<![CDATA[Fragmented hospital applications may require the same demographic, clinical, and administrative information to be entered repeatedly across roles and systems. This synthetic feasibility study develops an auditable framework that links field-level occurrence classification and process-variant analysis to a provisional Clinical Data Redundancy Index (CDRI) and a Fast Healthcare Interoperability Resources (FHIR) R4 target architecture. A fixed-seed simulation generated 480 synthetic journeys across outpatient, emergency, medical check-up, and inpatient pathways, yielding 6,634 events and 96 complete-sequence variants. Repeated occurrences were classified as passive display, clinical confirmation, correction, or full re-entry; only correction and full re-entry entered the provisional CDRI calculation. Under the prespecified base scenario of 88% automation coverage and a 0.87 residual waiting-time factor, median manual-entry time decreased from 10.72 to 7.13 minutes (33.44%), while median journey time decreased from 250.73 to 233.45 minutes (6.89%). Simulated discrepancy opportunities decreased from 210 to 48 (77.14%). These values demonstrate the behavior of the proposed evaluation chain under stated assumptions; they are not estimates of hospital performance or clinical effectiveness. The methodological contribution is the integration of field lineage, process mining, provisional redundancy measurement, FHIR redesign, paired scenario analysis, and an explicit empirical-validation pathway. External calibration and prospective hospital validation are required before practical adoption.]]>
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