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

Deadline for manuscript submissions: closed (28 February 2026) | Viewed by 23779

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Special Issue Editor

Dr. Mahmoud Elbattah

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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 250 words) can be sent to the Editorial Office for assessment.

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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Published Papers (9 papers)

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Research

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26 pages, 3523 KB

Open AccessArticle

A Copula-Based Joint Modeling Framework for Hospitalization Costs and Length of Stay in Massive Healthcare Data

by Xuan Xu and Yijun Wang

Systems 2026, 14(2), 226; https://doi.org/10.3390/systems14020226 - 23 Feb 2026

Viewed by 351

Abstract

In large-scale medical data, the connection between hospital length of stay and medical expenses shows a complex and nonlinear relationship instead of a straightforward positive link. This study proposes a Cox–Log-Logistic–Copula joint modeling framework to describe the marginal distributions and latent dependence between the two variables. Specifically, a semi-parametric Cox proportional hazards model is used for hospitalization duration, while a Log-Logistic model handles medical costs. The two margins are flexibly coupled through a Copula function to capture dynamic variations in cost levels during different hospitalization stages. To address computational challenges in large datasets, this study also includes subsample correction and one-step adjustment algorithms, combined with parallel computing strategies, to enhance estimation efficiency and accuracy. Empirical results show that the length of hospital stays and medical costs are not always positively related. In some cases, higher medical expenses occur during shorter stays, suggesting possible over-treatment or uneven resource distribution. The proposed framework proves to have strong explanatory power in identifying nonlinear patterns in healthcare behavior and offers a new quantitative tool for optimizing medical resource allocation and controlling costs. 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, 384 KB

Open AccessArticle

Access to Care in a Capacity-Constrained System: Do Coverage Expansions Improve Health Outcomes? Evidence from U.S. States, 2006–2023

by Bedassa Tadesse and Iftu Dorose

Systems 2026, 14(2), 224; https://doi.org/10.3390/systems14020224 - 22 Feb 2026

Viewed by 434

Abstract

Coverage expansions and affordability reforms often presume that improved access to care yields better population health. We examine this premise in a capacity-constrained healthcare system, where congestion and throughput determine whether potential access translates into realized care. Using U.S. state-year panel data from 2006 to 2023, we study (i) how healthcare workforce density relates to multiple access margins and (ii) whether the mortality effects of access improvements depend on local delivery capacity. Reduced-form estimates show that higher workforce density is associated with higher insurance coverage and fewer cost-related barriers to care, while associations with having a usual source of care are weaker. With full controls these relationships attenuate, and Medicaid expansion and poverty explain much of the remaining variation. Instrumental variable models suggest that policy-driven improvements in effective access are associated with lower mortality, although the first-stage strength varies across specifications. Interaction-IV estimates indicate capacity dependence: for all-cause and external-cause mortality, implied benefits are larger in lower-capacity settings and diminish as workforce density increases; for endocrine mortality, benefits are concentrated in higher-capacity settings, while respiratory effects are not detectable. Overall, the results support a systems perspective in which the health returns to access expansions depend on local delivery capacity, underscoring the importance of aligning access reforms with constraints in healthcare production and flow. Full article

(This article belongs to the Special Issue Advances in the Modeling and Analytics of Health and Healthcare Systems)

21 pages, 1111 KB

Open AccessArticle

Beyond Immediate Impact: A Systems Perspective on the Persistent Effects of Population Policy on Elderly Well-Being

by Haoxuan Cheng, Guang Yang, Zhaopeng Xu and Lufa Zhang

Systems 2025, 13(10), 897; https://doi.org/10.3390/systems13100897 - 11 Oct 2025

Viewed by 770

Abstract

This study adopts a systems perspective to examine the persistent effects of China’s One-Child Policy (OCP) on the subjective well-being of older adults, emphasizing structural persistence, reinforcing feedback, and path-dependent lock-in in complex socio-technical systems. Using nationally representative data from the China Longitudinal Aging Social Survey (CLASS-2014), we exploit the OCP’s formal rollout at the end of 1979—operationalized with a 1980 cutoff—as a quasi-natural experiment. A Fuzzy Regression Discontinuity (FRD) design identifies the Local Average Treatment Effect of being an only-child parent on late-life well-being, mitigating endogeneity from selection and omitted variables. Theoretically, we integrate three lenses—policy durability and lock-in, intergenerational support, and life course dynamics—to construct a cross-level transmission framework: macro-institutional environments shape substitution capacity and constraint sets; meso-level family restructuring reconfigures support network topology and intergenerational resource flows; micro-level life-course processes accumulate policy-induced adaptations through education, savings, occupation, and residence choices, with effects materializing in old age. Empirically, we find that the OCP significantly reduces subjective well-being among the first generation of affected parents decades later (2SLS estimate ≈ −0.23 on a 1–5 scale). The effects are heterogeneous: rural residents experience large negative impacts, urban effects are muted; men are more adversely affected than women; and individuals without spouses exhibit greater declines than those with spouses. Design validity is supported by a discontinuous shift in fertility at the threshold, smooth density and covariate balance around the cutoff, bandwidth insensitivity, “donut” RD robustness, and a placebo test among ethnic minorities exempt from strict enforcement. These results demonstrate how demographic policies generate lasting impacts on elderly well-being through transforming intergenerational support systems. Policy implications include strengthening rural pension and healthcare systems, expanding community-based eldercare services for spouseless elderly, and developing complementary support programs. Full article

