EAS Publisher | Enhancing Healthcare Communication Efficiency Through NLP-Driven Chatbots: Impact on Patient Satisfaction and Practitioner Workload

Enhancing Healthcare Communication Efficiency Through NLP-Driven Chatbots: Impact on Patient Satisfaction and Practitioner Workload

DOI : 10.36344/ccijmb.2022.v04i05.001

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Abstract: This study investigates the impact of Natural Language Processing (NLP)-enabled chatbot systems on healthcare communication to improve patient satisfaction and reducing clinician workload. Using a dual survey approach, data was generated for 100 patients and 50 clinicians, allowing quantitative assessment of user experience and operational efficiency. Results showed 20% increase in patient satisfaction and 30% reduction in workload due to features like speed of response, clarity and emotional intelligence. The analysis highlights that while chatbots are beneficial, there are disparities based on user digital literacy, emotional expectations and familiarity with Artificial Intelligence (AI). Ethical considerations, accessibility and context specific adaptation emerged as key factors for sustainability. Backed by literature from health, AI and education sectors, the study concludes that NLP powered chatbots can work if designed and implemented with inclusivity, trust and human centric values.

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