es primordial. Pero, ¿qué es exactamente lo que hace que un sistema de puntuación sea fiable y útil? A través del consenso científico, se han identificado varios factores clave que contribuyen a la robustez de estas escalas. Vamos a profundizar en los elementos cruciales:

  • Facilidad de uso: Este factor considera si el sistema puede aplicarse sin esfuerzo dentro de las limitaciones de tiempo y recursos financieros. Que un sistema sea fácil de usar es crucial para su adopción generalizada en entornos clínicos.
  • Sensibilidad al cambio: Un sistema de puntuación efectivo debe ser capaz de detectar cambios clínicamente significativos a lo largo del tiempo. Esta sensibilidad asegura que cualquier progreso o deterioro en la condición de un paciente se captura con precisión.
  • Fiabilidad interobservador: Esto se refiere a la consistencia de los resultados cuando diferentes observadores utilizan el sistema de puntuación. Una alta fiabilidad interobservador significa que diferentes dermatólogos llegarán a conclusiones similares, mejorando la credibilidad del sistema.
  • Variabilidad intraobservador: Esto analiza la consistencia de los resultados cuando el mismo observador utiliza el sistema de puntuación varias veces. Una baja variabilidad intraobservador indica que el sistema proporciona resultados similares todas las veces que un mismo dermatólogo evalúe un mismo caso.
  • Interpretabilidad: Un sistema de puntuación práctico debería proporcionar interpretaciones cualitativas significativas de sus puntuaciones, como categorizar la gravedad de una condición como leve, moderada o severa.

Estos criterios no solo aseguran la efectividad del sistema de puntuación sino también su aplicabilidad y fiabilidad en diversos escenarios clínicos.

Adaptado de "Methods and definitions to rate the quality of outcome measures". Schmitt, J., Langan, S., Deckert, S., Svensson, A., von Kobyletzki, L., Thomas, K., & Spuls, P. (2013). Assessment of clinical signs of atopic dermatitis: A systematic review and recommendation. Journal of Allergy and Clinical Immunology, 132(6), 1337--1347. doi:10.1016/j.jaci.2013.07.008.

Six ways in which APASI is better

Legit.Health is the revolutionary Clinical Data and Communication tool for Next-generation dermatologists that triples the empowerment of patients.

After 12 months using Legit.Health, in which we analysed the applicability of the tool at our hospital, we have drawn conclusions that help to propose a new care paradigm in the follow-up of psoriasis.

Dra. Elena Sánchez-Largo, Torrejon Hospital

The purpose of the deep learning algorithms is to relieve doctors from the tedious manual calculation of scoring systems and allow the practice of more objective evidence-based dermatology while speeding up the pathology reporting process and increasing patients' autonomy and control.

Legit.Health's algorithms automatically grade lesions just by looking at smartphone images and small patient-reported outcome measures (PROMs). In other words: the tool will automatically fill in most of the dermatology scoring systems, such as PASI, SCORAD, UAS, GAGS, and many more.

APASI: The bright future of Psoriasis severity assessment has arrived

Esto significa que la nueva versión de este sistema de puntuación extrae datos de manera precisa y consistente, tanto durante evaluaciones rutinarias como en investigación clínica. La mejora se puede ver en la siguiente tabla, que compara las métricas de rendimiento de la forma más común de utilizar los sistemas de puntuación:

Papel y lápizDigitalAutomático (IA)
Auto-supervisión--Realiza diagnóstico
Facilidad de uso≈ 600 segundos≈ 420 segundos≈ 23 segundos
Sensibilidad al cambio0 a 40 a 40 a 100
Variabilidad interobservadorMedia (20%)Media (20%)La más baja (8%)
Variabilidad intraobservadorAltaAltaCero

Tabla 1: Comparación entre diferentes métodos de puntuación de la severidad de una enfermedad. El método automático impulsado por inteligencia artificial presenta un mejor rendimiento en la mayoría de los indicadores.

Gracias a los algoritmos de aprendizaje profundo, Legit.Health libera a los médicos de la tediosa tarea de calcular manualmente los sistemas de puntuación y permite la práctica de una dermatología basada en evidencia más objetiva. Además, al utilizar algoritmos para medir la sequedad, la liquenificación, el eritema, el exudado, el edema y muchos más signos, la herramienta puede calcular signos visuales de manera más fiable y consistente.

1. Easier to use and faster than any other existing method

While an experienced physician might take six to seven minutes to completely fill in and calculate the PASI score of a patient, an inexperienced one will need ten minutes. Meanwhile, Legit.Health's algorithm only takes 23 seconds to get the final score, including capturing the image.

