Informatics in Radiation Oncology

Radiation oncology (RO) is one of the most technologically advanced and data-intensive disciplines within modern medicine. Radiation therapy relies heavily on a complex ecosystem of hardware and software to deliver ionising radiation safely. Clinical workflows have evolved from manual, paper-based processes to sophisticated digital treatment procedures that require automated exchange of data that drives the many different system components (e.g., the current use of online adaptive radiotherapy).

At the centre of this technological paradigm sits RO informatics. Broadly defined, medical informatics combines theoretical and practical methods to process, store, manage, and communicate healthcare data, transforming it into actionable clinical knowledge. In the context of RO, informatics encompasses the perspectives, data streams, and workflows of every clinical and technical discipline involved in patient care for RO treatments. This extends from data administration and clinical decision-making to dosimetric analysis and clinical tracking.

During the course of a patient’s radiotherapy treatment, a vast amount of information and data are continuously generated. This data collection begins with the initial diagnosis and tumour staging, continues with multidisciplinary tumour-board assessments, the determination of the treatment regimen and prescriptions, and extends through the planning CT scans and organ contouring to complex, multidimensional dose calculations in treatment planning systems (TPS). It culminates in daily fractionated radiotherapy sessions, which are monitored by record and verify (R&V) systems at the linear accelerators (Linacs), followed by long-term follow-up assessments. In parallel, administrative and organisational data are collected, such as those for initial admissions, patient appointments, billing and clinical-discharge reports.

Management of this dense, heterogeneous data, which comes in various forms including imaging and dose datasets, standardised or free-form questionnaires, and proprietary digital-file formats, requires highly focused informatics expertise.

The Traditional Clinical Workforce vs. The Digital Reality

The rapid pace of digitalisation has structurally shifted the baseline operations of traditional radiotherapy teams. Historically, the core operational framework was built around well-defined clinical tracks such as management of clinical assessments, treatment prescriptions and target-volume delineation (performed by radiation oncologists), overseeing technical quality assurance, equipment commissioning, and precise dose measurements and calculations (done by medical physicists and dosimetrists), and the execution of treatment simulations, patient positioning, and daily therapy delivery (executed by radiation therapists).

Many informatics tasks that are required with this emerging digitalisation have long been addressed by clinical teams on an ad-hoc basis (most frequently by medical physicists). However, the velocity of modern IT development has vastly outpaced this informal model. Today's clinical environment demands deep, foundational expertise in IT security, network topologies, relational databases, artificial intelligence (AI), and cross-system scripting.

Consequently, the specialist knowledge that clinicians in traditional roles have developed in this area is often no longer sufficient to manage the complexity of modern digital infrastructures and their demands.

Furthermore, general hospital-wide IT departments are poorly equipped to bridge this gap. They routinely lack a nuanced understanding of radiation-therapy-specific workflows and technical concepts. When critical software or machine connections fail mid-treatment, immediate and on-site domain expertise is paramount to maintaining patient safety and operational continuity.

To manage this digital ecosystem systematically, the responsibilities required of modern departments can be divided into six core areas.

1. System Administration and Technical Management are required to manage the foundational infrastructure and to monitor the daily operation of highly specialised software networks, including TPSs, R&V and patient management systems.
2. Interoperability Management harmonises documentation interfaces and ensures seamless cross-platform data exchange. This is critical, since clinical environments are highly fragmented as they rely on proprietary, isolated vendor solutions and localised databases.
3. Workflow Optimisation and Process Automation identify operational bottlenecks and deploy script-based automation routines. Eliminating repetitive, manual data entry directly minimises the risk of human error during clinical transcription.
4. Data Protection, Governance, and Security safeguard the structural integrity and strict confidentiality of clinical datasets while maintaining regulatory compliance. This includes deploying proactive defence measures against external cyberattacks and establishing precise protocols for crisis management.
5. Evaluation and Deployment of New Technologies involves critical assessment and integration of complex (AI-supported) data analysis tools. This area acts as a technical gatekeeper of clinical software deployment, performing data validation, running technical benchmarks, and continuously monitoring software performance and model outputs.
6. Data Science and Analysis mines data, programs and model databases to extract meaningful clinical insights from real-world data collected locally or through multi-centre networks. To support this foundation, data standards must be continuously developed, introduced, and strictly implemented.

The Critical Importance of Dedicated Informatics Personnel

Meeting the expansive challenges of digital advancement requires structural evolution. Existing clinical staff need comprehensive continuing education, refined task definitions, and updated training curricula in regard to data management and informatics, while new roles must be integrated to work alongside them.

As set out in the consensus paper by the International Society for Radiation Oncology Informatics and formally endorsed by professional associations including the German societies for medical physics (DGMP) and for RO (DEGRO), the Austrian societies for RO (ÖGRO) and for medical physics (ÖGMP), the Scientific Association of Swiss RO (SASRO) and the Society of Swiss Radiation Oncologists (SRO), modern RO clinics require embedded data scientists, computer scientists, or dedicated medical informatics specialists.

Delineating exactly what these new roles entail, and establishing who bears responsibility for specific tasks within a fully digital department, is a vital priority for healthcare managers and the entire radiotherapy community. Clear setting of boundaries prevents internal operational friction, optimises workflow handoffs and paves the way for future developments. As radiotherapy processes undergo a fundamental digital transformation, having specialized and technical experts on-site is no longer an optional luxury; it is indispensable to the modern, interdisciplinary clinical team.

Samuel Peters
HOCH Health Ostschweiz
Department of Radiation Oncology, Kantonsspital St.Gallen
St. Gallen, Switzerland