Ivy

Inspiration

Ivy, at its core, is intended to help supplement accessibility in clinical research. In the opening ceremony, the importance of including diversity in our development teams and our design processes was emphasized - but we also want to highlight this importance in the research phase. Too often, scientific research focusses on the experiences of a small population of white, educated, middle-class communities. This research then goes to inform our theories, it informs our design, it informs our healthcare. For us to understand how to make inclusive, equitable healthcare, it starts with making sure they are included in the research phase. With the desire to have decentralized clinical research, we want to ensure that home based clinical research is accessible to all - so that the healthcare that is produced represents the communities it is meant to serve.

What it does

Ivy is a web app service to help with the implementation of decentralized clinical research - research that can be done by a participant in the comfort of their own homes. Here, we have developed a participant focused application that guides the user through executing a clinical intervention independently and have to opportunity to report adherence to the intervention, symptom changes, and experiences. The application is built with user engagement in mind - messaging with diverse faces, push notifications, and gamification with in-built achievements. Further, video tutorials are provided to support the participant in completing the intervention with ease. The Ivy app then takes deidentified data from the subjects and can provide surface level data analytics and raw data to the experimenter for deeper analysis.

How we built it

Ivy consists of two major components: a frontend and a backend. The frontend consists of the user interface of the application, and it was built in Next.JS, and utilized such libraries as DaisyUI, Tailwind CSS, and CSS Modules. The user interface was primarily designed around tablet computers, with elements being specifically designed to accommodate the elderly. The backend was built using the Keystone CMS, and provided a robust data model for interacting with the frontend. Included with Keystone is also a powerful administrator panel, which is useful for managing data. Keystone additionally leverages Prisma in order to create programmatically defined schemas for interfacing with relational databases. In Ivy’s case, PostgresSQL was chosen, and a database instance in Amazon RDS was used to store the database.

Deployment is done to Amazon EC2, where all of the major components of the application are stored on a virtual machine.

Challenges we ran into

The first main challenge was ensuring our design catered effectively to the audiences with the largest technical gap. In this, we had to be intentional about the technological and motor skill differences between young/healthy participants and older/neurologically impaired participants. The challenge was to ensure that our designs were universally inclusive by accounting for the needs of these populations

Another challenge was to find ways to reduce the risk of dropping retention in the clinical research trials. To combat this, we engaged with research into adherence in clinical research in centralized (non-virtual) clinical trials and focused on the existing pain points in research. In particular focusing on messaging frequency and personification, and effectively informing participants of the procedures.

Finally, we wanted the virtual nature of this research to not reduce the comfort that can be gained from an in person practitioner. For this, we focused on welcoming faces and gentle messaging to create a more welcoming atmosphere. We also used gentle, nature based color schemes and branding to smooth out the often sharp undertone that comes with clinical procedures.

Launching this application on AWS proved to require a great deal of learning, as we were generally unfamiliar with the provisioning process. Learning the proper way to allocate resources was a hurdle at first, but was eventually overcome with the help of online documentation.

Accomplishments that we're proud of

From a development point of view, we are proud of the skills that we have developed over the course of producing this app. To have the functional tablet based service with back end data storage/handling, we developed and leveraged skills with ECR, ECS, and ....

What we learned

Accessibile UI design and using new AWS services!

What's next for Ivy

At present Ivy works in a beta stage that allows for data collection from an individual clinical trial. We hope to expand the platform to further develop the experimenter interface to allow for ease of implementation into any clinical research trial – a plug and play approach.

Following this we hope to implement principles of gamification into the experience of the app. In this, we intend to bulk out the ability to form streaks and unlock achievements through adherence to the clinical interventions. Further we intend to implement push notifications to prompt engagement with the app and form habitual engagement.

Built With

• apollo
• docker
• express.js
• graphql
• keystone
• postcss
• postgresql
• prisma
• react
• tailwindcss
• typescript