Disruptive Computational Technologies in Electronic Medical Records Management

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Published: Jul 17, 2025
DOI: https://doi.org/10.26265/jiim.v10i1.41805
Keywords:
Electronic Medical Record Electronic Medical Record System Electronic Patient Record Health Information Science Computer-Assisted Medical Decision Making
Artemis Chaleplioglou
https://orcid.org/0000-0002-6519-7428
Tasos Tsolakidis
Department of Archival, Library & Information Studies, University of West Attica
Abstract

Purpose – The adoption of disruptive computing technologies in hospital administration services has transformed the landscape of medical data and information handling. Electronic medical records (EMRs) contain patients’ health data generated in medical practices. This data can be converted into health information that pertains to individual patient health status, monitoring patient well-being, processing payments and financial transactions, providing statistics and demographics, and facilitating quality control of medical services.


Design/methodology/approach – This narrative literature review summarizes the current theoretical and practical frameworks for electronic medical record systems (EMRS), database structures, and information searching and retrieval strategies. The resources have been published in peer-reviewed journals indexed in PubMed, Scopus, Web of Science, and iCite databases.


Findings – EMR data stored in relational databases (RDB) are managed by RDB management systems (RDBMS) using structured query language (SQL) or not only SQL (NoSQL). Their efficient operation and content accuracy can be achieved by applying rules that ensure the atomicity and consistency of each transaction with the database, the isolation and synchronized control of the database, and the durability of the system against failures or errors. Current disruptive computational technologies, deep learning algorithms, artificial neural networks, recurrent neural networks (RNN), convoluted neural networks (CNN), and generative large language models (LLM) artificial intelligence (AI) systems can be utilized in these systems to uncover knowledge by answering complex health information queries.


Originality/value – Implementing AI systems in EMR RDBMS will enhance computer-assisted decision-making for various healthcare stakeholders, including medical practitioners, patients, and caregivers. From a clinical perspective, these systems may contribute equally to evidence-based and precision medicine. We will discuss the best practical and ethical considerations for their routine application.

Article Details
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Author Biography
Artemis Chaleplioglou

Artemis Chaleplioglou is an Assistant Professor of Health Information Science in the Department Archival, Library & Information Studies at the University of West Attica. She is a faculty member of the Information Management Laboratory of the University of West Attica.

She holds a PhD from the Ionian University, Department of Archives, Library Science & Museology on “Modern web technologies and information services: development, application and evaluation of novel librarianship tools and services”. She obtained a Master’s Degree in “Information Science – Organization and Management of Libraries”, and a Bachelor’s Degree in Archives, Library Science & Museology from the same University.

She served as Director of the Biomedical Research Foundation of the Academy of Athens Library and Editions Department from 2005 to 2023.

She was a post-doctoral researcher at the Ionian University, Department of Archives, Library Science & Museology between 2018 and 2022, and she served under an Academic Scholarship in the Department Archival, Library & Information Studies at the University of West Attica between 2020 and 2023.

She developed the Thesaurus of Medical and Biological Terms in Greek and English languages of the Greek National Documentation Centre in 2008 under the funding of the framework program “Development and Distribution of Librarianship Tools”.

She published the “Bibliographic Guide of Bibliometrics” for Kallipos, Open Academic Editions in 2022 (https://dx.doi.org/10.57713/kallipos-41)

She served as a Council Member of Greece in the European Association of Health Information Libraries (EAHIL) after general elections between 2008-2009, 2018-2022, and she has been reelected in 2023 (https://eahil.eu/about-eahil/council/).

Her research work has been published in international peer-reviewed journals and congresses. She is a peer-reviewer in academic journals of Information Science and Informatics (Scientometrics, JOLIS, BMC Bioinformatics, and more).

Research interests: Information Science, Librarianship, Health Libraries, Semantic Web, and Bibliometrics

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