Facial recognition payment via camera modules improves efficiency in the healthcare industry.

Facial recognition payment via camera modules significantly improves the overall operational efficiency of the healthcare industry through mechanisms such as rapid identity verification, automated settlement processes, and multi-stage efficiency optimization. Specifically, this is reflected in the following core aspects:

Patients need to carry multiple documents such as social security cards, ID cards, and medical insurance codes when seeking medical treatment. Manual verification is time-consuming (averaging 3-5 minutes per case) and is prone to interruption due to missing documents or inconsistent information.

3D Structured Light Camera: By projecting tens of thousands of infrared points to construct a facial depth model, it accurately identifies liveness, eliminates photo and video fraud, and achieves an accuracy rate of 99.99%.

Real-time Data Interaction: Seamlessly integrates with medical insurance platforms and hospital HIS systems, instantly retrieving patients' electronic medical records, medical insurance accounts, and other information upon facial recognition, achieving "person, document, and card matching" verification.

Efficiency Improvement: The identity verification time per case is reduced to 0.5-1 second, increasing the daily processing capacity of outpatient registration windows by 3-4 times.

Case Study: After deploying smart terminals certified by the National Healthcare Security Administration, patients at Yan'an Traditional Chinese Medicine Hospital no longer need to carry any documents; they can complete medical insurance registration and settlement simply by scanning their faces, reducing the processing time for a single transaction by more than 60%.

Cash, card, and QR code payments require manual operation by patients, which is prone to queues and backlogs due to network latency and equipment failure, and is difficult for the elderly to operate.

Full-Process Automation: After the patient scans their face, the system automatically links to their medical insurance account, splits the medical insurance payment and personal payment amount according to policy ratio, and completes the deduction simultaneously.

Offline Disaster Recovery Capability: Supports local caching of transaction data, which is automatically synchronized after the network is restored, ensuring payment continuity.

Efficiency Improvement: The payment time per transaction is reduced from 2-3 minutes to 3-5 seconds, and the overall consultation time is reduced by 20%-30%.

Data: After the Tianjin Municipal Medical Insurance Bureau deployed 5,500 smart terminals, insured individuals complete approximately 140,000 medical insurance payments daily via face recognition, accounting for 24% of all payments, with a peak daily processing volume exceeding 500,000 transactions.

After facial recognition payment, the system automatically pushes prescription information to the pharmacy. Patients can directly collect their medication using their facial recognition record, reducing waiting times.

By linking examination items with facial recognition, patients do not need to print reports; doctors can access results in real time, shortening the diagnostic cycle.

Facial recognition is supported in admission registration, deposit payment, and discharge settlement, avoiding multiple trips to the window for patients and improving inpatient turnover.

Real-Name Medical Treatment: Facial recognition payment ensures "person, ID card, and card matching," effectively preventing fraudulent activities such as misuse of medical insurance cards and theft.

Data Transparency: Electronic payment records are automatically synchronized to the hospital information system, reducing cash management costs and improving the traceability of accounts.

Case Study: After implementing facial recognition payment, a top-tier hospital reduced the waiting time for dispensing medication at the outpatient pharmacy from 15 minutes to 5 minutes, and the average daily number of inpatient discharges increased by 15%.

Facial recognition payment eliminates the need for mobile phones or memorizing passwords, solving the difficulties elderly people face in accessing medical care due to technical barriers. After installing facial recognition equipment at a county hospital, elderly patient satisfaction increased from 78% to 92%.

Patients in emergency situations no longer need to carry identification or cash; facial recognition allows for quick identity verification and payment, saving valuable time for emergency treatment.

Dual-lens Camera: Combining visible and infrared light, adapting to complex environments such as strong light and backlight.

Liveness Detection Algorithm: Identifying real people through dynamic features such as micro-expressions and blinking, preventing 3D mask attacks.

Lightweight Model: Deploying edge computing on terminal devices reduces data transmission latency and ensures real-time response.

Privacy Protection: Employing data anonymization and encrypted transmission technologies, complying with the Personal Information Protection Law and medical industry standards.

Deeply integrated with medical insurance platforms, hospital HIS, LIS, PACS and other systems to achieve data interconnection and interoperability, laying the foundation for scenarios such as electronic medical record sharing and remote settlement.