Citation: Dicuonzo, G.; Galeone, G.;
Shini, M.; Massari, A. Towards the
Use of Big Data in Healthcare: A
Literature Review. Healthcare 2022, 10,
1232. https://doi.org/10.3390/
healthcare10071232
Academic Editors: Keun Ho Ryu and
Nipon Theera-Umpon
Received: 29 May 2022
Accepted: 29 June 2022
Published: 1 July 2022
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Review
Towards the Use of Big Data in Healthcare: A Literature Review
Grazia Dicuonzo , Graziana Galeone * , Matilda Shini and Antonella Massari
Department of Economics, Management and Business Law, University of Bari Aldo Moro, Largo Abbazia Santa
Scolastica, 53, 70124 Bari, Italy; grazia.dicuonzo@uniba.it (G.D.); matilda.shini@uniba.it (M.S.);
antonella.massari@uniba.it (A.M.)
* Correspondence: graziana.galeone@uniba.it
Abstract:
The interest in new and more advanced technological solutions is paving the way for the
diffusion of innovative and revolutionary applications in healthcare organizations. The application of
an artificial intelligence system to medical research has the potential to move toward highly advanced
e-Health. This analysis aims to explore the main areas of application of big data in healthcare, as
well as the restructuring of the technological infrastructure and the integration of traditional data
analytical tools and techniques with an elaborate computational technology that is able to enhance and
extract useful information for decision-making. We conducted a literature review using the Scopus
database over the period 2010–2020. The article selection process involved five steps: the planning
and identification of studies, the evaluation of articles, the extraction of results, the summary, and
the dissemination of the audit results. We included 93 documents. Our results suggest that effective
and patient-centered care cannot disregard the acquisition, management, and analysis of
a huge
volume and variety of health data. In this way, an immediate and more effective diagnosis could be
possible while maximizing healthcare resources. Deriving the benefits associated with digitization
and technological innovation, however, requires the restructuring of traditional operational and
strategic processes, and the acquisition of new skills.
Keywords: artificial intelligence; big data analytics; healthcare
1. Introduction
The adoption of Fourth Industrial Revolution technologies, particularly artificial
intelligence (AI) and big data (BD), has been a major challenge for all industries [
1
]. The
increasing technological progress has initiated a digital transformation process in many
sectors, including healthcare [
2
], which is already moving toward Healthcare 4.0 due to the
impact of smart technologies [
3
,
4
] such as the Internet of Things (IoT) paradigm [
5
], cloud
and fog computing [5], and big data analytics (BDA) [6].
Healthcare institutions often face many challenges, ranging from epidemics to de-
termining the most suitable therapies for treating diseases. If an AI technology system
is applied to medical research, owing to the development, validation, and deployment
of various machine learning algorithms for industrial applications with sustainable per-
formance [
7
], it has the potential to diagnose, find vaccines, and personalize healthcare
services, moving toward highly advanced e-Health [8].
Patient-centered care cannot ignore the continuous expansion of data in terms of its
volume, variety, and velocity, propelling it toward a new technological paradigm, now
widely called BD [
9
,
10
]. The analysis of the enormous volume, heterogeneity, and velocity
of the information provided by BD allows for the extraction of the greatest value from
collected data and successfully solving and analyzing the relationships between differ-
ent variables that describe a patient’s vital functions and that can affect their health [
11
].
These data stimulate healthcare organizations to invest heavily in data analysis to facilitate
decision-making [
12
,
13
]. Integrating data on an individual’s unique characteristics, clinical
phenotypes, and biological information obtained from diagnostic imaging to laboratory
Healthcare 2022, 10, 1232. https://doi.org/10.3390/healthcare10071232 https://www.mdpi.com/journal/healthcare
