Modelling Semantic Interoperability in Distributed Health Information Systems Through Enabling Techniques

The evolution of distributed healthcare systems has accelerated the digitization of patient records and health data across facilities, yet semantic interoperability remains a critical challenge, particularly in low-resource contexts. This study explored the enablers of semantic interoperability in distributed health information systems in Kenya, focusing on the roles of Data Mapping Techniques, Security Techniques, Electronic Health Record (EHR) Standards, and System Usability. Four specific objectives guided the research: (i) to determine the relationship between Data Mapping Techniques and Semantic Interoperability, (ii) to assess the association between EHR Standards and Semantic Interoperability, (iii) to evaluate the impact of Security Techniques on Semantic Interoperability, and (iv) to develop and validate a Distributed Healthcare Data Integration and Semantic Interoperability Model (DHDI-SIM). Anchored in a pragmatic research paradigm and employing a descriptive-correlational design, the study sampled 301 respondents across four Level 5 hospitals in Kenya using stratified proportional random sampling. Instrument reliability was confirmed (Cronbach’s α > 0.7), while content and face validity were established through expert judgment with an average validity score of 0.93, supporting internal consistency and validity of measurement. Inferential statistical analyses revealed key relationships: a significant but weak positive correlation between Data Mapping Techniques and Semantic Interoperability (ρ = 0.030, p = 0.02); a negligible but significant correlation between EHR Standards and Semantic Interoperability (ρ = 0.007, p = 0.04); and a moderate positive relationship between Security Techniques and Semantic Interoperability (ρ = 0.053, p =0.002). Mediation analysis using PROCESS Macro (Model 4) confirmed that System Usability significantly mediates the effects of Security Techniques (β = 0.250, p < 0.001), Data Mapping Techniques (β = 0.120, p = 0.003), and EHR Standards (β = 0.312, p < 0.001) on Semantic Interoperability. The final integrative model, DHDI-SIM, quantifies the weighted contributions of three core constructs to Semantic Interoperability via System Usability: Data Mapping Techniques (5.0%), Security Techniques (10.4%), and EHR Standards (13.0%). Expert validation yielded a high approval rating (mean score = 4.479), affirming the model’s practical relevance and contextual accuracy. Theoretically, this study extends the Information Systems Success Model (ISSM) by operationalizing Semantic Interoperability through system-level and human-centered constructs in low-resource environments. Practically, it provides healthcare institutions with a tested framework for enhancing data integration, while policy-wise, it offers structured recommendations for implementing HL7/FHIR-compliant solutions, enforcing minimum security standards, and promoting usability-driven digital health adoption. The study concludes that achieving semantic interoperability in Kenya’s distributed healthcare systems requires a synergistic approach that combines technical standardization, security protocols, and human usability factors.