
Net Solutions' helped On Call Room (OCR) develop a
Mobile Social Platform for Healthcare Professionals
Client
The OCR
Industry
Healthcare
Technologies
iOS
Android

The On Call Room (OCR) is the brainchild of Dr. Sandeep Bansal, a doctor-turned- healthcare entrepreneur. Dr. Bansal wanted to introduce a unique product combining social care and healthcare technology. He approached Net Solutions with an initial idea, and our team not only collaborated with him to build an initial MVP, but also to help him launch a finished product.
At a high level, the idea was to create a mobile social networking app for healthcare professionals.
Based on the user types (admin and registered users), all members who log into the app have to provide login credentials. Therefore, the security of user info was a critical challenge in the project; it is also very important that the information shared will not to be used by other sources.
Maintaining the database of the 'Beats' section of the application was challenging, since content would be uploaded into it continuously. Moreover, with the increasing user base, the backend would need to be more organized to handle the traffic.
Since this was meant to be a one-of-a-kind social media app targeting the healthcare sector, our first challenge was to understand the target audience and create a rich user experience. This would help us understand what changes to introduce in the future versions of the app that wouldn't affect the follower base.
Encoding of data was implemented while being transferred from mobile to the backend, and further to HTTPS. Thus, the information shared at any stage stays safe.
The scope was huge and so was the backend management requirements. Due to this, indexing was carried out as part of an app optimization technique, and then database optimization ensured that the backend stayed sturdy.
We initiated stakeholder interviews as part of user research; after that, the target audience of the application was identified, and research was carried out among users between the ages of 18-65. The next steps were storyboarding, followed by user testing. A test flight was sent to more than 70 users from a medical background, who provided feedback on the prototype. After the modifications, based on the feedback from regression testing, an MVP was launched.