Welmo's Joint Research with IUHW Selected for KAKENHI Grant to Integrate Support Records into Regional Welfare Planning
Key facts
- Welmo's Joint Research with IUHW Selected for KAKENHI Grant to Integrate Support Records into Regional Welfare Planning
- A joint research project by Welmo Co., Ltd. and IUHW on utilizing AI to analyze care records for regional policy-making has been awarded a KAKENHI Grant-in-Aid. The three-year project starts in April 2026.
- Source: PR Times
- Date: May 27, 2026
Direct answer
A joint research project by Welmo Co., Ltd. and IUHW on utilizing AI to analyze care records for regional policy-making has been awarded a KAKENHI Grant-in-Aid. The three-year project starts in April 2026.
- Citation
- Welmo's Joint Research with IUHW Selected for KAKENHI Grant to Integrate Support Records into Regional Welfare Planning (May 27, 2026), PR Times
- Source
- PR Times
- Date
- May 27, 2026
A joint research project by Welmo Co., Ltd. and IUHW on utilizing AI to analyze care records for regional policy-making has been awarded a KAKENHI Grant-in-Aid. The three-year project starts in April 2026.
📋 Article Processing Timeline
- 📰 Published: May 27, 2026 at 10:00
- 🔍 Collected: May 31, 2026 at 22:59 (108h 59m after Published)
- 🤖 AI Analyzed: May 31, 2026 at 23:01 (1 min after Collected)
### Research Background: Voices Hidden in Support Records
While local governments are encouraged to formulate regional welfare plans, traditional methods like surveys often suffer from participant bias. Conversely, care and welfare sites generate vast amounts of "support records" from care managers and social workers, which have historically been used only for individual case management. This study aims to analyze these records as big data to reflect real-world needs in policy development.
### Research Overview and Welmo's Role
The project utilizes the structured recording method "F-SOAIP." Welmo, which released the F-SOAIP-compatible voice recording AI "Milmo Recorder" in 2024, will contribute the following:
- Technical cooperation in AI-based analysis and classification of record data.
- Provision of its F-SOAIP-based record creation system.
- Establishment of data management systems based on research ethics.
### Significance of the Research
1. **Value Creation for Support Records**: Demonstrating how daily records can influence community-wide welfare policies.
2. **Realizing Evidence-Based Planning**: Visualizing real-world issues that surveys might miss through data-driven insights.
3. **Scalability**: The model could be applied to other administrative plans and set a global standard for data utilization in social welfare.
Yusuke Kano, Chairman and President of Welmo, commented that the company aims to create new social value by linking its technology and expertise in the care sector with academic research.
FAQ
What type of research grant was awarded and what is the research period?
I was awarded a Grant-in-Aid for Scientific Research (Kakenhi) from the Japan Society for the Promotion of Science (JSPS) in the category of Basic Research (C). The research period is from April 2026 to March 2029, a duration of three years.
What is the specific theme of the collaborative research?
The theme is 'Building a New Practice Model to Utilize Regional Issues Extracted from Support Records in Regional Welfare Plans.' The aim is to develop a model that leverages support records as big data.
What is the 'F-SOAIP' recording method used in this research?
F-SOAIP is a method for structurally recording support practices according to the categories 'Focus (point of focus)', 'Subjective Data', 'Objective Data', 'Assessment', 'Intervention', and 'Plan', enabling efficient data processing.
What is Wellmo's specific role?
Wellmo provides AI-based analysis and classification technology for record data, a system for creating F-SOAIP format records (such as the Milmore Recorder), and ensures a data management system based on ethical standards.
What impact is this research expected to have on the care and welfare industry?
This research is expected to valueize daily support records as data for regional welfare policies, realize evidence-based planning (EBPM), and set standards for data utilization in the welfare sector both domestically and internationally.