Public Perception of Health Care Before, During, and After COVID-19: Longitudinal Analysis of Online Reviews

Online reviews of health care services represent a growing source of unsolicited, citizen-generated data that can complement traditional instruments for monitoring public perception of health systems. However, longitudinal analyses examining how citizens' perceptions evolved before, during, and after the COVID-19 pandemic remain scarce, and existing studies have rarely differentiated between levels of care.

This study aimed to examine the longitudinal evolution of public perception of a regional public health system over a 10-year period, with particular attention to differences between primary care and hospital services, and to assess whether the COVID-19 pandemic produced a temporary disruption or a more persistent structural shift in citizens' evaluation of health care.

A retrospective longitudinal observational study was conducted using 47,589 online reviews from 812 public health care facilities in Andalusia, Spain, collected from Google Maps between 2016 and 2025. Reviews were classified as positive or negative based on star ratings and validated against manual annotation using Cohen κ. The proportion of negative reviews was analyzed across 3 periods: prepandemic (2016-2019), pandemic (2020-2022), and postpandemic (2023-2025). Structural breaks were identified through change-point detection analysis. Logistic regression models with robust standard errors clustered at the facility level were used to quantify differences in negative sentiment across levels of care and over time.

The proportion of negative reviews increased from 38.7% (2598/6713) in the prepandemic period to 73.7% (13,296/18,046) during the pandemic, remaining elevated at 66.5% (15,181/22,830) in the postpandemic period. Change-point detection identified March 2020 as a major structural break. The pandemic had markedly different effects across levels of care: negative reviews in primary care rose from 34.8% (1330/3819) to 81.9% (10,138/12,371) during the pandemic, remaining at 75.7% (9464/12,505) postpandemic, whereas hospital care showed a more moderate increase from 43.8% (1268/2894) to 55.6% (3158/5675), remaining stable thereafter. Logistic regression models confirmed that the trajectory of negative perception in primary care diverged significantly from hospital care during and after the pandemic, with interaction terms indicating substantially higher odds of negative reviews in primary care during the pandemic (odds ratio 5.28, 95% CI 3.95-7.07) and postpandemic period (odds ratio 3.66, 95% CI 2.66-5.03).

The findings indicate that the COVID-19 pandemic was associated with a persistent structural shift in public perception of health care services rather than a temporary fluctuation and that this shift was disproportionately concentrated in primary care. The sustained deterioration in citizens' perception of primary care observed years after the acute crisis suggests that postpandemic recovery strategies should explicitly address the postcrisis phase and prioritize the relational and communicative dimensions of primary care alongside structural capacity. Large-scale digital trace data offer a scalable and continuous complement to traditional patient satisfaction instruments for monitoring health system legitimacy over time. These findings should be interpreted in light of the self-selection bias inherent to online reviews and the single-region scope of the analysis.