How Will Artificial Intelligence Lead the Future of Clinical Practice Guidelines

CHEN Yao-long; LUO Xu-fei; SHI Qian-ling; LYU Meng; ZHOU Qi; WANG Jian-jian; YANG Nan; GAO Dong-ping; YANG Shu; SHANG Hong-cai; YANG Ke-hu

doi:10.12290/xhyxzz.2021-0012

Volume 12 Issue 1

Jan. 2021

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Medical Journal of Peking Union Medical College Hospital > 2021 > 12(1): 114-121. > DOI: 10.12290/xhyxzz.2021-0012

CHEN Yao-long, LUO Xu-fei, SHI Qian-ling, LYU Meng, ZHOU Qi, WANG Jian-jian, YANG Nan, GAO Dong-ping, YANG Shu, SHANG Hong-cai, YANG Ke-hu. How Will Artificial Intelligence Lead the Future of Clinical Practice Guidelines[J]. Medical Journal of Peking Union Medical College Hospital, 2021, 12(1): 114-121. DOI: 10.12290/xhyxzz.2021-0012

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How Will Artificial Intelligence Lead the Future of Clinical Practice Guidelines

CHEN Yao-long^{1, 2, 3, 4, 5, ,},
LUO Xu-fei¹,
SHI Qian-ling⁶,
LYU Meng¹,
ZHOU Qi⁶,
WANG Jian-jian¹,
YANG Nan³,
GAO Dong-ping⁷,
YANG Shu⁸,
SHANG Hong-cai⁹,
YANG Ke-hu^{3, 4, 5}

1.
School of Public Health, Lanzhou University, Lanzhou 730000, China
2.
Lanzhou University Institute of Health Data Science, Lanzhou 730000, China
3.
Evidence-based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou 730000, China
4.
WHO Collaborating Center for Guideline Implementation and Knowledge Translation, Lanzhou 730000, China
5.
Lanzhou University, an Affiliate of the Cochrane China Network, Lanzhou 730000, China
6.
The First Clinical Medical College, Lanzhou University, Lanzhou 730000, China
7.
Institute of Medical Information & Library, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100020, China
8.
Chengdu University of Traditional Chinese Medicine, Chengdu 610075, China
9.
Key Laboratory of Chinese Internal Medicine of Ministry of Education, Beijing Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing 100700, China

Funds:

The National Key R&D Program of China 2018YFC1705500

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Corresponding author:
CHEN Yao-long Tel:86-931-8912639, E-mail: chenyaolong@vip.163.com
Received Date: January 04, 2021
Accepted Date: January 16, 2021
Issue Publish Date: January 29, 2021

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Abstract

Abstract

In the past decades, with the rapid development and progress of artificial intelligence (AI), its impact on the field of medicine is deepening. The AI guideline released by the Ministry of Science and Technology of the People's Republic of China also suggested increasing support for the application of AI in medicine. As an important guiding document in medical practice, clinical practice guidelines are of great significance and value in regulating the behavior of healthcare professionals and bridging the gap between the best evidence of research and current practice. How to use AI to accelerate the development process, improve efficiency, innovate the format of dissemination and implementation, and even lead the future of clinical practice guidelines has received more attention from researchers all over the world. This paper analyzed and discussed the current situation and prospects of AI in clinical practice guidelines. We also proposed ideas and suggestions on how to promote the integration of AI and guidelines.
- clinical practice guideline,
- artificial intelligence,
- machine learning,
- big data