This is key both from a time management perspective, allowing the doctors better use their time with the patient, and from a clinical perspective. The fact that many physicians won't fill in any scoring system for considering the process too tedious and time-consuming and would rather make a gut estimate of the severity of the disease is incompatible with the modern idea of practising evidence-based medicine.

2. APASI assists the doctor in the diagnosis of the disease

The algorithm developed by Legit.Health isn't limited to simply measuring the severity, like the PASI does. It can also help assess whether or not the condition is actually psoriasis. The APASI has been trained using the input of top dermatologists to distinguish between hundreds of conditions, including most types of psoriasis.

This means that APASI will distinguish between several types of psoriasis and assist the doctor in the disease assessment process, not only making it quicker by providing relevant information but improving the rate of correct diagnosis by 23%

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3. APASI can detect small changes in the evolution of the pathology

Legit.Health's tool analyzes the pathologies using a validated scoring system that has both the lowest MID (Minimal important Difference) and is sensible to the lowest LDC (Lowest Detectable Change), which means the algorithm analyzes every image with more precision and attention to detail than any human observer would.

In clinical trials, quantification of the disease is critical to measure the efficacy of an investigational treatment by comparing the severity of disease before therapy to that measured after treatment.

Richard G. Langley, MD,a and Charles N. Ellis, MDb Halifax, Nova Scotia, and Ann Arbor, Michigan Evaluating psoriasis with Psoriasis Area and Severity Index, Psoriasis Global Assessment, and Lattice System Physician's Global Assessment

Furthermore, it has a higher validity and reliability while maintaining comparable clinimetric properties, thanks to the intrinsic functioning of computer vision algorithms.

4. Greatly reduces inter-observer variability

Our data indicate that even experienced investigators had difficulty with PASI in rating the area of involvement […], especially among patients with more severe psoriasis.

Richard G. Langley, MD,a and Charles N. Ellis, MDb Halifax, Nova Scotia, and Ann Arbor, Michigan Evaluating psoriasis with Psoriasis Area and Severity Index, Psoriasis Global Assessment, and Lattice System Physician's Global Assessment

The experimental results show that APASI outperforms the baseline methods when it comes to inter-observer variability, achieving a mean absolute percentage of error of just 13%, way below the usual 20% that can be observed in the classical application of the traditional scoring systems.

5. Zero intra-observer variability

The algorithmic nature of the APASI eliminates entirely, and without question, the intra-observer variability, as every reading is reliably consistent.

This allows the doctor to not rely on his memory when assessing the severity of the psoriasis, so they can focus on the analysis of the contextual information. In this sense, the more objective data reduces considerably the risk of misdiagnosing, providing a more objective, accurate, and precise way of tracing the development of the disease.

To judge a treatment effect, the variation in rating a patient from time to time should be low

Richard G. Langley, MD,a and Charles N. Ellis, MDb Halifax, Nova Scotia, and Ann Arbor, Michigan Evaluating psoriasis with Psoriasis Area and Severity Index, Psoriasis Global Assessment, and Lattice System Physician's Global Assessment

This becomes especially important in clinical trials, where reducing this kind of variability is key to gathering the precise data required in this kind of study.

6. More accessible and easier-to-read data

Last but not least, Legit.Health's interface provides access to all the relevant information about the patient in an easy-to-read manner.

Every data derived from the APASI is clearly displayed on the screen, showing the severity of the affection and the different factors considered by the algorithm when analyzing the image and their scores.

The app also provides a handy graff that shows the evolution of the disease across time and makes following the healing process and the effectiveness of the treatment really easy.

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In conclusion

The revolutionary and innovative APASI represents the future of dermatology. We are giving doctors access to the best tool for the diagnosis of psoriasis and allowing them to practice evidence-based medicine and improve the communication between doctor and patient.

Thanks to Legit.Health, doctors across the globe can improve their correct diagnosis rate by 23% and make treatment easier to follow for the patient by making them active participants in their own recovery.

There is no denying that the use of algorithms that estimate the severity of the disease represents a bright future for the practice of dermatology and that will, without doubt, help advance the field.

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Doctor burnout: 6 simple ways Legit.Health helps reduce it

· 10 min de lectura
Andy Anguilar
CEO at Legit.Health

Doctor Burnout

Introduction

In the healthcare sector, a silent but pervasive challenge impacts the well-being of those at the frontline of patient care. This challenge is doctor burnout, a state of physical, emotional, and mental exhaustion caused by prolonged stress in the medical profession. The repercussions of doctor burnout extend beyond the healthcare providers; they also affect the quality of care received by patients.

