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What we did


Developed on

  • phython
  • javascript
  • react
  • django
  • spring
  • redis
  • logstash
  • rabbitmq
Python, Java, JavaScript, React, Django, Flask, Spring, Hibernate, Tornado, SQLAlchemy, PostgreSQL, Redshift, Elasticsearch, Logstash, Redis, RabbitMQ
An overview

A complete patient engagement solution that improves communication, retention and health outcomes of patients

Engaging patients in their own health care routine is difficult. The negligence in taking care of the patient not only causes harm to them, but also to healthcare providers. It leads to added costs for plans and providers, and poor health outcomes for consumers.

To tackle this, mPulse offers a conversational AI solution where they send tailored appointment reminders, medication reminders, insurance renewal reminders to users and help them take charge of their own health. They also use machine learning to understand their users’ preferable mode and frequency of communication to enhance the patient experience.

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the challenge

Tackling the scalability issue to provide a seamless customer experience

As the platform was growing, mPulse wanted us to help them in making the platform more secure, efficient and fast. The earlier platform had some limitations related to performance and scalability. Our partners realized that in order to grow the platform the right way, there was an urgent need to address the scalability and make the platform future-ready.

our approach

Glued to users’ problems, not our assumptions

We spent our initial days trying to understand the product, the business problem, and the goals of end users. Since healthcare is a complex domain, we know that the only way to solve problems is to keep our human rationale aside and think through the heart of the problem-- why do patients need tailored conversations? What could happen if patients don’t receive timely updates? Why is secure channel messaging important? Why 1 million messages in a day?

To uncover answers to these questions, our team went to visit the mPulse headquarters in the US and spoke to everyone across diverse parts of the business. We talked to people from marketing, sales, and design and spent time listening and learning about the challenges they face. Working collaboratively through many workshops and meetings, we were able to paint a picture of what problem we were trying to solve.


Engineering a robust solution

Improving the scalability, security and privacy of data was of utmost importance to us. So, we began with building a robust architecture for the platform to ensure security management and scalability requirements.

Our engineering team also implemented a secure messaging channel which works on a host of latest technologies (Java, Spring, Hibernate, Python, Tornado, Celery, Postgres) and is deployed on AWS. This messaging channel allows sending secure messages to only the intended recipients, thereby improving data security and privacy.

Till date, we’ve worked on many different modules of the platform which has not only helped the end users but also the sales team at mPulse who directly interacts with their customers. In one of the modules, we’ve worked on implementing Elasticsearch which has greatly reduced the search time, thereby making the core platform faster and more efficient.

We have also been working on performance improvements of the existing code. In different modules, we did a few API integrations (Compass, Eloqua) to streamline processes like medication reminders, creating and queueing of campaigns, and file processing. We’ve also used tools like Burp suite, WhiteSource to do vulnerability checks on our code.

our design process

Beginning with a right foundation

To create a new campaign, the users earlier had to get in touch with the mPulse Mobile’s customer support team who, in turn, created a new campaign as per the customer requirements.

To make the platform self-sufficient, mPulse Mobile’s team and Design team at Quovantis collaborated to redesign the platform. The purpose of the redesign was to make it easier for the users to plan, create, and analyze their campaigns.

During the design phase, our biggest challenge was to figure out how to make the workflows extremely simple to use so that the end users don’t feel as if something has drastically changed in the way they work and their world is falling apart with this major overhaul. We had to ensure that the process flows remained intact and did not hinder the user’s existing mental models of completing a task.

User flow diagram for “Create Program” workflow - one of the main feature within program manager module
ui design

Improving usability and user experience of the system with our visual designs

Since the platform has huge amounts of data, it was a challenge to work on creating simple workflows for our users. Nonetheless, it was a challenge that we loved solving!

For instance, the program manager module was a complex screen with all elements crucial to campaign creation. So, we designed it with progressive disclosure technique that revealed one step at a time. This way, users can focus on creating device specific campaigns without any information overload.

Following the same thought, we have maintained the simplicity, visual hierarchy and consistency in all the flows of the application. In fact, even the colors are used keeping in mind mPulse’s branding colors.

the outcome

A transformative digital experience and better business outcomes

Our partnership with mPulse is in an ongoing phase and we’re glad that we could assist mPulse in creating a technically-sound patient engagement platform. Today, mPulse has successfully transitioned to a better performing, scalable solution with more improvements on the way.

The platform is foundational for client engagement and business growth. Quovantis’s responsiveness, timely communication, collaboration, and a strong sense of ownership have contributed to our success.

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