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Creating value from data

using the example of a radiation clinic
HomeBlogCreating value from data – using the example of a radiation clinic
28.08.2023
Consulting, Digital transformation

Data in itself is worthless. Value is only created when decisions are made on the basis of the data - what does it cost and what is the benefit? In radiation clinics, with their high level of IT support, a lot of data can be accessed digitally. This facilitates fully automated quality assurance monitoring of clinical processes. In the event of unexpected deviations, suitable corrections can be initiated promptly, resources can be made available as required and processes can be optimized. The data always remains under the control of those responsible at the clinic. And fully automatic documentation is also created for verification purposes.

The illustration shows a typical course of radiotherapy treatment. Patients are first examined using computer tomography and other imaging techniques (magnetic resonance imaging, positron emission tomography). This is done in order to determine as precisely as possible the extent of the target volume - the tumor - and the surrounding risk structures - eyes, optic nerve, spinal cord. Based on this information, the parameters for the linear accelerator are optimized during radiation planning, including calculation of the expected dose distribution in the patient. The tumor should receive a high dose, while the surrounding tissue and, above all, risk structures should receive the lowest possible dose.

Procedure and exemplary presentation of examination data in the radiation clinic. University Hospital Erlangen

Every treatment plan must be verified. This is done using measuring phantoms or software that is independent of the radiation planning. For example, the radiotherapy sessions take place in 30 sessions spread over six weeks. Reproducible positioning of the patient must be ensured for each radiotherapy session. The positioning relative to the treatment beam is then adjusted using imaging on the accelerator. Only then is the irradiation carried out, which only takes a few minutes.

Heterogeneous medical device network

High quality requirements, cost pressure and clinical processes that extend across a large number of medical devices, especially large devices such as linear accelerators and tomographs, require efficient and smooth data exchange. The heterogeneity due to the different medical device manufacturers for diagnostic, planning and radiation systems is supplemented by the systems for quality control, data management and administration required in the process.

The advantage:
Due to the requirements, there is a high level of IT support and a huge amount of data is already available in digital form.

The disadvantage:
The integration of such a large number of uncoordinated systems presents a challenge with ever new surprises.

As part of the "DigiValMed - Development of a 'digital twin' in the hospital network context as an online validation laboratory for medical device networks" project funded by the Bavarian Ministry of Economic Affairs, sepp.med and its project partner, the radiation clinic at Erlangen University Hospital, were able to demonstrate the added value of fully automated quality assurance.

Particular attention was paid, among other things, to checking relevant correlations in clinical processes, as the following example shows: In an irradiation plan, risk structures must be segmented and labeled so that they are not exposed to any dose during irradiation if possible. These include the eyes in the head and the spinal cord in the chest area. As soon as a junior doctor has segmented the risk structures in the radiation plan, he or she sends the plan to a senior doctor for approval. Before the radiation treatment plan reaches the senior physician, a quality assurance server can automatically check this data for compliance with the currently stored guidelines. If an expected risk structure is missing, the processor is informed and can react. The added value arises from the fact that the senior physician saves time reviewing treatment plans with missing risk structures.

Other examples are

  • Scheduling:
    In certain cases, a magnetic resonance imaging (MRI) scan must be performed before the patient undergoes radiotherapy. Sometimes the appointment for this is postponed until after the radiotherapy appointment. If the MRI is not available, the radiotherapy must be postponed. For the patient, this can mean a loss of time and quality of life, and for the clinic it reduces the utilization of the radiation system.
  • Utilization:
    After a patient is admitted, a treatment plan is drawn up in which the form of treatment and the expected number of sessions are determined. Based on the current status of the therapy plans, a forecast can be made of possible overloads in individual departments with their medical equipment. This data can be used to plan ahead in terms of load distribution and investments.
  • Documentation:
    All relevant transitions in the clinical process, which are identified on the basis of data in the medical device network, can be saved fully automatically and retrieved as documentation. This reduces the workload of the entire staff. Proof can also be provided in a legally compliant manner.

Outlook

In order to gain added value from data, the following questions can generally be asked:

Where do I have pain?
Mostly it's about costs, time, skills and the associated quality.

What do I need to know in order to

  • be able to react promptly? This reduces costs and/or time.
  • avoid something? This saves money and/or time.
  • to improve something? This saves money and/or time and/or quality.

And if the necessary data is not yet available digitally, the familiar question arises: what does digitization cost and what are the benefits?

In the results presented here, I have omitted one essential aspect, the discussion of which goes beyond the scope of this article: data security and the protection of personal data, especially health data. Just this much: thanks to our many years of experience in the development and quality assurance of medical software and its approval, we were able to develop software as part of the DigiValMed funding project without having access to the data. In close coordination with the data protection officer, the data always remained under the complete control of the radiation clinic.