扩大我们的掌握:人工智能是医疗质量的下一个飞跃

J. Kalra, Patrick J Seitzinger
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摘要

医疗保健质量和改进依赖于认识和改进实践模式。人工智能涉及使用机器学习和模式识别来模拟通常由人类进行的思维过程的自我学习系统。该项目的目的是评估医疗保健质量的现状和挑战,并为人工智能技术的创新应用开辟一条道路,以加强医疗保健战略。跨医学学科进行了知识整合,以确定医疗保健服务中的关键挑战,并评估如何利用人工智能来提高医疗保健质量。目前,全球约有一半的人口在看医生时与医生相处的时间不到5分钟。医生打断病人讲述自己的故事平均需要23.1秒。世界上大多数患者在其一生中都会经历一次或多次诊断错误。对现有证据的系统评价和叙述性评价报告了不同的全球诊断错误率,从5%到23.5%不等。目前医生的自杀率是一般人群的1.5到4.5倍。30-50%的医科学生和住院医生经历过倦怠。职业倦怠使医疗差错率几乎翻了一番,而涉及重大差错的医生的自杀意念增加了三倍。人工智能技术有可能在提高诊断准确性、减轻医疗差错、筛查和早期诊断、确定疾病易感性和进展方面产生变革性影响。人工智能的优势包括效率、准确性、预测/建模、标准化、抗疲劳、自我纠正能力和准确性。人工智能的缺点包括开发成本、立法不明确、整合问题、缺乏可解释性、数字素养不足、数据共享有限以及对已知的恐惧。即使在医疗保健领域有了前所未有的创新,我们也必须利用经过验证的、真正的医疗保障和改进方法,包括识别漏洞、减轻偏见和确保医疗公平。人工智能提供了一种工具,可以解决医疗保健服务中长期存在的问题,并实现以前我们无法掌握的医疗保健质量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Expanding Our Grasp: Artificial Intelligence as the Next Leap Forward in Healthcare Quality
Healthcare quality and improvement relies on recognizing and improving patters of practice. AI involves self-learning systems using machine learning and pattern recognition to emulate thought processes typically conducted by humans. The purpose of this project was to assess the current state and challenges of healthcare quality and to charter a path forward for innovative applications of Artificial Intelligence technology to strengthen healthcare strategies. Knowledge integration was conducted across medical disciplines to identify key challenges in healthcare delivery and assess how Artificial Intelligence can be leveraged to strengthen healthcare quality. Currently, approximately half of the global population spends less than 5 minutes with their physician during doctor visits. It takes on average of 23.1 seconds for a physician to interrupt patients while they are telling their story. Most patients around the world will experience one or more diagnostic errors in their lifetime. Systematic reviews and narrative reviews of the available evidence report varying global diagnostic error rates ranging from 5% to 23.5%. Currently the physician suicide rate that is 1.5 to 4.5 times higher than that of the general population. Between 30-50% of medical students and residents experience burnout. Burnout is nearly doubling the rate of medical errors, and physicians involved in major errors are experiencing a threefold increase in suicidal ideation. AI technology has the potential to have transformative effects on increasing diagnostic accuracy, mmitigating medical errors, screening and early diagnosis, ddetermining disease susceptibility and progression. Advantages of AI include efficiency, accuracy, prediction/modelling, standardization, immune to fatigue, self-correcting abilities, and accuracy. Drawbacks of AI include developmental costs, unclear legislation, integration issues, lack of explainability, insufficient digital literacy, limited data sharing, and fear of the known. Even with unprecedented innovations in healthcare, we must utilize tried and true methods of healthcare assurance and improvement including identifying vulnerabilities, mitigating biases, and ensuring health equity. AI presents a tool to address longstanding issues in healthcare delivery and achieve a caliber of healthcare quality that was previously beyond our grasp.
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