CQL for FHIR – Clinical Quality Language
CQL (Clinical Quality Language) is a standardized language used in healthcare to express clinical quality measures and decision support rules. It is the industry standard (and regulated) means of quality measures and decision support across FHIR implementations.
What is CQL?
The function of CQL is to standardize human-readable expressions of clinical logic for different types of clinical algorithms predominantly quality measures.
CQL is a HL7 standard which ensures that it is widely recognized and used within the healthcare industry. This standardization helps to ensure consistency and interoperability across different healthcare IT systems.
Example of CQL code:
define "Breast Cancer Screening":
exists (From [Patient] P
where P.gender = 'Female' and P.age in 50 to 74 years and exists (From [Encounter] E where E.type = 'Outpatient' and E.date >= P.birthDate + 50 years and E.date <= P.birthDate + 74 years and exists (From [Procedure] Pr where Pr.code in ('MAMMOGRAM_CODE')))
Key components of CQL
Interoperability: CQL is designed to work with other healthcare data standards, such as FHIR and Quality Data Model (QDM) which enables it to be applied consistently across different platforms and data formats.
Readability and Flexibility: CQL is both human-readable and machine-executable, which allows for the expression of complex clinical concepts in a way that can be understood by both healthcare professionals and IT systems. Expression of Logic: CQL provides a standardized way to express the logic behind clinical guidelines, rules, and protocols.
Example Usages
- Quality Measurement and Reporting: CQL is used to create clinical decision support rules, which help guide healthcare providers in decision-making by providing real-time alerts or recommendations. For example, CQL can be used to define rules for drug-drug interactions, allergy checks, or patient eligibility for certain treatments based on clinical data stored in FHIR resources. The language allows the integration of complex clinical logic into electronic health record (EHR) systems, ensuring that providers have up-to-date and actionable insights at the point of care.
- Value based care: By leveraging CQL in conjunction with FHIR healthcare organizations can automate the tracking and reporting of quality measures that are central to value-based care models. E.g. CQL can be used to monitor whether patients meet certain clinical criteria, such as appropriate screenings, immunizations, etc. which directly affect reimbursement rates and quality incentives.
- Clinical Decision Support (CDS) Logic: CQL is used to create clinical decision support rules, which help guide healthcare providers in decision-making by providing real-time alerts or recommendations. For example, CQL can be used to define rules for drug-drug interactions, allergy checks, or patient eligibility for certain treatments based on clinical data stored in FHIR resources. The language allows the integration of complex clinical logic into electronic health record (EHR) systems, ensuring that providers have up-to-date and actionable insights at the point of care
Overall, CQL plays a critical role in improving the quality and consistency of care by enabling the precise and standardized expression of clinical logic.
CQL for CMS compliance
The Centers for Medicare & Medicaid Services (CMS) was among the early adopters of the Clinical Quality Language (CQL) and continues to lead efforts to integrate this standard with Fast Healthcare Interoperability Resources (FHIR). Together, CQL and FHIR form the foundation of Digital Quality Measures (dQMs). CMS is transitioning all quality measures in its reporting programs to dQMs, leveraging these standards to enhance data quality, streamline data aggregation, and enable the execution of quality measures using standardized tools. Instead of requiring hospitals to implement specific quality measures each reporting year, data can now be consistently captured as FHIR resources. A CQL engine can then execute all quality measures seamlessly, without the need for additional customization. Most importantly, this approach allows continuous monitoring, enabling healthcare providers to identify care gaps and measure improvements in real time.
CQL on Firely Server
The Firely Server includes a fully production-ready CQL engine capable of executing custom CQL measures, CMS’s Digital Quality Measures (dQMs), and quality measures defined by the National Committee for Quality Assurance (NCQA). Compliant with the international Using CQL with FHIR implementation guide, the Firely Server provides backend service APIs for executing quality measures efficiently. The results are generated as FHIR MeasureReports, which detail the measured populations for quality assessment and can serve as a foundation for deeper data analysis. Beyond calculating official measures from CMS and NCQA for reporting purposes, the Firely Server can also identify care gaps based on custom-defined criteria, offering a powerful tool for proactive healthcare management.
Customers:
Connect with us
Find out more about Firely’s stand-alone FHIR consulting services
Connect with our team by filling out the following form.