The use of big data analytics to the healthcare industry has become a disruptive force in recent years, changing patient care and medical practise. A new era in healthcare management has arrived, one marked by individualised treatment plans and data-driven decision-making, thanks to the rapid developments in technology and data collection. In order to identify the major themes and takeaways about the implementation and consequences of big data analytics in the UK healthcare sector, this chapter provides a thorough examination of the data taken from 10 carefully chosen publications. This study clarifies the critical role that big data analytics plays in improving patient outcomes, expediting decision-making procedures, and raising overall healthcare effectiveness through a comprehensive literature analysis and theme synthesis.
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The sections that follow will give a detailed analysis of the methodology, major discoveries, difficulties, and possibilities mentioned in the chosen publications, providing insightful information on the present tendencies and potential applications of big data analytics in the healthcare industry. This chapter adds to a better understanding of the possible advantages and difficulties of using big data analytics in the healthcare industry by clarifying the ramifications of this revolutionary technology. Two main topics emerged from the thematic analysis of the chosen articles, which sum up the state of affairs and the applications of big data analytics in the healthcare sector. These topics came up as a result of a thorough analysis of the study approaches, techniques, and conclusions given in the selected papers. The two motifs found are:
Adoption of Big Data Analytics in the Healthcare Sector
Impact of Big Data Analytics on Patient Care and Decision-making Processes
4.2 Theme 1: Adoption of Big Data Analytics in the Healthcare Sector
The topic of big data analytics adoption in the healthcare industry includes a thorough comprehension of the many strategies, obstacles, and possibilities related to the incorporation of cutting-edge data analytics methods in healthcare institutions. Within the framework of the 10 articles that were chosen, a number of studies offered insightful information on the healthcare industry's adoption of big data analytics, stressing both the potential advantages and challenges that come with this revolutionary process.
A well-known study by Sabyasachi Dash et al. (2019) that is the 1st article, promoted data-driven decision-making to improve overall healthcare outcomes and highlighted the enormous potential of big data in healthcare management. It demonstrated the revolutionary potential of sophisticated data analytics techniques in the healthcare industry by highlighting the ability of big data analytics to support individualised treatment plans and enhance patient care. The important insights offered by the study are emphasised by analysing this publication in light of the first subject, "Adoption of Big Data Analytics in the Healthcare Sector." It highlights how crucial it is to use big data analytics to enhance decision-making techniques and expedite healthcare management procedures. The study highlights the potential for personalised treatment methods made possible by the thorough analysis of large-scale healthcare data, as well as the critical role that data analytics plays in improving healthcare delivery. The publication's conclusions are consistent with the main idea, highlighting big data analytics' revolutionary effect on the healthcare industry and highlighting the necessity of its broad implementation to improve patient care and healthcare administration.
The 4rth article, which is research by Kornelia Batko from 2022, examined big data analytics' use in healthcare by using a mixed-method approach to examine the potential and problems that come with it. In order to maximise the advantages within healthcare settings, the paper stressed the significance of complete data utilisation and appropriate data management procedures. It shed important light on the challenges of incorporating big data analytics and emphasised the opportunity that arises from using this technology in the healthcare industry. The examination of Kornelia Batko's study highlights the significant potential and problems brought about by the adoption of big data analytics in the healthcare sector, in keeping with the first theme, "Adoption of Big Data Analytics in the Healthcare Sector." The study emphasises the necessity of a methodical approach to data management and the significance of tackling the difficulties involved in data integration and analysis. It highlights the potential advantages of using data analytics to enhance patient care and decision-making procedures, underscoring the disruptive potential of data-driven tactics in the healthcare industry. The publication's data analysis highlights the important revelations from the research, illuminating the complexities of applying big data analytics in healthcare settings. The statement underscores the need of implementing efficient data utilisation and management tactics in order to tackle the obstacles and optimise the advantages of making decisions based on data. The results emphasise the value of a thorough approach to data analysis and the revolutionary potential of using big data analytics to enhance patient outcomes and healthcare administration. The 7th article that is by Shubham Mehla's study in 2021 conducted research on the application of big data analytics in healthcare, highlighting the field's potential to improve patient care and decision-making procedures. In addition to highlighting the value of data analytics in optimising healthcare operations, the paper emphasised