At Legit.Health, we recognize the critical importance of supporting healthcare professionals. Our dedication to enhancing the lives of doctors and patients is reflected in our advanced artificial intelligence technology. Designed to streamline clinical workflows, our AI tools aim to alleviate the daily pressures faced by physicians, promoting a more sustainable work environment and better patient outcomes.

Traditional consultation
8 medical acts per hour

Doctor consultation

With Legit.Health
52 medical acts per hour

Doctor remote

Doctor burnout, a serious problem

Doctor burnout represents a significant and complex issue within the medical community. The World Health Organization defines burnout as an occupational phenomenon characterized by chronic work-related distress. It includes emotional exhaustion and irritability, a gradual loss of empathy and an increase in negative feelings such as cynicism, and a sense that your own professional effectiveness is rapidly decreasing.

This pervasive issue transcends borders, cultures, and languages, suggesting that its roots are deeply embedded in the fundamental nature of medical practice. It's not only a matter of individual well-being but also of the efficiency and effectiveness of healthcare systems globally.

While completely eradicating doctor burnout may not be immediately feasible, it is imperative for the medical community and society at large to address the cultural, social, and economic factors contributing to this crisis. As a part of this community, it is our responsibility to critically evaluate and actively work towards mitigating the causes of this widespread concern—a concern that directly impacts the backbone of our healthcare systems and, consequently, our overall societal health.

A bad situation, made worse by COVID-19

The challenge of doctor burnout, already significant prior to COVID-19, has been dramatically intensified by the pandemic. This global health crisis has pushed the medical community to unprecedented limits, further amplifying issues that were already present.

Doctors have long faced intense work hours, emotional and physical fatigue, and a sense of powerlessness within a system that can often feel unwieldy and unsupportive. The pandemic has undone many of the strides made in recent years to manage doctor workloads and improve overall well-being. A startling statistic reveals the depth of this crisis: three in five doctors report feeling depleted at the end of a workday, and 44% describe their work as emotionally draining.

Subjecting healthcare professionals to such relentless stress not only endangers their health but also poses severe risks to patient care and safety. While tackling the systemic roots of this issue remains a long-term goal, immediate and effective strategies are essential to alleviate the burden on doctors and mitigate the consequences of burnout.

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6 Ways Legit.Health reduces doctor burnout

At Legit.Health, we provide a groundbreaking Clinical Data and Communication Tool tailored for modern dermatologists. This tool is designed not just to simplify clinical tasks but to empower patients in their care journey. Below are six key ways our platform reduces the stress and workload contributing to doctor burnout.

Legit.Health is the revolutionary Clinical Data and Communication tool for Next-generation dermatologists that triples the empowerment of patients.

The purpose of deep learning algorithms used in Legit.Health is to help doctors make an informed decision, putting all the processing power and stored data of a cutting-edge computation at the service of the physician's performance.

Legit.Health's algorithms automatically grade lesions just by looking at smartphone images and small patient-reported outcome measures (PROMs). In other words: the tool will automatically fill in most of the dermatology scoring systems, such as PASI, SCORAD, UAS, as well as estimate the pre-malignancy of any lesion.

How does this revolutionary tool for next-generation doctors work?

1. Minimize the time spent on menial tasks

One of the main causes of doctor burnout is not having enough quality time with the patients. After all, the doctor has dedicated years of training to be able to help people, and spending time performing tasks that seem unimportant is quite frustrating.

This is especially true in dermatology, where they often need to linger counting lessions or calculating affected area and severity scores instead of actually interacting with the patient. Sadly, to this day, the best the market could offer to doctors looking to make these tasks easier and faster were digital calculators that still require a high degree of attention.

Thanks to Legit.Health, that has changed, as the new algorithmic artificial intelligence tool can diagnose a pathology and determine its severity in less than 23 seconds, reducing the burnout in doctors who want to focus on the person in front of them.

Our deep learning algorithms offer enhanced decision support for dermatologists. By leveraging advanced computational power and a vast repository of data, Legit.Health assists doctors in making more informed, efficient diagnoses and treatment plans.

2. Reduce time spent generating a paper trail

Many doctors feel that to keep up in their field and carry on with a successful career, they need to be published in top journals. This frustration forces them to carry out the complex clinical trials that push the borders of scientific progress beyond what could be imagined a decade ago.

However, the lack of time in the hands of these physicians supposes a problem yet another time, as the requirements to carry on this kind of study often imply a heavy paper trail that must be kept up to date with precise data. This supposes more time spent filling in forms and registering information manually, leading to more doctor burnout.

