Towards an using of big data in healthcare: a literature review

The interest for new and more advanced technological solutions and, therefore, towards the use of Information and Communication Technologies (ICT) is paving the way for the spread of innovative and revolutionary applications in all business processes (Aceto et al., 2018). Even in healthcare organizations the demand for new and more advanced solutions from science and technology is becoming a solid reality. The Artificial Intelligence (IA) system applied to medical research has the potential to be able to diagnose, find vaccines or detect an epidemic and, therefore, and then move towards highly advanced e-Health (Tsikala Vafea et al., 2020). The pandemic emergency has led to extreme applications of artificial intelligence so that, through information resulting from the cross-reference of data from even heterogeneous sources, it is possible to draw deductions and derive correlations useful to predict clinical outcomes of patients, identify models that can lead to scientific findings that can pave the way for early diagnosis of Covid-19 infections while maximizing health care resources (Radanliev et al., 2020) and contributing to the containment of pandemic risk on national territory (Fusco et al., 2020). Effective and patient-centered care cannot disregard the acquisition, management and analysis of a huge volume and variety of health data and gleaning new insights from that analysis—which is part of what is known as Big Data (Bates et al., 2014). The most relevant sources for the acquisition of large data in health care comes from medical recordings (Nambiar et al., 2013) as well as external data source. Additional data sources are increasingly available such us data derived from Internet use (social media) and smart application (Sadilek et al., 2012; Wicks et al., 2010). The potential acquisition and analysis of BDA requires a restructuring of the technological infrastructure and integrate traditional data analytical tools & techniques with an elaborate computational technology able to enhance and extract information useful for decision-making. Moreover it is important making the digital transformation of healthcare compatible with high standards of security and respect for data protection principles (Costa, 2014; Senthilkumar et al., 2018). This work aims to investigate the sustainability of Big Data use on the healthcare system in terms of improvement of services provided, changes in skills and abilities, efficiency of the organizational structure and operating costs