DXHR Launches Generative AI E-learning for Nursing and Care Staff, Aiming to Reduce Record-Keeping Time by up to 70% via Voice Input

DXHR Inc. (Headquarters: Shibuya, Tokyo; CEO: Kazunari Maeda) has announced the launch of an industry-specific generative AI utilization training program titled 'Generative AI E-learning for Nursing and Care Staff.'

This 12-chapter, 12-hour e-learning program systematically teaches how to apply generative AI across all areas of nursing and care site operations, including record-keeping, handovers, assessments, care plan creation, patient/family communication, safety management, administrative tasks, shift scheduling, and staff development. The key feature is a workflow design centered on 'Smartphone Voice Input x AI,' allowing staff who are uncomfortable with PCs to complete records and reports simply by speaking.

[Background and Objectives]
In nursing and care environments, chronic labor shortages lead to significant time spent on documentation. With nursing records taking approximately 15 minutes each and shift handover preparations often exceeding 30 minutes, many staff are forced to work overtime for documentation purposes.

While generative AI is advancing in many industries, adoption in medical and care settings has been hindered by factors such as low PC literacy among staff and concerns regarding専門terminology and formatting. Consequently, DXHR has broken down nursing and care work into 69 tasks and systematized the optimal AI solutions for each.

[Service Overview]
This training consists of three blocks totaling 12 chapters: 'Introduction & General Skills (Ch. 1-3 / 3 hours),' 'Industry Specialization (Ch. 4-11 / 8 hours),' and 'Retention & On-site Deployment (Ch. 12 / 1 hour).'

Feature 1: Immediate Use via Smartphone Voice Input
By dictating a 30-second memo at the bedside, AI automatically converts it into SOAP-formatted nursing or care records. Even staff who struggle with keyboards can utilize AI simply by 'speaking.'

Feature 2: Building Facility-Specific AI Assistants
Staff learn to utilize Claude Projects or NotebookLM to build 'facility-specific AI assistants' trained on their own manuals, guidelines, and care plan examples.

Feature 3: Return Time to Patients through Efficiency
Through practical exercises, staff experience significant time reductions: 70% for SOAP records (15 to 4 minutes), 70% for handover preparations, 40% for care plan creation, and 83% for shift scheduling (180 to 30 minutes).