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1 – 2 of 2Kevin Wang and Peter Alexander Muennig
The study explores how Taiwan’s electronic health data systems can be used to build algorithms that reduce or eliminate medical errors and to advance precision medicine.
Abstract
Purpose
The study explores how Taiwan’s electronic health data systems can be used to build algorithms that reduce or eliminate medical errors and to advance precision medicine.
Design/methodology/approach
This study is a narrative review of the literature.
Findings
The body of medical knowledge has grown far too large for human clinicians to parse. In theory, electronic health records could augment clinical decision-making with electronic clinical decision support systems (CDSSs). However, computer scientists and clinicians have made remarkably little progress in building CDSSs, because health data tend to be siloed across many different systems that are not interoperable and cannot be linked using common identifiers. As a result, medicine in the USA is often practiced inconsistently with poor adherence to the best preventive and clinical practices. Poor information technology infrastructure contributes to medical errors and waste, resulting in suboptimal care and tens of thousands of premature deaths every year. Taiwan’s national health system, in contrast, is underpinned by a coordinated system of electronic data systems but remains underutilized. In this paper, the authors present a theoretical path toward developing artificial intelligence (AI)-driven CDSS systems using Taiwan’s National Health Insurance Research Database. Such a system could in theory not only optimize care and prevent clinical errors but also empower patients to track their progress in achieving their personal health goals.
Originality/value
While research teams have previously built AI systems with limited applications, this study provides a framework for building global AI-based CDSS systems using one of the world’s few unified electronic health data systems.
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This study employs the social ecology model to comprehensively explore the complex challenges young Black men face in South Africa and aims to highlight the importance of…
Abstract
Purpose
This study employs the social ecology model to comprehensively explore the complex challenges young Black men face in South Africa and aims to highlight the importance of collaboration in addressing these multifaceted issues.
Design/methodology/approach
A multidisciplinary approach combines insights from sociology, education and the health literature with regard to government reports and academic data, and provides a holistic analysis of challenges faced by young Black men. Furthermore, it emphasises formal and informal learning, social and environmental influences and health disparities.
Findings
Young Black men in South Africa encounter complex challenges throughout their developmental journey, including limited family support, educational barriers, financial constraints, societal expectations and health disparities. Therefore, collaboration among stakeholders is essential for creating an equitable and inclusive environment that supports their development.
Originality/value
This research provides a comprehensive understanding of the challenges faced by young Black men in South Africa by emphasising the interconnectedness of informal education, economic empowerment and healthcare. Future research should focus on longitudinal studies, cultural influences and international comparisons, informing evidence-based interventions for a more equitable society.
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