Health Systems最新文献_第2页

Designing a minimum-cost health system for countrywide universal coverage. 设计全国范围内全民覆盖的最低成本卫生系统。

IF 1.2

Health Systems Pub Date : 2025-10-21 eCollection Date: 2026-01-01 DOI: 10.1080/20476965.2025.2570686

João Flávio de Freitas Almeida, Fabricio Oliveira, Samuel Vieira Conceição, Virginie Goepp, Francisco Carlos Cardoso de Campos

{"title":"Designing a minimum-cost health system for countrywide universal coverage.","authors":"João Flávio de Freitas Almeida, Fabricio Oliveira, Samuel Vieira Conceição, Virginie Goepp, Francisco Carlos Cardoso de Campos","doi":"10.1080/20476965.2025.2570686","DOIUrl":"https://doi.org/10.1080/20476965.2025.2570686","url":null,"abstract":"Effectiveness of health systems is achieved through universal coverage, while efficiency is reached by minimizing the cost of delivery. This study presents a novel analysis for designing national health systems, considering workforce, equipment, global costs and accessibility in different geographical contexts. Designed to be a medium- and long-term strategic planning tool, our model offers a practical solution by assessing projected health infrastructure and resources and evaluates health requirements using data from the OECD, the World Bank, OpenStreetMap, and national health statistics. Applied to Brazil, Finland, and France, the analysis is in line with UN Sustainable Development Goal 3.8 and the WHO's Human Resources for Health strategy. The findings suggest that regions with dispersed populations, such as central-western Brazil and northern Finland, would benefit from small hospitals, clinics and health centers. Brazil should hire more health professionals, purchase more radiotherapy equipment and invest $7.95 billion in logistics to reduce patient travel times, particularly for the 1,222 municipalities most affected by low accessibility. Finland would benefit from additional hospital beds and CT scanners, while France could benefit from a more centralized health care model, with municipalities providing all levels of care. France should also invest more in nursing staff and mammography equipment.","PeriodicalId":44699,"journal":{"name":"Health Systems","volume":"15 2","pages":"91-110"},"PeriodicalIF":1.2,"publicationDate":"2025-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13244518/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148212764","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Outpatient chemotherapy planning and decision making: a systematic review. 门诊化疗计划和决策：系统回顾。

IF 1.2

Health Systems Pub Date : 2025-09-15 eCollection Date: 2026-01-01 DOI: 10.1080/20476965.2025.2556061

Nazila Bazrafshan, Sarah S Lam

{"title":"Outpatient chemotherapy planning and decision making: a systematic review.","authors":"Nazila Bazrafshan, Sarah S Lam","doi":"10.1080/20476965.2025.2556061","DOIUrl":"https://doi.org/10.1080/20476965.2025.2556061","url":null,"abstract":"Outpatient chemotherapy is experiencing increased demand while available resources are limited and costly. It is important to have efficient planning for outpatient chemotherapy to optimize the utilization of resources while maintaining the optimal quality of care services. This paper provides a comprehensive review of research studies on outpatient chemotherapy planning (OCP) and decision making. A total of 1,262 articles were retrieved from the most prominent databases (Scopus, PubMed, Web of Science, and Science Direct) and other resources, 99 of which passed the inclusion criteria and were included in this study for analysis. A bibliometric analysis was subsequently conducted with a comprehensive classification of studies based on several predefined criteria that included decision level, problem scope, performance metrics and objectives, complexity factors, methodology, and solution methods. The papers are reviewed in structured categories to provide a detailed overview of this field and highlight the areas that need to be focused on, and the gaps and limitations are summarized. Finally, future research trends on OCP and several promising lines of research that are worthy of study in the future are identified and discussed.","PeriodicalId":44699,"journal":{"name":"Health Systems","volume":"15 2","pages":"140-173"},"PeriodicalIF":1.2,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13188538/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147989389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Generative AI models for type 2 diabetes mellitus risk prediction. 2型糖尿病风险预测的生成式AI模型。