(This article belongs to the Special Issue Advances in the Modeling and Analytics of Health and Healthcare Systems)

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22 pages, 5972 KB

Open AccessArticle

Evaluation and Optimization Research on the Spatial Distribution of Automated External Defibrillators Based on a Genetic Algorithm: A Case Study of Central Urban District of Nanjing, China

by Ge Shi, Jiahang Liu, Chuang Chen, Jingran Zhang, Jinghai Xu, Yu Chen, Jiaming Na and Wei Chen

Systems 2025, 13(1), 64; https://doi.org/10.3390/systems13010064 - 20 Jan 2025

Cited by 1 | Viewed by 2865

Abstract

Automated external defibrillators (AEDs) are portable emergency medical devices critical for resuscitating individuals experiencing sudden cardiac arrest. The installation of AEDs in public spaces is essential for enhancing society’s emergency response capabilities. However, many cities in China currently face issues such as inadequate AEDs deployment and uneven distribution. This study aims to explore a rational layout plan for AEDs through systematic site optimization. Initially, this paper evaluates the current spatial configuration of AEDs in the central urban district of Nanjing using various spatial analysis methods. Subsequently, a coverage model is constructed to simulate the coverage capacity of potential emergency needs for new facilities, and a genetic algorithm is utilized to solve it. Finally, an AED site selection experiment is conducted, and the site selection results are discussed and analyzed in conjunction with practical conditions. The research conclusions are as follows: (1) AED distribution in Nanjing’s central urban district is clustered, with some areas lacking facilities, and the coverage rate of AEDs within 100 m and 200 m ranges is relatively low, particularly across different types of venues; and (2) the optimization experiment, with 90 new site selection points, effectively addressed AED distribution gaps, significantly improved coverage, and ameliorated the overall distribution across various public venues. This study provides a scientific basis for the rational placement of AEDs in urban public spaces through systematic analysis and optimization experiments. It enhances the efficiency of current AED deployment in the main urban areas of Nanjing and offers significant insights for the optimization of urban emergency resource allocation. Full article

(This article belongs to the Special Issue Advances in the Modeling and Analytics of Health and Healthcare Systems)

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17 pages, 363 KB

Open AccessArticle

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 2005

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 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 KB

Open AccessArticle

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

Cited by 5 | Viewed by 5662

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 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 KB

Open AccessArticle

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 11 | Viewed by 2881

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 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 KB

Open AccessArticle

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

Cited by 1 | Viewed by 1836

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 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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Review

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21 pages, 986 KB

Open AccessReview

Integrating Large Language Models into Medication Management in Remote Healthcare: Current Applications, Challenges, and Future Prospects

by Ho Yan Kwan, Jethro Shell, Conor Fahy, Shengxiang Yang and Yongkang Xing

Systems 2025, 13(4), 281; https://doi.org/10.3390/systems13040281 - 10 Apr 2025

Cited by 8 | Viewed by 5152

Abstract

The integration of large language models (LLMs) into remote healthcare has the potential to revolutionize medication management by enhancing communication, improving medication adherence, and supporting clinical decision-making. This study aims to explore the role of LLMs in remote medication management, focusing on their impact. This paper comprehensively reviews the existing literature, medical LLM cases, and the commercial applications of LLMs in remote healthcare. It also addresses technical, ethical, and regulatory challenges related to the use of artificial intelligence (AI) in this context. The review methodology includes analyzing studies on LLM applications, comparing their impact, and identifying gaps for future research and development. The review reveals that LLMs have shown significant potential in remote medication management by improving communication between patients and providers, enhancing medication adherence monitoring, and supporting clinical decision-making in medication management. Compared to traditional reminder systems, AI reminder systems have a 14% higher rate in improving adherence rates in pilot studies. However, there are notable challenges, including data privacy concerns, system integration issues, and the ethical dilemmas of AI-driven decisions such as bias and transparency. Overall, this review offers a comprehensive analysis of LLMs in remote medication management, identifying both their transformative potential and the key challenges to be addressed. It provides insights for healthcare providers, policymakers, and researchers on optimizing the use of AI in medication management. Full article

(This article belongs to the Special Issue Advances in the Modeling and Analytics of Health and Healthcare Systems)

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