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References

[1]	He JX, Baxter SL, Xu J, et al. The practical imple-mentation of artificial intelligence technologies in medicine[J]. Nat Med, 2019, 25: 30-36. DOI: 10.1038/s41591-018-0307-0
[2]	Oliveira T, Novais P, Neves J. Development and implementation of clinical guidelines: An artificial intelligence perspective[J]. Artif Intell Rev, 2014, 42: 999-1027. DOI: 10.1007/s10462-013-9402-2
[3]	Isern D, Moreno A. Computer-based execution of clinical guidelines: a review[J]. Int J Med Inform, 2008, 77: 787-808. DOI: 10.1016/j.ijmedinf.2008.05.010
[4]	Luo XF, Xiao YJ, Liu X, et al. How to Combine Artificial Intelligence with Clinical Practice Guideline: A Scoping Review[C/OL].(2019-10-31). https://journals.lww.com/ijebh/fulltext/2019/12000/abstracts_for_the_gin_and_jbi_conference,_adelaide.2.aspx.
[5]	Benjamens S, Dhunnoo P, Meskó B. The state of artificial intelligence-based FDA-approved medical devices and algorithms: an online database[J]. NPJ Digit Med, 2020, 3: 118. DOI: 10.1038/s41746-020-00324-0
[6]	李博, 李科, 曾东, 等.基于语义关系的高血压临床指南知识库构建[J].中国数字医学, 2013: 64-67. Li B, Li K, Zeng D, et al.Construction of Hypertension Clinical Guideline Knowledge Base Based on Semantic[J].Zhongguo Shu Zi Yi Xue, 2013: 64-67.
[7]	蒲晓蓉, 陈柯成, 刘军池, 等. COVID-19中国诊疗方案的机器学习智能分析方法[J].生物医学工程学杂志, 2020, 37:365-372. Pu XR, Chen KC, Liu JC, et al. Machine learning-based method for interpreting the guidelines of the diagnosis and treatment of COVID-19[J].Sheng Wu Yi Xue Gong Cheng Xue Za Zhi, 2020, 37:365-372.
[8]	Chen XL, Chen J, Cheng G, et al. Topics and trends in artificial intelligence assisted human brain research[J]. PLoS One, 2020, 15: e0231192. DOI: 10.1371/journal.pone.0231192
[9]	Ertle AR, Campbell EM, Hersh WR. Automated application of clinical practice guidelines for asthma management[J]. Proc AMIA Annu Fall Symp, 1996:552-556.
[10]	Ohno-Machado L, Gennari JH, Murphy SN, et al. The guideline interchange format: a model for representing guidelines[J]. J Am Med Inform Assoc, 1998, 5: 357-372. DOI: 10.1136/jamia.1998.0050357
[11]	Dubey AK, Chueh H. Using the extensible markup language (XML) in automated clinical practice guidelines[J]. Proc AMIA Symp, 1998:735-739.
[12]	Mani S, Shankle WR, Dick MB, et al. Two-stage machine learning model for guideline development[J]. Artif Intell Med, 1999, 16: 51-71. DOI: 10.1016/S0933-3657(98)00064-5
[13]	Shiffman RN, Karras BT, Agrawal A, et al. GEM: a pro-posal for a more comprehensive guideline document model using XML[J]. J Am Med Inform Assoc, 2000, 7: 488-498. DOI: 10.1136/jamia.2000.0070488
[14]	Metfessel BA. An automated tool for an analysis of compli-ance to evidence-based clinical guidelines[J]. Stud Health Technol Inform, 2001, 84: 226-230.
[15]	Shahar Y, Young O, Shalom E, et al. The Digital electronic Guideline Library (DeGeL): a hybrid framework for representation and use of clinical guidelines[J]. Stud Health Technol Inform, 2004, 101: 147-151.
[16]	Kaiser K, Akkaya C, Miksch S. How can information extraction ease formalizing treatment processes in clinical practice guidelines? A method and its evaluation[J]. Artif Intell Med, 2007, 39: 151-163. DOI: 10.1016/j.artmed.2006.07.011
[17]	Terenziani P, Montani S, Bottrighi A, et al. Applying artificial intelligence to clinical guidelines: the GLARE approach[J]. Stud Health Technol Inform, 2008, 139: 273-282.
[18]	Bui DD, Jonnalagadda S, Del Fiol G. Automatically finding relevant citations for clinical guideline development[J]. J Biomed Inform, 2015, 57: 436-445. DOI: 10.1016/j.jbi.2015.09.003
[19]	Beller E, Clark J, Tsafnat G, et al. Making progress with the automation of systematic reviews: principles of the International Collaboration for the Automation of Systematic Reviews (ICASR)[J]. Syst Rev, 2018, 7: 77. DOI: 10.1186/s13643-018-0740-7
[20]	Bowles J, Caminati MB, Cha S, et al. A framework for automated conflict detection and resolution in medical guidelines[J]. Sci Comput Program, 2019, 182:42-63. DOI: 10.1016/j.scico.2019.07.002
