# Towards the Use of Big Data in Healthcare: A Literature Review
## 4 Results
### Big Data and Digital Transformation  
The literature review showed that the digital health phenomenon is a true paradigm of innovation that allows for increasing the quality of health services and shaping them according to the needs of the patient, proceeding to the control of their health in real time regardless of geographical location [99; 100]. It also requires the main political, legal, and medical players to reconsider the risks associated with the processing of data in the health sector; promote a cultural change, even more than an organizational one, in digital transformation; and investigate new protocols for a more efficient and secure transmission of sensitive health data [97; 98; 99; 100; 101]. To manage data in a structured way and address the privacy system effectively and more robustly, healthcare organizations are looking for AI and analytics techniques that will enable them to consolidate organizational resources and develop new data-driven and integrated governance [102]. Managing an integrated healthcare solution requires security of medical data, which can be achieved with the cryptosystem, which has been found to be highly secure against attacks and interference [103]. The goal is to allow the development of ways to monitor the health conditions of the population using a huge volume, variety, and velocity of data from a wide range of healthcare networks in an aggregate and anonymous form [104; 105; 106] and improve its performance. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Refs.** & **Author** & **Title** & **Cited** \\ \hline
[13] & [PERSON]; [PERSON] (2012) & Business intelligence and analytics: from big data to big impact. & 6862 \\ \hline
[86] & [PERSON]; [PERSON]; [PERSON] & Virtually Perfect? Telemedicine for Covid-19. & 2423 \\  & [PERSON] (2020) & & Big data in health care: Using analytics to identify and manage \\ \hline
[9] & [PERSON]; [PERSON]; [PERSON] \\  [PERSON]; [PERSON]; [PERSON] (2014) & & high-risk and high-cost patients & 1030 \\ \hline
[5] & [PERSON]; [PERSON]; [PERSON]; [PERSON] (2016) & The internet of things in healthcare: An overview. & 592 \\ \hline
[17] & [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON], & & \\  & Y.; [PERSON]; [PERSON]; [PERSON]; [PERSON]; & COVID-19: Challenges to GIS with Big Data. & 423 \\  & [PERSON]; et al. (2020) & & \\ \hline
[58] & [PERSON]; [PERSON] (2013) & & Data and Disease Prevention: From Quantified Self to & 196 \\  & & Quantified Communities & 184 \\ \hline
[72] & [PERSON]; [PERSON] (2013) & Leveraging big data analytics to reduce healthcare costs. & 179 \\ \hline
[38] & [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON] (2016) & & Integrative methods for analyzing big data in precision medicine. & 179 \\ \hline
[85] & [PERSON]; [PERSON] (2012) & & A cloud computing based 12-lead ECG telemedicine service. & 148 \\ \hline
[57] & [PERSON]; [PERSON]; [PERSON], & & Big Data in Science and Healthcare: A Review of Recent Literature & 133 \\  & [PERSON]; [PERSON] (2014) & & and Perspectives. & 133 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Top ten articles per citations on theme 1: Big Data and awareness. The optimal use of resources has a critically important role for healthcare operators in assessing the quality of the healthcare service provided and also requires appropriate technologies to ensure the rational use of resources [107; 108; 109]. [PERSON] et al. (2021) claim that extracting new insights from existing volumes of structured and unstructured data related to medical treatments and products improves decision-making and enables a better understanding of each patient's costs [93; 110]. The result may be an important analytical capability of BD through the definition of previously unobserved patterns and improved resource efficiency through the identification of costly healthcare services, such as unnecessary diagnostic tests and additional treatments [111; 19].