The Application of Computer Technology to Clinical Practice Guideline Implementation: A Scoping Review

Area of Science:

• Health Informatics
• Artificial Intelligence in Medicine
• Clinical Practice Guideline Implementation

Background:

• Implementing clinical practice guidelines (CPGs) is challenging.
• Computer technology and artificial intelligence (AI) offer potential solutions.
• Previous reviews have explored AI applications in healthcare, but a focused review on CPG implementation is needed.

Purpose of the Study:

• To systematically review the application of computer technology and AI in CPG implementation.
• To identify the main domains and methods used for AI-assisted CPG implementation.
• To understand the current landscape and future directions of AI in CPGs.

Main Methods:

• A comprehensive literature search was conducted across multiple databases (PubMed, Embase, Web of Science, Cochrane Library, CNKI, WanFang DATA, VIP, CMB) from inception to December 2021.
• Studies utilizing computer technology and AI to promote CPG implementation were included.
• A total of 117 studies were selected from 10,429 identified articles.

Main Results:

• AI applications focused on four main areas: content classification/extraction (17.9%), knowledge representation (40.2%), knowledge verification (12.8%), and knowledge integration (29.1%).
• AI methods for classification/extraction included pattern-based algorithms and machine learning.
• Knowledge representation techniques were most frequently used for representation, verification, and integration.

Conclusions:

• Computer technology and AI are increasingly applied to CPG implementation, primarily in content classification, knowledge representation, verification, and integration.
• AI offers significant potential to improve the usability and application of CPGs in clinical practice.
• Further research can explore advanced AI techniques for more sophisticated CPG implementation support.