Clinical Workflow Optimization Using Artificial Intelligence for Dermatological Conditions (IDEI_2023)

March 18, 2024 updated by: AI Labs Group S.L

Optimization of Clinical Workflow in Patients With Various Dermatological Conditions Through Artificial Intelligence

Artificial intelligence (AI) based on imaging holds tremendous potential to enhance visual diagnostic accuracy in the medical field. Amid the COVID-19 pandemic, limited access to in-person healthcare services drove shifts in medical care, hastening the adoption of telemedicine. In this context, AI usage for triage and decision support may be crucial for professionals to manage workload and improve performance. In dermatology, pigmented lesions, acne, and alopecia are three recurring pathology groups with high demand in dermatological centers. Both triage, clinical evaluation, and patient follow-up require in-person resources and specialist dedication. Employing tools like AI can benefit these professionals in reducing such processes and optimizing workload.

Advancements in image recognition and interpretation, as well as in artificial intelligence, have spurred innovations in diagnosing various pathologies, including skin conditions. Computer-Aided Diagnosis (CAD) systems and other algorithm-based technologies have demonstrated the ability to classify lesion images with a competency comparable to that of an expert physician.

In this study, the Legit.Health tool, developed by AI LABS GROUP S.L., which utilizes artificial intelligence to optimize clinical flow and patient care processes for skin conditions, will be evaluated. The purpose of this tool is to automatically prioritize patients with greater urgency, assign the type of consultation (dermatological or aesthetic), enhance diagnostic capability and detection of malignant pigmented lesions in auxiliary staff, and provide a visual record (photograph) of the condition for later review by external experts.

Thus, the main objective of this study is to validate that Legit.Health, based on Artificial Intelligence, improves efficiency in clinical flow and patient care processes, thereby reducing time and cost of patient care through enhanced diagnostic accuracy and severity determination.

The secondary objectives focus on measuring the diagnostic performance of Legit.Health:

Demonstrate that Legit.Health enhances healthcare professionals' ability to detect malignant or suspicious pigmented lesions.

Demonstrate that Legit.Health improves healthcare professionals' ability and precision in measuring the degree of involvement in patients with female androgenetic alopecia.

Demonstrate that Legit.Health improves healthcare professionals' ability and precision in measuring the degree of involvement in patients with acne.

Additionally, the study aims to assess the utility of this tool:

Automate the triage/initial assessment process in patients presenting with pigmented lesions.

Evaluate the reduction in healthcare resources usage by the center by reducing the number of triage consultations and directing the patient directly to the appropriate consultation (esthetic or dermatological).

Evaluate Legit.Health's usability by the patient. Demonstrate that Legit.Health increases specialist satisfaction. Evaluate the reduction in healthcare resources usage by reducing the number of triage consultations and directing the patient directly to the appropriate consultation, whether in aesthetic or dermatological settings.

Methodology Study Design Type This is an observational study, both prospective with a longitudinal character and retrospective case series.

Study Period This study estimates a recruitment period of 3 months. The total study duration is estimated at 6 months, including the previous time for retrospective analysis and the necessary time after recruiting the last subject for database closure and editing, data analysis, and preparation of the final study report.

The total study duration for each participant with pigmented lesions will be 1-3 months. The duration for patients with acne and alopecia will be 1 day.

Study Population Adult patients (≥ 18 years) with skin pathologies treated at the Dermatology Unit of IDEI.

Study Overview

Status

Recruiting

Conditions

Detailed Description

Artificial intelligence (AI) based on images presents enormous potential for improving visual diagnostic accuracy in the medical field. During the COVID-19 pandemic, limited access to in-person healthcare services drove changes in medical care, accelerating the adoption of telemedicine. In this context, the use of AI for triage and decision support can be crucial for professionals to manage workload and improve performance. In dermatology, pigmented lesions, acne, and alopecia are three recurring pathology groups with high demand in a dermatological center. Both triage of these patients, clinical evaluation, and their follow-up require in-person resources and the dedication of the specialist and staff. The use of tools like AI can benefit these professionals in reducing these processes and optimizing the workload.

Advances in image recognition and interpretation, as well as in artificial intelligence, have driven innovations in diagnosing various pathologies, including skin conditions. Computer-Aided Diagnosis (CAD) systems and other algorithm-based technologies have demonstrated their ability to classify lesion images with a competency comparable to that of an expert physician.

In this study, the Legit.Health tool, developed by AI LABS GROUP S.L., which uses artificial intelligence to optimize clinical flow and the care process of patients with skin conditions, will be evaluated. The purpose of this tool is the automatic prioritization of patients with greater urgency, assigning them the type of consultation (dermatological or aesthetic), improving the diagnostic capacity and detection of malignant pigmented lesions in auxiliary staff, as well as providing a visual record (photograph) of the condition for later review by external experts.

Thus, the main objective of this study is to validate that the Legit.Health tool, based on Artificial Intelligence, improves efficiency in clinical flow and the care process of patients, reducing the time and cost of care per patient through enhanced diagnostic accuracy and determination of the degree of malignancy or severity.

The secondary objectives focus on measuring the diagnostic performance of Legit.Health:

Demonstrate that Legit.Health improves the ability of healthcare professionals to detect malignant or suspicious pigmented lesions.

Demonstrate that Legit.Health improves the ability and precision of healthcare professionals in measuring the degree of involvement in patients with female androgenetic alopecia.