Legit.Health helps set up both traditional and decentralized clinical trials thanks to its many algorithmic functions such as our pixel-to-CSV converters, automatic patient-reported outcome measures, match inclusion algorithms and dermatology image quality algorithms.

All this technology is put in the hands of the doctor to make the data collecting process not only fast but also more accurate and objective, as the algorithm doesn't hold any of the bias a human might.

One of the standout features is the ability to automatically grade lesions using only smartphone images and patient-reported outcome measures (PROMs). This means Legit.Health's tool can autonomously complete most dermatology scoring systems including PASI, SCORAD, and UAS, and also assess the pre-malignancy of lesions.

3. Makes communication with the patient easier

Another of the causes of doctor burnout is the perception of a loss of connection with the patient and their needs, as many physicians feel like they are forced to focus on data and statistics and not on the human side of the trade.

It is a well-known fact that the communication between doctor and patient is one of the cornerstones of modern medicine, and the efforts to make that communication more fluid and effective should not fall on the physician's shoulders alone.

That's why one of the biggest focuses of Legit.Health is streamlining the communication by making the process as smooth as possible, connecting patient and doctor through an app that allows for messages, pictures, and requests not only to be filled in remotely but also filtered by priority. All this makes the communication happening at the appropriate pace for the physician.

doctors and patients using Legit.Health

Better communication between patients and doctors build better relationships

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4. Makes the pressure of over-specialization less impactful

The medical profession demands an extraordinarily high level of specialization, with many cases requiring in-depth knowledge not just in a general field, but in very specific conditions. This need for specialization can be particularly burdensome for primary care physicians who often encounter a broad spectrum of diseases, yet may lack the specialized knowledge for accurate diagnosis and treatment.

Legit.Health effectively bridges this gap by providing doctors with access to the consolidated expertise of leading specialists in various diseases. This is coupled with the robust processing capabilities of our deep learning algorithms, offering a swift and reliable source for second opinions.

This feature proves invaluable for primary care doctors, who can utilize Legit.Health to gain quick, objective insights akin to consulting with a specialist, without the time-consuming process of referring to extensive manuals. Dermatologists also benefit when they encounter conditions outside their specific area of expertise, enabling them to use our tool as a trustworthy resource for confirming diagnoses.

Ultimately, by equipping physicians with this level of support and knowledge, Legit.Health significantly alleviates the overwhelming pressure to be an expert in all areas, thus contributing to the reduction of doctor burnout.

5. Comply with applicable regulations, including GDPR

One of the biggest causes of doctor burnout is having to deal with nonmedical matters such as regulations, as many feel they didn't devote their life to the practice of medicine to then expend their limited time and energy on such comparatively menial matters.

Of course, despite not being a very appealing job, taking care of regulations, normative and patient data are crucial for the proper workflow of a medical centre, and it's a task that someone should take care of.

That's why at Legit.Health we have put a strong focus on making it easier to comply with all those regulations, being the GDPR the best example of how we approach data protection and how we take this work off the shoulders of doctors, so they can focus on what's important.

Hospitals are privacy and GDPR compliant with Legit.Health's artificial intelligence

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6. Reducing the number of patient complaints

Lastly, we have to consider the pressure patient complaints put on the back of the doctors. They are of course a valuable tool to avoid bad practices and gather feedback, but often the fear, lack of knowledge or a misunderstanding can be the cause of a complaint that could be avoided.

The strain this puts on physicians contributes to the burnout effect greatly, and the solution to it is clear: to reduce the number of complaints, not by making it harder for the patients to speak their voice, but by reducing the instances where those complaints must not rise.

A better informed and more satisfied patient is less likely to misunderstand or misrepresent a situation, thus improving the patient's experience, we reduce the stress on the doctor.

Legit.Health strives to improve the communication between patient and doctor, making the patient feel understood and in control. Better informed patients make better decisions, take their treatment more seriously, and trust their doctor more.

In conclusion

When we set ourselves to the task of creating the perfect tool to have an impact on our users' quality of life, we did it with both patients and doctors in mind.

We have taken into account the experiences of doctors and the extensive literature produced about this topic in the last years to develop our software so it makes the life of the doctors who use it easier and less stressful.

The main objective is, and will always be, to improve the performance of the doctor and to increase the patient's quality of life.