IF 2.2

Health Systems Pub Date : 2025-09-03 eCollection Date: 2026-01-01 DOI: 10.1080/20476965.2025.2546904

Elsa Sharu Johnson, Uma Gandhi, U Srinivasulu Reddy, Umapathy Mangalanathan

{"title":"Generative AI models for type 2 diabetes mellitus risk prediction.","authors":"Elsa Sharu Johnson, Uma Gandhi, U Srinivasulu Reddy, Umapathy Mangalanathan","doi":"10.1080/20476965.2025.2546904","DOIUrl":"10.1080/20476965.2025.2546904","url":null,"abstract":"Diabetes, precisely Type II Diabetes Mellitus (T2DM), is a prevalent global chronic condition. This study focuses on improving the accuracy of predicting T2DM onset and risk by utilizing Generative Artificial Intelligence (GenAI) based synthetic data generation and innovative feature selection techniques. GenAI models such as Deep Tabular Augmentation (DTA) and Large Language Models (LLM) were utilized to address class imbalance and data scarcity of diabetes class for prediction. The Representative Instances-based Fuzzy Rough Set Feature Selection (FRS-RI) method was employed for optimal feature selection. Three diabetes datasets - Sylhet, Obesity, and Diagnostic Features - were employed. After FRS-RI feature selection and synthetic data generation, Machine Learning (ML), Ensemble Learning (EL), and Deep Learning (DL) models were trained on these datasets. The ML, EL, and DL models achieved impressive accuracy, precision, and recall scores: 95.19%, 0.96, and 0.94 for the Sylhet Dataset; 100%, 1.00, and 1.00 for the Obesity dataset; and 97.44%, 0.97, and 0.94 for the NIDDK-DF Dataset. The model's ability to generalize to new diabetic data was demonstrated by enhanced test accuracies of 98.37% and 97.33% obtained when the suggested techniques were applied to benchmark datasets such as PIMA and LMCH, respectively. Emphasis was also placed on model explainability to justify predictions for clinical presentation.","PeriodicalId":44699,"journal":{"name":"Health Systems","volume":"15 1","pages":"66-89"},"PeriodicalIF":2.2,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13353440/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148425175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Accessibility of big data in medicine: adjusting the duration of antibiotic treatment for gram-negative bloodstream infections. 医学大数据的可及性：调整革兰氏阴性血流感染的抗生素治疗时间。

IF 2.2

Health Systems Pub Date : 2025-08-11 eCollection Date: 2026-01-01 DOI: 10.1080/20476965.2025.2544549

Liat Toderis, Iris Reychav, Roger McHaney, Itai Gueta, Dafna Yahav, Ronen Loebstein

{"title":"Accessibility of big data in medicine: adjusting the duration of antibiotic treatment for gram-negative bloodstream infections.","authors":"Liat Toderis, Iris Reychav, Roger McHaney, Itai Gueta, Dafna Yahav, Ronen Loebstein","doi":"10.1080/20476965.2025.2544549","DOIUrl":"10.1080/20476965.2025.2544549","url":null,"abstract":"The current article describes a process to mitigate challenges that arise when medical practitioners and data specialists operate with differing terminologies and face technological and organizational barriers in accessing and utilizing medical big data. We present a structured methodology for improving access to clinical data and apply this approach using a case study focused on optimizing antibiotic management for patients with gram-negative bloodstream infections. Using the ArchiMate® organizational architecture language, we developed a project framework that aligns strategic, business, application, and technological layers of hospital operations. Each component was used to articulate project goals, guide the implementation process, and track intervention outcomes. After implementing a real-time monitoring tool and engaging clinicians directly in the data workflow, 65% of the identified patients received targeted interventions, and the median duration of antibiotic therapy was reduced from 6 to 5 days. Our approach enabled faster decision-making, and drove meaningful organizational change - demonstrating how structured data access can lead to improved healthcare delivery and patient outcomes.","PeriodicalId":44699,"journal":{"name":"Health Systems","volume":"15 1","pages":"51-65"},"PeriodicalIF":2.2,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12915387/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146229036","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Adaptive vaccination and surveillance testing strategies for infectious diseases with diverse strain dynamics. 具有不同菌株动态的传染病的适应性疫苗接种和监测检测策略。

