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User Guides
CARIN Implementation Guide for Blue Button®
User Guides
USCDI Core Data Standards
Best Practices/Checklists
Digital Quality Overview
Best Practices/Checklists
Transforming Clinical Data to FHIR®

You don’t need to have all of your data in FHIR® to start using digital quality measures. Here are some different approaches to preparing your clinical data.

Best Practices/Checklists
Clinical Quality Language and CQL Engines: The Basics

NCQA digital quality measure specifications are expressed using the Clinical Quality Language (CQL) standard for representing a clinical quality measure as an electronic document. Learn more about CQL and resources for building and maintaining CQL engines that can run digital HEDIS.

Best Practices/Checklists
HEDIS Implementation Guide: An Overview
User Guides
SDOH and Health Equity Standards: Gravity Project

The Gravity Project was created as a collaborative community to expand Social Determinants of Health (SDOH) Core Data for Interoperability. Standardizing SDOH codes facilitates the exchange of this data for care coordination, patient care, clinical research and more.

Best Practices/Checklists
Clinical Data For Quality Use: The Basics

FAQs

How do dQMs help health care consumers?

As Congress continues to advance price transparency and value-based care, dQMs can revolutionize consumer choice. Through combined price and quality outcomes, consumers can get a true picture of the value of their care. Publicly available quality measurement information is about 2 years out of date; dQMs allow providers to view patient outcomes and needed interventions in real time.

What are the benefits of dQMs versus traditional quality measures and eCQMs?

BenefitsTraditional MeasureseCQMsdQMs
Data sourcesMultipleSingleMultiple
Data capture uses existing workflows
Uses standard terminology
Uses standard measure logicVariable
Allows versatility in calculation and reportingLimitedLimited
Employs modular software solution
Timely data sharing
Automated data exchange via APIs
Promotes interoperability using broadly applicable data exchange methods
Leverages common data collection requirements
Harmonizes measurement across settings