Cloud-Based Data Analytics for Healthcare 5.0

Cloud-Based Data Analytics for Healthcare 5.0

K. Kavitha, C. Kumuthini
Copyright: © 2024 |Pages: 13
DOI: 10.4018/979-8-3693-2639-8.ch004
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Abstract

Healthcare 5.0 is a system capable of delivering diverse healthcare services. It achieves this through the utilization of cutting-edge technologies like cloud computing, big data analytics, internet of things (IoT), artificial intelligence (AI), and blockchain. Data analytics has set off a critical component of healthcare, empowering providers and researchers to extract valuable insights from huge amounts of healthcare data. With the advent of cloud computing, data analytics in healthcare has reached new heights, offering unprecedented opportunities for research advancements, sound decision making, and improved patient outcomes. This chapter explores the roles of data analytics and cloud computing, the key applications, analytics tools, benefits, challenges, and future prospects of cloud-based data analytics in the healthcare sector. Thus, this chapter explores the transformative impact of cloud-based data analytics in healthcare.
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2. Role Of Data Analytics In Healthcare

2.1 Power of Data Analytics

Data analytics is the process of collecting, organizing, analyzing, and interpreting huge volume of data to discover meaningful patterns, insights, and trends (Berisha, Mëziu & Shabani, 2022). In healthcare industry, data analytics plays a pivotal role in extracting valuable information from huge set of data generated by various sources like medical devices, administrative systems, electronic health records (EHRs) and wearable smart devices.

By applying advanced analytical techniques to healthcare data, organizations can gain a clear understanding of patient populations, treatment outcomes, disease trends, and operational efficiency. Data analytics enables healthcare professionals to make data-directed decisions, improve patient care, enhance operational processes, and drive better health outcomes.

2.2 Use of Big Data in Healthcare

Big data has revolutionized the healthcare industry. Big data refers to very large datasets containing greater variety of data with more velocity. Big data exceeds the capabilities of traditional databases. Big data in healthcare, includes different data types, such as clinical, genomic, financial, and patient-generated data.

By leveraging big data through data analytics, healthcare organizations can make valuable insights that were previously not accessible. For example, analyzing huge volumes of patient data can help identify disease patterns, risk factors, and optimal treatment approaches. It can also support population health management, personalized medicine, and public health interventions. It transforms care delivery, improve patient outcomes, and reduce costs.

2.3 From Descriptive to Predictive Analytics

Healthcare data analysis has undergone a transformation from descriptive analytics, which revolves around summarizing past data, to predictive analytics, a method that employs historical data for anticipating forthcoming events or results. Predictive analytics utilizes diverse statistical and machine learning methods to detect patterns and construct predictive models (Shahajad, Gambhir & Gandhi, 2021).

Within the realm of healthcare, predictive analytics finds applications in anticipating disease outbreaks, projecting patient readmission rates, approximating patient risk scores, and enhancing treatment strategies. Through the utilization of predictive analytics, healthcare providers can proactively recognize patients at high risk, intervene at an earlier stage, and allocate resources more optimally. This transition from descriptive to predictive analytics empowers healthcare institutions to shift from a reactive approach to an active and preventive form of care.

Figure 1.

Benefits of big data in healthcare

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