Transforming oncology documentation exchange through intelligent automation: Operational outcomes and organizational lessons from a cancer center implementation.

Abstract

e13659 Background: Timely exchange of oncology clinical documentation is vital for care coordination, yet many cancer centers rely on manual, fax-based note routing despite widespread adoption of electronic health records (EHRs). Manual workflows are labor-intensive, error-prone, and poorly suited for high-volume oncology care centers with complex referral networks, leading to delays, misrouted notes, and administrative burden. The Automated Intelligent Note Routing (AINR) system was implemented over 3.5 years starting in 2021 and designed to replace manual documentation exchange. AINR automatically detects signed oncology notes in the EHR and routes them using rule-based logic supported by standardized provider data, prioritized registries, and automated audit reporting. Methods: This mixed-method analysis used qualitative and quantitative operational data, including stakeholder interviews, workflow observations, governance records, and system audit logs. Outcomes assessed included efficiency, accuracy, timeliness, labor utilization, and workflow accountability. AINR implementation was staged in phases with iterative refinement based on daily monitoring and exception reporting. Results: The implementation of the AINR resulted in significant reductions in (1) clinical note processing time, (2) staff hours dedicated to documentation routing, which has enabled the redeployment of staff toward exception management and data quality oversight, and (3) the number of misrouted notes. In addition to these direct clinical process and resource utilization benefits, the patient care process involving multiple organizations is streamlined, facilitating patient-centered, evidence-based continuity of cancer treatment. Remaining transmission failures were largely attributable to organizational factors, including incomplete provider relationships and recipient opt-outs, rather than technical limitations. Conclusions: AINR significantly improved the efficiency, accuracy, and reliability of oncology documentation exchange while driving meaningful workflow redesign. Successful automation required shifting accountability for provider data upstream and redefining medical records roles from manual processing to proactive exception management. This analysis demonstrates that documentation automation in oncology is most effective when approached as an organizational transformation, supported by governance and change management, and underscores the central role informatics can play in enabling success.