Trends and Futuristic Applications of Big Data and Electronic Health  Record Data in Empowering Constructive Clinical Decision Support  Systems

Authors

  • Krishna Jayanth Rolla Department of Biotechnology, Sri Indu Engineering College, Telangana 501510, India.

DOI:

https://doi.org/10.48165/bpas.2023.39.2.6

Keywords:

Big data, Computerized Clinical Decision Systems, Electronic Health Record Data, Artificial Intelligence, Medicine.

Abstract

Modern healthcare benefits significantly from big data, electronic  healthcare record data technologies, and artificial intelligence, which  provide robust tools for the collection and analysis of vast and diverse  datasets originating from various sources, such as clinical care,  administration, and research. This advancement enables the creation  of information technology infrastructures that facilitate the  realization of the "Learning Healthcare System Cycle," wherein  healthcare practice and research seamlessly intertwine in a  synergistic manner. This review focuses on illustrating how the  integration of extensive data collections, empowered by big data, can  enhance clinical decision-making and advance biomedical research.  Most importantly, electronic health records offer several benefits,  including heightened accessibility to patient information, enhanced  interdisciplinary communication, improved continuity of care, legible documentation, minimized duplication, and increased efficiency. The  incorporation of computerized physician order entry within electronic  medical records contributes to patient safety by mitigating medication  errors and offering clinical guidance through prompts and alerts  during electronic order entry. Furthermore, when evidence-based  clinical decision support is integrated with electronic health records,  it serves as a valuable tool for guiding healthcare providers and  clinicians in aligning their clinical practices with meaningful use  standards and compliance with quality metrics. This review also  outlines the contemporary application of clinical decision support  systems in the field of medicine. Its types, their existing practical  applications with documented effectiveness, prevalent challenges, and  potential adverse consequences. The review concludes by offering  evidence-based guidelines aimed at mitigating risks associated with  support systems design, implementation, evaluation, and ongoing  maintenance. 

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Published

2023-12-30

Issue

Vol. 39 No. 2 (2023): Bio-Science Research Bulletin (Jul-Dec) 2023

Section

Articles

How to Cite

Trends and Futuristic Applications of Big Data and Electronic Health  Record Data in Empowering Constructive Clinical Decision Support  Systems. (2023). Bio Science Research Bulletin, 39(2), 78–91. https://doi.org/10.48165/bpas.2023.39.2.6