To provide references to and give suggestions to the development and optimiza-tion of Digital Intelligence (DI) technology in management of non-hospitalized patients by systematical review the application of digital technology in non-hospital settings.

We designed the search strategy and used the words " rare diseases"" patient management"" non-hospitalized management"" community management"" digital intelligence"" big data"" telemedicine" as MESH terms or free words. We searched the database of PubMed, Science-Direct, Web of Science, CNKI, Wanfang and VIP from the beginning of the database to July 2024 and used computer retrieval to get the literatures on the application of DI technology in the management of patients with rare diseases in non-hospital setting. We extracted the information of the first author, country or region, publication time, research participants, DI technology application, and application effect for summary analysis.

A total of 13 articles were included in this study, which were from 8 countries or regions. We found that DI technologies used were in the following forms: Internet information platform, wearable devices, telemedicine management platform and electronic database. The DI technology was used by the patients with rare diseases, patient caregivers and professional medical staffs. The application of all the forms above in different populations had good effect. The Internet information platform helped patients and their caregivers learn more about the disease and improved their self-management ability. The wearable device helped monitor the health status of patients in real time and predict the risk of emergent events. The telemedicine management platform facilitated to optimize the allocation of medical resources and strengthen doctor-patient communication. The electronic health database promoted the interconnection of data inside and outside the hospital and improved the accuracy of decision-making through data sharing.

The application of DI technology in the management of patients with rare diseases in non-hospitalized settings has shown positive results. In the future, it is necessary to correct the shortcomings and to deal with the challenges in terms of accuracy, readiness, applicability, and privacy protection. Besides, the DI can be integrated into the tri-level management system of patients known as the "patient-community-hospital". It is advisable to take the advantages of digital intelligence technology to improve the efficiency and quality of management of patients in non-hospitalized settings.