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Health organization challenges in health data governance implementation: A systematic review
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Health data governance is essential for optimal processing of data collection, sharing, and reuse. Although the World Health Organization (WHO) has proposed practical guidelines for managing health data during the pandemic, the Organization for Economic Cooperation and Development (OECD) found that many countries still lack the use of health data for decision-making. Therefore, this research aimed to identify and assess the challenges faced by health organization in implementing health data governance from various countries based on research articles. The challenges were assessed based on key components of health data governance from practitioner and scientist perspectives. These components include stakeholder, policy, data management, organization, data governance maturity assessment, and goals. The method used followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for collecting and reporting. Data were collected from several databases online with large repositories of academic studies, including IEEE Xplore, ScienceDirect, National Library of Medicine, ProQuest, Taylor and Francis Group, Scopus, and Wiley Online libraries. Based on the 41 papers reviewed, the results showed that policy was found to be the biggest challenge for health data governance. This was followed by data management such as quality, ownership, and access, as well as stakeholders and data governance organization. However, there were no challenges regarding maturity assessment and data governance goals, as the majority of research focused on implementation. Policy and policymaker awareness were identified as major components for the implementation of health data governance. To address challenges in data management and governance organization, creating committees focused on these components proved to be an effective solution. These results provided valuable recommendations for regulators and leaders in a healthcare organization to optimally implement health data governance.
Title: Health organization challenges in health data governance implementation: A systematic review
Description:
Health data governance is essential for optimal processing of data collection, sharing, and reuse.
Although the World Health Organization (WHO) has proposed practical guidelines for managing health data during the pandemic, the Organization for Economic Cooperation and Development (OECD) found that many countries still lack the use of health data for decision-making.
Therefore, this research aimed to identify and assess the challenges faced by health organization in implementing health data governance from various countries based on research articles.
The challenges were assessed based on key components of health data governance from practitioner and scientist perspectives.
These components include stakeholder, policy, data management, organization, data governance maturity assessment, and goals.
The method used followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for collecting and reporting.
Data were collected from several databases online with large repositories of academic studies, including IEEE Xplore, ScienceDirect, National Library of Medicine, ProQuest, Taylor and Francis Group, Scopus, and Wiley Online libraries.
Based on the 41 papers reviewed, the results showed that policy was found to be the biggest challenge for health data governance.
This was followed by data management such as quality, ownership, and access, as well as stakeholders and data governance organization.
However, there were no challenges regarding maturity assessment and data governance goals, as the majority of research focused on implementation.
Policy and policymaker awareness were identified as major components for the implementation of health data governance.
To address challenges in data management and governance organization, creating committees focused on these components proved to be an effective solution.
These results provided valuable recommendations for regulators and leaders in a healthcare organization to optimally implement health data governance.
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