Inpatient morbidity and structural care burden in oropharyngeal carcinoma in Germany: a nationwide cross-institutional EHR analysis using an AI-enabled data network

Abstract Purpose This study aims to characterize hospitalization-level morbidity and care burden associated with oropharyngeal carcinoma (OPC) in Germany and assess the contribution of terminology-based extraction from narrative electronic health record (EHR) documentation beyond structured administrative coding. Methods This nationwide retrospective observational study analyzed inpatient data from 96 German tertiary care hospitals (2016–2022). OPC hospitalizations were identified using ICD-10-GM principal diagnosis codes. Treatment patterns, morbidity indicators, and resource utilization measures were derived from OPS procedural codes, structured clinical variables, and terminology-based extraction from predefined narrative EHR sections. Analyses were conducted at the hospitalization level. Results Among 13,925 OPC hospitalizations, major pharyngeal resections were documented in 9.0% of cases. The proportion reconstructed with microvascular free flaps more than doubled, while resections without reconstruction declined. Robotic-assisted surgery was documented in 0.1% of OPC hospitalizations. Mechanical ventilation was documented in 3.7% of cases, and 19.7% had documentation indicative of tracheostomy. Median hemoglobin decreased during hospitalization, and documented RBC transfusion use increased descriptively from 5.4% in 2016 to 7.6% in 2022. The in-hospital mortality rate was 2.8%. Terminology-based EHR extraction identified additional documentation of selected comorbidities and morbidity markers beyond structured coding alone. Conclusion Hospitalization-level OPC care in German tertiary hospitals involves substantial inpatient care burden, including complex reconstruction, airway-related morbidity, and physiologic morbidity markers. Combining structured administrative data with terminology-based extraction from narrative EHR documentation provided additional routine-data markers beyond coding alone. These findings should be interpreted as complementary hospitalization-level information rather than as validated clinical endpoints or evidence of causal treatment effects.