AcneIDEI_2023NCT06263413
Clinical Workflow Optimization Using Artificial Intelligence for Dermatological Conditions
An observational study of Acne and Acne Vulgaris, run by AI Labs Group S.L at 1 site in Spain.
Trial summary
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. Read more about this study
- Who is it for?
- Ages 16 years and older
- Conditions the study is for
- Acne, Acne Vulgaris, Alopecia, Androgenetic
- How many people
- 150 participants
- Where
- 1 siteSpain
- Study dates
- 15 Jan 2024to 30 Sep 2024
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 16 years and older
- All sexes
- No healthy volunteers
- Child, Adult, Older adult
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
Who may be able to join
- 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.
Who cannot join
- Patients deemed by the investigator to be unable or unwilling to comply with the study procedures.
Trial locations and contacts
1 site in 1 country.
Miguel Sánchez-Viera, PhD contact
Spain1 site, 1 recruiting
- Recruiting
IDEI Hospital
Madrid, 28009
Miguel Sánchez-Viera, PhD, +34 915740990, sanchez.viera@ideidermatologia.com
Miguel Sánchez-Viera, PhD
About this study
Official title: 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.
Read more
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.
Read the 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.
- Keywords
- Acne, Androgenetic alopecia, Pigmented lesions, Artificial Intelligence, Algorithms, Classification, Detection
- Medical subject headings
- Acne Vulgaris, Alopecia
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| 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 being measured
The primary outcome is the main question the study is designed to answer.
Concordance between the physician's diagnosis and that of the tool.
Analysis of concordance between the diagnosis issued by the dermatologist and that determined by the Legit.Health tool.
Measured: At the moment of enrollment up to 1 year
Agreement of detected malignancy between the dermatologist and Legit.Health tool
Correlation analysis of the suspected malignancy between the dermatologist and the Artificial Intelligence tool
Measured: At the moment of enrollment up to 1 year
Secondary outcomes (2)
Acne severity
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
Measured: At the moment of enrollment up to 1 year
Severity of alopecia
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
Measured: At the moment of enrollment up to 1 year
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted16 Feb 2024
- Study start15 Jan 2024
- Primary completion30 Jun 2024 (estimated)
- Study completion30 Sep 2024 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for AcneStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Other
- Enrolment
- 150 participants (estimated)
Sponsor and investigators
- Lead sponsor
- AI Labs Group S.L
- Sponsor type
- Industry (pharma, biotech, devices)
- Collaborators
- Instituto de Dermatología Integral (IDEI)
- Responsible party
- Sponsor
- Investigators
- Miguel Sánchez-Viera, PhD, Principal investigator, IDEI Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06263413
- Sponsor's protocol ID
- 24.12.2266-GHM
- Acronym
- IDEI_2023
- Status last verified
- Mar 2024
- First submitted
- 8 Feb 2024
- Last updated
- 19 Mar 2024
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 19 Mar 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Optimization of Clinical Workflow in Patients With Various Dermatological Conditions Through Artificial Intelligence
- ClinicalTrials.gov ID
- NCT06263413
- Acronym / sponsor ID
- IDEI_2023 / 24.12.2266-GHM
- Keywords
- Acne, Androgenetic alopecia, Pigmented lesions, Artificial Intelligence, Algorithms, Classification, Detection
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 150 participants (estimated)
- Lead sponsor
- AI Labs Group S.LIndustry (pharma, biotech, devices)
- Collaborators
- Instituto de Dermatología Integral (IDEI)
- Study start
- 15 Jan 2024 (actual)
- Primary completion
- 30 Jun 2024 (estimated)
- Study completion
- 30 Sep 2024 (estimated)
- First posted
- 16 Feb 2024 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
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 design
- Observational model
- Cohort
- Time perspective
- Other
- Number of arms
- 3
| Arm | Type | Receives |
|---|---|---|
| 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 |
Who may qualify
- Ages
- 16 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older adult
- 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
Key inclusion criteria (6 listed)
- 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.
Key exclusion criteria (1 listed)
- Patients deemed by the investigator to be unable or unwilling to comply with the study procedures.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
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.
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
2 secondary outcomes
Acne severity
Time frame: At the moment of enrollment up to 1 year
Severity of alopecia
Time frame: At the moment of enrollment up to 1 year
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 19 Mar 2024.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Miguel Sánchez-Viera, PhD contact
Miguel Sánchez-Viera, PhD principal investigator
IDEI Hospital
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Acne and Acne Vulgaris, run by AI Labs Group S.L at 1 site in Spain.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 6 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 19 Mar 2024. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Spain. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Miguel Sánchez-Viera, PhD (sanchez.viera@ideidermatologia.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Concordance between the physician's diagnosis and that of the tool. (time frame: At the moment of enrollment up to 1 year). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 19 Mar 2024.