In many radiation oncology departments today, the path from diagnosis to treatment feels more like an obstacle course than a care pathway. Patient registration begins with stacks of paperwork. CT simulations capture crucial tumor images, but transferring them into the treatment planning system can take up to 17 mouse clicks—a tedious, error-prone process that slows everything down.1 Clinicians then juggle multiple vendor-specific platforms—PACS, EMRs, TPS, QA systems—repeating data entry across each one just to keep the patient journey moving. According to a study published in the National Library of Medicine, the average time from patient intake to first dose delivery can take weeks—a long period of time where the cancer goes untreated.
Intelligent Radiation Therapy changes this. Built as a fully interoperable, open-architecture platform, iRT brings together every stakeholder—oncologists, radiologists, medical physicists, and dosimetrists—into a single, unified workflow. It integrates with all major systems—OIS, PACS, EMR, TPS, QA—allowing real-time data sharing without redundant clicks, repeated logins, or compatibility headaches.
The results are dramatic. Radiation oncologists rated the use of the iRT sim order form as 51% less time-consuming than their existing paper-based workflow for preparing simulation prescriptions. Radiation oncologists rated the possibility of making human errors in preparing treatment planning prescriptions 42% less likely with the iRT plan intent form compared to their existing paper-based workflow. Overall treatment initiation times have dropped from 30.3 days to just 8.7 days across all satellite sites.2
In this white paper, we take a deep dive on the 4 benefits iRT enables as a result of its open architecture.
- Based on measurements of individual radiation oncologists’ experiences at two medical centers in Europe and India after completion of radiation therapy workflow tasks in
a clinical setting. The study was facilitated by a third-party consulting agency and sponsored by GE HealthCare. These results are based on a small sample size and other user experiences may vary based on workflows and other factors. ↩︎ - These data are based on analysis of over 11,000 treatment plans at a large academic hospital, following the implementation of a workflow efficiency solution. iRT was developed using a solution from a large academic hospital as a foundation, with extended connectivity and interoperability capabilities. Any results achieved using iRT may vary based on differences in workflows, patient populations, or other factors. ↩︎