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Automatic Urticaria Activity Score (AUAS): A Novel Technology for Urticaria Severity Assessment Based on Automatic High-Precision Hive Counting

· 6 min de lectura
Taig Mac Carthy
Co-founder at Legit.Health
Alfonso Medela
CAIO at Legit.Health
Ruben Garcia Castro
Ruben Garcia Castro
Dermatologist
Antonio Martorell
Antonio Martorell
Dermatologists and Medical Lead at Legit.Health
Disclaimer

This post is a summary of a scientific publication published in the Journal of Investigative Dermatology (JID) Innovations. We encourage you to read the whole publication, which is embedded below.

Read the paper

We invite you to read the full paper for yourself, or you can scroll down to read the summary in this educational blog post.

Introduction

We introduce AUAS, an automatic equivalent of UAS that deploys a deep learning lesion-detecting algorithm, called Legit.Health-UAS-HiveNet. Our results show that our algorithm assesses the severity of Chronic Urticaria cases with a performance comparable to that of expert physicians.

Furthermore, the algorithm can be implemented into CADx systems to support doctors in their clinical practice and act as a new endpoint in clinical trials.

The real impact of the Legit.Health-UAS-HiveNet in clinical practice resides on the power to support physicians during not only the diagnostic process but also in the monitoring of patients with chronic types of urticaria, by helping them prescribe treatments and increase the adequacy of treatments.

Automatic Urticaria Activity Score (AUAS): A Novel Technology For Urticaria Severity Assessment Based On Automatic High-Precision Hive Counting Regarding clinical trials, the AUAS has the potential of becoming a new clinical endpoint that could increase both the quality and the quantity of data available to researchers.

Regarding clinical trials, the AUAS has the potential of becoming a new clinical endpoint that could increase both the quality and the quantity of data available to researchers.

Automatic Urticaria Activity Score (AUAS): A Novel Technology For Urticaria Severity Assessment Based On Automatic High-Precision Hive Counting

Authors of the publication

Rubén Garcia

Rubén Garcia

Hospital Universitario Fundación Jiménez Díaz

Alejandro Vilas

Alejandro Vilas

Complejo Hospitalario U. de Ferrol

Laura Vergara

Laura Vergara

Hospital Universitario de Toledo

Taig Mac Carthy

Taig Mac Carthy

Department of Clinical Endpoint Innovation Legit.Health

Fernando Alfageme

Fernando Alfageme

Hospital Puerta de Hierro

Ana María González

Ana María González

Hospital de Zamora

Ignacio Hernandez

Ignacio Hernandez

Medical Data Science Legit.Health

Alfonso Medela

Alfonso Medela

Medical Data Science Legit.Health

What is urticaria severity scoring?

Urticaria is a very common disease characterized by erythematous, edematous, itchy, and transient plaques that involve the skin and mucous membranes. It can be classified into subtypes such as acute spontaneous urticaria, chronic spontaneous urticaria, chronic inducible urticaria, and episodic chronic urticaria.

Diagnosis of chronic urticaria is usually performed through clinical observation. In other words: the assessment of the disease's severity is performed through manual scoring systems that are filled in subjectively.

The most commonly used scoring system is the Urticaria Activity Score (UAS), which can also be used for 7 consecutive days, in which case it is referred to as UAS7.

The problem with visual scoring

The most indisputable limitation of manual scoring systems is the inherent difficulty of human beings to quantify parameters in an objective, stable and precise way.

Humans have a limited ability to count hives, quantify the surface area of a lesion or quantify the redness of an area. This human limitation in parameter estimation is also reflected in the effort and time required to complete the urticaria activity questionnaires, which end up being a very unrewarding task for patients and may result in poor adherence.

On the other hand, scoring systems classify disease severity using a limited range of scores, with three or four categories, such as: none, mild, moderate and severe in the case of the UAS. Indeed, questionnaires have a very high minimum detectable change, as they are discrete ranges rather than continuous scales.

And finally, these questionnaires are susceptible to bias. This is especially true in cases where the patient knows that the treatment they receive will be determined by the information they provide. And due to the asynchronous nature of the reported measure, the clinical team lacks the means to ensure that the values reported by the patient are chronologically accurate or simply truthful, which precludes external verification.

The goal of the Automatic UAS

In this work, we propose the Automatic Urticaria Activity Score (AUAS), an automatic version of the objective part of the UAS that applies convolutional neural networks to count hives automatically with high precision.

The goal is to assist clinicians in filling scoring systems such as the UAS in a more objective way and quicker, which could improve health outcomes and provide high-quality endpoints to measure the effectiveness of the treatments for urticaria.

Explanation of Hives Identification

Explanation of how the artificial intelligence identifies hives in urticaria images.

The solution

We trained trained a hive-counting neural network called Legit.Health-UAS-HiveNet.

