diff --git a/summaries/hl7.fhir.uv.cql.md b/summaries/hl7.fhir.uv.cql.md
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@@ -1,7 +1,7 @@
-This standard aims to streamline the use of [Clinical Quality Language](https://build.fhir.org/ig/HL7/cql) (CQL) with FHIR resources in healthcare settings. It provides a unified approach for representing and evaluating clinical logic across various scenarios, including decision support, public health reporting, and research eligibility criteria.
+# General
 
-The standard defines profiles for packaging CQL and its compiled form as FHIR Library resources. It also includes profiles for representing information about logic libraries and their evaluation results. A key feature is the specification of a CQL evaluation service, enabling consistent implementation across different systems.
+[Clinical Quality Language (CQL)](http://cql.hl7.org) is a computer programming language used for decision support, public health reporting, and research/trial eligibility criteria.
 
-Healthcare providers can use this standard to implement computable knowledge artifacts that support clinical decision-making and quality reporting. Software developers benefit from clear guidelines for building systems that author, manage, and evaluate CQL-based FHIR artifacts. Healthcare organizations can leverage the standard to improve data exchange and streamline quality reporting processes.
+This standard defines ways to use CQL with FHIR (as the most general purpose way to access healthcare information systems consistently). Healthcare providers can use this standard to share the rules that support clinical decision-making and quality reporting with each other, and software developers get clear guidelines for building systems that support this.
 
-By consolidating common elements from previous standards, this guide reduces redundancy and simplifies future development efforts. It provides best practices for authoring CQL with FHIR data models, addressing common challenges such as handling missing information and terminology use.
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+Sharing this knowledge leads to economies of scale and better healthcare outcomes for less cost.