The goal of structuring electronic health data with multiple models has created an interoperability paradox. We analyzed over 140,000 aggregated clinical data elements to identify the root causes of this semantic failure. Key challenges include semantic drift from non-versioned dictionaries, missing traceability from attribute modification, and loss of context when form layout is absent in the data warehouse. This work demonstrates that the solution is not the creation of new models, but the implementation of robust data governance, mandated versioning, and semantic standardization using semantic-centered approaches.