Primary care general practitioners encounter significant challenges in diagnosing and managing skin diseases, highlighting the urgent need for artificial intelligence (AI) assisted systems. Although AI has the potential to improve diagnostic and treatment efficiency, research on its application in primary care settings remains limited.

To investigate the effectiveness and impact of an AI-assisted system in supporting primary care general practitioners with the diagnosis and management of skin diseases.

From December 2022 to March 2024, 19 general practitioners from community health centers in Hangzhou were voluntarily recruited for this study. They were randomly divided into two groups: an AI group with 10 physicians and a control group with 9 physicians. During this period, these physicians treated a total of 90 patients with skin diseases: 50 in the AI group and 40 in the control group. Physicians in the AI group utilized the Ruifu AI-assisted system for diagnosing and managing dermatological diseases, whereas those in the control group followed standard treatment protocols without AI assistance. Both groups compiled patients' medical records, auxiliary examination reports, and photographs of skin lesions during consultations. Two skin disease experts were invited to conduct remote consultations to evaluate the diagnostic accuracy of the two groups. On the first day (1 d) and the fourteenth day (14 d) of treatment, patients underwent assessments using the Dermatology Life Quality Index (DLQI), and satisfaction surveys were conducted separately for patients in the AI and control groups. A questionnaire survey was administered to doctors in the AI group to assess their experience with the Ruifu AI-assisted system.

No significant differences were observed in gender, age, or education level among patients in the AI and control groups (P>0.05), nor among physicians in terms of gender, age, education, and professional titles (P>0.05). The AI group's general practitioners achieved higher diagnostic accuracy for skin diseases than those in the control group (64.0% vs 37.5%, P=0.012). Fourteen days post-treatment, improvements in the DLQI scores were observed in both the AI and control groups, with significant differences (P<0.05), and the improvement in the AI group was more significant (P<0.05). The satisfaction level of the AI group was higher than that of the control group (P=0.024), and there was a positive correlation between the 14 d DLQI score and patient satisfaction in the AI group (r_s=0.471, 95%CI=0.186-0.683, P=0.002), the correlation between the improvement in DLQI score and patient satisfaction was even more significant (r_s=0.816, 95%CI=0.676-0.899, P<0.001). The results of the questionnaire survey revealed that a majority of physicians demonstrated a positive attitude towards their use of the AI-assisted system, acknowledging its practical value in several areas: diagnosis selection (70.0%), auxiliary diagnosis (80.0%), treatment recommendations (60.0%), and the provision of professional knowledge (90.0%). Remarkably, 90.0% of the physicians indicated their intention to continue utilizing the AI-assisted system.

In the primary care setting, the application of AI-assisted systems has enhanced the diagnostic accuracy of general practitioners in identifying skin diseases, improves the quality of life for patients, and increases patient satisfaction. The majority of general practitioners report positive experiences with the use of AI-assisted systems.

基层全科医生在皮肤病诊断和管理方面面临挑战，凸显了对人工智能（AI）辅助系统的迫切需求。AI技术在提高诊疗效率中具有潜力，但目前针对其在基层医疗实践中的应用研究相对有限。

探讨AI辅助系统在基层全科医生皮肤病诊断与病程管理中的应用效果。

于2022年12月—2024年3月，在杭州市社区卫生服务中心招募自愿参与研究的全科医生19名，采用随机数字表法，将其分为AI组10名、对照组9名；选取该时期两组医生接诊的皮肤病患者90例，AI组50例、对照组40例。AI组医生使用睿肤AI辅助系统进行皮肤病的诊断和病程管理，对照组医生不使用AI系统、按常规流程诊治，两组医生在接诊过程中均收集了患者的病历、实验室检查结果和皮损照片。由2名皮肤病专家远程会诊，评估两组医生的诊断准确性。分别于接诊的第1、14天对患者进行皮肤病生活质量指数（DLQI）评分，对两组患者进行满意度测评，对AI组全科医生进行睿肤AI辅助系统使用体验测评。

AI组和对照组患者的性别、年龄、学历比较，差异无统计学意义（P>0.05）；两组医生的性别、年龄、学历、职称比较，差异无统计学意义（P>0.05）。AI组全科医生的皮肤病诊断准确率高于对照组（64.0% vs 37.5%，P=0.012）。治疗14 d后，AI组、对照组患者的DLQI评分较治疗前均有改善（P<0.05），AI组改善程度优于对照组（P<0.05）。AI组患者的满意度高于对照组（P=0.024），AI组患者第14天DLQI评分与患者满意度呈正相关（r_s=0.471，95%CI=0.186~0.683，P=0.002），DLQI评分的改善程度与患者满意度亦呈正相关（r_s=0.816，95%CI=0.676~0.899，P<0.001）。问卷调查结果显示，大多数医生对AI辅助系统的使用体验持积极态度，认为其在诊断选择（70.0%）、辅助诊断（80.0%）、治疗建议（60.0%）和专业知识提供方面（90.0%）具有实际价值，90.0%的医生表示会继续使用AI辅助系统。

在基层医疗环境中应用AI辅助系统可以提升全科医生的皮肤病诊断准确率，改善患者的生活质量和就诊满意度，且大多数医生对AI辅助系统的使用体验持积极态度。