Inferensys

Glossary

CDS Hooks

An HL7 specification defining a pattern for invoking clinical decision support services from a user's workflow within an electronic health record, using a hook-based pattern and FHIR for data payloads.
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CLINICAL DECISION SUPPORT INTEROPERABILITY

What is CDS Hooks?

CDS Hooks is an HL7 specification that defines a pattern for invoking clinical decision support services from a user's workflow within an electronic health record, using a hook-based pattern and FHIR for data payloads.

CDS Hooks is an HL7 specification that defines a pattern for invoking clinical decision support services from a user's workflow within an electronic health record, using a hook-based pattern and FHIR for data payloads.

The specification defines a set of hooks—named workflow events like patient-view or order-select—that trigger an EHR to send a request to an external CDS service. The service receives a FHIR bundle containing contextually relevant clinical data, executes its logic, and returns a response containing informational cards with actionable suggestions, links, or SMART app launch points, all within the clinician's native workflow.

ARCHITECTURE

Key Features of CDS Hooks

CDS Hooks is an HL7 specification that defines a pattern for invoking clinical decision support services from a user's workflow within an electronic health record, using a hook-based pattern and FHIR for data payloads.

CDS HOOKS EXPLAINED

Frequently Asked Questions

Clear, technical answers to the most common questions about the HL7 CDS Hooks specification for integrating clinical decision support into EHR workflows.

CDS Hooks is an HL7 specification that defines a hook-based pattern for invoking clinical decision support (CDS) services directly from a user's workflow within an Electronic Health Record (EHR). It works by having the EHR fire a hook—a specific event in the user's workflow like patient-view or order-select—which triggers a real-time RESTful API call to an external CDS service. The EHR sends a JSON payload containing the context of the event and relevant FHIR resources as data. The CDS service then analyzes this data and returns a set of cards back to the EHR, which are rendered natively in the clinician's interface. These cards can contain informational text, suggested actions like creating a new order, or links to launch a SMART on FHIR application for a more complex interaction. This architecture decouples the decision logic from the EHR vendor's codebase, allowing third-party developers to build and deploy clinical reasoning tools that work across any CDS Hooks-compliant EHR.

Prasad Kumkar

About the author

Prasad Kumkar

CEO & MD, Inference Systems

Prasad Kumkar is the CEO & MD of Inference Systems and writes about AI systems architecture, LLM infrastructure, model serving, evaluation, and production deployment. Over 5+ years, he has worked across computer vision models, L5 autonomous vehicle systems, and LLM research, with a focus on taking complex AI ideas into real-world engineering systems.

His work and writing cover AI systems, large language models, AI agents, multimodal systems, autonomous systems, inference optimization, RAG, evaluation, and production AI engineering.