To make artificial intelligence accessible to the healthcare professional, we developed a fully integrated CADx system, a web application that integrates Legit.Health-UAS-HiveNet algorithm and calculates the patient-based UAS by looking at images taken with smartphone cameras.

The CADx system works in three stages: image and itchiness input, processing of the images, and the creation of a report with the severity assessment.

CADx System Report

Caption of a full report from the CADx system. The chart at the top right shows the evolution of the urticaria, by plotting the AUAS scores across time.

The report can also combine the scores of multiple images uploaded in the same day to provide the global AUAS score.

In other words: if the user uploads pictures of several body parts, the report of the CADx system shows both the local and the global AUAS scores. The global AUAS is calculated by summing the results of all the images processed by the CADx system.

Automatic Urticaria Report

Automatic Urticaria Activity Score

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Conclusion

In this work, we have presented the AUAS, the first artificial intelligence that automatically fills in the UAS scoring system by looking at smartphone images. The main advances in this algorithm are reducing the time spent by patients in filling in the manual severity scoring system and standardizing urticaria assessment with reduced inter-observer variability and higher reliability.

We were able to overcome clinical assessment variability by developing a merging algorithm that fuses all experts' annotations to create a consensus.

The AUAS as a scoring system presents improved clinimetric properties, but it also carries the advantage of providing a picture of the lesion along with the severity score, which allows researchers greater oversight of studies. In conclusion, we believe that the AUAS and Legit.Health-UAS-HiveNet has the potential to improve health outcomes, reduce costs, and increase the practice of evidence-based medicine in health organizations.

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Use Case: How Torrejón Hospital implemented A.I. into their workflow to manage patients remotely

· 7 min de lectura
Andy Anguilar
CEO at Legit.Health

dermatology with artificial intelligence

Healthcare provider Ribera Salud and Legit.Health started working together in one of the group's hospitals, the Torrejón Hospital, to implement the revolutionary algorithmic technology that, 2 years later, has shown excellent results.

In 2020, the healthcare provider Ribera Salud and Legit.Health started working together in one of the group's hospitals, the Torrejón Hospital, to implement the revolutionary algorithmic technology that, 2 years later, has shown excellent results thanks to the amazing job done by the doctors.

The pandemic could be a blessing in disguise, as it forced the teams to truly push the possibilities of remote care to new heights. In this particular case, the team at Torrejón Hospital needed to follow up on the patient's treatment but could not ensure all of them could go to the medical centre due to COVID-19.

Under these circumstances at hand, Legit.Health was the perfect tool for the job.

Video Summary

Watch Dr Elena Sanchez Largo's presentation: Artificial Intelligence for Remote Monitoring of Patients With Skin Conditions, where she lays out an overview of how the hospital uses Legit.Health's solution.

Next to Dr Sanchez-Largo, the co-founder of Legit.Health, Taig Mac Carthy, explains some of the key components of the solution, such as the severity measure feature, which automates the filling of scoring systems like PASI or SCORAD.

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It is pretty easy to see how a telematic tool like Legit.Health can help to monitor patients remotely. But, how does it manage not to add to the doctor's workload by making them have to worry about yet another system? Let's find out.

First Step: Patient registration

Implementing a new system into an established workflow is a dreaded task for most people. After all, that workflow has been honed and perfected along with years of adjustment and modifications, and including a new element to it can feel like throwing a wrench into a well-oiled machine.

Thankfully, the process of onboarding new patients is both easy and contained in time, as it only needs to happen once.

Once the doctors at Torrejón Hospital had access to their Legit.Health account (a process that barely takes two minutes) they just needed to, as a part of a visit, ask for the Patient's Name, Surname, Email, or Telephone, and input their Pathology information.

Onboarding

The onboarding process only takes part once for each patient.

This process takes no more than a minute, and it only needs to happen once, but if you want to avoid it completely it is possible to avoid this step altogether thanks to Legit.Health's Dermatology API.

In Torrejón Hospital's case, the patients confirmed their account and logged in with their password on the spot, and were instructed by the doctor to check their email or phones for alerts asking them to take pictures for the monitoring.

In total, both doctors and patients have spent around 5 minutes combined to set up this process. And although at Torrejón Hospital the medical team chose to take this process into their own hands, at other centres they leave the patient registration step in the hands of their non-medical teams.

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Second step: Follow up

Once the system had been set up, each Torrejón Hospital patient began a continuous use loop, where the follow-up and monitorization process gets simplified by the algorithm into a single decision by the doctors.

Each time a patient uploads a picture, either because the doctor had set an upload pattern for them on their last visit or because they felt like their condition has changed significantly, the algorithm processes the information.

