A pioneering AI-driven tool has emerged in Japan in a significant stride towards efficiency and precision in healthcare. Designed to streamline the often lengthy and intricate preliminary patient interviews, this tool is poised to revolutionize the medical landscape in the country.
Japanese startup Ubie, at the forefront of medical innovation, has introduced a game-changing Large-Language Model (LLM) feature. Integrated into its AI-powered patient service platform, this feature, known as the “Medical Interview Summary Function,” promises to simplify and accelerate the information-gathering process during patient interviews.
How It functions
The Medical Interview Summary Function is a notable addition to the Ubie Medical Navi platform, which replaces conventional paper-based medical questionnaires with digital forms. Patients must respond to 20-30 questions about their symptoms and lifestyle via the digital interface. This tool’s LLM-driven capacity to automatically summarize patients’ responses, presenting a concise summary to attending physicians.
To ensure the utmost accuracy and reliability of the summarized information, the tool retains the original text as a reference point throughout the summarization process. This dual-layer approach safeguards against any potential loss of critical details, maintaining the integrity of patient records.
Remarkably, this innovative summary feature is made available to the entire cohort of 1,500 healthcare professionals currently utilizing the Ubie Medical Navi platform, spread across 47 prefectures in Japan. Importantly, it is being offered without any additional cost, reflecting Ubie’s commitment to enhancing the healthcare landscape in the country.
A response to healthcare realities
The genesis of this summary feature can be traced back to the feedback from busy healthcare practitioners. They voiced their desire for a tool that would enable them to quickly and briefly comprehend patient concerns and symptoms. The time-consuming process of manually sifting through exhaustive preliminary interviews and preparing notes prompted Ubie to develop this cutting-edge solution.
Enhancing patient communication and efficiency
Field trials with users of the Ubie Medical Navi platform underscore the tangible benefits of this LLM-driven feature. It not only elevates the quality of patient communication but also bolsters operational efficiency. The feedback from users suggests high satisfaction levels, indicating the tool’s enduring value.
One doctor user praised the tool’s efficacy, stating, “The [LLM-driven] summarised text is very easy to understand, and we can now grasp and communicate with patients more promptly than ever before. In the past, we had to selectively copy and paste text from Ubie into the [EMR]. Still, the time and effort required for this process have been greatly reduced, which is also helpful from the perspective of improving operational efficiency. Currently, we turn on the medical interview summary function for most of our medical examinations, and it has already become indispensable for us.”
A wider trend in healthcare
Adopting generative AI tools is not unique to Japan; it’s part of a broader trend sweeping the healthcare landscape in the Asia-Pacific region. Singapore’s national health technology agency, Synapxe, is collaborating with Microsoft to develop LLMs that assist healthcare professionals in the public sector. Additionally, a startup based in Malaysia and Singapore has recently launched its generative AI tool, capable of translating medical jargon, complex health reports, and imaging data into digestible visual content.
In India, medical AI startup AI4Rx has introduced the MedBeat HealthConnect patient and doctor apps, featuring AI-powered summaries of patients’ potential symptoms and diseases, mirroring the approach of Ubie’s LLM-based offering.
While the adoption of generative AI holds significant promise, it has challenges, particularly in the medical and healthcare domains. Kota Kubo, co-founder and co-CEO of Ubie, emphasized the need for careful and responsible use of generative AI in healthcare. He acknowledged the technology’s innovative nature but also underscored the importance of addressing issues related to reliability, ethical considerations, patient privacy, and medical ethics.
Kubo stated, “Generative AI, including LLM, is rapidly being utilised in many industries and professions in Japan. Because of the innovative nature of the technology, a number of issues need to be sorted out, such as its reliability and ethical considerations. Particularly in the medical and healthcare fields, more careful use is required considering its impact on consumers and patients, privacy protection, medical ethics, etc.”
He further affirmed Ubie’s commitment to utilizing its experience and knowledge to harness generative AI safely and effectively on its platform. The overarching goal is to enhance healthcare professionals’ productivity and guide patients toward the most appropriate care.