ORIGINAL RESEARCH article
Front. Public Health
Sec. Digital Public Health
Volume 13 - 2025 | doi: 10.3389/fpubh.2025.1535270
This article is part of the Research TopicThe Impact of Robotic Technologies on Customer Experience and AdoptionView all 3 articles
Effectiveness of Conversational Script Optimization by Intelligent Consultation Robots on Daily Work Efficiency in Vaccination Clinics
Provisionally accepted
- 1Minglou Street Community Health Service Center in Yinzhou District, Ningbo, China
- 2Shensu Science & Technology (Suzhou)Co .,Ltd., Suzhou, China
- 3Ningbo Yinzhou District Center for Disease Control and Prevention, Ningbo, China
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The study assesses the impact of conversational scripts used by an intelligent consultation robot on the daily operations of vaccination clinics, with the aim of exploring its role in enhancing preventive vaccination services. A pilot project of the intelligent consultation robot system was conducted at the vaccination clinic of Minglou Street Community Health Service Center in Yinzhou District, Ningbo City, where the iteration process of the robot's conversational scripts and logs of call interactions with users were meticulously documented. Using call data collected from January to May 2024, a pre-post comparison research method was employed to analyze the impact of script iterations on operational efficiency, labor costs, and customer satisfaction. The refinement of conversational scripts allowed the robot to manage user inquiries more effectively, enhancing the interaction experience and reducing reliance on manual services.
Keywords: Intelligent Consultation Robot, Vaccination services, Conversational Script Impact, dialogue guidance strategy, Work efficiency, Patient Satisfaction
Received: 21 Jan 2025; Accepted: 23 May 2025.
Copyright: © 2025 Zhou, Xu, Shi, Xiang, Chen, Yao and Hu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Yinjun Hu, Shensu Science & Technology (Suzhou)Co .,Ltd., Suzhou, China
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