EHR
‐Integrated Synoptic Operative Reporting for Head and Neck Oncologic Surgery
Miriam N. Lango, Avery Sinnathamby, Marc‐Elie Nader, Paul W. Gidley, Karen Y. Choi, Mark Zafereo, Carly E. A. Barbon, Kristen B. Pytynia, Anastasios Maniakas, Amy Hessel, Ryan P. Goepfert, Faisal I. Ahmad, Jennifer L. Anderson, Sahil K. Kapur, Jolyn S. Taylor ABSTRACT
Objective
To describe the development and implementation of electronic health record (EHR)‐integrated synoptic operative templates for head and neck oncologic surgery and to evaluate documentation adherence and performance.
Methods
Single‐institution retrospective quality improvement study of extirpative oncologic resections (mucosal, cutaneous, thyroid, salivary gland, and skull base) performed at a tertiary academic cancer center from January 2025 through April 2026. Tumor‐specific adaptive synoptic templates were developed through literature review, professional society guidance, and subspecialty consensus and integrated into the EHR. Adherence was defined as synoptic template use for eligible cases; performance was defined as the proportion of cases with complete and internally consistent synoptic data, with an acceptable rate set at 90% or higher. The first 253 consecutive cases with synoptic documentation underwent detailed performance review.
Results
Departmental adherence increased from 49% to 69%–78% over the final 6 months and varied among surgeons (range, 7%–100%). Surgeons who personally completed operative reports adhered more often than those delegating to trainees (85% vs. 56%; p < 0.001), as did high‐volume surgeons (85% vs. 56%; p < 0.001). Among 253 reviewed cases, 239 (94.5%) met the completeness and consistency target. Missing data exceeded inaccuracies (12 vs. two cases). Performance failures were more frequent with the thyroid template than with all other templates combined (10.8% vs. 1.8%; p < 0.001).
Conclusion
EHR‐integrated synoptic operative templates for head and neck oncologic surgery demonstrate acceptable documentation performance but variable uptake. The underlying structured data framework may support multicenter standardization, registry‐based outcomes research, and AI‐enabled surgical documentation.
Level of Evidence
Not applicable.