Demonstrate that Legit.Health improves the ability and precision of healthcare professionals in measuring the degree of involvement in patients with acne.

Additionally, the study aims to assess the utility of this tool:

Automate the triage/initial assessment process in patients consulting for pigmented lesions.

Evaluate the reduction in healthcare resource usage by the center by reducing the number of triage consultations and directly referring the patient to the appropriate consultation (esthetic or dermatological).

Evaluate Legit.Health's usability by the patient. Demonstrate that Legit.Health increases specialist satisfaction. Evaluate the reduction in healthcare resource usage by reducing the number of triage consultations and directly referring the patient to the appropriate consultation, whether in aesthetic or dermatological settings.

Methodology:

Study Design Type:

This is an observational study, both prospective with a longitudinal character and retrospective case series.

Study Period:

This study estimates a recruitment period of 3 months.

The total study duration is estimated at 6 months, including the previous time for retrospective analysis and the necessary time after recruiting the last subject for database closure and editing, data analysis, and preparation of the final study report.

The total study duration for each participant with pigmented lesions will be 1-3 months. The duration for patients with acne and alopecia will be 1 day.

Study Population:

Adult patients (≥ 18 years) with skin pathologies treated at the Dermatology Unit of IDEI.

Study Type

Observational

Enrollment (Estimated)

150

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Contact Backup

Study Locations

  • Spain
      • Madrid, Spain, 28009
        • Recruiting
        • IDEI Hospital
        • Sub-Investigator:
          • Alfonso Medela, MsC
        • Sub-Investigator:
          • Taig Mac Carthy, MsC
        • Contact:
        • Principal Investigator:
          • Miguel Sánchez-Viera, PhD
        • Sub-Investigator:
          • Concetta Alessandro, MD
        • Sub-Investigator:
          • Alejandra Capote, MD
        • Sub-Investigator:
          • Pablo López-Andina, MD
        • Sub-Investigator:
          • Allison Marie Bell-Smythe Sorg, MD
        • Sub-Investigator:
          • Alejandra Vallejos, MD
        • Sub-Investigator:
          • Isabel del Campo, MD
        • Sub-Investigator:
          • Juliana Machado, MD
        • Sub-Investigator:
          • Raúl Lucas-Escobar, MD
        • Sub-Investigator:
          • Beatriz Torres

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Child
  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Sampling Method

Non-Probability Sample

Study Population

Patients with pigmented lesions and suspected malignancy, patients diagnosed with inflammatory acne and women with androgenetic alopecia. All these people will be treated at the dermatology service of IDEI hospitals

Description

Inclusion Criteria:

  • Patients aged 18 years or older (16 years for acne).
  • Patients with pigmented lesions meeting any of the following conditions:
  • Presenting for the first time with a pigmented lesion.
  • Previously scheduled for dermoscopy consultation for the first time or for review of pigmented lesions.
  • Patients with active inflammatory acne.
  • Women with androgenetic alopecia.

Exclusion Criteria:

  • Patients deemed by the investigator to be unable or unwilling to comply with the study procedures.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Patients with pigmented lesions and suspected malignancy
Patients treated at IDEI hospitals and with pigments skin lesions, which are suspected malignancy. The practitioners will take a photo of the lesion and upload into the tool so as to confirm both the diagnosis and suspicion of malignancy
Patients diagnosed with acne
Patients treated at IDEI hospitals and diagnosed with acne. Practitioners will take a photo of patients' face and upload it into the tool so as to check the severity of acne and compare it with the gold standard
Patients diagnosed with femenine androgenetic alopecia
Patients treated at IDEI hospitals and diagnosed with femenine androgenetic alopecia. Practitioners will take a photo of the top of the head and upload it into the tool so as to check the severity of alopecia and compare it with the gold standard

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Concordance between the physician's diagnosis and that of the tool.
Time Frame: At the moment of enrollment up to 1 year
Analysis of concordance between the diagnosis issued by the dermatologist and that determined by the Legit.Health tool.
At the moment of enrollment up to 1 year
Agreement of detected malignancy between the dermatologist and Legit.Health tool
Time Frame: At the moment of enrollment up to 1 year
Correlation analysis of the suspected malignancy between the dermatologist and the Artificial Intelligence tool
At the moment of enrollment up to 1 year

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Acne severity
Time Frame: At the moment of enrollment up to 1 year
Severity of acne assessed by both physicians and Legit.Health tool through lesion counting. A correlation analysis will be performed to check differences of criteria between them
At the moment of enrollment up to 1 year
Severity of alopecia
Time Frame: At the moment of enrollment up to 1 year
Severity of androgenetic alopecia assessed by both physicians and Legit.Health tool with the Ludwig scale. A correlation analysis will be performed to check differences of criteria between them
At the moment of enrollment up to 1 year

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

AI Labs Group S.L

Collaborators

Instituto de Dermatología Integral (IDEI)

Investigators

  • Principal Investigator: Miguel Sánchez-Viera, PhD, IDEI Hospital

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

January 15, 2024

Primary Completion (Estimated)

June 30, 2024

Study Completion (Estimated)

September 30, 2024

Study Registration Dates

First Submitted

February 8, 2024

First Submitted That Met QC Criteria

February 15, 2024

First Posted (Actual)

February 16, 2024

Study Record Updates

Last Update Posted (Actual)

March 19, 2024

Last Update Submitted That Met QC Criteria

March 18, 2024

Last Verified

March 1, 2024

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • 24.12.2266-GHM

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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