Survey of smart public healthcare in Taiwan finds reliability rated weakest against importance

An exploratory survey of adults in Taiwan has found that people rate the perceived performance of smart public healthcare services lower than the importance they assign to those services across every dimension measured, with reliability showing the largest gap. The study, published in BMC Health Services Research, combined a modified SERVQUAL framework with importance–performance analysis and used structural equation modeling to test whether the proposed measurement structure held up. It did not.

The research was conducted as a cross-sectional online survey in December 2024, recruiting 203 adults through convenience and network-referral sampling. Respondents rated the importance of 20 ideal-service attributes and the perceived performance of 20 corresponding attributes of actual services. These attributes were organized into five modified SERVQUAL dimensions: tangibles, reliability, responsiveness, assurance, and empathy. Four overall evaluations were also collected.

Across all five dimensions, mean perceived-performance ratings were numerically lower than importance ratings. Reliability showed the largest mean discrepancy at −0.526, followed by tangibles at −0.510, assurance at −0.473, responsiveness at −0.454, and empathy at −0.379. The authors treated these performance-minus-importance differences as descriptive discrepancies rather than as conventional SERVQUAL expectation–perception gaps, a deliberate methodological choice that shapes how the results should be read.

The structural equation modeling component was used diagnostically, to examine the measurement structure of separate importance-based and perceived-performance models. The diagnostics did not support the proposed five-dimensional structure. The dimensions were not empirically distinct, with latent correlations reaching as high as 0.992. The importance-based model produced a non-positive-definite latent covariance matrix, and the perceived-performance model produced an inadmissible estimate known as a Heywood case. Because of these problems, the structural coefficients were not interpreted substantively.

Despite the measurement problems, the item-level importance–performance analysis identified three attributes, all related to community-based and continuing care, that showed relatively high importance but relatively low perceived performance. These attributes are presented as candidate areas for further service design inquiry rather than as established intervention priorities.

The authors are careful about the limits of the study. Because the sample was recruited through convenience and network-referral sampling and is not representative of users of Taiwan’s public healthcare system, the findings are framed as a starting point for stakeholder engagement, co-design, and measurement refinement. The study does not provide evidence of causal effects, and the modified SERVQUAL structure requires refinement and independent validation before it can support structural or comparative conclusions.

The methodological transparency is notable. Here, the modeling diagnostics were reported in full, including the non-positive-definite covariance matrix and the Heywood case, and the authors declined to interpret the structural coefficients that those problems invalidated. The result is a paper that reports what its instrument could and could not support.

For health services researchers, the study illustrates both the appeal and the fragility of adapting SERVQUAL to smart public healthcare contexts. The importance–performance analysis, which used standardized item scores, still yielded usable descriptive results even though the latent structure failed validation. The identified community-based and continuing care attributes offer a concrete lead for follow-up work with actual service users and stakeholders.

The study is open access and was published on 29 October 2026. As an exploratory survey with a modest, non-representative sample, its contribution lies in generating hypotheses and refining measurement instruments for future, more representative studies of smart public healthcare services in Taiwan, rather than in establishing how the system as a whole performs.

Subject of Research: Importance and perceived performance of smart public healthcare services among adults in Taiwan, assessed with modified SERVQUAL, importance–performance analysis, and structural equation modeling diagnostics.

Article Title: Importance and perceived performance of smart public healthcare services among adults in Taiwan: an exploratory survey integrating modified SERVQUAL, importance–performance analysis, and SEM-based measurement diagnostics

Article References: Tseng, L.-Y. (2026). Importance and perceived performance of smart public healthcare services among adults in Taiwan: an exploratory survey integrating modified SERVQUAL, importance–performance analysis, and SEM-based measurement diagnostics. BMC Health Services Research. https://doi.org/10.1186/s12913-026-15965-2

Image Credits: AI Generated

DOI: 10.1186/s12913-026-15965-2

Keywords: smart healthcare, public healthcare, Taiwan, SERVQUAL, importance-performance analysis, structural equation modeling, service quality, cross-sectional survey, health services research, community-based care, continuing care, measurement validation