After analysing the image, if the algorithms detect an increase in severity or in the suspicion of malignancy or pre-malignancy, it will flag the picture as urgent and show it to the doctor first.

Continuous use

Brief description of what Doctors and Patients do when using Legit.Health

The doctor then can, at any time, review all the pictures sent to them by their patients, being able to set up a face-to-face consultation if they think is necessary or simply send a message to the patients with indications about the treatment and the upload pattern.

This not only takes a minimal amount of work for the doctor for each patient, but in fact increases the efficiency significantly.

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The true heroes of the story

The implementation of new technology is most challenging for doctors, as they are already very busy with the clinical workload. Luckily, the great dermatologists at Torrejón are very innovative professionals, who aim at improving their daily practices by finding better ways to care for patients.

The main conclusion here is that technology comes second, and clinical talent comes first. If the medical team is talented and capable, any solution can flourish. And that is precisely what happened when Hospital U. of Torrejón implemented Legit.Health.

The best results we can show you of how this project has worked, are the words of some of the doctors involved:

Dr Elena Sánchez-Largo

Dra. Elena Sanchez Largo

The use of applications for telematic follow-up allows the flow of information between doctor and patient without the need for face-to-face consultations, adjusting it to a more real time and allowing changes in the therapeutic attitude more quickly and effectively.

Dr. Elena Sánchez-Largo, Torrejón Hospital

Dr Elena Sánchez-Largo has put Legit.Health to work with her Psoriasis patients at Torrejón Hospital, achieving great results.

She reports that 27% of her patients benefited from an early adjustment to their treatment, all thanks to the improvement in the communication between doctor and patient.

You can follow Elena Sánchez-Largo on twitter

Dr Marta Andreu

Dra. Marta Andreu

This telematic follow-up prevented school absences in paediatric patients, work absences in adults, and allowed the follow-up of patients in quarantine due to COVID-19 or with diseases that make it difficult to travel. Both patients and their dermatologists showed a high degree of satisfaction with the use of the app, with 100% of patients interested in continuing to use the tool.

Dr. Marta Andreu, Torrejón Hospital

Dr. Marta Andreu puts into perspective the use of the app at Torrejón hospital, saying it was used in patients of Psoriasis, Atopic Dermatitis, Urticaria, Acne, and Hidradenitis Suppurativa. She highlights the good reception of the app from the patients and how its use improved the satisfaction they had with the medical centre.

You can find Dr. Marta Andreu on LinkedIn.

In future posts, we hope to highlight also the work and talent of their colleagues, such as Dr. Leticia Calzado, Dr. Marta Andreu, Dra. Marta Ruano or Dr. Javier Alcántara, to name a few. Truly highly innovative healthcare professionals who are exploring the best ways of caring for their patients and improving health systems.

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This free 23-day trial of Legit.Health gives clinics and hospitals a hands-on look at how to drive increased adherence and improve patient outcomes, as well as improving efficiency and overall quality of life.

Telemedicine: 5 great challenges of implementing it

· 7 min de lectura

Telemedicine

Introduction

In recent years, society as a whole has started to get used to the inevitability of a fully digital world embedding itself in all aspects of life, including healthcare.

And although there are many benefits the applied practice of telemedicine brings, there are also challenges to overcome before we can start to reap the benefits of this novel way of understanding healthcare.

Dermatologists highlight the usefulness of images in remote monitoring of chronic pathologies. That is why the tool is still in use today in our care activity, and we continue to explore new uses and improvements to it in the future.

Dr. Marta Andreu, Torrejón Hospital

Telemedicine is a reality, not a prediction

Digital disconnection is no longer a possibility for the average person. To this day and age, where every home has an internet connection and every pocket is laced with a smartphone, trying to deny the power the global net holds over our daily lives is as ridiculous as impractical.

Of course, the healthcare world is no different in that regard. Those who try to resist this wave of modernization are quickly being left behind or are being forced to adapt. It is common for concepts like telemedicine to be treated in future tense, but the COVID-19 pandemic has shown us that the time of predictions is over.

It is time to face the challenges that this new form of healthcare brings to us.

The past of remote care

One of the first practical usages of telemedicine happened in the late 1950s, in the state of Nebraska, where a state hospital and a psychiatric institution implemented a closed-circuit television link in order to help to monitor the conditions of patients remotely.

Although technology did rapidly advance in the following decades, its application to the remote care of patients never got through to be majorly used. Thus far, the most notorious advancement consists in a telephonic consultation, despite being widely considered an insufficient measure by both physicians and patients.

