Changes in inpatients' perceptions of the quality of smart healthcare services at county-level public hospitals in Chongqing: a repeated cross-sectional study, 2019-2025
- 1Center for Medical and Social Development Research, School of Public Health, Chongqing Medical University
Abstract
Objective: This study examined temporal changes in the quality of smart healthcare services perceived by inpatients at county-level public hospitals in Chongqing across three survey waves conducted in 2019, 2021, and 2025, and assessed differences across patient subgroups. The findings may inform evaluations of smart healthcare development and the ongoing optimization of healthcare services.
Methods: Questionnaire data collected from inpatients at six county-level public hospitals were analyzed. A SERVQUAL-based instrument assessed patients' expectations and perceptions across reliability, assurance, responsiveness, economic, empathy, and tangibles, and calculated service quality scores accordingly. Analysis of variance was used to assess trends in each dimension, while multivariable linear regression and interaction analyses were used to examine temporal changes in service quality scores and differences across subgroups.
Results: A total of 855 inpatients participated in this study. The mean gap between patients' perceived and expected service quality increased from −0.72 ± 0.60 in 2019 to −0.46 ± 0.47 in 2025, differences among the three survey waves were statistically significant ( P < 0.001). Among the six dimensions, assurance (−0.76 to −0.39), reliability (−0.73 to −0.41), tangibles (−0.64 to −0.34), responsiveness (−0.63 to −0.40), and empathy (−0.65 to −0.42) all showed a significant improvement ( P < 0.001). The economic dimension showed the smallest numerical change (−0.93 to −0.82), differences across the three survey waves were not statistically significant ( F = 1.390, P = 0.250). Service quality scores differed significantly by survey year, age, educational attainment, monthly income, and residence. In particular, patients aged 60 years or older ( B = −0.212, P < 0.001) and those with a bachelor's degree or higher ( B = −0.117, P = 0.019) reported lower scores.
Conclusion: Perceived smart healthcare service quality improved across the three survey waves in county-level public hospitals in Chongqing, and the gap between patients' expectations and perceptions gradually narrowed. However, improvement in the economic dimension was limited. These findings underscore the importance of continuing to advance technological upgrades while promoting the mutual recognition of diagnostic test results across institutions, exploring communication tools such as intelligent consultation systems and bedside interactive terminals, and delivering smart healthcare services tailored to diverse patient needs.
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BibTeX
@article{wen2026changes,
title = {{Changes in inpatients' perceptions of the quality of smart healthcare services at county-level public hospitals in Chongqing: a repeated cross-sectional study, 2019-2025}},
author = {Siyu Wen and Wei Gu and Quanxin Deng and Binyuan Ma and Jing Li},
journal = {Frontiers in Public Health},
year = {2026},
month = oct,
doi = {10.3389/fpubh.2026.1942631},
url = {https://www.frontiersin.org/articles/10.3389/fpubh.2026.1942631/full},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Changes in inpatients' perceptions of the quality of smart healthcare services at county-level public hospitals in Chongqing: a repeated cross-sectional study, 2019-2025
AU - Siyu Wen
AU - Wei Gu
AU - Quanxin Deng
AU - Binyuan Ma
AU - Jing Li
PY - 2026
DA - 2026/10/21
JO - Frontiers in Public Health
DO - 10.3389/fpubh.2026.1942631
UR - https://www.frontiersin.org/articles/10.3389/fpubh.2026.1942631/full
AB - Objective: This study examined temporal changes in the quality of smart healthcare services perceived by inpatients at county-level public hospitals in Chongqing across three survey waves conducted in 2019, 2021, and 2025, and assessed differences across patient subgroups. The findings may inform evaluations of smart healthcare development and the ongoing optimization of healthcare services. Methods: Questionnaire data collected from inpatients at six county-level public hospitals were analyzed. A SERVQUAL-based instrument assessed patients' expectations and perceptions across reliability, assurance, responsiveness, economic, empathy, and tangibles, and calculated service quality scores accordingly. Analysis of variance was used to assess trends in each dimension, while multivariable linear regression and interaction analyses were used to examine temporal changes in service quality scores and differences across subgroups. Results: A total of 855 inpatients participated in this study. The mean gap between patients' perceived and expected service quality increased from −0.72 ± 0.60 in 2019 to −0.46 ± 0.47 in 2025, differences among the three survey waves were statistically significant ( P < 0.001). Among the six dimensions, assurance (−0.76 to −0.39), reliability (−0.73 to −0.41), tangibles (−0.64 to −0.34), responsiveness (−0.63 to −0.40), and empathy (−0.65 to −0.42) all showed a significant improvement ( P < 0.001). The economic dimension showed the smallest numerical change (−0.93 to −0.82), differences across the three survey waves were not statistically significant ( F = 1.390, P = 0.250). Service quality scores differed significantly by survey year, age, educational attainment, monthly income, and residence. In particular, patients aged 60 years or older ( B = −0.212, P < 0.001) and those with a bachelor's degree or higher ( B = −0.117, P = 0.019) reported lower scores. Conclusion: Perceived smart healthcare service quality improved across the three survey waves in county-level public hospitals in Chongqing, and the gap between patients' expectations and perceptions gradually narrowed. However, improvement in the economic dimension was limited. These findings underscore the importance of continuing to advance technological upgrades while promoting the mutual recognition of diagnostic test results across institutions, exploring communication tools such as intelligent consultation systems and bedside interactive terminals, and delivering smart healthcare services tailored to diverse patient needs.
SN - 2296-2565
ER -