Article type
Abstract
Background:
In the landscape of evidence-based medicine, the 6S evidence pyramid underscores the importance of integrating the best available evidence into a computerized decision support system. Translating text-based clinical practice guidelines (CPGs) into digital knowledge bases represents a pivotal step in expediting the integration of these guidelines into health care systems. However, this process remains challenging due to the complexity and heterogeneity of guideline representations. A comprehensive, integrated, and computerized platform is essential to seamlessly streamline the translation of guidelines into decision support tools, thereby facilitating the delivery of evidence-based and personalized care.
Objective:
To develop an artificial intelligence–powered, dynamic, automated, and collaborative workflow for efficient translation, deployment, and continuous updating of clinical practice guidelines in a digital format.
Methods:
We initiated our efforts by collecting synthesized evidence and available CPGs for integrated traditional Chinese and Western medicine. Subsequently, we constructed a universal formal, fine-grained, evidence-based, and modular-designed CPG knowledge representation model based on ontology. This model provides support for semantic processing and computational application of guideline documents. Lastly, we plan to build the Ontology-oriented Knowledge for Clinical Practice Guideline (OCKPG) platform.
Results:
We have designed the OCKPG logo, which symbolizes knowledge (the book), ontology (the circle with dots), and guidelines (the compass). The slogan "Bring Guidelines to the Digital Age" encapsulates the platform's mission. The platform comprises 7 conceptual modules, including the homepage, CPG ontology base, knowledge base (comprising knowledge graphs and rules), applications, collaborative tools, help, and account management. Based on a crowdsourcing theory, we plan to implement a project management system to expand and optimize platform contents. We have designed 4 levels of user roles, enabling standard users, CPG developers, knowledge graph developers, knowledge-based application developers, and platform administrators to access and contribute to the platform's resources. All users have the ability to search elements within the ontology and knowledge base, while developers can create applications for downstream use, such as APIs for clinical decision support systems.
Conclusions:
We anticipate that the OKCPG platform will expedite the process of making CPGs computable and facilitate practical implementations, ultimately enhancing the precision and automation of clinical decision-making processes.
In the landscape of evidence-based medicine, the 6S evidence pyramid underscores the importance of integrating the best available evidence into a computerized decision support system. Translating text-based clinical practice guidelines (CPGs) into digital knowledge bases represents a pivotal step in expediting the integration of these guidelines into health care systems. However, this process remains challenging due to the complexity and heterogeneity of guideline representations. A comprehensive, integrated, and computerized platform is essential to seamlessly streamline the translation of guidelines into decision support tools, thereby facilitating the delivery of evidence-based and personalized care.
Objective:
To develop an artificial intelligence–powered, dynamic, automated, and collaborative workflow for efficient translation, deployment, and continuous updating of clinical practice guidelines in a digital format.
Methods:
We initiated our efforts by collecting synthesized evidence and available CPGs for integrated traditional Chinese and Western medicine. Subsequently, we constructed a universal formal, fine-grained, evidence-based, and modular-designed CPG knowledge representation model based on ontology. This model provides support for semantic processing and computational application of guideline documents. Lastly, we plan to build the Ontology-oriented Knowledge for Clinical Practice Guideline (OCKPG) platform.
Results:
We have designed the OCKPG logo, which symbolizes knowledge (the book), ontology (the circle with dots), and guidelines (the compass). The slogan "Bring Guidelines to the Digital Age" encapsulates the platform's mission. The platform comprises 7 conceptual modules, including the homepage, CPG ontology base, knowledge base (comprising knowledge graphs and rules), applications, collaborative tools, help, and account management. Based on a crowdsourcing theory, we plan to implement a project management system to expand and optimize platform contents. We have designed 4 levels of user roles, enabling standard users, CPG developers, knowledge graph developers, knowledge-based application developers, and platform administrators to access and contribute to the platform's resources. All users have the ability to search elements within the ontology and knowledge base, while developers can create applications for downstream use, such as APIs for clinical decision support systems.
Conclusions:
We anticipate that the OKCPG platform will expedite the process of making CPGs computable and facilitate practical implementations, ultimately enhancing the precision and automation of clinical decision-making processes.