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Related Concept Videos

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:
Methods Of Healthcare Delivery System01:26

Methods Of Healthcare Delivery System

At the different levels of the healthcare system, we see varying methods of healthcare used. These methods include managed care systems, case management, and primary healthcare.
Managed Care System:
The managed care system is designed to control the cost while maintaining the quality of care. The patient's care from admission to discharge is planned by the primary care provider or the case manager, also known as the gatekeeper. In a managed care system, the number of care providers is limited...
Ethical Standards I01:25

Ethical Standards I

The American Nurses Association (ANA) created and implemented the first nationally accepted Code of Ethics for Nurses with Interpretive Statements. The Code of Ethics is a living document regularly updated by the ANA and establishes an ethical standard that is non-negotiable for nurses in all roles and settings.
The Code of Ethics provisions outline the nurse's duty to the patient, the healthcare team, the profession, and society. The Code's fundamental principles include advocacy,...
Healthcare Associated Infections II: Preventive Measures01:22

Healthcare Associated Infections II: Preventive Measures

Essential infection prevention measures are based on the knowledge of the infection chain, the modes of transmission in healthcare settings, and the use of the best practices in all healthcare settings. Compulsory public reporting of healthcare-associated infection rates is needed to allow individuals and the community to make informed choices regarding selecting a healthcare facility.
The best practices for preventing healthcare-associated infections include hand hygiene, patient risk...
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...
Documentation in Long-Term and Home Healthcare Setting01:29

Documentation in Long-Term and Home Healthcare Setting

Documentation in long-term care facilities and home healthcare settings is crucial for ensuring continuous, coordinated, and comprehensive care for patients. Each setting has its specific documentation processes and tools:
Long-Term Care Facilities

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Related Experiment Video

Updated: Jul 4, 2026

Executing Complexity-Increasing Queries in Relational (MySQL) and NoSQL (MongoDB and EXist) Size-Growing ISO/EN 13606 Standardized EHR Databases
07:26

Executing Complexity-Increasing Queries in Relational (MySQL) and NoSQL (MongoDB and EXist) Size-Growing ISO/EN 13606 Standardized EHR Databases

Published on: March 19, 2018

Data-Oriented Practices for Sustainable Healthcare Organizations.

Abdullateef Almuhrij1,2, Abdullah Alanazi1,2, Mohammed Alanazi1,2

  • 1King Saud Ibn Abdulaziz University for Health Sciences, Saudi Arabia.

Studies in Health Technology and Informatics
|July 3, 2026
PubMed
Summary
This summary is machine-generated.

Data governance is crucial for sustainable healthcare organizations, improving decision-making, competitive advantage, and operational effectiveness. Standardized guidelines are needed due to healthcare

Keywords:
Data GovernanceDigital TransformationHealth Information ManagementSustainable Organizations

Related Experiment Videos

Last Updated: Jul 4, 2026

Executing Complexity-Increasing Queries in Relational (MySQL) and NoSQL (MongoDB and EXist) Size-Growing ISO/EN 13606 Standardized EHR Databases
07:26

Executing Complexity-Increasing Queries in Relational (MySQL) and NoSQL (MongoDB and EXist) Size-Growing ISO/EN 13606 Standardized EHR Databases

Published on: March 19, 2018

Area of Science:

  • Healthcare Management
  • Information Governance
  • Organizational Sustainability

Background:

  • Data-driven decision-making is critical in healthcare, impacting patient lives and organizational viability.
  • Effective data governance extends beyond mere compliance, underpinning organizational sustainability.
  • The healthcare industry faces unique challenges in data standardization due to process complexity and data heterogeneity.

Purpose of the Study:

  • To review the literature of the past decade on the roles of data governance in achieving sustainable healthcare organizations.
  • To identify key contributions of data governance to organizational transformation and competitive advantage.
  • To highlight the need for standardized best practices in healthcare data governance.

Main Methods:

  • Systematic literature review of studies published in the last decade.
  • Analysis of fifteen selected studies focusing on data governance in healthcare.
  • Synthesis of findings regarding the impact and roles of data governance.

Main Results:

  • Data governance transforms organizations, enhances competitive advantage, and boosts performance and effectiveness.
  • It harmonizes processes and data through flexible, scalable, and structured management practices.
  • Key outcomes include improved data flow, data reuse, and organizational interoperability.

Conclusions:

  • Data governance is essential for sustainable healthcare organizations, enabling transformation and improving operations.
  • Standardization of data governance practices in healthcare is underdeveloped and necessary.
  • Further empirical research is required to understand context-dependent outcomes of data governance.