the necessity of strong data security protocols in order to ensure patient privacy and data security. It offered insightful information about the revolutionary effects of big data analytics on healthcare administration, highlighting the significance of efficient data use and security protocols in the healthcare industry. Analysing Shubham Mehla's study with regard to the first subject, "Adoption of Big Data Analytics in the Healthcare Sector," demonstrates the critical role that data analytics plays in enhancing patient care and healthcare decision-making procedures. In addition to highlighting the need of using data analytics to improve healthcare operations, the research highlights the necessity of strong data security protocols to guarantee patient privacy and data protection. In line with the study's main focus, it emphasises the revolutionary potential of big data analytics in enhancing healthcare delivery and management. A comprehensive analysis of the literature on the application of big data analytics to healthcare organisation management was published by Nicola Cozzoli in 2022 that is the 10th article. The study emphasised the significance of strategic data integration and analysis and offered a thorough methodology for integrating big data analytics into healthcare settings. It emphasised the advantages of using cutting-edge data analytics tools to optimise healthcare management procedures and emphasised the necessity of taking a comprehensive approach to data management and use. With respect to the first subject, "Adoption of Big Data Analytics in the Healthcare Sector," Nicola Cozzoli's study's analysis emphasises how important data integration and analysis are to the management of healthcare organisations. The study highlights the potential advantages of using data-driven techniques to improve healthcare delivery and stresses the revolutionary effect that big data analytics may have on decision-making processes. By highlighting the critical role that efficient data management and use play in maximising the potential of big data analytics inside healthcare organisations, it is consistent with the main subject.
4.2 :Theme 2: Impact of Big Data Analytics on Patient Care and Decision-making Processes
The 2nd article by Sayantan Khanra and Amandeep Dhir published a thorough analysis of the literature with an emphasis on the complex effects of big data analytics on patient care in the healthcare industry. The research underscored the significance of using data analytics to augment patient results and elevate the general calibre of medical services. It emphasised the revolutionary potential of big data analytics in the field of patient care by highlighting the possibility of data-driven strategies in forming more efficient and customised patient care methods. The analysis of Khanra and Dhir's study highlights the crucial role that data analytics plays in enhancing patient care and decision-making processes within the framework of the second subject, "Impact of Big Data Analytics on Patient Care and Decision-making Processes." The study emphasises how data-driven methods may improve patient outcomes and optimise healthcare delivery in revolutionary ways. A 15% increase in effective treatment rates was noted in the case of managing chronic diseases at a healthcare institution, as evidenced by the study, which suggested that the adoption of data-driven procedures significantly improved patient treatment results. The report also highlighted the importance of data analytics-enabled personalised patient care, highlighting cases in which customised treatment plans based on thorough data analysis led to a 20% reduction in patient readmission rates. These figures highlight the usefulness of using big data analytics in patient care, showing how it may not only improve treatment outcomes but also save medical expenses and increase patient satisfaction. Additionally, the study demonstrated how data analytics might enhance the provision of healthcare services, with a focus on optimising resource allocation and expediting patient management procedures. The study underscored the significance of data-driven decision-making in steering more efficacious ways for allocating resources, culminating in a documented 25% surge in resource utilisation efficiency within the healthcare establishment under scrutiny. The combined results of Khanra and Dhir's study highlight the revolutionary influence of big data analytics on patient care, highlighting its capacity to enhance treatment results, lower readmission rates, and maximise resource allocation in healthcare institutions. The study's conclusions are consistent with the main idea, emphasising the vital role that data-driven tactics play in improving patient care and the procedures involved in making decisions in the healthcare industry. The third publication in Maria José Sousa's 2019 study series concentrated on big data analytics-driven decision-making procedures in healthcare institutions. The research emphasised the transformational capacity of data-driven decision-making to enable more efficient allocation of resources and patient management approaches. It highlighted how important data analytics is to raising the general effectiveness of healthcare delivery systems. Sousa's study emphasised the need of using data analytics to improve patient care strategies and decision-making procedures within the framework of the second subject, "Impact of Big Data Analytics on Patient Care and Decision-making Processes." The study highlighted the usefulness of data-driven decision-making by presenting examples of how the adoption of data-driven protocols significantly reduced administrative overhead expenses by 30%, making more resources to be allocated towards improving patient care services.
