Currently, the number of patients per doctor is increasing exponentially in North America. In addition, the number of patients each doctor has to take care of will increase even more under the current Pandemics situation. It can be said that the core of our project is to find a way to solve this problem with a limited number of doctors to increase the number of patients to take care of.
What it does
one of the ways I came up with was to use telemedicine to help doctors take care of more patients. In addition, in order to reduce unnecessary time, we have introduced OPQRST methods that allow rapid diagnosis. From the patient's point of view, it's a little simpler, but it's easier to express one's pain, and doctors can also easily understand the generalized patient's pain expressions, which can save more time. This is because doctors do not have to understand each patient's expression.
How I built it
We designed the user interface of Nightingale on the Webflow platform. We could format the questionnaires in HTML and CSS files through its visual editor. Simultaneously, we attempted to set up a micro web server through the Flask framework. With the framework, it is possible to also validate and transact the input data from the front-end:
When a patient inputs the health information into forms, the application saves and reorganizes data to create their Electronic Health Record (EHR). Then, it sends a copy of the EHR to the server so that the medical team can access the information on a real-time basis. This medical dashboard can display multiple EHRs with one of two sorting options: by timestamp (default) and by a numeric indicator based on discomfort level.
To calculate the indicator value, we sum:
- the discomfort level (from 1 to 10),
- the frequency pattern of the pain (1 for occasional and 2 for constant or pulsing),
- the pain's spread to other body parts(0 for no and 1 for yes), as well as the patient's personal information such as:
- the age group of the patient (2 for [0, 4] or 65+ years old and 1 for else), and
- BMI (2 for over 35, 1 for under 18.5 or over 30, and 0 otherwise).