Real-time analysis and display of quantitative measures to track and improve clinical workflow

Purpose: Radiotherapy treatment planning is a complex process with multiple, dependent steps involving an interdisciplinary patient care team. Effective communication and real-time tracking of resources and care path activities are key for clinical efficiency and patient safety. Materials and Methods: We designed and implemented a secure, interactive web-based dashboard for patient care path, clinical workflow, and resource utilization management. The dashboard enables visualization of resource utilization and tracks progress in a patient's care path from the time of acquisition of the planning CT to the time of treatment in real-time. It integrates with the departmental electronic medical records (EMR) system without the creation and maintenance of a separate database or duplication of work by clinical staff. Performance measures of workflow were calculated. Results: The dashboard implements a standardized clinical workflow and dynamically consolidates real-time information queried from multiple tables in the EMR database over the following views: (1) CT Sims summarizes patient appointment information on the CT simulator and patient load; (2) Linac Sims summarizes patient appointment times, setup history, and notes, and patient load; (3) Task Status lists the clinical tasks associated with a treatment plan, their due date, status and ownership, and patient appointment details; (4) Documents provides the status of all documents in the patients' charts; and (5) Diagnoses and Interventions summarizes prescription information, imaging instructions and whether the plan was approved for treatment. Real-time assessment and quantification of progress and delays in a patient's treatment start were achieved. Conclusions: This study indicates it is feasible to develop and implement a dashboard, tailored to the needs of an interdisciplinary team, which derives and integrates information from the EMR database for real-time analysis and display of resource utilization and clinical workflow in radiation oncology. The framework developed facilitates informed, data-driven decisions on clinical workflow management as we seek to optimize clinical efficiency and patient safety.