Patient Engagement and Satisfaction in Ai-Enhanced Healthcare Management

This study looks into how patient involvement and satisfaction are affected by AI-enhanced healthcare administration. Using a descriptive methodology and secondary data gathered from reliable sources, the research takes an interpretive approach within a deductive paradigm. The findings of the investigation indicate that artificial intelligence (AI)-driven solutions, such as chatbots and virtual assistants, enhance patient engagement by providing easy access to healthcare knowledge and customized interactions. Additionally, patients are happy with the effectiveness and customized care that AI systems offer. Nonetheless, consumer happiness levels are influenced by the caliber of contacts and worries about the confidentiality of data. Transparency, dependability, data privacy, provider expertise, and education for patients all influence people's trust in AI technologies. For artificial intelligence integration to be successful, a technical assessment emphasizes the significance of algorithm efficiency, scalability, seamless integration, data protection, and continuous maintenance. Patient-centered design should be prioritized, stakeholders should be informed, and AI systems should be continuously monitored. Prospective investigations ought to concentrate on extended periods, tailored treatment schemes, psychological assistance, reducing bias, economies of scale, and innovative artificial intelligence approaches.