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. 2025 Jun 9:13:1535270.
doi: 10.3389/fpubh.2025.1535270. eCollection 2025.

Effectiveness of conversational script optimization by intelligent consultation robots on daily work efficiency in vaccination clinics

Bei Zhou #  1 , Yan Xu #  2 , Jirong Shi  1 , Yi Xiang  3 , Daifei Chen  1 , Qingkui Yao  1 , Yinjun Hu  2
Affiliations

Effectiveness of conversational script optimization by intelligent consultation robots on daily work efficiency in vaccination clinics

Bei Zhou et al. Front Public Health. .

Abstract

Introduction: Vaccines are essential for reducing infectious disease incidence, but challenges like public awareness and healthcare workloads persist. This study aimed to evaluate the impact of optimizing conversational scripts of an intelligent consultation robot on enhancing operational efficiency in vaccination clinics.

Methods: A pilot project was conducted at the vaccination clinic of Minglou Street Community Health Service Center in Ningbo's Yinzhou District. The robot system, developed by Shensu Science and Technology, was implemented from January to May 2024 with four experimental phases. The study used a pre-post comparison framework to assess changes in labor costs, work efficiency, and user satisfaction.

Results: As the scripts evolved, there was a notable increase in automated response rates and a decrease in human support transfers. User satisfaction improved, particularly in the final phase. The robot became more effective at managing user inquiries, reducing reliance on manual services.

Discussion: Optimizing the robot's conversational scripts significantly improved daily operational efficiency in the vaccination clinic. By automating routine consultation tasks, the robot reduced healthcare professionals' workloads. Future research could explore further refinements to dialogue strategies and expand the robot's applications in healthcare settings.

Keywords: conversational script impact; dialogue guidance strategy; intelligent consultation robot; patient satisfaction; vaccination services; work efficiency.

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Conflict of interest statement

YH was employed by Shensu Science and Technology (Suzhou) Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Example Interaction with the intelligent consultation robot system in a vaccination clinic. Dialogue translated from Chinese for clarity.
Figure 2
Figure 2
Research flowchart: assessing the impact of conversational script optimization on operational efficiency in a vaccination clinic.
Figure 3
Figure 3
Temporal trends in two indicators across Exp. 1–4: Experimental 1–4. (A) Direct human support transfer rates over weeks for the four experimental phases. The blue solid line with diamond markers represents the weekly rates, while the red dashed line indicates the smoothed trend. (B) Fully automated response rate over weeks for the four experimental phases. The blue solid line with hourglass markers indicates the weekly rates, and the red dashed line represents the smoothed trend.
Figure 4
Figure 4
(A) Boxplot of direct human support transfer rates for each of the four experimental phases based on daily statistics. (B) Boxplot of fully automated response rate for each of the four experimental phases based on daily statistics.
Figure 5
Figure 5
Weekly trends in the average number of routine questions per call and the average number of routine questions resolved per call for the four experimental phases. The yellow bars represent the average number of routine questions per call, and the blue bars indicate the average number of routine questions resolved per call across the observed weeks. The dashed lines represent the smoothed trend lines, illustrating the overall direction of the data over time.
Figure 6
Figure 6
(A) Boxplot of average number of routine questions per call for each of the four experimental phases based on daily statistics. (B) Boxplot of average number of routine questions resolved per call for each of the four experimental phases on daily statistics.
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