Long-term care insurance supervision
Decision maker / Buyer：Medical insurance bureau / insurers / big-data group
Pain Points
- Disability assessment unreliable
- Care services hard to supervise
- Manual auditing too costly
Recommended Device Combination
Flagship · mass-produced: AI Health Guardian & Fall Detection Monitor (batch supply ready); other devices supplied per project.
ZQ-SH100 AI Health Guardian, ZQ-D100 Fall Detection Monitor, ZQ-ZH100 Care Data Hub, ZQ-GJ100 Human Trajectory Monitor, An Shou Hu platform
Delivered Value
Triple cross-validation of device, clock-in and human audit: 5–7 days of continuous collection covers the full assessment cycle, care services leave a traceable record, and audit conclusions are evidence-based and reviewable; data is managed by the big-data group — devices never replace human auditors, they only provide objective evidence.
How it applies
For medical-insurance bureaus and insurers in long-term-care pilots: guardians and fall detectors deployed in homes, 5-7 days of continuous activity/sleep data cross-validated with clock-ins and human audits; data hosted under supervisory control as objective evidence for disability assessment, service oversight and fund settlement.
Long-term care insurance supervision
Triple cross-validation of device, clock-in and human audit: 5–7 days of continuous collection covers the full assessment cycle, care services leave a traceable record, and audit conclusions are evidence-based and reviewable; data is managed by the big-data group — devices never replace human auditors, they only provide objective evidence.