Remote Medical Treatment

Inspiration

Typical regular doctor visits are currently at a slow crawl or standstill. Both patients and medical staff are at risk of infection for in person visits. There is a need to provide a low cost, and private solution for doctors, patents and caregivers that allows a quick and secure delivery of minimal PHI

What it does

Video conferencing and existing mobile applications that can link a patient & doctor serve an important purpose. But as of yet, these mediums have increased office bottlenecks and/or fail to resume demand or eliminate risk of infection. The Remote Medical application uses encrypted image transmission to give the clinical staff an early view of their patient who is requesting care. With this image the staff can quickly and accurately determine if a call, conference, prescription refill or in-person meet should take place. Having the secure image linked to existing in-house patient data gives the best possible risk/reward outcome by allowing the doctor to put context into the situation while maitaining a 'safe-distance'. Remote Medical utilizes Auth0 authentication protocols and intelligent database design to authorize and then authenticate a patient. Once authorized the patient will receive a secure link to a basic form that takes a note and at least one image. The image name and content is encrypted and 'chunked' into small sizes before it is securely stored in a MongoDB database that can only be seen by the doctor's office. Once uploaded into the database the clinical staff will have a tabular CRM-like view of patient form submissions('events') with their respective images.

Melanoscan is a lightweight, portable and state of the art scanning device that has been successfully implemented for the early detection of skin cancer in Stamford, CT for 15 years. It is a total immersion photo/video device that is patented and has a short-range whole body telemedicine system for enhanced medical evaluations. This radiology like scanning service enables a handsfree mode to automate the acquisition and distribution of high-quality physical examinations. Utilizing a secure wireless network, the Melanoscan camera arrays surround the body and simultaneously capture images that are securely stored and then analyzed for variations in pigment and changes in spot sizes through time. Through the development process Dr. Rhett Drugge, M.D. and his team have assembled the technology to quickly grab both the image and associated data extracted through popular vision API's in order to track and train sophisticated analytics. This device has a short relative lead time and can quickly be deployed anywhere. With the images and anlaytics in a standardized format, models can be quickly built to assess the liklihood a patient has or does not have COVID-19. The Melanoscan device should serve on the front-lines of patient scans to create the 'safest-distance' and protect our healthcare workers at all costs.

How I built it

MongoDB, Express, Node and React framework

Challenges I ran into

Time and manpower was a major constraint.

Accomplishments that I'm proud of

Establishing the authentication handshake and bringing an advance analytic image device to the front lines in order to reduce healthcare worker risk and jump-start the recognition of infection.