[21]	Graham SS, Majdik ZP, Clark D, et al. Relationships among commercial practices and author conflicts of interest in biomedical publishing[J]. PLoS One, 2020, 15: e0236166. DOI: 10.1371/journal.pone.0236166
[22]	Clark J, Glasziou P, Del Mar C, et al. A full systematic review was completed in 2 weeks using automation tools: a case study[J]. J Clin Epidemiol, 2020, 121: 81-90. DOI: 10.1016/j.jclinepi.2020.01.008
[23]	Marshall IJ, Wallace BC. Toward systematic review automation: a practical guide to using machine learning tools in research synthesis[J]. Syst Rev, 2019, 8: 163. DOI: 10.1186/s13643-019-1074-9
[24]	Marshall C, Brereton P. Systematic review toolbox: a catalogue of tools to support systematic reviews[C/OL].(2015-05-08).https://www.researchgate.net/publication/275967185_Syste-matic_Review_Toolbox_A_Catalogue_of_Tools_to_Support_Systematic_Reviews.
[25]	Akl EA, Meerpohl JJ, Elliott J, et al. Living Systematic Review Network. Living systematic reviews: 4. Living guideline recommendations[J]. J Clin Epidemiol, 2017, 91:47-53. DOI: 10.1016/j.jclinepi.2017.08.009
[26]	Else H. How a torrent of COVID science changed research publishing-in seven charts[J]. Nature, 2020, 588: 553. DOI: 10.1038/d41586-020-03564-y
[27]	Groot P, Hommersom A, Lucas P. Adaptation of clinical practice guidelines[J].Stud Health Technol Inform, 2008, 139:121-139.
[28]	Gagliardi AR, Marshall C, Huckson S, et al. Developing a checklist for guideline implementation planning: review and synthesis of guideline development and implementation advice[J]. Implement Sci, 2015, 10:19. DOI: 10.1186/s13012-015-0205-5
[29]	Landis Lewis Z, Mello-Thoms C, Gadabu OJ, et al. The feasibility of automating audit and feedback for ART guideline adherence in Malawi[J]. J Am Med Inform Assoc, 2011, 18: 868-874. DOI: 10.1136/amiajnl-2011-000097
[30]	Wahl B, Cossy-Gantner A, Germann S, et al.Artificial intelligence (AI) and global health: how can AI contribute to health in resource-poor settings?[J]. BMJ Glob Health, 2018, 3:e000798. DOI: 10.1136/bmjgh-2018-000798
[31]	Shrank WH, Rogstad TL, Parekh N. Waste in the US Health Care System: Estimated Costs and Potential for Savings[J]. JAMA, 2019, 322:1501-1509. DOI: 10.1001/jama.2019.13978
[32]	Marshall IJ, Kuiper J, Wallace BC. RobotReviewer: evaluation of a system for automatically assessing bias in clinical trials[J]. J Am Med Inform Assoc, 2016, 23: 193-201. DOI: 10.1093/jamia/ocv044
[33]	Brouwers MC, Kho ME, Browman GP, et al. AGREE Ⅱ: advancing guideline development, reporting and evaluation in health care[J]. CMAJ, 2010, 182: E839-E842. DOI: 10.1503/cmaj.090449
[34]	Chen YL, Yang KH, Marušic A, et al. A reporting tool for practice guidelines in health care: the RIGHT statement[J]. Ann Intern Med, 2017, 166: 128-132. DOI: 10.7326/M16-1565
[35]	Tokalić R, Viđak M, Buljan I, et al. Reporting of Clinical Practice Guidelines: Practical Testing of AGREE and RIGHT Checklists[J]. J Gen Intern Med, 2020, 35:2167-2172. DOI: 10.1007/s11606-020-05819-w
[36]	Hussain M, Hussain J, Sadiq M, et al. Recommendation statements identification in clinical practice guidelines using heuristic patterns[C/OL].(2018-07-27).https://www.computer.org/csdl/proceedings-article/snpd/2018/08441036/13bd1sv5NyA.
[37]	Schünemann HJ, Wiercioch W, Etxeandia I, et al. Guidelines 2.0: systematic development of a comprehensive checklist for a successful guideline enterprise[J]. CMAJ, 2014, 186: E123-E142. DOI: 10.1503/cmaj.131237
[38]	National Institute for Health and Care Excellence. Develop-ing NICE guidelines: the manual[M/OL].(2020-10-15). https://www.nice.org.uk/process/pmg20/chapter/introduction.
[39]	Manning CL. Artificial intelligence could bring relevant guide-lines into every consultation[J]. BMJ, 2019, 366: l4788.
[40]	Liu XX, Rivera SC, Moher D, et al. Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension[J]. BMJ, 2020, 370:m3164.

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