Department of dermatology, Skane University Hospital
Lund, 22185, Sweden
Location status: Recruiting
NCT Number: NCT05033678
The study has 2 parts. Part 1 will investigate the effects of introducing teledermoscopy in clinical practice, more specifically the change in referral patterns, the risk of undetected skin cancers and the effect on diagnostic accuracy in general practitioners.
Part 2 will investigate how to introduce artificial intelligence (AI) within teledermocsopy. In this study the investigators will measure the diagnostic accuracy of teledermoscopic assessors that had access to the results of artificial intelligence algorithm compared to those who did not.
Data will be collected through teledermoscopic referrals, patient records, national registries and questionnairs.
Interested in participating?
Request Info15 year and older
All sexes
Observational
Lund, 22185, Sweden
Location status: Recruiting
Study objective:
Material and methods:
4.2. In part 2, measures of diagnostic accuracy will be estimated comparing dermatologists with and without access to diagnostic algorithm support. Measures reported include sensitivity, specificity, and Area under ROC-curve (AUROC). The study will also report the impact the results of the artificial intelligence has on the willingness to change a diagnosis or a management plan.
5.2. To detect a difference in "unimaged skin cancers" between teledermoscopy and conventional care of patients 1200 cases and 2400 controls need to be included.
5.3. To detect a 10% difference in sensitivity/ specificity of diagnostic ability in PCPs before and after working with teledermoscopy 3400 patients need to be included.
5.4. To investigate how artificial intelligence should be implemented in clinical care the investigators have calculated that 6000 patients are needed to detect a 10% difference in sensitivity and specificity in the subgroups.
Ethical considerations and data management:
Data will be collected using Dermicus®, a CE-certified digital platform and mobile application. With the application downloaded on iPhones®, locked for any other uses, the history of the patients are registered. Then, by connecting the iPhone to a dermoscope, macroscopic and dermoscopic images are captured. All data will be stored on the servers of the health care region of Skåne, where the studies are conducted. Once a case has been created and sent to the data base all information will be deleted from the iPhone®. Additional data will also be retrieved from relevant medical records, e.g. histopathological diagnosis, and manually registered in an electronic database at a highly secure location (LUSEC/ REDCap provided by Lund University) . Data collected from PCP and dermatologists by questionnaires will also be registered in this data base by means of electronic surveys (REDCap). Information from primary care on total number of visits, referrals to dermatologists and referrals to pathology regarding skin lesions will be extracted from patient administrative systems. Age- and sex matched controls will be used for the study investigating missed skin cancer. These controls will be randomly selected from patients that was referred to a skin clinic by paper referral during the same period as the teledermoscopically referred patients were gathered. Algorithms for skin cancer diagnosis will be implemented in the web platform of Dermicus for the studies of introduction of artificial intelligence. Teledermoscopic assessors will be instructed on when and how to use these different tools.
Every month the newly entered data will be checked for completeness, and in the case of missing data, reminders to participating investigators will be send.
When the data sets are complete, identifiers (such as personal identification number) will be replaced by a code kept secure at a different location than the data set. Data will thereafter be extracted from the data base to perform statistical analysis.
The study is approved by the Swedish Ethical Review Authority and all relevant approvals for data extraction and data storage has been obtained.
Healthy volunteers accepted: Yes
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Exclusion criteria
Assessors of teledermoscopy will be randomly assigned to use the results of artificial intelligence when the assess a teledermoscopic case.
Time frame: 2 years
Measure how referral patterns are affected by the introduction of teledermoscopy
Time frame: 8 years
Measuring if the diagnostic accurcy differs depending on if physician can see the results of the artificial intelligence.
Time frame: 2 years
Measuring if the risk of undetected skin cancer increases with the use of teledermoscopy
Time frame: 8 years
Measuring if the diagnostic accuracy and the willingness to reconsider the preliminary diagnosis differs according to when in the process a physician is presented with the results of the artificial intelligence
Time frame: From 2021 to 2025
We will investigate whether the use of image enhancements in teledermoscopy affects the diagnostic accuracy in teledermaoscopy
Time frame: 2021-2024
We will investigate if there are special situations when single reader evaluations are insufficient in teledermoscopy
Contact information is provided by the study sponsor or research team.
Region Skane
Other
Teledermoscopy and Artificial Intelligence: Effects of Implementation in Clinical Practice
OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.
View the official ClinicalTrials.gov record (opens in a new tab)This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.
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