Case Study

Read about how we helped the Chief Technology Officer and product team at an electronic medical record company build an app prototype with a personalized user experience and predictive response features. We used a data-driven learning algorithm to identify patterns in responses patients input into a ChatBot, helping the product team demonstrate innovation and raise money for development.

Problem

An innovative healthcare technology company in the chronic illness space wanted to reimagine their form-based approach for capturing patient health information by:

  1. Increasing the quality and value of information captured.
  2. Engaging patients in the process; and 3) Providing a unique experience within their market.

 

Solution

Synaptiq analyzed their existing forms and applied data science and machine learning techniques to their historical patient information. From this analysis, numerous user experience improvements and data clean-up tasks were identified, and interesting new relationships between symptoms and conditions were discovered in their data

From these findings, Synaptiq developed a full-stack prototype application to test the improved patient intake experience. It was a novel mobile-first, chatbot experience based on a data-driven algorithm that learns about the patient and asks questions based on previous responses

How Machine Learning Helped

The client demonstrated the prototype to its investors to help raise more money and plans to integrate it into their cloud based platform in the coming year.