Intelligent Healthcare Chatbot to Enhance Patient Satisfaction and Engagement with Implementation of Advance HCI Techniques
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ID: 312604
2026
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Abstract
Effective communication is crucial to the quality of healthcare delivery, whereas communication breakdowns between patients and healthcare providers are an ongoing issue. AI Chatbot have proven to be a potential solution to enhance patient interaction and satisfaction through availability and customization. The purpose of this research was to develop and evaluate an AI-based healthcare Chatbot, created in accordance with the principles of advanced HCI, to improve patient interdependence and satisfaction and to compare the performance of the developed Chatbot with the existing healthcare Chatbot. The Chatbot has been created based on publicly available healthcare datasets in Kaggle, and preprocessing, including cleaning and parting of the data and correction of spelling mistakes, have been done. Principles of HCI like usability, accessibility, error handling, and user feedback were taken into consideration and performance determined by usability testing of 150 users, engagement metrics evaluation, and deep-learning testing using accuracy, precision, and recall. It was found that usability was very high (88% of tasks in 12.5 seconds on average, 8% error rate), user satisfaction was 4.6/5 on average, and 85% were of the opinion that the interface was easy to use. The engagement metrics showed that the average session time was 4.5 minutes, 78% of tasks completed and 62% retention rate. The deep learning model was 91.3 %, 89.7 %, and 87.5 % accurate, precise, and recalled, respectively, in terms of the ability to interpret patient requests. Altogether, the HCI-based AI Chatbot enhanced patient engagement and satisfaction considerably through usability, accessibility, and receptive interactions, the error management, individualized communication, and multimodal interface, which supported effective patient-providing communication. The next idea that should be incorporated in the future work is to combine multilingual support, voice-based interaction, and connectivity with the electronic health record in order to increase its efficacy.
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imported_1777055203_69ebb5e3aea88
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| Authors | Nasreen Jawaid |
| Journal | Journal of Computing & Biomedical Informatics |
| Year | 2026 |
| DOI |
10.56979/1101/2026/1186
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| URL | |
| Keywords | Keywords not found |
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