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Data-Driven Technology Medical Malpractice: A Narrative Review on the Legal Implications in Clinical Settings
Abstract
Many hospitals employ machine learning algorithms in clinical settings. This technology causes ethical and legal issues including data biases resulting in harm. This narrative research seeks to demonstrate the link between data-driven algorithms in healthcare decision-making and discrimination to certain demographic groups. English peer-reviewed papers from 2020 to June 24, 2024, were searched on Google Scholar. The primary findings revealed ethical issues with clinical AI technology. However, there is a notable lack of well-established protocols to determine liability for AI errors. This cutting-edge technology promises to boost operational efficiency but may simultaneously damage healthcare providers' reputations and patient safety. To safeguard patients and staff, steps must be taken with regard to quality assurance practices prior to implementation.
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