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Digital Quality Measure Operations—The Big Picture

 (#1 in a series of 4 blogs that preview Track 2 of the 2021 Digital Quality Summit sessions.) 

The first session will provide a track overview and will preview all sessions in the context of the overall ecosystem. We’ll establish a framework that shows how different concepts, standards and technologies enable health plans to operate
in a digital quality model. 

We’ll start with a high-level overview of the quality data ecosystem. This is important for understanding the digital model we’re moving toward, where health plan quality operations are today (admin-data driven, supplemental data, MRR) and how to make the transition. We’ll use a simple matrix to review all relevant HEDIS measure terminology and standards and their relationship to one another. 

Then we’ll introduce operating models—these let us illustrate, standardize and simplify data flows going forward. They allow us to understand what data will be available, in what formats (standards), how it flows and where aggregators fit in and how they are beneficial. Operating models also help us put the current state of the quality data ecosystem in context, which is important for mapping a path from how we operate now to simpler, faster, less-expensive digital measure operations. We’ll elaborate on: 

· Types of data 

· Data flows (including sourcing, transformation and storage). 

· Data sources and aggregators (including data collection methods from the common bulk/batch and flat files and chart collection, to standards-based APIs [yup: FHIR]). 

· Validation flows (how auditing and validation work today and how we can streamline the process). 

We’ll also hear about the important work of the DaVinci Project (an HL7 workgroup focused on adoption of the FHIR standard for payer use cases). DaVinci has developed a Data Exchange for Quality Measures (DEQM) framework and a corresponding implementation guide that specifies three exchange scenarios common in modern API-based architecture: Submit Data (push), Collect Data (pull) and Subscription. We’ll put that in context of current and alternative future models, and connect the dots. 

Throughout, we’ll emphasize clarity. We’ll present “the big picture,” where different pieces fit and how they relate—but we’ll try to keep things simple. 

With the big picture established, subsequent sessions can be a deeper dive into the concepts introduced in Session 1. Upcoming blogs will preview those sessions.  


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· Are there questions or subtopics you’d like us to address during DQS?