Health Data Analytical Platform helps users find the patients that have the most in common with them, so they can share health experiences and find unprecedented social support.

What We Did

• Web Development We were brought in after the MVP for Health Data Analytical Platform (at the time, HealClick) had been launched. The site was in Ruby on Rails but the team that had been working on it had trouble with scaling and performance-tuning core features. The core features we were brought in to repair included a real-time health tracker and data visualization graph, a main page feed with dynamic filters for over 100k posts, a treatment review directory containing thousands of treatment reviews, and a patient-matching algorithm that dynamically matches 5000+ patients based on health profiles.

1. Tracker and Data Visualization

We rewrote the entire health tracker in javascript and implemented the 3rd party fastclick library to reduce symptom input speeds from over 1 second to a few milliseconds. This increased the number of daily tracker by 10x. We rewrote the data visualization graph in Javascript and the 3rd party Highcharts library to speed up load times from over 8 seconds to under 1.5 seconds. We also added dynamic date filters and symptom selection filters (so users could eyeball whether 1 symptom is changing due to a particular treatment taken).

2. Main Feed and Treatment Directory

We rewrote the main page feed and treatment review directory from Ruby on Rails to AngularJS, Rails API, and SOLR. We reduced page load speed on the main page feed from 4 seconds to under 1 second, and reducing page load speed on the treatment review directory from 8 seconds to under 1.5 seconds. We also added the ability to filter the treatments dynamically using thousands of symptom and condition filters.

3. Patient Matching

We refactored the patient matching algorithm and added SOLR and delayed jobs. Each job was reduced from 8 minutes to 30 seconds. We then load tested it to demonstrate scalability to a community with 50k users. A year after this feature was shelved, we successfully re-launched it in September 2015.

• iOS and Android development We were hired to consult the team on cross-device solutions to deploy iOS and Android apps using a single codebase and build the first release of the app. The decision came down to Ionic and Xamarin, and we chose Ionic because the in-house team has javascript developers and wanted to take over the app. (At the time React Native was not available)

Within 8 weeks, we deployed a stable and thoroughly-tested first release. The technologies used were JavaScript, AngularJS, Ionic, HTML, CSS, Apache Cordova, and Rails for the API. The health graph was implemented using Highcharts, a 3rd party data visualization Javascript library. (Note: The app is not in app stores as it was reserved by the team for private research use).