患者满意度:人工智能在医疗保健中的作用

M. A. Jabbar, Hena Iqbal, Udit Chawla
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摘要

人工智能(AI)的应用几乎可以体现在医疗保健系统的方方面面,因为它有可能影响医疗保健的几乎每一个方面,从检测疾病、严重或复杂的慢性疾病到控制、预防和治疗。随着医疗保健领域的技术创新、升级和采用,要求医疗保健专业人员做好充分准备,接受不断发展的技术及其应用,以提供最佳的医疗保健设施,这就催生了关于机器学习(ML)、人工智能、深度学习(DL)等在医疗保健领域的作用的各种研究。同样,数字化医院、医疗设施、记录和数据的兴起也导致了医疗保健领域的改进,这反过来又增加了整个医疗保健系统领域对专家、专业人士、经验丰富且精通数字知识的员工团队的需求。了解这些先进技术的作用,对健康、生活方式和整个医疗保健系统产生的影响,以及患者对其的看法,将为人工智能及其成果的改进和应用指明方向,从而为患者和社会创造一个更加健康的世界。本研究的目的是创建一个患者满意度模型,并就影响接受人工智能治疗的若干患者满意度的因素对其进行验证。本研究选择了美国、加拿大、澳大利亚、阿联酋和中国作为调查地点,因为这些国家都是先进国家,与其他国家相比,人工智能在这些国家的使用率最高。在我们之前的研究中,我们进行了探索性因子分析(EFA),对人工智能治疗患者的构建进行了初步了解。患者满意度主要有六个方面:第一个因子是个人接触 (PT),第二个因子是全面差距 (CG),第三个因子是可接受性 (AB),第四个因子是神经紧张 (NR),第五个因子是错误报告 (WR),第六个因子是开明 (EL)。在确认性因子分析(CFA)和结构方程模型(SEM)的帮助下,研究结果表明,患者满意度的构念水平表明 PT 对患者满意度的影响更大,与其他构念相比,它是患者满意度的最显著因子。因此,我们可以得出结论,在接受人工智能治疗之前,PT 仍然是患者心目中最重要的因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Patient Satisfaction: The Role of Artificial Intelligence in Healthcare
Applications of artificial intelligence (AI) can be seen in almost every aspect of the healthcare system, as it has potential to affect almost every facet of the healthcare, from detection of ailments and serious or complex chronic diseases to their control, prevention and cure. With technological innovations, upgradation and adoption in the field of healthcare, healthcare professionals are required to be well prepared to accept the continuously evolving technology and its application to provide best healthcare facilities, which gave rise to the various studies on the role of the machine learning (ML), AI, deep learning (DL), etc., in the field of healthcare. Similarly, the rise in digitalised hospitals, medical facilities, records and data has resulted in the improvisation in the field of healthcare, which in turn has increased the need of experts, professionals, experienced and digitally literate workforce teams in the field of entire healthcare system. Understanding the roles of these advanced technologies, impacts being created on the health, lifestyle and the entire healthcare system, along with the perception of the patients towards it, will shape the way for the improvements and the applications of AI and its outcomes to be achieved, resulting in healthier world for the patients and the society. The objective of the study is to create a patient satisfaction model and validate it with respect to factors influencing patient satisfaction of several patients undergoing AI treatment factors. In the study, the United States, Canada, Australia, UAE and China were chosen as a place of survey, as these are advanced countries and the use of AI is highest in these countries compared to other countries, and survey was done with the help of structured questionnaire. In our earlier study, exploratory factor analysis (EFA) was performed for initial knowledge development on the construct of patients undergoing AI treatment. Patient satisfaction rests on six broad dimensions: First factor is personal touch (PT), second factor is comprehensive gap (CG), third factor is answerability (AB), fourth factor is nerve racking (NR), fifth factor is wrong reporting (WR) and sixth factor is enlightened (EL). With the help of confirmatory factor analysis (CFA) and structured equation modelling (SEM), it has emerged from the study that patient satisfaction level of the construct suggests that PT will have a greater impact on patient satisfaction, and it is the most significant factor of patient satisfaction compared to other constructs. Thus, we can conclude that PT still remains the most important factor in the minds of patients before undergoing AI treatment.
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