Today, the urge of using telemedicine is rather a reality than a remote possibility. The pandemic of 2020 rapidly changed the perception and necessities of many, forcing the healthcare community to prioritize efficiency and implement all the tools at their disposal.

What does the future look like?

Even though it is foolish to try to predict what future technologies will be developed in the next decade, we can learn from the most recent advancements to make an educated guess on the scientifical progress that will shape the future of healthcare.

An example can be the expansion of portable wirelessly accessible sensors, built into smartphones, smartwatches and other wearable devices, that allow doctors to collect data about their patients in real life and with minimal interference on their day-to-day life.

Another very promising prospect is Artificial Intelligence. Projects based on this technology have shown great results in the last couple of years in areas as diverse as oncology, radiotherapy, neurology, and dermatology.

One shining example of the use of Artificial Intelligence is Legit.Health, the revolutionary Clinical Data and Communication tool for Next-generation dermatologists that applies clinically validated algorithms and computer vision technology to enhance their medical practice.

The purpose of the deep learning algorithms is to relieve doctors from the tedious manual calculation of scoring systems and to allow the practice of a more objective evidence-based dermatology while speeding up the pathology reporting process and increasing patients' autonomy and control.

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The 5 challenges of modern telemedicine

Financing

As commonly happens when suggesting to introduce a new technology or infrastructure, detractors rise money as an issue. However, considering only the potential costs of overhauling the medical system to make it more telematic is rather reductive unless the potential savings and profits are taken into account.

Balancing the economic costs and benefits of telemedicine will be without any doubt one of the biggest challenges to overcome, and the companies that offer services in this field need to keep that in mind. That's why Legit.Health keeps its pricing flexible and its technological requirements simple, so that any medical centre or institution can afford the small investment required.

Regulations

Another big challenge to overcome before adopting a fully telemetric system has to do with laws and regulations. It varies from country to country, but anywhere you go in the world, the implementation of medical devices is heavily regulated.

Additionally, if those devices manage patient information, laws like GDPR come into place to guarantee the security and integrity of the data. That's why any attempt of leaning into telemedicine requires addressing these issues.

Legit.Health not only has the European CE marking, but is a tool that is fully compliant with the GDPR as well as all other European standards, taking some of the burden and the hard work associated with keeping these matters in check. In other words, your work will be mostly done for you when the time for an audit comes.

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Adoption

All the fancy technology in the world is equally useful or wasteful if those who are meant to use it do not know how to or do not want to adopt it. In this case, the challenge is twofold, as doctors and patients must come to terms with the idea of including these new technologies in the dynamics that have been ingrained in our collective mind for centuries.

Not only we need to convince patients that they can effectively communicate with their doctors via computers and smartphones, but we also need to help doctors adapt their usual routines to this novel systems.

This is why, Legit.Health has been developed with ease of use in mind. After being taken by the patient, the picture is analysed by the clinically validated algorithm and its results are sent to the doctor, who benefits from the consistency of the data generated by this process and greatly facilitates the work of monitoring rashes and disease development.

Telemedicine with Legit.Health

Technology

Technology has been the focus of telemedicine for a long time. However, telemedicine is really about the services and not about the uniqueness of the latest technology. An approach based on services and positive health outcomes means that no matter how much technology changes, the medical centre will have a system in place to implement it.

Legit.Health enables medical centres to merge technology and service into one easy-to-use package, offering both a plethora of tools for the medical practice and multiple options to provide their patients with the services they need to feel cared for.

Evidence

In the medical world, good ideas amount to nothing if they aren't backed by solid clinical evidence. This is true for procedures, drugs, medical devices and, of course, general concepts or services such as telemedicine.

Gathering scientific evidence might be the most difficult challenge telemedicine has to overcome before it can succeed. Every system, application, medical device or technology put in place to make this change possible must be thoroughly tested before it's implemented into a real-life setting.

Legit.Health participates in a myriad of clinical trials that pit algorithmic technology and application design against real medical scenarios in several European medical centres. As a company, we highly value our presence on medical journals, and helping to advance the field of dermatology is one of our main purposes.

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In conclusion

Although the road ahead is long and tortuous, the healthcare community as a whole has already begun to take the first steps towards a future where telemedicine is a reality.

Thanks to technological advances by companies such as Legit.Health and initiatives by medical service providers such as DKV, to name a few, both patients and doctors are becoming more accustomed to the reality of remote medicine.

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This free 23-day trial of Legit.Health gives clinics and hospitals a hands-on look at how to drive increased adherence and improve patient outcomes, as well as improving efficiency and overall quality of life.