Structural Equation Modeling in Pharmacy Services
Summary
Structural equation modeling (SEM) has emerged as a pivotal analytical framework in pharmacy services research, enabling simultaneous estimation of complex relationships among observed indicators and latent constructs such as service quality, patient satisfaction and loyalty. By integrating measurement and structural components, SEM offers a unified approach to assess how service attributes (for example counselling, dispensing accuracy or digital interfaces) influence intermediate outcomes (trust, perceived value, emotional response) and, ultimately, patient-centred endpoints (adherence, loyalty, health outcomes). Its capacity to disentangle direct, indirect and mediating pathways supports evidence-based optimisation of pharmacy workflows, informs resource allocation and underpins forecasting of service fees. Globally, SEM has facilitated cross-cultural comparisons of service perceptions, illuminated the role of psychological factors in online medicine uptake and guided strategic interventions to bolster patient engagement. In practice, SEM has been applied to evaluate modular service innovations—from home delivery and telepharmacy to loyalty programmes—and to predict their impact on budgetary planning and quality improvement initiatives.
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Structural Equation Modeling in Pharmacy Services publication trend
The graph below shows the total number of articles in structural equation modeling in pharmacy services across all publications each year (not limited to Nature Index journals).
Technical terms
Structural Equation Modeling (SEM): A multivariate statistical technique that simultaneously estimates relationships among observed indicators and unobserved (latent) constructs within a unified framework.
Latent Variable: An abstract, unmeasured construct inferred from multiple observed indicators, such as “patient trust” or “service quality.”
Measurement Model: The component of SEM that specifies how latent variables are operationalised by observed measures.
Path Coefficient: A standardised estimate of the strength and direction of the relationship between two variables within the structural model.
Partial Least Squares (PLS): A component-based SEM approach prioritising predictive accuracy and allowing for complex models with smaller sample sizes and fewer distributional assumptions.
References
- Building Patient Loyalty in Pharmacy Service: A Comprehensive Model. Indonesian Journal of Pharmacy (2021).
- Projection of future pharmacy service fees using the dispensing claims in hospital and clinic outpatient pharmacies: national health insurance database between 2006 and 2012. BMC Health Services Research (2018).
- Who Are the Online Medication Shoppers? A Market Segmentation of the Swedish Welfare State. Journal of Theoretical and Applied Electronic Commerce Research (2024).
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