Certilytics AI History: A Data-Driven Approach Built for Healthcare

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May 10, 2024

A Timeline of Certilytics Innovative Use of AI to Improve Health and Lower Costs

The news about AI seems to be everywhere. ChatGPT and other generative AI applications are making waves in many industries. But healthcare organizations like yours need a data partner experienced in applying these data advancements to value-based care.

We’ve been doing just that for years. Let’s take a trip back in time to see how we’ve been using AI to deliver data-backed solutions to overcome healthcare’s biggest challenges.

2014: We started by applying AI to healthcare through foundational partnerships

Certilytics was established through two foundational partnerships with Fortune 25 healthcare companies. We saw firsthand how these large data sets of medical and pharmacy claims had the potential to transform clinical and financial outcomes if aggregated and enriched with predictive insights.

So we set to work on using AI to build market-leading, scalable, and unified predictive models from a data analytics platform we built from scratch.

2017: Our first predictive models launch, and start find savings.

A large national health plan chose to work with Certilytics to implement a new, integrated population health management program based on Certilytics AI-driven data analytics platform that connected cost savings with clinical outcomes. We launched our first predictive models and began a five-year measurement program that found consistent savings ranging from $100-$200 PMPY, creating the basis of one of our most sought-after programs, ROI analysis.

2018: Deep Learning enters the picture and our predictive models deliver the richest possible views of a member

Our team of data scientists train more predictive models using deep learning, compressing 250,000+ medical codes into 250 deep features and leveraging unique healthcare-focused data domains in order to deliver the richest possible view of a member across time and datasets to make new predictions.

2021: Our predictive model library expands with the application of more machine learning techniques.

We continued applying various AI and machine learning techniques in designing, deploying and calibrating until our library reached a milestone of over 100 predictive healthcare models. We also established a process to build customized models for our customers.

2023: To date we’ve generated over 67 billion scores for over 83 million patients with our 1000s+ predictive model library.

Our customers use our AI-generated approach to accomplish their value-based goals ranging from identifying modifiable patient and provider outcomes, ROI analysis, accelerating growth, and implementing strategic population health initiatives to maximize member behavior change.


Ready to start using AI-driven predictive insights to improve health outcomes and lower costs?

Learn about our AI-centered solutions by scheduling a meeting with our team.