Experion Technologies developed and deployed an interactive care-management platform for patients with neurodegenerative disorders that successfully improves and reinforces their routine habits. The platform provides streamlined caregiver management solutions for organizations, medical practitioners, patients, and caregivers’ families. As the users are predominantly senior citizens with neurodegenerative disorders, who cannot provide direct feedback, the client wanted to deploy an embedded analytics solution that analyzes the platform’s feature acceptance and user experience among its users.
The existing platform, developed by Experion, uses visual maps that tap into the patient’s brain’s habit memory system to improve cognition and reinforce routine habits. These visual maps were designed to accommodate the patient’s cultural, ethnic, behavioral, and other personal attributes.
The client, however, had very little visibility into
- The patient behavior – how the visual maps were being consumed in terms of regularity and ease of navigation on a day to day basis.
- The improvement, progress, and challenges the patient would face while using the platform.
- How to enhance the user experience based on different ability levels at various stages of the medical condition continuously.
Experion recommended implementing an embedded analytics solution using the Firebase, BigQuery, and Google Analytics platforms, based on the client’s business objectives. Experion made use of its expertise in providing data & analytics solutions and defined the benefits analytics could bring in to meet the requirements of the client.
The solution was built with a data strategy that would record an individual user’s entire session experience, including logs of every click event or interaction in detail. Embedded within the application, the solution sends these details to Firebase, where funnels, experience charts, and other analyses are done. The data is then accessed using BigQuery for turning out insights such as usage duration and progression comparison across the patients’ population, at an individual level. Machine learning algorithms were implemented to add intelligence to the platform. The platform also generates a data story trail that verifies or validates the user story, identifies the gaps, and provides relevant solutions. The platform incorporates further detailing of data to generate meaningful insights and provide actionable recommendations.
- Embedded analytics solution enables automated data collection related to real-world application usage
- Provides actionable insights based on the navigation journey, the time spent, and the difficulty each patient faces.
- Enables collection of feedback from users with cognitive challenges, which is otherwise difficult to capture
- Provides inputs for future iterations of the product based on actual usage, providing a clear product roadmap for the customer.