IF 2.2

Health Systems Pub Date : 2025-08-05 eCollection Date: 2025-01-01 DOI: 10.1080/20476965.2025.2533783

Xilin Zhang, Ozgur M Araz, Zeynep Ertem

{"title":"Adaptive vaccination and surveillance testing strategies for infectious diseases with diverse strain dynamics.","authors":"Xilin Zhang, Ozgur M Araz, Zeynep Ertem","doi":"10.1080/20476965.2025.2533783","DOIUrl":"10.1080/20476965.2025.2533783","url":null,"abstract":"The dynamic nature of epidemic diseases presents significant challenges for containment and healthcare resource allocation, particularly as viral strains evolve and outbreak conditions shift over time. While interventions such as testing, vaccination, and quarantine have been widely implemented, most models assess these strategies in isolation. However, we evaluate the combined impact of all aforementioned interventions and optimize resource allocation for maximum effectiveness. This study introduces an adaptive compartmental epidemiological model (SEIR) that integrates dynamic vaccination accessibility and diagnostic surveillance testing strategies, allowing for optimized intervention strategies in response to real-time outbreak progression and demographic variations. Simulation results demonstrate that vaccination effectively reduces infection peaks, while adaptive testing strategies delay peak occurrences and mitigate severity by continuously adjusting to outbreak dynamics and available healthcare resources. By integrating real-time surveillance, strategic testing allocation, and vaccination planning, this model provides a scalable and flexible framework for epidemic preparedness. These findings offer actionable insights for policymakers, guiding the development of robust surveillance systems, optimized resource distribution, and predictive epidemic control measures to mitigate future outbreaks.","PeriodicalId":44699,"journal":{"name":"Health Systems","volume":"14 4","pages":"307-322"},"PeriodicalIF":2.2,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12777841/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145935445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A systematic review of operational research modelling for alcohol consumption and its consequences. 对酒精消费及其后果的运筹学模型的系统回顾。

IF 2.2

Health Systems Pub Date : 2025-08-03 eCollection Date: 2026-01-01 DOI: 10.1080/20476965.2025.2523751

Elin H Williams, Paul R Harper, Geraint I Palmer, Daniel Gartner

{"title":"A systematic review of operational research modelling for alcohol consumption and its consequences.","authors":"Elin H Williams, Paul R Harper, Geraint I Palmer, Daniel Gartner","doi":"10.1080/20476965.2025.2523751","DOIUrl":"10.1080/20476965.2025.2523751","url":null,"abstract":"Recent research has revealed how operational research (OR) models and methods have been successfully applied to model alcohol consumption and its consequences (ACC). However, to date, there is no systematic review of OR methods to model ACC that can provide a broad overview of the utilisation of OR methods in this field. In this paper, we contribute to the OR literature as follows. Firstly, we provide a structured taxonomy which helps categorising the literature. Secondly, we conduct a systematic and reproducible search to identify publications that have utilised OR methods to model ACC. Thirdly, we categorise the relevant publications using the taxonomy and provide a dataset of the classification. Our findings highlight that recent research has focused on modelling consumption behaviours, particularly by utilising graph and network methods. Moreover, previous research has been predominantly led by the social sciences and public health fields and less so by the OR domain. Our results reveal gaps in the literature, including limited whole systems modelling and scarce interdisciplinary collaboration across research domains. The development of a future research agenda using our taxonomy and literature review may help closing these gaps and, ultimately, improve planning decisions to improve health, social care, and crime systems.","PeriodicalId":44699,"journal":{"name":"Health Systems","volume":"15 1","pages":"6-41"},"PeriodicalIF":2.2,"publicationDate":"2025-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12915404/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146229014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The combined use of natural language processing and electronic health records data to identify historical tolerances of β-lactams and promote clinician confidence in future use. 结合使用自然语言处理和电子健康记录数据来确定β-内酰胺的历史耐受性，并提高临床医生对未来使用的信心。

