Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/134012
Title: Technological progress in electronic health record system optimization : systematic review of systematic literature reviews
Authors: Negro Calduch, Elsa
Azzopardi Muscat, Natasha
Krishnamurthy, Ramesh S.
Novillo Ortiz, David
Keywords: Medical records -- Data processing
Medical records -- Technological innovations
Natural language processing (Computer science)
Medical informatics -- Data processing
Systematic reviews (Medical research)
Issue Date: 2021
Publisher: Elsevier
Citation: Negro Calduch, E., Azzopardi Muscat, N., Krishnamurthy, R. S., & Novillo Ortiz, D. (2021). Technological progress in electronic health record system optimization: Systematic review of systematic literature reviews. International Journal of Medical Informatics, 152, 104507.
Abstract: Background: The recent, rapid development of digital technologies offers new possibilities for more efficient implementation of electronic health record (EHR) and personal health record (PHR) systems. A growing volume of healthcare data has been the hallmark of this digital transformation. The large healthcare datasets’ complexity and their dynamic nature pose various challenges related to processing, analysis, storage, security, privacy, data exchange, and usability. Materials and Methods: We performed a systematic review of systematic reviews to assess technological progress in EHR and PHR systems. We searched MEDLINE, Cochrane, Web of Science, and Scopus for systematic literature reviews on technological advancements that support EHR and PHR systems published between January 1, 2010, and October 06, 2020. Results: The searches resulted in a total of 2,448 hits. Of these, we finally selected 23 systematic reviews. Most of the included papers dealt with information extraction tools and natural language processing technology (n = 10), followed by studies that assessed the use of blockchain technology in healthcare (n = 8). Other areas of digital technology research included EHR and PHR systems in austere settings (n = 1), de-identification methods (n = 1), visualization techniques (n = 1), communication tools within EHR and PHR systems (n = 1), and methodologies for defining Clinical Information Models that promoted EHRs and PHRs interoperability (n = 1). Conclusions: Technological advancements can improve the efficiency in the implementation of EHR and PHR systems in numerous ways. Natural language processing techniques, either rule-based, machine-learning, or deep learning-based, can extract information from clinical narratives and other unstructured data locked in EHRs and PHRs, allowing secondary research (i.e., phenotyping). Moreover, EHRs and PHRs are expected to be the primary beneficiaries of the blockchain technology implementation on Health Information Systems. Governance regulations, lack of trust, poor scalability, security, privacy, low performance, and high cost remain the most critical challenges for implementing these technologies.
URI: https://www.um.edu.mt/library/oar/handle/123456789/134012
Appears in Collections:Scholarly Works - FacHScHSM



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