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The Digital Transformation of Healthcare
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The Digital Transformation of Healthcare

A special issue of Digital (ISSN 2673-6470).

Deadline for manuscript submissions: closed (20 October 2023) | Viewed by 2236

Special Issue Editors

Prof. Dr. Dimitrios Dionisios Koutsouris

E-Mail Website
Guest Editor
Division of Information Transmission Systems and Material Technology, National Technical University of Athens, 10682 Athens, Greece
Interests: biomedical signal processing; clinical engineering; image processing
Special Issues, Collections and Topics in MDPI journals
Dr. Athina Lazakidou

E-Mail Website
Guest Editor
Department of Economics, Digital Health Applications and Health Economics Analytics Laboratory, University of Peloponnese, 221 00 Tripoli, Greece
Interests: health information systems; medical databases; E-health applications

Special Issue Information

Dear Colleagues,

Digital Transformation in Healthcare is the positive impact of technology in healthcare. The healthcare industry is facing the third wave of IT digital technologies with implications so profound analysts believe it is a new era of global computing. Indeed, for all organizations, digital transformation will be galvanized by foundational technologies such as mobility, Internet of Things (IoT), Big Data and Unified Computing (UC).

Thanks to technology, patients get better treatment with virtual reality tools, wearable medical devices, telehealth, and 5G mobile technology. Doctors, on the other hand, can streamline their workflows using artificial intelligence-powered systems.

Nowadays, a numerous scientific community is involved in such studies and, even though many conferences on digital health applications take place regularly, there is room for further initiatives. This open-source Special Issue with cheap publication costs wishes to provide a good opportunity for presenting research results that are immediately readable and usable by other researchers.

The Special Issue aims at collecting recent research on all the below-listed topics. Review papers are also welcome.

Topics of interest include (but are not limited to):

  • Electronic and Mobile Health (eHealth, mHealth)
  • Internet Health Care and Telemedicine
  • Health Information Systems
  • Health Informatics
  • Personalized Medicine
  • Medical Data Systems
  • Medical Device Interoperability
  • Software as a Medical Device (SaMD)
  • Wireless/wearable Medical Devices
  • Biomedical Engineering
  • Connected Health
  • Genomics and Personal Genetic Information
  • Wellness and Prevention
  • Gerontology and Social Care Services
  • Patient Accessibility
  • Advanced Analytics and Artificial Intelligence in Medicine
  • Geographical Information Systems in Healthcare
  • Big Data Analytics in Health Applications

Prof. Dr. Dimitrios Dionisios Koutsouris
Dr. Athina Lazakidou
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Digital is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (2 papers)

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Research

39 pages, 5364 KiB  
Article
Data-Driven Enterprise Architecture for Pharmaceutical R&D
by Nailya Uzhakova (née Sabirzyanova) and Stefan Fischer
Digital 2024, 4(2), 333-371; https://0-doi-org.brum.beds.ac.uk/10.3390/digital4020017 - 22 Apr 2024
Viewed by 491
Abstract
This paper addresses the research gap in the realm of data-driven transformation by leveraging the Resource-Based View (RBV) theory and the dynamic capabilities concept to the contours of a data-driven enterprise. It confronts the limitations of conventional digital and data transformation programs, which [...] Read more.
This paper addresses the research gap in the realm of data-driven transformation by leveraging the Resource-Based View (RBV) theory and the dynamic capabilities concept to the contours of a data-driven enterprise. It confronts the limitations of conventional digital and data transformation programs, which often prioritize technological enhancements over crucial organizational and cultural shifts. Proposing a more holistic perspective, the Data-Driven Enterprise Architecture Framework (DDA) is introduced, emphasizing the domain decomposition and productization of an architecture, distributed ownership, and federated governance, while ensuring the continuous harmonization of data, application, and business architecture. A case study featuring a leading pharmaceutical company illustrates the practical implementation of the DDA framework as a pillar of their Digital Transformation Strategy. By integrating scalable and distributed data architecture into the overarching Enterprise Architecture landscape, the company has initiated their data-driven transformation journey, showcased through their initial and very early results. This research not only offers valuable insights for pharmaceutical organizations navigating the complexities of data-driven transformations, but also addresses a research gap in the field. Full article
(This article belongs to the Special Issue The Digital Transformation of Healthcare)
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19 pages, 1630 KiB  
Article
On the Effectiveness of Fog Offloading in a Mobility-Aware Healthcare Environment
by Ferdous Sharifi, Ali Rasaii, Amirmohammad Pasdar, Shaahin Hessabi and Young Choon Lee
Digital 2023, 3(4), 300-318; https://0-doi-org.brum.beds.ac.uk/10.3390/digital3040019 - 23 Nov 2023
Viewed by 772
Abstract
The emergence of fog computing has significantly enhanced real-time data processing by bringing computation resources closer to data sources. This adoption is very beneficial in the healthcare sector, where abundant time-sensitive processing tasks exist. Although such adoption is very promising, there is a [...] Read more.
The emergence of fog computing has significantly enhanced real-time data processing by bringing computation resources closer to data sources. This adoption is very beneficial in the healthcare sector, where abundant time-sensitive processing tasks exist. Although such adoption is very promising, there is a challenge with the limited computational capacity of fog nodes. This challenge becomes even more critical when mobile IoT nodes enter the network, potentially increasing the network load. To address this challenge, this paper presents a framework that leverages a Many-to-One offloading (M2One) policy designed for modelling the dynamic nature and time-critical aspect of processing tasks in the healthcare domain. The framework benefits the multi-tier structure of the fog layer, making efficient use of the computing capacity of mobile fog nodes to enhance the overall computing capability of the fog network. Moreover, this framework accounts for mobile IoT nodes that generate an unpredictable volume of tasks at unpredictable intervals. Under the proposed policy, a first-tier fog node, called the coordinator fog node, efficiently manages all requests offloaded by the IoT nodes and allocates them to the fog nodes. It considers factors like the limited energy in the mobile nodes, the communication channel status, and low-latency demands to distribute requests among fog nodes and meet the stringent latency requirements of healthcare applications. Through extensive simulations in a healthcare scenario, the policy’s effectiveness showed an improvement of approximately 30% in average delay compared to cloud computing and a significant reduction in network usage. Full article
(This article belongs to the Special Issue The Digital Transformation of Healthcare)
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