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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.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...

Health Information Technology and Healthcare Information System

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:

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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,...

Nursing Clinical Information System

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Statistical Analysis System (SAS)

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Updated: May 29, 2026

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Published on: February 23, 2019

Large scale healthcare data integration and analysis using the semantic web.

John Timm¹, Sondra Renly, Ariel Farkash

¹IBM Almaden Research Center 640 Harry Rd, San Jose, CA 95120, US.

Studies in Health Technology and Informatics

|September 7, 2011

Summary

This summary is machine-generated.

This study introduces tools integrating Semantic Web technologies to improve healthcare data interoperability. This enhances collaboration among diverse experts, leading to better patient care and clinical research.

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A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

Published on: September 20, 2018

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Last Updated: May 29, 2026

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Published on: February 23, 2019

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

Published on: September 20, 2018

Area of Science:

Health Informatics
Semantic Web Technologies
Data Interoperability

Background:

Healthcare data interoperability is crucial for effective data sharing across diverse systems.
Achieving interoperability requires well-defined semantics and consistent implementation.
Collaboration among domain experts is essential for healthcare data integration.

Purpose of the Study:

To describe tooling that integrates Semantic Web technologies with common tools.
To facilitate cross-domain collaborative development for data interoperability.
To improve patient care and clinical research outcomes through enhanced collaboration.

Main Methods:

Data harmonization and representation
Model transformation
Instance generation
Application on the Hypergenes EU project using an Essential Hypertension disease model and CDA template.

Main Results:

Demonstrated successful application of the approach on the Hypergenes project.
Facilitated collaboration between clinical providers, researchers, IT experts, and data consumers.
Showcased the integration of Semantic Web technologies into healthcare interoperability toolkits.

Conclusions:

Integrating Semantic Web technologies enhances opportunities for beneficial collaboration in healthcare.
Improved collaboration leads to advancements in patient care.
Enhanced clinical research outcomes are achievable through better data interoperability.