|
The Future of Clinical Practice Guidelines: Integrating Artificial Intelligence for Optimal Care
|
Shahram Tofighi   , Rezvan Rahimi , Hanieh Zehtab Hashemi |
| Medical Academy of IRI, Dept. of Foresight and Theory Building, Force Group of Digital Health |
|
|
Abstract: (3295 Views) |
Background: Clinical practice guidelines (CPGs) are currently the optimal way to transfer information to healthcare professionals to ensure that their clinical actions are evidence-based. However, the process of developing and implementing these CPGs faces challenges. Artificial Intelligence (AI), particularly machine learning, natural language processing, and decision support systems, can be employed as effective solutions to transform the development and implementation process of CPGs and address the challenges in this field. This study aimed to investigate the role of AI in the development and implementation of CPGs.
Methods: In this review study, PubMed and Google Scholar databases were searched using selected keywords, including clinical practice guidelines, artificial intelligence, machine learning, and clinical decision support systems, and their English equivalents, from 2013 to 2023.
Results: AI has the potential to revolutionize the development and implementation process of CPGs. The reviewed studies demonstrated that AI can be used in data analysis, evidence synthesis, decision support, customization, continuous updating, and quality assurance of CPGs. Challenges and ethical considerations in this field, such as data quality, transparency and interpretability, accountability, inclusiveness, ethical considerations, legal and regulatory frameworks, also need to be addressed.
Conclusion: AI has the potential to improve the traditional approach of CPGs development and implementation. Advanced research and collaboration between AI experts, healthcare professionals, and policymakers are necessary to refine and optimize the role of AI in clinical guidelines. This collaborative effort will ensure that AI remains a valuable tool in improving patient outcomes, promoting evidence-based decision-making, and shaping the future of health and treatment. |
|
| Keywords: Artificial Intelligence, Evidence-based Medicine, Machine Learning, Natural Language Processing, Practice Guidelines |
|
|
Full-Text [PDF 336 kb]
(849 Downloads)
|
Letter: Review Article |
Subject:
Special
Received: 2023/09/20 | Accepted: 2023/09/22 | ePublished ahead of print: 2023/09/20 | Published: 2023/09/21
|
|
|
|
|
|
