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Advances in the Modeling and Analytics of Health and Healthcare...
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Advances in the Modeling and Analytics of Health and Healthcare Systems

A special issue of Systems (ISSN 2079-8954). This special issue belongs to the section "Systems Practice in Social Science".

Deadline for manuscript submissions: 31 May 2025 | Viewed by 4421

Special Issue Editor

Dr. Mahmoud Elbattah

E-Mail Website
Guest Editor
1. Faculty of Environment and Technology, University of the West of England, Bristol BS16 1QY, UK
2. Laboratoire Modélisation, Information, Systèmes (MIS), University of Picardie Jules Verne, 80080 Amiens, France
Interests: health informatics; machine learning; modeling and simulation; knowledge graphs

Special Issue Information

Dear Colleagues,

This Special Issue, “Advances in the Modeling and Analytics of Health and Healthcare Systems”, delves into the intersection of cutting-edge modeling techniques and advanced analytics applied to the intricate landscape of health and healthcare systems. With a focus on innovation, this collection aims to explore the latest methodologies that enhance our understanding of the complex dynamics within health systems, from macro-level organizational structures to micro-level patient interactions. For instance, recent methodologies, such as agent-based modeling and deep learning algorithms, have shown promise in elucidating the intricate relationships between healthcare providers, patients, and healthcare resources.

This Special Issue welcomes contributions that employ sophisticated modeling frameworks, data-driven analytics, and interdisciplinary approaches to address challenges in healthcare delivery, resource optimization, patient outcomes, and public health. For instance, we encourage studies showcasing the efficacy of predictive modeling in identifying high-risk patient populations for targeted interventions, thereby fostering improved care coordination and reduced healthcare costs. Moreover, we welcome contributions spotlighting machine learning applications that exhibit promise in analyzing large-scale healthcare datasets to unveil hidden patterns and correlations, paving the way for more personalized treatment strategies and enhanced patient outcomes.

Topics of interest include, but are not limited to, predictive modeling, machine learning applications, simulation studies, and network analyses, providing a comprehensive exploration of the tools and methodologies shaping the future of health system research.

Dr. Mahmoud Elbattah
Guest Editor

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. Systems is an international peer-reviewed open access monthly 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 2400 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.

Keywords

  • healthcare modeling
  • predictive analytics
  • health system dynamics
  • patient-centric modeling
  • interdisciplinary healthcare research
  • machine learning in healthcare
  • simulation for healthcare systems
  • optimizing resource allocation in healthcare
  • public health analytics
  • enhancing patient outcomes.

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  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (4 papers)

