Ryukyu University Hospital adopts Ubie’s generative AI, improving CRC registry workflow efficiency by 2.33x

Ubie, Inc., whose mission is to “guide people to appropriate medical care through technology,” announced that Ryukyu University Hospital has introduced “Ubie Generative AI.” The processing efficiency of registry registration work handled by CRCs, or clinical research coordinators, improved from 1.85 cases per hour to 4.31 cases per hour, a 2.33-fold increase. In addition, the creation of initial hospitalization records based on faxed documents during emergency transfers has been shortened from around two hours to as little as five minutes, driving workflow transformation across multiple departments, from clinical research support to daily operations. The initiative comes as Japan’s physician work-style reform continues to accelerate task shifting in medical settings, while improving the working environment for all healthcare professionals remains an urgent issue. With the 2026 medical fee revision expected to further strengthen evaluation of medical DX and data utilization, healthcare providers are being asked to make fundamental improvements in operational efficiency to build sustainable care delivery systems. Ryukyu University Hospital is the only advanced treatment hospital in Okinawa Prefecture and the southernmost and westernmost university hospital in Japan. In January 2025, it relocated to the Nishifutenma Campus in Ginowan City and now plays a central role in Okinawa’s healthcare infrastructure. Like many medical institutions, the hospital faces heavy documentation burdens for physicians, nurses, and other medical staff. It had become difficult to secure enough time to prepare clinical records such as discharge summaries, creating a need for systems that can more reliably support medical quality. Against this backdrop, the hospital decided to adopt Ubie Generative AI, which offers a high degree of prompt customization and can be used flexibly by both beginners and experts. In CRC registry operations, staff previously had to review large volumes of electronic medical records and manually enter dozens of data items into databases, limiting throughput to 1.85 cases per hour. After introducing Ubie Generative AI, the workflow changed so that necessary information is organized from medical records before staff review and enter it, raising throughput to 4.31 cases per hour and reducing the workload on CRCs. The hospital has also applied the tool to record creation using paper-based clinical information. In one emergency transfer case, staff created initial hospitalization records from a 23-page fax, completing work that usually takes about two hours in as little as five minutes. For informed consent records, physicians explain the use of AI transcription to patients, obtain consent, and then use AI to transcribe spoken explanations under appropriate privacy safeguards. This significantly reduces the burden of rewriting verbal explanations into formal documentation. Doctors already using the system have said that AI should be used for informed consent records because it makes the process dramatically easier, and rollout is expanding across multiple departments and professional roles. Ryukyu University Hospital plans to expand Ubie Generative AI to all clinical departments. Through active internal training, case sharing, and deeper integration with electronic medical records, the hospital aims to improve automation and accuracy, secure more time for staff to engage with patients, and further enhance the quality of care. Tetsuo Hirata, vice director of Ryukyu University Hospital, said that physicians and nurses spend extensive time on documentation and that insufficient time can sometimes lead to incomplete discharge summaries, creating challenges for medical quality and safety. He expects generative AI to help produce high-quality documents quickly, contributing not only to workload reduction but also to improvements in healthcare quality and safety. Toshinari Yamamoto, who is responsible for medical DX at the hospital, said the hospital has promoted DX by leveraging in-house technical capabilities and self-developed tools despite budget constraints. By combining the flexibility of Ubie Generative AI with the hospital’s technical strengths, it has achieved highly customized AI use cases. Going forward, the hospital wants to go beyond efficiency gains and increase the time healthcare professionals spend with patients. Hospital physicians also commented that generative AI can streamline the organization and analysis of large datasets in clinical research, improving both the speed and quality of research. They noted that deeper data integration with electronic medical records would further accelerate clinical research. In CRC registry work, staff said the achieved registration volume would not have been possible without Ubie Generative AI, emphasizing that successful AI adoption starts from concrete on-site problems rather than AI deployment as an end in itself. Ubie Medical Navi is a service package for medical institutions that supports hospital management improvement and higher quality of care. It includes Ubie AI Monshin, Ubie Generative AI, and Ubie DPC Supporter. As of April 2026, Ubie Generative AI had been introduced at more than 130 hospitals, including university hospitals, while the broader series has been adopted by over 1,800 hospitals and clinics across all 47 prefectures in Japan. Founded in May 2017 by physicians and engineers, Ubie is a healthtech startup that develops AI-powered services to help people access medical care that fits their needs.