Clinical validation of AI for continuous and remote monitoring of the severity of the patient's condition
Conclusions
The study conducted to evaluate the clinical performance, efficacy, and safety of the device has yielded promising results. The comprehensive analysis of the CUS, Data Utility questionnaire, SUS, and Patient Satisfaction questionnaire has provided valuable insights into the tool's effectiveness in supporting dermatologists in their clinical practice.
The observed sample mean of 76.67 on the CUS suggests that the device has been positively received by the participating specialists. Noteworthy is the unanimous agreement on the ease of use and the high rating for optimizing time according to each patient's needs. It's also worth noting that, despite that the medical device was positively rated by the specialists, the goal of achieving a mean of 80.00 on the CUS was not reached. This result was due to the lower sample size of specialists who completed the questionnaire. In this way, an outlier, and due to the small sample size, impacted disproportionately the overall result, especially for questions 7, 8, 9 and 11. As can be seen by the higher standard deviation and lower mean average in these specific questions. We need to take this fact into account for the following studies and implement measures to mitigate this effect, such as a larger sample size, which could have diluted the effect of the outliers over the statistical outcomes, or predefined management for outliers.
Additionally, the device demonstrated efficiency in generating reports, receiving high ratings from the specialists. These outcomes affirm the device's potential to streamline clinical workflows and enhance patient care.
The Data Utility questionnaire revealed unanimous agreement among specialists regarding the usefulness of a device to facilitate their regular practice. Moreover, the majority expressed a preference for utilizing a device to identify the severity of cases, indicating its potential as an aid in diagnostic support.
The System Usability Scale assessment further underlines the positive reception of the device. Specialists found the tool to be user-friendly, with high scores indicating ease of navigation and minimal complexity. The unanimous agreement on the ease of use and the absence of perceived expertise required to navigate the device emphasize its accessibility and suitability for clinicians.
Patient satisfaction is a crucial aspect of any medical tool or platform. The results of the Patient Satisfaction questionnaire indicate a generally positive response from patients. They found the device to be easy to use, useful in monitoring their condition, and were satisfied with the care provided through the device.
In conclusion, the device has demonstrated notable clinical utility, usability, and safety in the evaluation of dermatological pathologies. The positive responses from both specialists and patients affirm its potential to serve as a valuable clinical decision-support tool. Further research and real-world application are warranted to explore the device's broader impact on dermatological practice and patient care.
Summary
- Code: LEGIT_COVIDX_EVCDAO_2022
- Status: Finished
- Start date: March 3rd, 2022
- Finish date: October 23rd, 2023
- Acceptance criteria:
- A score of 8 or higher in the Clinical Utility Score (CUS) filled by the medical staff
Background and rationale
The COVID-19 pandemic has disrupted healthcare systems globally, particularly in managing non-urgent medical conditions, including dermatology. The reduction of in-person consultations has left many dermatological patients without timely care, exacerbating conditions such as skin cancer and chronic diseases like psoriasis and eczema. The pandemic has underscored the critical need for an efficient, remote diagnostic system to ensure continuous monitoring and timely intervention for dermatological conditions, particularly in countries with an already imbalanced ratio of dermatologists to patients.
Currently, the diagnosis and monitoring of dermatological conditions heavily rely on subjective human assessments, which are prone to inconsistencies and biases. Physicians face challenges in quantifying lesions or disease severity accurately, and patient-reported outcomes often lack reliability. This situation has been further complicated by COVID-19, as patients avoid in-person visits, leading to delayed diagnoses and worsening of conditions. There is an urgent need for reliable tools that can support remote diagnosis and activity tracking of skin pathologies, which would reduce the risks of transmission while maintaining high standards of care.
This study seeks to address these challenges by clinically validating an innovative artificial intelligence (AI) tool designed for remote and continuous monitoring of dermatological conditions. Leveraging the Legit.Health platform, this AI-powered tool can enhance diagnostic precision, reduce human error, and improve the management of chronic skin diseases. By enabling patients to be evaluated from home and providing physicians with a more objective measurement tool, this technology has the potential to improve both patient outcomes and healthcare efficiency.
Design
A prospective, observational and analytical study designed to evaluate the effectiveness of the device in remotely monitoring chronic dermatologic pathologies. The research encompassed a diverse cohort of 180 patients, which represent the studied population with various dermatological conditions. Data collection will include questionnaires, photograph analysis, and patient satisfaction surveys. The study adhered to strict ethical guidelines, ensuring patient confidentiality and compliance with international standards. Patients were provided with detailed information and informed consent. The study's robust methodology aimed to assess the clinical utility and usability of the device.
Product Identification
| Information | |
|---|---|
| Device name | Legit.Health Plus (hereinafter, the device) |
| Model and type | NA |
| Version | 1.0.0.0 |
| Basic UDI-DI | 8437025550LegitCADx6X |
| Certificate number (if available) | MDR 792790 |
| EMDN code(s) | Z12040192 (General medicine diagnosis and monitoring instruments - Medical device software) |
| GMDN code | 65975 |
| Class | Class IIb |
| Classification rule | Rule 11 |
| Novel product | FALSE |
| Novel related clinical procedure | FALSE |
| SRN | ES-MF-000025345 |