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Related Experiment Video

Updated: Dec 3, 2025

A Web Tool for Generating High Quality Machine-readable Biological Pathways

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Published on: February 8, 2017

Translating an evidence-based clinical pathway into shareable CDS: developing a systematic process using publicly

Jeremy J Michel^1,2, Emilia J Flores³, Lauren Dutcher^4,5

¹Evidence-based Practice Center, Center for Clinical Evidence and Guidelines, ECRI, Plymouth Meeting, Pennsylvania, USA.

Journal of the American Medical Informatics Association : JAMIA

|October 29, 2020

Summary

This summary is machine-generated.

A new 4-phase process translates clinical pathways into shareable, computer-readable clinical decision support (CDS) artifacts. This systematic approach uses publicly available tools and improves pathway clarity for evidence-based CDS development.

Keywords:

clinical decision support clinical quality language pathways, dissemination, Clostridoides difficile

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Area of Science:

Health Informatics
Clinical Decision Support Systems
Knowledge Engineering

Background:

Clinical pathways (CPs) contain valuable evidence-based information but are often not in a computer-readable format.
Translating semi-structured CPs into shareable, computable clinical decision support (CDS) artifacts is a significant challenge in health informatics.

Purpose of the Study:

To develop and validate a systematic, transparent process for translating evidence-based clinical pathways (CPs) into shareable, computer-readable clinical decision support (CDS) artifacts encoded in Clinical Quality Language (CQL).

Main Methods:

A 4-phase process was developed using publicly available tools: eGLIA, GEM Cutter, Value Set Authority Center (VSAC), and the CDS Authoring Tool.
CP content was extracted into discrete clinical concepts, encoded using standard terminologies into value sets, evaluated using wireframes, and structured as CQL-encoded CDS artifacts.
The process incorporated quality control steps and intermediate products to ensure transparency and reusability.

Main Results:

A systematic 4-phase process successfully translated a CP into a CQL-based CDS artifact.
The translation process identified ambiguities and gaps within the original CP, leading to its improvement.
Publicly available tools were largely sufficient, though manual encoding was needed for some complex concepts.

Conclusions:

Standardized development of CDS from CPs is feasible using the described systematic process.
CPs serve as a valuable resource for developing evidence-based CDS.
While existing tools facilitate CDS development, enhancements are needed for modeling complex CDS statements.