A layered computer-interpretable guideline model for easing the update of locally adapted clinical guidelines

Area of Science:

• Computer Science
• Medical Informatics
• Knowledge Engineering

Background:

• Maintaining computer-interpretable guidelines is challenging due to evolving medical knowledge.
• Customizing guidelines for local practice settings adds complexity.
• Existing methods require significant effort for updates and adaptations.

Purpose of the Study:

• To develop and evaluate a novel layered framework for customizing and maintaining computer-interpretable guidelines.
• To support knowledge engineers in managing complex guideline adaptations.
• To improve the efficiency and accuracy of guideline maintenance processes.

Main Methods:

• Developed a layered framework using the PROforma formalism for computer-interpretable guidelines.
• The framework separates original guidelines (primary layer) from local customizations (secondary layers).
• Utilized Java code to integrate layers into a single, enactable guideline; pilot experiment conducted.

Main Results:

• Participants using the layered framework completed guideline updates more quickly.
• Fewer errors were observed in the update process when using the layered framework compared to a single-layer approach.
• The pilot experiment supported the hypothesis that the layered framework enhances maintenance efficiency.

Conclusions:

• The proposed layered framework effectively supports knowledge engineers in maintaining customized computer-interpretable guidelines.
• This approach streamlines the adaptation of clinical guidelines to local contexts.
• The findings suggest a more efficient and accurate method for managing evolving medical knowledge in digital formats.