传统医疗从业者面临的挑战从Siddha系统过渡到信息技术为基础的方法在金奈,印度

Shankar Unnikrishnan, D. A. Kumari
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引用次数: 0

摘要

传统医学体系在人类生活中有着强大的根基。人类的福祉和医疗保健需求一直被这个深刻的历史医疗体系所照顾。一种这样的医学体系起源于印度南部,是悉达医学体系。悉达罗框架是神秘科学的宝库,集中体现了老悉达罗对科学的热切追求。注册的和传统的悉达哈医生实践这些古老的医疗服务——基于珍贵的悉达哈掌纹手稿。这些手稿的主要部分比记录的传统信息更没有防御能力。以这种方式,本综述计划报告并定量剖析金奈传统悉达修持者的社区信息。这篇文章强调了在金奈Siddha医学系统中,Siddha从业者向基于信息技术的方法过渡所遇到的挑战。在这项研究中,向金奈的56名Siddha从业者提供了一份问卷,并根据与大数据存储库的利用、电子报告的使用、个性化患者护理管理、使用人工智能和机器学习的循证决策支持系统以及预防疾病数据有关的问卷对数据进行了评估。研究发现,从业人员强烈需要改变以it为基础的系统,以记录个性化的患者护理管理,并利用数据库报告观察到的各个方面。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Challenges Faced by the Traditional Medical Practitioners from Siddha System towards Transition to Information Technology-based Approaches at Chennai, India
Traditional System of Medicine has its strong roots in human life since eons. The wellbeing and health care needs of the Human kind has been taken care consistently by this profound historical medical system. One such system of medicine which has its origin from Southern part of India is Siddha System of Medicine. Siddha framework is a treasure-house of mystery science, epitomizing the consequences of the ardent pursuit thereof by the old Siddhars. The registered and traditional Siddha Doctors practice these ancient medical services - based on the treasured Palm scripts of Siddhars. A major part of these manuscripts are more defenseless than the recorded conventional information. In this manner, the current review was planned to report and quantitatively dissect the neighborhood information on the customary Siddha practitioners in Chennai. This article highlights the challenges encountered by the Siddha practitioners towards the transition to an information technology-based approach in the Siddha system of medicine at Chennai. In this study, a questionnaire was provided to 56 Siddha practitioners in Chennai and the data were evaluated based on a questionnaire pertaining to utilisation of big data repository, use of electronic reporting, personalized patient care management, evidence-based decision supporting system using Artificial Intelligence and Machine Learning and data on preventive diseases. The study observed that the practitioners felt a strong need for change to IT-based systems for recording the personalized patient care management and utilising the databases for reporting the various aspects observed.
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