ArticleEuropean journal of operational research2023
Resource planning strategies for healthcare systems during a pandemic.
Article in European journal of operational research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 82 citations in OpenAlex.
- A stochastic programming approach for dynamic allocation of bed capacity and assignment of patients to collaborating hospitals during pandemic outbreaks.Health care management science · 2026Article
- The Role of Artificial Intelligence in Modern Medicine: Clinical Applications, Economic Implications, and Ethical Considerations.Current pharmaceutical design · 2026Review
- Trends in access to primary care among Canadian older adults before, during, and following the COVID-19 public health emergency.Scientific reports · 2025Article
- Reflexive thematic analysis of emergency department medical records of dementia patients regarding the identification of last days of life.Palliative & supportive care · 2025Article
- Association between healthcare resources, healthcare systems, and population health in European countries.BMC health services research · 2025Article
- Unlocking potential: innovative "private-non-profit" partnership for empowering children with disabilities in resource-limited settings in Nepal.Frontiers in public health · 2025Article
- Joint spatiotemporal evaluation of multiple healthcare resources: hospitals, hospital beds and physicians across 365 Chinese cities over 22 years.Frontiers in public health · 2025Article
- Risk analysis and assessment method for infectious diseases based on information entropy theory.Scientific reports · 2024Article
- Timely accessibility to healthcare resources and heatwave-related mortality in 7 major cities of South Korea: a two-stage approach with principal component analysis.The Lancet regional health. Western Pacific · 2024Article
- Evaluation of healthcare-related factors influencing mental health of Taiwanese citizens among different age groups.Scientific reports · 2024Article
- Two-stage multi-objective optimization for ICU bed allocation under multiple sources of uncertainty.Scientific reports · 2023Article
- Management of cancer cachexia towards optimizing care delivery and patient outcomes.Asia-Pacific journal of oncology nursing · 2023Review
- A simulation model for predicting hospital occupancy for Covid-19 using archetype analysis.Healthcare analytics (New York, N.Y.) · 2023Article
- Supply chain planning of vaccine and pharmaceutical clusters under uncertainty: The case of COVID-19.Socio-economic planning sciences · 2023Article
- Data quality assessment in emergency medical services: an objective approach.BMC emergency medicine · 2023Article
- Machine learning based integrated scheduling and rescheduling for elective and emergency patients in the operating theatre.Annals of operations research · 2023Article
- From numbers to medical knowledge: harnessing combinatorial data patterns to predict COVID-19 resource needs and distinguish patient subsets.Frontiers in medicine · 2023Article
- Introduction to the special issue on the role of operational research in future epidemics/ pandemics.European journal of operational research · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 4 institutions in 5 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We study resource planning strategies, including the integrated healthcare resources' allocation and sharing as well as patients' transfer, to improve the response of health systems to massive increases in demand during epidemics and pandemics. Our study considers various types of patients and resources to provide access to patient care with minimum capacity extension. Adding new resources takes time that most patients don't have during pandemics. The number of patients requiring scarce healthcare resources is uncertain and dependent on the speed of the pandemic's transmission through a region. We develop a multi-stage stochastic program to optimize various strategies for planning limited and necessary healthcare resources. We simulate uncertain parameters by deploying an agent-based continuous-time stochastic model, and then capture the uncertainty by a forward scenario tree construction approach. Finally, we propose a data-driven rolling horizon procedure to facilitate decision-making in real-time, which mitigates some critical limitations of stochastic programming approaches and makes the resulting strategies implementable in practice. We use two different case studies related to COVID-19 to examine our optimization and simulation tools by extensive computational results. The results highlight these strategies can significantly improve patient access to care during pandemics; their significance will vary under different situations. Our methodology is not limited to the presented setting and can be employed in other service industries where urgent access matters.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.