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Issues And Trends In Healthcare Delivery System

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.
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Updated: May 15, 2025

Hydra, a Computer-Based Platform for Aiding Clinicians in Cardiovascular Analysis and Diagnosis

Hydra, a Computer-Based Platform for Aiding Clinicians in Cardiovascular Analysis and Diagnosis

Published on: September 26, 2018

Software Quality Injection (QI): A Quality Driven Holistic Approach for Optimising Big Healthcare Data Processing.

Tia Haddad¹, Pushpa Kumarapeli¹, Simon de Lusignan²

¹School of Computer Science and Mathematics, Kingston University London.

Studies in Health Technology and Informatics

|April 9, 2025

Summary

This study introduces a cloud-computing framework to manage Big Healthcare Data (BHD). It enhances data quality and system resilience for critical healthcare applications.

Keywords:

Applied computing architectural tactics big healthcare data (BHD)cloud computing quality attributes

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Area of Science:

Applied Computing
Software Engineering
Health Informatics

Background:

Big data expansion fuels software development innovation.
Big Healthcare Data (BHD) presents unique challenges due to multi-structured and complex data types.
Resilient and scalable architectures are crucial for addressing BHD quality issues.

Purpose of the Study:

To propose a holistic framework for managing and optimizing Big Healthcare Data (BHD) processing.
To outline an approach for ensuring optimal data handling in critical healthcare workflows.
To enhance system quality attributes for BHD management.

Main Methods:

Adopting advanced cloud-computing strategies.
Implementing a holistic framework for BHD processing.
Utilizing sophisticated orchestration capabilities for real-time adjustment of software functionalities.

Main Results:

Enhanced system quality attributes for BHD processing.
Improved data handling for critical healthcare workflows.
Streamlined operations and bolstered system resilience.

Conclusions:

The proposed cloud-computing framework effectively addresses BHD challenges.
The framework optimizes BHD processing, enhancing data quality and system resilience.
This approach supports advanced analytics and innovation in healthcare computing.