Big Data Analytics in Healthcare
1 IEEE/CAA JOURNAL OF AUTOMATICA SINICA, VOL. 8, NO. 1, JANUARY 2021 Big Data Analytics in Healthcare — A Systematic Literature Review and Roadmap for Practical Implementation Sohail Imran, Tariq Mahmood, Ahsan Morshed, and Timos Sellis, Fellow, IEEE Abstract—The advent of healthcare information management practitioners and professionals to successfully implement BDA systems (HIMSs) continues to produce large volumes of initiatives in their organizations. healthcare data for patient care and compliance and regulatory Index Terms—Big data analytics (BDA), big data architecture, requirements at a global scale. Analysis of this big data allows for healthcare, NoSQL data stores, patient care, roadmap, systematic boundless potential outcomes for discovering knowledge. Big data literature review. analytics (BDA) in healthcare can, for instance, help determine causes of diseases, generate effective diagnoses, enhance QoS I. Introduction guarantees by increasing efficiency of the healthcare delivery and effectiveness and viability of treatments, generate accurate The advent of healthcare information management systems predictions of readmissions, enhance clinical care, and pinpoint (HIMSs) is now generating huge volumes of patient-centered, opportunities for cost savings. However, BDA implementations in granular-level healthcare data. The high velocity of this data any domain are generally complicated and resource-intensive influences the relationship of hospitals and clinics with their with a high failure rate and no roadmap or success strategies to guide the practitioners. In this paper, we present a comprehensive patients and necessitates the use of analytics to tap into the roadmap to derive insights from BDA in the healthcare (patient needs, attitudes, preferences, and characteristics of clinical care) domain, based on the results of a systematic literature entities such as patients and practitioners [1]–[3].
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