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医疗保健领域大数据的挑战与机遇:一项系统综述。

Challenges and Opportunities of Big Data in Health Care: A Systematic Review.

作者信息

Kruse Clemens Scott, Goswamy Rishi, Raval Yesha, Marawi Sarah

机构信息

School of Health Administration, Texas State University, San Marcos, TX, United States.

出版信息

JMIR Med Inform. 2016 Nov 21;4(4):e38. doi: 10.2196/medinform.5359.

Abstract

BACKGROUND

Big data analytics offers promise in many business sectors, and health care is looking at big data to provide answers to many age-related issues, particularly dementia and chronic disease management.

OBJECTIVE

The purpose of this review was to summarize the challenges faced by big data analytics and the opportunities that big data opens in health care.

METHODS

A total of 3 searches were performed for publications between January 1, 2010 and January 1, 2016 (PubMed/MEDLINE, CINAHL, and Google Scholar), and an assessment was made on content germane to big data in health care. From the results of the searches in research databases and Google Scholar (N=28), the authors summarized content and identified 9 and 14 themes under the categories Challenges and Opportunities, respectively. We rank-ordered and analyzed the themes based on the frequency of occurrence.

RESULTS

The top challenges were issues of data structure, security, data standardization, storage and transfers, and managerial skills such as data governance. The top opportunities revealed were quality improvement, population management and health, early detection of disease, data quality, structure, and accessibility, improved decision making, and cost reduction.

CONCLUSIONS

Big data analytics has the potential for positive impact and global implications; however, it must overcome some legitimate obstacles.

摘要

背景

大数据分析在许多商业领域都展现出前景,医疗保健行业也在审视大数据,以期为诸多与年龄相关的问题提供答案,尤其是痴呆症和慢性病管理方面的问题。

目的

本综述的目的是总结大数据分析所面临的挑战以及大数据在医疗保健领域带来的机遇。

方法

对2010年1月1日至2016年1月1日期间的出版物进行了总共3次检索(PubMed/MEDLINE、CINAHL和谷歌学术搜索),并对医疗保健领域中与大数据相关的内容进行了评估。根据研究数据库和谷歌学术搜索的结果(N = 28),作者总结了内容,并分别在“挑战”和“机遇”类别下确定了9个和14个主题。我们根据出现频率对这些主题进行了排序和分析。

结果

首要挑战是数据结构、安全性、数据标准化、存储与传输以及诸如数据治理等管理技能方面的问题。所揭示的首要机遇包括质量改进、人群管理与健康、疾病早期检测、数据质量、结构与可及性、决策改善以及成本降低。

结论

大数据分析具有产生积极影响和全球意义的潜力;然而,它必须克服一些合理的障碍。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2704/5138448/86989a98a3c0/medinform_v4i4e38_fig1.jpg

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