LumenLab, a digital innovation center owned by MetLife, a US life insurance company, is launching a block-chain-based insurance solution for diabetic patients.
Lumen Lab will be conducting a new project under the Singapore Mongolian MAS regulation. This pilot project, named Vitana, is targeted at gestational diabetes patients as an automation insurance product. Patients with gestational diabetes are known to take one out of every five pregnant women in Singapore.
The project is a joint project with Vault Dragon, an insurance company SwissRe, which provides EMR for the block chain professional electronic medical records system. The block-chain solution is designed to securely integrate EMR data and automatically settle at the point of diagnosis. No complaints about insurance coverage need to be handled manually.
Currently, most of the EMR in Singapore is handled manually. If you are insured, you must first pay the treatment fee directly. If you use the block chain system, you can check the diagnosis contents based on the EMR data provided by the bolt dragon safely or decide if you have any complaints. If it is confirmed, the encrypted customer account information is sent to the insurance company through the smart contract to make automatic payment. It is not an additional collection or storage of patient data on the Matt Lite server.
In April, Camelot Consulting Group in Germany said it had developed a solution that used block chains to manage sensitive medical data. All parties authorized by the patient’s treatment process have access to distributed data storage based on block-chain technology and all data transactions are stored in an encrypted chain of blocks and then exchanged directly between authorized parties. Integration of system integration, temperature, location and management in real time. The company notes that patient personal data is still being delivered in an analog manner, and that there is a high risk that data will be erroneous or misused during this process. A block chain approach can prevent misuse or misuse of data or samples being cured. For more information, please click here .