Deerwalk Blog

A Single Source of Truth in Population Health Analytics

Posted by Scott MacEwen on September 22, 2016

The_Truth_Image.jpgNo, I am not talking about the Dalai Lama. I am talking about having a Population Health Analytics strategy that incorporates a Single Source of Truth (SSOT).  In the past this strategy was often synonomous with a healthcare data warehouse. But with Big Data solutions, it's commonly referred to as a "Data Lake".  More and more often, our customers refer to it as their single source of truth, so we decided to adopt the phrase and expand on it.

A single source of truth allows us to look at populations based on characteristics across all of your various data inputs, not just one system and the static reports that have been built within the confines of that system.  We bring in 26 different data types, and that number grows as our clients use the platform to analyze data in different ways, identify and predict risk, measure programs, interpret trends and many other uses. Clinical managers and analysts that use our population health analytics platform are enabled to ask active queries of "what if" statements of the risk profile that you want to manage, predict, ...or even avoid.

To do all these things you need a population health analytics platform that acts as a single source of truth, not just the ability across data sets to identify and measure different populations. It is critical to incorporate a data management process with a rules engine that can handle differences in data input (and quality), and transform that data into complete and consistent pictures of a member and their healthcare events. This is critical to providing accurate and intuitive data to manage and meet business various use needs. How you calculate utilization measures, quality metrics, where your benchmark measures and calculations come from - all these things matter in order to have a population health analytics strategy that incorporates a single source of truth (see earlier blog from Ed Hausman on utilization metrics).

Population health analytics users are starting to greatly expand what data sets they integrate, and looking at new and different ways to use their data assets to improve their business and member health.  We are glad they are looking to our platform as their the single source of truth!

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To learn more about Deerwalk's Population Health Analytics solutions, including Deerwalk Data Integrator, please visit us at Deerwalk.

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