IF 2.2

Health Systems Pub Date : 2025-07-16 eCollection Date: 2026-01-01 DOI: 10.1080/20476965.2025.2534454

Matthew Gray, Richard D Boyce, Sandra L Kane-Gill

{"title":"The combined use of natural language processing and electronic health records data to identify historical tolerances of β-lactams and promote clinician confidence in future use.","authors":"Matthew Gray, Richard D Boyce, Sandra L Kane-Gill","doi":"10.1080/20476965.2025.2534454","DOIUrl":"10.1080/20476965.2025.2534454","url":null,"abstract":"We used natural language processing (NLP) to improve the utility of clinical decision support (CDS) β-lactam allergy alerts and promote informed allergy evaluation. NLP was performed on a corpus of clinical notes from hospital-based encounters to identify previous tolerance of β-lactam products using a rule-based approach. Historical tolerance of β-lactams was then combined with structured electronic health records data to produce improved CDS alerts. A survey was used to evaluate the utility of the improved alerts compared to standard allergy alerts. The rule-based pipeline identified previous β-lactam tolerance in between 3% and 28.4% of clinical notes and performed with high positive predictive value (83.6-97.6%) and recall (71.2-79.4%). The surveyed clinicians (N = 9) reported increased confidence in using β-lactam products despite the presence of a documented β-lactam allergy when using the information presented by the NLP-enriched CDS alerts, and all surveyed clinicians indicated the alerts would improve the care of their patients. NLP of clinical notes shows potential to improve the utility of CDS allergy alerts. Clinicians were receptive to allergy alerts containing NLP-derived information. Allergy-related CDS alerts should be improved to provide additional information such as historical tolerance of relevant products to empower providers to make informed decisions regarding patient allergies.","PeriodicalId":44699,"journal":{"name":"Health Systems","volume":"15 1","pages":"42-50"},"PeriodicalIF":2.2,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13353335/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148425142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Revolutionising health monitoring: IOT-Based system with machine learning classification. 革命性的健康监测：基于物联网的系统与机器学习分类。

IF 2.2

Health Systems Pub Date : 2025-05-26 eCollection Date: 2025-01-01 DOI: 10.1080/20476965.2025.2507620

Alka Mishra, Aryan Dewangan, Mayank Dewangan

{"title":"Revolutionising health monitoring: IOT-Based system with machine learning classification.","authors":"Alka Mishra, Aryan Dewangan, Mayank Dewangan","doi":"10.1080/20476965.2025.2507620","DOIUrl":"10.1080/20476965.2025.2507620","url":null,"abstract":"In the pursuit of revolutionising health monitoring, this study introduces an IoT-based smart health monitoring system coupled with a machine learning classification framework. This innovative system tracks five crucial health parameters - Temperature, SPO2, Glucose level, Pulse rate, and Heart rate - providing a comprehensive overview of an individual's health status in real-time. Leveraging these parameters, a dataset is constructed, facilitating the application of four distinct machine learning algorithms: Support Vector Machine (SVM), Decision Tree, Random Forest, and CN2 rule induction. Remarkably, the classification accuracy achieved by these models demonstrates their efficacy, with SVM scoring 0.859, Tree achieving 0.996, Random Forest attaining 0.984, and CN2 rule induction reaching 0.902, respectively. Notably, among these algorithms, the Tree model emerges as the most superior, showcasing its potential for effectively analysing this type of dataset and enhancing the performance of health monitoring systems. Further, ThingSpeak has been utilised as IoT platform within our health monitoring system that facilitates the seamless collection of real-time data from diverse medical devices such as heart rate monitors and glucose metres. With applications in healthcare, home monitoring, sports, fitness, and industrial safety, the system offers versatile solutions for proactive health management and improved well-being.","PeriodicalId":44699,"journal":{"name":"Health Systems","volume":"14 4","pages":"291-306"},"PeriodicalIF":2.2,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12777905/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145935392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Leveraging quality improvement initiatives to support development of decision support tools in healthcare. 利用质量改进计划来支持医疗保健领域决策支持工具的开发。

