Healthcare analytics in non-profits: Evidence from North America

Thomas Oliver Kellerton, Meredith Claire Smith
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Abstract

Background: The implementation of Big Data analytics in healthcare has an incredible chance of improving the quality of care, minimizing waste and error, and also decreasing the cost of care. Purpose: This systematic comment of literature objectives to discover the assortment of Big Data analytics in healthcare, including its applications and challenges in the adoption of its in healthcare. Furthermore, it intends to figure out the strategies to overcome the challenges. Data sources: An organized search of the articles was carried out on five primary scientific databases: ScienceDirect, Taylor, Francis and Emerald. The information articles on Big Data analytics in healthcare published from January 2017 to January 2022 are deemed. Data extraction: two reviewers independently extracted information on definitions of Big Data analytics; sources and applications of Big Data analytics in the healthcare field; challenges and strategies to overcome the issues in healthcare. Results: A complete of fifty eight articles are selected as per the inclusion needs and examined. The analyses of these posts placed that scientists do not have consensus about the useful definition of Big Data in serious healthcare. Big Data analytics finds the application for healthcare option support, optimization of healthcare operations, and reduction of treatment cost. The chief fight in serious adoption of Big Data analytics is non accessibility of evidence of its in healthcare. Conclusion: This review analysis unveils that there is a paucity of information on evidence of world utilization that is real of Big Data analytics in healthcare. Keywords: Big data, healthcare analytics.
非营利组织的医疗保健分析:来自北美的证据
背景:在医疗保健领域实施大数据分析有很大的机会提高医疗质量,最大限度地减少浪费和错误,并降低医疗成本。目的:这篇系统的文献评论旨在发现医疗保健领域大数据分析的分类,包括其在医疗保健领域的应用和挑战。此外,它打算找出克服挑战的策略。数据来源:对五个主要科学数据库(ScienceDirect、Taylor、Francis和Emerald)进行了有组织的文章检索。以2017年1月至2022年1月期间发表的医疗保健领域大数据分析相关信息文章为准。数据提取:两名审稿人独立提取大数据分析定义信息;大数据分析在医疗领域的来源和应用;克服医疗保健问题的挑战和战略。结果:根据纳入需要,共选择了58篇文章进行了检查。对这些帖子的分析表明,科学家们对大数据在严肃医疗领域的有用定义尚未达成共识。大数据分析发现了医疗保健选项支持、医疗保健操作优化和降低治疗成本的应用。真正采用大数据分析的主要障碍是无法获得医疗领域的证据。结论:这篇综述分析揭示了大数据分析在医疗保健领域的全球应用证据的信息缺乏。关键词:大数据,医疗分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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