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Related Experiment Video

Updated: May 8, 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 governance frameworks and change management.

Richard Egelstaff1, Marilyn Wells

  • 1Central Queensland University, Rockhampton Australia.

Studies in Health Technology and Informatics
|September 11, 2013
PubMed
Summary
This summary is machine-generated.

Effective data governance is crucial for healthcare systems, ensuring data protection and appropriate access. This involves understanding data characteristics and usage to establish the right data and access levels for security and compliance.

Related Experiment Videos

Last Updated: May 8, 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:

  • Health Informatics
  • Information Governance
  • Data Management in Healthcare

Background:

  • Electronic data protection and accessibility are critical in healthcare.
  • Determining appropriate data access levels requires careful consideration of data characteristics and intended use.
  • Data governance principles address these challenges within healthcare systems.

Purpose of the Study:

  • To discuss the multifaceted aspects of data governance frameworks within healthcare systems.
  • To explore the organizational and individual transformations necessitated by data governance implementation.
  • To highlight the importance of data governance for secure and effective healthcare data management.

Main Methods:

  • Literature review of data governance principles and frameworks.
  • Analysis of challenges in implementing data governance in healthcare.
  • Exploration of organizational and individual adaptation strategies.

Main Results:

  • Data governance frameworks provide a structure for managing data assets.
  • Successful implementation requires addressing data characteristics, access controls, and user roles.
  • Healthcare organizations face significant changes in policies, procedures, and culture.

Conclusions:

  • Robust data governance is essential for safeguarding sensitive health information.
  • Understanding and adapting to data governance requirements are vital for healthcare professionals and organizations.
  • Implementing comprehensive data governance strategies enhances data integrity, security, and usability.