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Research

17 pages, 363 KiB  
Article
Protocol for Identifying and Retaining Critical Knowledge in a Public Health Administration
by Núria Arimany-Serrat, Maria Antentas-Peraile and Elisenda Tarrats-Pons
Systems 2024, 12(11), 505; https://doi.org/10.3390/systems12110505 - 19 Nov 2024
Viewed by 555
Abstract
The Secretary of Public Health (SSP) faces a looming skills gap due to retirements and rotations of civil service staff. Critical knowledge retention is crucial across all generational cohorts due to the retirement and turnover of workers. This study develops a protocol that [...] Read more.
The Secretary of Public Health (SSP) faces a looming skills gap due to retirements and rotations of civil service staff. Critical knowledge retention is crucial across all generational cohorts due to the retirement and turnover of workers. This study develops a protocol that addresses the knowledge retention needs of the four generations (Baby Boomers, X, Y, Z) that coexist in the workforce to ensure the continuity of the Public Health Secretariat. The objective of the study is to develop a protocol for the management, transfer, and retention of critical knowledge. A scoping review is conducted in Scopus and Web of Science to develop the protocol, to identify critical knowledge workers through tool scores. The instrument developed in this research includes two pilots on Baby Boomer and Millennial workers. Both workers had critical and essential knowledge for the continuity of the organisation. The Baby Boomer worker presented a higher amount of tacit, operational, and individually owned knowledge, while the Millennial worker showed a predominance of tacit technological knowledge. This protocol provides a practical and adaptable approach to identifying and prioritising critical knowledge holders, allowing organisations to map and determine the amount of essential knowledge within the workforce. An important limitation of the study is the small sample of workers who participated in the pilot test of the protocol. Further research is therefore recommended in other public administrations and across all generations in employment. Full article
(This article belongs to the Special Issue Advances in the Modeling and Analytics of Health and Healthcare Systems)
22 pages, 1491 KiB  
Article
Digital Transformation: A Challenge for the Romanian Health System
by Nicu Rotaru and Eduard Edelhauser
Systems 2024, 12(9), 366; https://doi.org/10.3390/systems12090366 - 14 Sep 2024
Viewed by 950
Abstract
This study analyzes the current status of the digitalization of the Romanian Health System (RHS). Data were collected from 135 active public and private health professionals using an online questionnaire with 102 items. The results of the analysis show that, if the qualification [...] Read more.
This study analyzes the current status of the digitalization of the Romanian Health System (RHS). Data were collected from 135 active public and private health professionals using an online questionnaire with 102 items. The results of the analysis show that, if the qualification level and the experience of managers are high, seniority in management positions is an essential factor in the adoption of digital technologies, the digitalization of health services increases the efficiency and quality of medical and management services, and the success of the implementation of digital technologies is conditioned by the harmonization of a variety of factors because there are differences between the public and private sectors in terms of the economic efficiency determined by the adoption of digital technologies. There are also differences in the implementation of digital technologies between the national and worldwide levels, there are specific technologies that positively influence managerial performance, and the innovation process is conditioned by the management level. Because Romanian health service managers are updated with new technologies, they can ensure the implementation of digital technologies, considering that economic efficiency and managerial performance are directly related to the level of adoption and the type of technologies implemented. Full article
(This article belongs to the Special Issue Advances in the Modeling and Analytics of Health and Healthcare Systems)
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16 pages, 1699 KiB  
Article
Enhanced Medical Education for Physically Disabled People through Integration of IoT and Digital Twin Technologies
by Abhishek Kumar, Abdul Khader Jilani Saudagar and Muhammad Badruddin Khan
Systems 2024, 12(9), 325; https://doi.org/10.3390/systems12090325 - 26 Aug 2024
Cited by 1 | Viewed by 1512
Abstract
This research presents an innovative approach to revolutionize IoT service development in medical education, specifically designed to empower individuals with physical disabilities. By integrating digital twin technology, we offer dynamic virtual representations of tangible assets, facilitating real-time simulation, monitoring, and feedback. A unique [...] Read more.
This research presents an innovative approach to revolutionize IoT service development in medical education, specifically designed to empower individuals with physical disabilities. By integrating digital twin technology, we offer dynamic virtual representations of tangible assets, facilitating real-time simulation, monitoring, and feedback. A unique visual response algorithm has been developed to enhance the processing of visual vector data, resulting in a more efficient IoT service development process. Our method demonstrates superior performance over traditional techniques, particularly in achieving higher intrinsic variable merging values, which is critical for accurate and accessible visualization. The practical applications of this technology are highlighted through case studies that demonstrate how physically disabled students can benefit from interactive and immersive educational experiences. For instance, students can engage with the digital twins of medical equipment, allowing them to practice procedures and gain hands-on experience in a virtual environment without physical barriers. This approach not only improves accessibility but also personalizes learning experiences, adapting to the unique needs of each student. The research underscores the importance of inclusive design in developing IoT services, ensuring higher inclusivity rates and addressing diverse learning patterns. The findings suggest that the integration of IoT and digital twin technologies can significantly enhance medical education, making it more accessible, effective, and inclusive for physically disabled individuals. This study lays the groundwork for future advancements in this field, highlighting the potential for ongoing technological innovations to further transform medical education. Full article
(This article belongs to the Special Issue Advances in the Modeling and Analytics of Health and Healthcare Systems)
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24 pages, 14732 KiB  
Article
How to Effectively Promote Vaccination during Public Health Emergencies: Through Inter-Organizational Interaction
by Yuwei Song, Ruining Ma, Chenxi Lian, Yanan Guo and Shi An
Systems 2024, 12(8), 312; https://doi.org/10.3390/systems12080312 - 21 Aug 2024
Viewed by 734
Abstract
Vaccination is the key to interrupting the transmission of viruses, reducing public health losses, and improving the efficiency of public health emergency management. The implementation of vaccination requires communication between the government and the public, and the participation of multiple subjects. Strengthening the [...] Read more.
Vaccination is the key to interrupting the transmission of viruses, reducing public health losses, and improving the efficiency of public health emergency management. The implementation of vaccination requires communication between the government and the public, and the participation of multiple subjects. Strengthening the coordination of multiple subjects in the process of vaccination can improve the vaccination rate and broaden its scope. Therefore, from the perspective of inter-organizational interaction, a public health emergency vaccination game model based on health management departments, vaccinologists, and the public was constructed in this study. With the objective of improving the effectiveness of vaccination, the influential factors in a public health emergency vaccination game system and game subjects’ strategy selection were explored using a numerical simulation analysis. The research results showed that the range of vaccination, the diversification of vaccination information release, the level of emergency coordination between health management departments and vaccinologists, and the public’s awareness of emergency protection can all effectively promote vaccination. Among them, the effects of vaccination range (δ) and the diversification of vaccination information release (φ) on game subjects’ strategy selection fluctuated, but did not affect the overall trend. Both the level of emergency collaboration (θ) and public safety awareness (ε) can enhance the initiative of game subjects to participate in vaccination. When the stable strategy combination formed by the game system are positive promotion strategy, active guidance strategy and active vaccination strategy, the convergence rate of health management departments and vaccinologists to form a stable strategy is greater than that of the public. Further, the implications of promoting the effective implementation of vaccination are put forward via improving the vaccination strategy, strengthening vaccination collaboration, mobilizing the enthusiasm of vaccinologists, and enhancing the initiative of the public. Full article
(This article belongs to the Special Issue Advances in the Modeling and Analytics of Health and Healthcare Systems)
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