Summary
Client:- Remedo (Smart Health Assistant)
Duration:- January 2020 - Present
Location:- India
Platform:- IOS, Android
Technology Stack:- React native, Spring boot, Angular, Jenkins
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Idea
Study shows that one in every five Indians is affected by chronic disease. Around 60% of deaths is due to non-communicable diseases. Patient's nowadays have lot of questions and they expect more than prescriptions. With the rise of complex conditions integrated care is in need by the market. Remedo wanted to build an engagement platform that drives the better patient connect throughout their care journey well beyond the clinic visit. Remedo wanted to create a smart platform which connects doctors and patients throughout their care journey. Remedo also wanted to provide personalized care plans according to patient's condition. This is when Remedo selected Code Symphony as a technology partner to help them address their needs with an efficient IT solution.

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Remedo Doctor's App
Remedo Doctor's App is a one stop solution for Doctors to guide their patients throughout the care journey. Below is the highlights of the features that Doctor's can use within the app.

• Set an appointment with the patient
• Manage patient's information (Personal info, prescriptions, reports )
• Add Services to offer
• Add Timeslots
• Manage Billings
• Digital Prescriptions

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Provide Care Plans
Doctor's can invite patient's to their personalized care plans. Personalized care plans help Doctors to understand their patient's condition better and suggest them activities, actions, lessons & exercise accordingly.
‍Development WorkAfter we designed the user interface and user experience for the mobile apps, our development team was engaged to implemented the designs into a native mobile apps on the apple and google play store.

The core features of the web app included a superadmin role to add new clinics, an admin role to add new patients and monitor each patient’s data, and a smart algorithm that interprets significant changes on each patient’s graph.

The challenge with the web app was making sure we were developing an MVP (minimal viable prototype) of the algorithm used to detect symptom changes. At one point, we discussed machine learning to cover more subtle scenarios, but instead we agreed to launch with a simpler formula that would cover the most common changes. This ended up being a worthy compromise that allowed us to get to market faster.

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