Implementation of Big Data in Health Information Systems: Sample Approaches in Saudi Hospital

Abstract

Big data concept provides opportunity to exchange patient's medical information to the different healthcare providers. Health Information System (HIS) has created the ability to electronically store, maintain and move data across the world in a matter of seconds and has the potential to provide healthcare with tremendous increasing productivity and quality of services. Big data analytics is a growth area with the potential to provide useful insight in health information system. Big Data can unify all patient related data to get more option to view patient records to analyze and predict early disease detection. Big data supports and improve clinical practices, new drug development and health care financing process. Implementation of Health Information system (HIS) continues to expand infrastructure in Medical field due to enormous number of patient comes across to store medical data. In this paper we focus the Big data concept to increase and store patients details in Saudi public hospitals with maximum utilization. Most of the Saudi public and private hospitals Health information system locally connected and maintained by own hospital admin. There is no system implemented to share the patient health record, treatment details and medical prescription data to other hospital. The main problem in the Saudi hospital, Health information is not centralized due to unstructured, semi structured data maintain by the Saudi hospital. Proper Health information system is able to offer correct and complete personal health and medical summary through the Big data methods. This paper introduces the Big Data concept and characteristics, health care data and some major issues of Big Data. Big Data methods and challenges in medical applications and health information system are also discussed in this study. This study provides a base model to increase the use of big data in health information system and can assist to understand the breadth of big data applications.

Intelligent Construction and Mechanism of Educational Big Data Information for Resource Sharing

“…Among them, S k is the difference between the weights of two adjacent iterations, y k is the difference between the partial derivatives of two adjacent iterations, and γ k is the value of a partial derivative [20,21].…”

Data Harmonization for Heterogeneous Datasets: A Systematic Literature Review

“…In Saudi Arabia, patient health data generated in public and private hospitals are not shared and integrated with the health information system due to a lack of heterogeneity. Therefore, the Banu, Kuppuswamy, and Sasikala [63] team proposed a NLP and BDA-based systems. Lastly, online FHIR-based web portals were developed by using NLP techniques and open-source tools on the Mayo Clinic dataset to centralize the data generated in a heterogeneous format that was revealed by the researchers Hong, Wen, Shen, et al [64].…”

“…[57] Healthcare Helps in patient-lefted care decision-making among stakeholders [58] Healthcare Helps in finding the patient having obesity and comorbidities [59] Healthcare Helps in developing patient diagnostic criteria and representation [61] General-Purpose Support in integration, storage, computation, and visualization [62] Healthcare Open biomedical repositories can be developed in semantic web formats [60] Healthcare Normalizing and integration of structured and unstructured EHR data [63] Healthcare Helps health information system to keep a record of patients' data [64] Healthcare Helps in standardizing the clinical data normalization In previous studies, SSU heterogeneous data were used in the form of text, images, audio, video, and social media formats. The BD and BDA literature reviews proposed so many models and frameworks for data harmonization or integration.…”