Smak Gregoor Anna M, Sangers Tobias E, Eekhof Just Ah, Howe Sydney, Revelman Jeroen, Litjens Romy Jm, Sarac Mohammed, Bindels Patrick Je, Bonten Tobias, Wehrens Rik, Wakkee Marlies
Department of Dermatology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, the Netherlands.
Department of Public Health and Primary Care, Leiden University Medical Centre, Leiden, the Netherlands.
EClinicalMedicine. 2023 May 25;60:102019. doi: 10.1016/j.eclinm.2023.102019. eCollection 2023 Jun.
Artificial intelligence (AI)-based mobile phone apps (mHealth) have the potential to streamline care for suspicious skin lesions in primary care. This study aims to investigate the conditions and feasibility of a study that incorporates an AI-based app in primary care and evaluates its potential impact.
We conducted a pilot feasibility study from November 22nd, 2021 to June 9th, 2022 with a mixed-methods design on implementation of an AI-based mHealth app for skin cancer detection in three primary care practices in the Netherlands (Rotterdam, Leiden and Katwijk). The primary outcome was the inclusion and successful participation rate of patients and general practitioners (GPs). Secondary outcomes were the reasons, facilitators and barriers for successful participation and the potential impact in both pathways for future sample size calculations. Patients were offered use of an AI-based mHealth app before consulting their GP. GPs assessed the patients blinded and then unblinded to the app. Qualitative data included observations and audio-diaries from patients and GPs and focus-groups and interviews with GPs and GP assistants.
Fifty patients were included with a median age of 52 years (IQR 33.5-60.3), 64% were female, and 90% had a light skin type. The average patient inclusion rate was 4-6 per GP practice per month and 84% (n = 42) successfully participated. Similarly, in 90% (n = 45 patients) the GPs also successfully completed the study. GPs never changed their working diagnosis, but did change their treatment plan (n = 5) based on the app's assessments. Notably, 54% of patients with a benign skin lesion and low risk rating, indicated that they would be reassured and cancel their GP visit with these results (p < 0.001).
Our findings suggest that studying implementation of an AI-based mHealth app for detection of skin cancer in the hands of patients or as a diagnostic tool used by GPs in primary care appears feasible. Preliminary results indicate potential to further investigate both intended use settings.
SkinVision B.V.
基于人工智能（AI）的手机应用程序（移动健康）有潜力简化基层医疗中对可疑皮肤病变的护理。本研究旨在调查一项将基于人工智能的应用程序纳入基层医疗并评估其潜在影响的研究的条件和可行性。
我们于2021年11月22日至2022年6月9日在荷兰的三个基层医疗机构（鹿特丹、莱顿和卡特韦克）开展了一项试点可行性研究，采用混合方法设计来实施一款用于皮肤癌检测的基于人工智能的移动健康应用程序。主要结果是患者和全科医生（GP）的纳入率和成功参与率。次要结果是成功参与的原因、促进因素和障碍，以及对未来样本量计算的两种途径的潜在影响。患者在咨询全科医生之前被提供使用基于人工智能的移动健康应用程序。全科医生在不知情的情况下对患者进行评估，然后再了解应用程序的情况。定性数据包括患者和全科医生的观察结果和音频日记，以及与全科医生和全科医生助理的焦点小组讨论和访谈。
纳入了50名患者，中位年龄为52岁（四分位间距33.5 - 60.3），64%为女性，90%为浅肤色类型。每个全科医生诊所每月的平均患者纳入率为4 - 6名，84%（n = 42）成功参与。同样，90%（n = 45名患者）的全科医生也成功完成了研究。全科医生从未改变他们的工作诊断，但确实根据应用程序的评估改变了他们的治疗计划（n = 5）。值得注意的是，54%患有良性皮肤病变且风险评级低的患者表示，这些结果会让他们放心并取消去看全科医生的预约（p < 0.001）。
我们的研究结果表明，研究在患者手中使用基于人工智能的移动健康应用程序进行皮肤癌检测或作为基层医疗中全科医生使用的诊断工具似乎是可行的。初步结果表明有潜力进一步研究这两种预期的使用场景。
SkinVision B.V.
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