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Related Concept Videos

Issues And Trends In Healthcare Delivery System01:29

Issues And Trends In Healthcare Delivery System

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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.
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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,...
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Nursing Clinical Information System (NCIS)
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Specialized care provided over an extended period is called tertiary care. Usually, a primary or secondary care physician will refer a patient to tertiary care. A patient's maximum physical and mental function is restored in tertiary care, which is caused due to the impact of a chronic illness or condition. Tertiary care aims to achieve the highest level of functioning possible while managing chronic illness. For example, a patient who falls and fractures their hip will need secondary care...
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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

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Optimized cluster based routing protocol for IoT enabled healthcare data networks.

Sree Chandra Swarna1, Venkata Ratnam Kolluru2, Balamuralikrishna Potti3

  • 1Department of ECE, Koneru Lakshmaiah Education Foundation, Guntur, Andhra Pradesh, India. sreechandra23@gmail.com.

Scientific Reports
|April 15, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces a novel routing protocol for Internet of Things (IoT) healthcare networks, enhancing data transmission efficiency and security. The Grey Wolf Optimization-based Multi-Adaptive Routing Protocol (GWO-MARP) significantly improves network performance and reduces energy consumption.

Keywords:
Cluster headCognitive radio networksHunting behaviourInternet of thingsRouting protocol

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Area of Science:

  • Computer Science
  • Network Engineering
  • Telecommunications

Background:

  • Internet of Things (IoT) integration in healthcare enables real-time monitoring but faces challenges in Cognitive Radio Networks (CRNs).
  • Key issues include high energy consumption, routing delays, and security vulnerabilities in existing IoT healthcare networks.
  • Traditional cluster-based routing methods often rely on static or energy-weighted cluster head selection, limiting adaptability.

Purpose of the Study:

  • To propose a novel Grey Wolf Optimization-based Multi-Adaptive Routing Protocol (GWO-MARP) for IoT-enabled healthcare networks.
  • To address challenges of energy consumption, routing delays, and security in IoT-enabled CRNs.
  • To enhance the robustness, scalability, and energy efficiency of data transmission in healthcare IoT systems.

Main Methods:

  • Developed GWO-MARP, a cluster-based routing protocol utilizing adaptive meta-heuristic intelligence.
  • Implemented a multi-objective fitness function for dynamic cluster head selection, balancing residual energy, network lifetime, link quality, and security cost.
  • Employed the Grey Wolf Optimization (GWO) algorithm's hunting behavior for optimal path formation and secure, energy-aware data transmission.

Main Results:

  • GWO-MARP demonstrated significant performance improvements compared to existing protocols (DA-EDC, MT-DQL, SDL).
  • Achieved higher throughput (44.30 kbps), improved packet delivery ratio (99.6%), and reduced end-to-end delay (1.175 ms).
  • Showcased substantial reduction in energy consumption (0.103 J) for a network of 200 nodes.

Conclusions:

  • The proposed GWO-MARP protocol effectively overcomes limitations of traditional routing methods in IoT healthcare networks.
  • Results validate the protocol's capability for robust, scalable, and energy-efficient data transmission.
  • GWO-MARP offers a promising solution for enhancing the performance and reliability of IoT-enabled healthcare applications.