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Artificial Intelligence in Healthcare Delivery System in Nepal: Identifying Challenges and Proposing a Conceptual Framework through Narrative Synthesis
ABSTRACT
Background:
The application of Artificial Intelligence (AI) in the Healthcare Delivery System(HDS) holds significant potential to improve outcomes. The current state of healthcare in Nepal underscores a pressing need for state-of-the-art technologies to enhance patient care and optimize clinical results.
Objective:
This paper aims to provide insights into the benefits and the societal, ethical, and legal concerns of implementing AI in Nepal's HDS. The primary goal is to develop and propose a suitable conceptual framework to guide policymakers on the implementation of such technologies in the health sector.
Methods:
The study was conducted through a detailed narrative review of existing foreign frameworks concerning the use of AI in healthcare systems. Authors also studied existing challenges of implementing AI in HDS in Nepal, in relation to the current status of HDS, societal, legal, and technological aspects of Nepal.
Results:
A relevant and context-specific conceptual framework for AI in the HDS for Low- and Middle-Income Countries (LMICs) was developed. This framework integrates the unique socio-technical, ethical, and infrastructural dimensions of Nepal's healthcare landscape.
Conclusions:
This work contributes considerable information for authorities responsible for policy formulation. The proposed framework provides a crucial foundation for guiding the responsible and effective implementation of AI technologies within Nepal's health sector.
Citation
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.