Launch of 'KanGO', an AI Assistant Dedicated to Home Nursing

TomoaZ Co., Ltd. (Headquarters: Fukuoka Prefecture; Representative: Haruki Hayashi; hereinafter 'TomoaZ') has announced the launch of 'KanGO,' an AI assistant designed for home nursing stations. KanGO not only automatically generates nursing records from conversations during home visits but also proactively suggests observation points for the next visit based on accumulated user data. It is an all-in-one AI solution dedicated to home nursing, supporting both field nurses and management.

Background: The Reality of Home Nursing - Increasing Demand without Balanced Quality and Volume With the accelerating aging of society, the demand for home nursing is growing every year. However, in the field, a structural problem exists where increased demand does not directly translate into improved business performance. Home nursing station revenue depends on the number of visits, but there is an upper limit to the number of visits one nurse can handle per day, making it difficult to increase volume amid staff shortages. Even more serious is the reality that visit volume and quality of care are easily caught in a trade-off. Nurses spend about two hours a day on documentation and communication, time that cannot be spent on actual care. Cutting corners on records increases the risk of overlooking changes in patient conditions. Maintaining quality means volume cannot increase, and chasing volume decreases quality—nursing managers and staff have long struggled with this dilemma. KanGO was developed to solve these structural issues.

Three Reasons to Choose KanGO 1. AI-Driven Automatic Documentation and Flexible Format Support (including Psychiatric Care) AI listens to the dialogue during the visit and automatically generates nursing records just by answering questions. Supported formats cover major field-standard formats such as SOAP, Home Nursing Record I/II, DO records, and rehab records, as well as specialized formats for psychiatric care. It reduces documentation time by up to 80% (from about two hours to 20-40 minutes), allowing that time to be used for increasing visit volume.

2. AI Proactively Suggests Future Nursing Care Based on accumulated user data, the AI anticipates and suggests observation points and assessment perspectives for the next visit. Nurses no longer need to think from scratch about 'what to check,' allowing them to focus on higher-quality care. Automatic reflection questions are also prompted after the day's visits, contributing to the growth of less experienced nurses.

3. 'When, Where, Who, and What' Becomes Management Data Accumulated visit records, AI suggestion history, and nurse activity logs in KanGO are data assets that can be used directly for management decisions. - Real-time tracking of visit volume and operational status - Visualization of care quality per user - Tracking of staff skills and growth - Optimization of profitability and personnel allocation Managers can provide appropriate staff management and review performance indicators based on data, rather than relying on intuition or personal reports. By bridging the information gap between the field and management, it boosts the performance of the entire station.

Security and Compliance Communication and stored data are protected by TLS and AES-256 encryption, complying with the 'Safety Management Guidelines for Information Systems and Services Handling Medical Information' (the Three Ministries' Two Guidelines) established by the MHLW, METI, and MIC. Furthermore, all data storage and processing are completed within domestic data centers, realizing a secure environment that medical institutions can use with peace of mind.

Future Outlook KanGO aims to become the 'Operating System' for home nursing stations. We aim for a world where every operation of the business—from field nursing records to reflection and management decision-making—is centered around KanGO. We are building cooperative relationships with medical receipt and electronic medical record vendors to seriously engage with the next generation of community healthcare.