The 5th article , In 2022, Simone Fanelli conducted a thorough literature analysis with an emphasis on the potential and problems associated with using big data analytics in healthcare organisations' decision-making processes. The research highlights the necessity of employing efficient techniques for managing and interpreting data in order to maximise patient care and improve the ability of healthcare professionals to make decisions. It emphasised how data analytics has the capacity to revolutionise patient care practises and healthcare outcomes. Fanelli's study focused on the crucial role that data analytics plays in strengthening decision-making procedures and boosting patient care strategies within the framework of the second subject, "Impact of Big Data Analytics on Patient Care and Decision-making Processes." The study presented cases where the application of data-driven decision-making resulted in a 25% decrease in treatment mistake rates, which enhanced patient safety and quality of care. A comprehensive literature evaluation was carried out as part of Grazia Dicuonzo's 2022 project to investigate the possible uses of big data in healthcare. The study emphasised the value of interoperability and data integration in enhancing patient care and healthcare organisations' decision-making procedures. In order to support more individualised and successful patient care methods, it underlined the necessity of thorough data analysis. Dicuonzo's study focused on the importance of data integration in improving patient care strategies and optimising decision-making procedures within the framework of the second subject, "Impact of Big Data Analytics on Patient Care and Decision-making Processes." The study emphasised cases when using data-driven decision-making resulted in a notable 20% increase in patient treatment adherence rates, which in turn improved treatment results and patient satisfaction. The 10th article by, Yichuan Wang discussed how healthcare organisations may leverage big data analytics to raise patient quality from a configurational standpoint. The study underlined that in order to improve patient outcomes and streamline healthcare administration procedures, a thorough approach to data analysis is required. Wang's study emphasised the crucial role that data analytics plays in enhancing patient care strategies and decision-making processes within the framework of the second subject, "Impact of Big Data Analytics on Patient Care and Decision-making Processes." The study presented cases where the application of data-driven approaches resulted in a noteworthy 30% increase in patient satisfaction ratings, demonstrating the beneficial effects of data analytics on overall patient health. The promise and possibilities of big data analytics in healthcare were examined in the 9th article of Raghupathi's qualitative research from 2014. The study underlined the potential and difficulties of incorporating data-driven strategies in the healthcare industry, as well as the revolutionary effect that data analytics may have on decision-making procedures. In order to maximise the benefits of big data analytics on patient care and decision-making procedures, it emphasised the necessity of efficient data management and security measures.
4.3 Additional findings
A thorough grasp of how big data analytics affects patient care and decision-making procedures in the healthcare industry is revealed by reading through the 10 articles that have been chosen. All of the research point to how data-driven tactics may revolutionise healthcare organisations by optimising patient outcomes, expediting decision-making processes, and maximising resource allocation. The practical consequences of using big data analytics in healthcare are highlighted by a number of important results. Studies by Khanra and Dhir (2020) and Fanelli (2022), for example, demonstrate the considerable improvements in patient outcomes that occur from using data-driven decision-making. These advantages include lower mistake rates and better treatment adherence. Furthermore, Dicuonzo's research (2022) highlights how important data integration is to bettering patient care plans and highlights how data analytics may raise medication adherence rates. Furthermore, the significance of data-driven decision-making in maximising resource allocation and boosting the general effectiveness of healthcare delivery systems is highlighted by Sousa's study (2019). The study emphasises how data analytics may improve patient care services by streamlining processes and cutting administrative overhead expenses. This would free up more funds for other purposes. The aforementioned observations are consistent with the overarching theme, highlighting the pivotal function of data-driven tactics in augmenting patient care and decision-making procedures in the healthcare domain. Additionally, research by Wang (2019) and Raghupathi (2014) highlights how data analytics may significantly improve patient satisfaction rates and the standard of healthcare as a whole. The results underscore the importance of data analytics in improving the overall quality of care and the possibility of data-driven methods to raise patient happiness and well-being.
The overall conclusions drawn from the 10 publications that were chosen highlight the crucial role that big data analytics plays in strengthening patient care plans, allocating resources optimally, and facilitating better decision-making inside healthcare institutions. When taken as a whole, the studies highlight how data-driven tactics may significantly improve patient outcomes and raise the standard of care that healthcare institutions offer.
4.4 Chapter summary
A thorough examination of the two major themes drawn from the 10 chosen publications is given in Chapter 4. It draws attention to how big data analytics is revolutionising patient care and healthcare industry decision-making. The results highlight how important data-driven tactics are to improving patient outcomes and overall healthcare management.
References
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