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Related Concept Videos

Issues And Trends In Healthcare Delivery System01:29

Issues And Trends In Healthcare Delivery System

The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
Health Information Technology and Healthcare Information System01:30

Health Information Technology and Healthcare Information System

Health Information Technology (HIT)
Health Information Technology, commonly called HIT, integrates advanced information systems and technology in healthcare settings. Its primary functions include:
Current Trends in Nursing II01:30

Current Trends in Nursing II

Trends in nursing are multifactorial and associated with changes in society, within the nursing profession, and in other professions. Notably, telehealth and remote nursing contribute to successful healthcare delivery for numerous patients and help reduce stress for nurses due to nursing shortages. Nurses can reach patients, monitor their conditions, and interact with them using computers, audio, visual accessories, and telephones—for example, remote patient monitoring systems. Likewise,...
Current Trends in Nursing I01:28

Current Trends in Nursing I

Current trends in nursing include:
Integrated Healthcare System01:20

Integrated Healthcare System

An integrated healthcare system (IHS) is a set of organizations that provides for or arranges to provide coordinated and continuous service to a defined population. The IHS takes responsibility for that particular population's health status and outcome, both clinically and fiscally. An integrated healthcare system is a well-organized, well-coordinated, and collaborative network. The integrated delivery system is a network that connects different healthcare providers to deliver organized,...
Methods of Documentation VI: Case Management Model01:15

Methods of Documentation VI: Case Management Model

The case management model is a multidisciplinary approach that involves healthcare professionals from diverse disciplines, such as physicians, nurses, therapists, social workers, and pharmacists, working collaboratively to address the various needs of patients. Each healthcare professional brings unique expertise and perspectives, contributing to a more comprehensive understanding of the patient's condition and tailoring treatment plans accordingly.
For example, a patient with a chronic illness...

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Related Experiment Videos

Artificial Intelligence in Demand and Capacity Modelling of Healthcare Systems.

Caio Ribeiro, Yulei Fan, Charlotte Mullins

    IEEE Journal of Biomedical and Health Informatics
    |June 12, 2026
    PubMed
    Summary

    Artificial intelligence (AI) offers advanced methods for healthcare systems management, improving demand and capacity modeling. Addressing challenges like data quality and ethics is crucial for AI integration in healthcare.

    Related Experiment Videos

    Area of Science:

    • Healthcare Management
    • Artificial Intelligence
    • Operations Research

    Background:

    • Healthcare systems face increasing complexity in management.
    • Advanced methodologies are needed for resource allocation, service delivery, and strategic planning.
    • Artificial intelligence (AI) provides data-driven insights for operational decisions.

    Purpose of the Study:

    • To conduct a comprehensive scoping review of AI-based approaches for demand and capacity modeling in healthcare systems.
    • To examine AI methods applied to demand prediction (outpatient, ED, admissions, LOS) and capacity planning (beds, workforce, equipment).
    • To report trends in AI model design, learning paradigms, performance, data usage, and the link between demand and capacity predictions.

    Main Methods:

    • Scoping review of AI applications in healthcare demand and capacity modeling.
    • Analysis of AI model design, learning paradigms, performance metrics, and data utilization.
    • Examination of data infrastructure, datasets, and the role of explainable AI.

    Main Results:

    • AI models are increasingly used for predicting healthcare demand and planning capacity.
    • Trends show diverse AI model designs and learning paradigms.
    • Explainable AI is gaining importance for transparency and trust in AI applications.

    Conclusions:

    • AI offers significant potential for optimizing healthcare systems management.
    • Challenges such as data privacy, ethics, quality, interpretability, bias, and interoperability must be addressed for successful AI integration.
    • Future research should focus on overcoming these challenges to develop sustainable, fair, and resilient healthcare systems.