Hemmo Lotem Michal, Tzezana Roey, Levtzion-Korach Osnat
Osheya- Woman lead wellness, Health leaders forum.
Yuval Ne'eman Workshop for Science, Technology and Security, Tel Aviv University, Ramat Aviv.
Harefuah. 2021 Jan;160(1):24-29.
The fourth industrial revolution has led to a paradigm shift in the world of data; this paper reviews the implications on the medical and health services. These changes include: -The transition to big data: New layers of information such as longitudinal data, OMICS, information from social networks and the internet will be added to the conventional sources of information: anamnesis, physical examination, lab results etc. and will assist in medical decisions. -The transition to medical prediction: The information will allow not only diagnosing the current medical situation, but will also enable predicting the patient's risk level for developing certain diseases in the future. -The transition to artificial intelligence systems: This will enable analysis and generate insights into the vast amount of available information. -The decline in data production and data analysis costs: Much of the information will be collected by the patient himself and derived from his wearable devices. Information that was previously costly and exclusively owned by health officials, will be owned by others including the patient himself. These changes pose risks alongside the opportunities. The pace and quality of incorporating all this data depends on two opposing forces: technological innovation on the one hand, and system barriers on the other. Barriers include objections from users, budgetary constraints, patient privacy and regulatory barriers. The healthcare system must prepare wisely, but quickly, for the dramatic changes.
第四次工业革命引发了数据领域的范式转变；本文回顾了其对医疗卫生服务的影响。这些变化包括：
向大数据的转变：诸如纵向数据、组学、来自社交网络和互联网的信息等新的信息层面将被添加到传统信息来源中，如病历、体格检查、实验室检查结果等，并将有助于医疗决策。
向医学预测的转变：这些信息不仅能诊断当前的医疗状况，还能预测患者未来患某些疾病的风险水平。
向人工智能系统的转变：这将能够对大量可用信息进行分析并产生见解。
数据生产和数据分析成本的下降：许多信息将由患者自己收集，并来自其可穿戴设备。以前成本高昂且由卫生官员独家拥有的信息，将归包括患者自己在内的其他人所有。这些变化在带来机遇的同时也带来了风险。整合所有这些数据的速度和质量取决于两种相反的力量：一方面是技术创新，另一方面是系统障碍。障碍包括用户的反对、预算限制、患者隐私和监管障碍。医疗保健系统必须明智而迅速地为这些巨大变化做好准备。
