Luna D, Mayan J C, García M J, Almerares A A, Househ M
Daniel Luna, MD, MSc, PhD (Cand.), Chief Information Officer, Hospital Italiano de Buenos Aires, Pte. Perón 4190 (C1181ACH), Capital Federal, Argentina, Tel/Fax: +54 11 4959 0507, E-mail:
Yearb Med Inform. 2014 Aug 15;9(1):36-41. doi: 10.15265/IY-2014-0012.
The volume of data, the velocity with which they are generated, and their variety and lack of structure hinder their use. This creates the need to change the way information is captured, stored, processed, and analyzed, leading to the paradigm shift called Big Data.
To describe the challenges and possible solutions for developing countries when implementing Big Data projects in the health sector.
A non-systematic review of the literature was performed in PubMed and Google Scholar. The following keywords were used: "big data", "developing countries", "data mining", "health information systems", and "computing methodologies". A thematic review of selected articles was performed.
There are challenges when implementing any Big Data program including exponential growth of data, special infrastructure needs, need for a trained workforce, need to agree on interoperability standards, privacy and security issues, and the need to include people, processes, and policies to ensure their adoption. Developing countries have particular characteristics that hinder further development of these projects.
The advent of Big Data promises great opportunities for the healthcare field. In this article, we attempt to describe the challenges developing countries would face and enumerate the options to be used to achieve successful implementations of Big Data programs.
数据量、数据生成速度、数据种类以及数据缺乏结构化等问题阻碍了数据的使用。这就需要改变信息的获取、存储、处理和分析方式，从而引发了被称为大数据的范式转变。
描述发展中国家在卫生部门实施大数据项目时所面临的挑战及可能的解决方案。
在PubMed和谷歌学术上进行了非系统性的文献综述。使用了以下关键词：“大数据”“发展中国家”“数据挖掘”“卫生信息系统”和“计算方法”。对所选文章进行了主题综述。
实施任何大数据项目都存在挑战，包括数据的指数级增长、特殊的基础设施需求、对训练有素的劳动力的需求、对互操作性标准达成共识的需求、隐私和安全问题，以及需要纳入人员、流程和政策以确保其被采用。发展中国家具有一些阻碍这些项目进一步发展的特殊特征。
大数据的出现为医疗保健领域带来了巨大机遇。在本文中，我们试图描述发展中国家将面临的挑战，并列举用于成功实施大数据项目的选项。
