From 8e8e9fd9a73489da097d2911108c7bd8d1d03e5b Mon Sep 17 00:00:00 2001 From: Bryn Rhodes Date: Wed, 5 Mar 2025 22:16:53 -0700 Subject: [PATCH] Update hl7.fhir.uv.cql.md --- summaries/hl7.fhir.uv.cql.md | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/summaries/hl7.fhir.uv.cql.md b/summaries/hl7.fhir.uv.cql.md index 8d57d09..b683534 100644 --- a/summaries/hl7.fhir.uv.cql.md +++ b/summaries/hl7.fhir.uv.cql.md @@ -1,7 +1,9 @@ +# General + 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. 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. 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. -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. \ No newline at end of file +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.