Big data analytics in healthcare: a systematic literature review
Abstrak
ABSTRACT The current study performs a systematic literature review (SLR) to synthesise prior research on the applicability of big data analytics (BDA) in healthcare. The SLR examines the outcomes of 41 studies, and presents them in a comprehensive framework. The findings from this study suggest that applications of BDA in healthcare can be observed from five perspectives, namely, health awareness among the general public, interactions among stakeholders in the healthcare ecosystem, hospital management practices, treatment of specific medical conditions, and technology in healthcare service delivery. This SLR recommends actionable future research agendas for scholars and valuable implications for theory and practice.
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Awais Ahmed Syed Attique Shah Rui Xi + 2 lainnya
2023
Big Data Analytics (BDA) has garnered significant attention in both academia and industries, particularly in sectors such as healthcare, owing to the exponential growth of data and advancements in technology. The integration of data from diverse sources and the utilization of advanced analytical techniques has the potential to revolutionize healthcare by improving diagnostic accuracy, enabling personalized medicine, and enhancing patient outcomes. In this paper, we aim to provide a comprehensive literature review on the application of big data analytics in healthcare, focusing on its ecosystem, applications, and data sources. To achieve this, an extensive analysis of scientific studies published between 2013 and 2023 was conducted and overall 180 scientific studies were thoroughly evaluated, establishing a strong foundation for future research and identifying collaboration opportunities in the healthcare domain. The study delves into various application areas of BDA in healthcare, highlights successful implementations, and explores their potential to enhance healthcare outcomes while reducing costs. Additionally, it outlines the challenges and limitations associated with BDA in healthcare, discusses modelling tools and techniques, showcases deployed solutions, and presents the advantages of BDA through various real-world use cases. Furthermore, this study identifies and discusses key open research challenges in the field of big data analytics in healthcare, aiming to push the boundaries and contribute to enhanced healthcare outcomes and decision-making processes.
R. Pagani Vander Luiz da Silva T. C. D. S. Pasquini + 2 lainnya
19 Juli 2022
Abstract In different studies in the field of healthcare, big data analytics technology has been shown to be effective in observing the behaviour of data, of which analysed to allow the discovery of relevant insights for strategy and decision making. The objective of this study is to present the results of a systematic review of the literature on big data analytics in healthcare, focussing in technologies, main areas and purposes of adoption. To reach its objective, the study conducts an exploratory research, through a systematic review of the literature, using the Methodi Ordinatio protocol supported by content analysis. The results reveal that the use of tools implies work performance at the clinical and managerial level, improving the cost–benefit ratio and reducing the time factor in the practice of the workforce in health services. Thus, this study hopes to contribute to the technological advancement of computational intelligence applied to healthcare.
Michele Milone F. P. Salvatore Nicola Cozzoli + 1 lainnya
22 Juni 2022
Background Multiple attempts aimed at highlighting the relationship between big data analytics and benefits for healthcare organizations have been raised in the literature. The big data impact on health organization management is still not clear due to the relationship’s multi-disciplinary nature. This study aims to answer three research questions: a) What is the state of art of big data analytics adopted by healthcare organizations? b) What about the benefits for both health managers and healthcare organizations? c) What about future directions on big data analytics research in healthcare? Methods Through a systematic literature review the impact of big data analytics on healthcare management has been examined. The study aims to map extant literature and present a framework for future scholars to further build on, and executives to be guided by. Results The positive relationship between big data analytics and healthcare organization management has emerged. To find out common elements in the studies reviewed, 16 studies have been selected and clustered into 4 research areas: 1) Potentialities of big data analytics. 2) Resource management. 3) Big data analytics and management of health surveillance systems. 4) Big data analytics and technology for healthcare organization. Conclusions In conclusion is identified how the big data analytics solutions are considered a milestone for managerial studies applied to healthcare organizations, although scientific research needs to investigate standardization and integration of the devices as well as the protocol in data analysis to improve the performance of the healthcare organization.
A. Ślęzak Kornelia M. Batko
6 Januari 2022
The introduction of Big Data Analytics (BDA) in healthcare will allow to use new technologies both in treatment of patients and health management. The paper aims at analyzing the possibilities of using Big Data Analytics in healthcare. The research is based on a critical analysis of the literature, as well as the presentation of selected results of direct research on the use of Big Data Analytics in medical facilities. The direct research was carried out based on research questionnaire and conducted on a sample of 217 medical facilities in Poland. Literature studies have shown that the use of Big Data Analytics can bring many benefits to medical facilities, while direct research has shown that medical facilities in Poland are moving towards data-based healthcare because they use structured and unstructured data, reach for analytics in the administrative, business and clinical area. The research positively confirmed that medical facilities are working on both structural data and unstructured data. The following kinds and sources of data can be distinguished: from databases, transaction data, unstructured content of emails and documents, data from devices and sensors. However, the use of data from social media is lower as in their activity they reach for analytics, not only in the administrative and business but also in the clinical area. It clearly shows that the decisions made in medical facilities are highly data-driven. The results of the study confirm what has been analyzed in the literature that medical facilities are moving towards data-based healthcare, together with its benefits.
Fatna El Mendili Y. Idrissi Youness Filaly + 1 lainnya
30 Maret 2023
Medicine is constantly generating new imaging data, including data from basic research, clinical research, and epidemiology, from health administration and insurance organizations, public health services, and non-conventional data sources such as social media, Internet applications, etc. Healthcare professionals have gained from the integration of big data in many ways, including new tools for decision support, improved clinical research methodologies, treatment efficacy, and personalized care. Finally, there are significant advantages in saving resources and reallocating them to increase productivity and rationalization. In this paper, we will explore how big data can be applied to the field of digital health. We will explain the features of health data, its particularities, and the tools available to use it. In addition, a particular focus is placed on the latest research work that addresses big data analysis in the health domain, as well as the technical and organizational challenges that have been discussed. Finally, we propose a general strategy for medical organizations looking to adopt or leverage big data analytics. Through this study, healthcare organizations and institutions considering the use of big data analytics technology, as well as those already using it, can gain a thorough and comprehensive understanding of the potential use, effective targeting, and expected impact.
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