IF 1.2

Health Systems Pub Date : 2025-05-05 eCollection Date: 2025-01-01 DOI: 10.1080/20476965.2025.2500285

Joe Viana, Christos Vasilakis, Neophytos Stylianou

{"title":"Leveraging quality improvement initiatives to support development of decision support tools in healthcare.","authors":"Joe Viana, Christos Vasilakis, Neophytos Stylianou","doi":"10.1080/20476965.2025.2500285","DOIUrl":"10.1080/20476965.2025.2500285","url":null,"abstract":"Modelling and simulation studies have been used to inform the choices and development of quality improvement (QI) initiatives in health care, for example, by helping refine the intervention to be implemented or support decisions around the management of demand and capacity. We do not know whether a modelling study can itself be informed by a QI project and what are the associated benefits and challenges. In this research, we sought to investigate the opportunities and challenges associated with an ongoing health service-led QI project in informing the development of a stochastic simulation-based decision support tool to inform decisions around the commissioning of anticoagulation services for patients with atrial fibrillation. We found that the positive synergies offered by the QI project included good access to stakeholders and envisaged end users, co-producing relevant and impactful scenarios for experimentation, as well as access to good quality individual patient level data. On the other hand, substantial effort was required to populate input parameters with values that pertain to the natural history of the disease and the effectiveness of the different treatments. Our findings indicate that, if stakeholders require modelling results to inform aspects of a QI project, upfront investment is needed to ensure timely interaction between the two studies.","PeriodicalId":44699,"journal":{"name":"Health Systems","volume":"14 4","pages":"323-336"},"PeriodicalIF":1.2,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12777901/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145935415","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Towards a solution to the global healthcare crisis: using hierarchical decomposition and theory of constraints (TOC) to address the healthcare supply chain wicked problem. 解决全球医疗保健危机：利用层次分解和约束理论（TOC）解决医疗保健供应链问题。

IF 2.2

Health Systems Pub Date : 2025-02-28 eCollection Date: 2025-01-01 DOI: 10.1080/20476965.2025.2460632

James F Cox, Victoria J Mabin

{"title":"Towards a solution to the global healthcare crisis: using hierarchical decomposition and theory of constraints (TOC) to address the healthcare supply chain wicked problem.","authors":"James F Cox, Victoria J Mabin","doi":"10.1080/20476965.2025.2460632","DOIUrl":"10.1080/20476965.2025.2460632","url":null,"abstract":"Healthcare is facing a crisis globally, with rising demand and technological advances escalating costs and outpacing supply. The healthcare supply chain (HCSC) encompasses various links, from primary and specialty care to hospitals, which often fail to function quickly, seamlessly, or cost-effectively individually or together. Indeed, the complexities of healthcare make this a \"wicked problem\" without easy solutions. Research has typically focused on individual links in the supply chain oversimplifying and neglecting their interdependence. Key characteristics - such as the system's hierarchical structure, diverse stakeholder involvement, interdependencies among links, the importance of timeliness, and the need to cope with complexity, change, and uncertainty - are frequently overlooked. Addressing the healthcare crisis requires a pragmatic approach to improving service delivery. This paper advocates for a systems perspective, allowing a breakdown of the problem into manageable units of analysis based on the system hierarchy, viewing each link in the HCSC as integral to the whole. We outline a multimethodology that capitalises on HCSC characteristics to enhance patient flow and provide timely, high-quality, and cost-effective care. It emphasises classifying, prioritising, and synchronising treatment based on urgency. The paper also discusses existing solutions to the system's components and presents a comprehensive strategy for the overall issue.","PeriodicalId":44699,"journal":{"name":"Health Systems","volume":"14 4","pages":"249-275"},"PeriodicalIF":2.2,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12777895/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145935362","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0