“We don’t have enough equipment capacity in Austria,” explained radiologist Franz Frühwald in the APA interview. The number of cash register devices is limited by the large device plan. The examination time has been shortened with new tomographs, but these are needed for more and more diagnoses.
Problems have recently been reported in media reports, particularly with magnetic resonance imaging (MR/MRI) in Vienna. Those affected have to wait up to around 60 days for an MRI examination in diagnostic centers in the federal capital, according to the social security online waiting time survey. The portal also shows similar periods for institutes in Vorarlberg, for example.
Rendi-Wagner measures from 2017
In 2017, the then Health Minister Pamela Rendi-Wagner (SPÖ) initiated measures to ensure computer tomography (CT) examinations within a maximum of ten working days and MRI examinations within a maximum of 20 working days, or faster in urgent cases. The situation for the patients then improved. The situation was different back then, reported Frühwald. All institutes had capped contracts and were no longer paid following reaching the previous year’s sales, which meant that the technically possible capacities were not exhausted.
“Now we have the situation where all the devices that are available outside of the hospitals are working at 100 percent capacity,” said the head of a diagnostic institute in St. Pölten. In more and more medical treatment guidelines, an MRI is required if certain illnesses or injuries are suspected because, for example, only one of ten possible diagnoses can be recognized on an X-ray, Frühwald explained regarding the increased need for such examinations. In addition, there is a lack of staff, “which is currently making the situation difficult and leading to further waiting times”.
“We won’t be able to fix the waiting time”
“We will not be able to solve the waiting time problem by speeding up the devices,” the university lecturer continued. In the early days of MR technology, there were “time slots” of 90 minutes per patient, but we have now reduced them to ten to 15 minutes, said Joachim Bogner, managing director of the medical device manufacturer Siemens Healthineers Austria, in an interview with the APA. Thanks to innovations and, among other things, the use of artificial intelligence, the duration of the examination might be shortened without reducing the quality of the cross-sectional images. This helps to examine more patients per device, but “of course the technology is not the sole panacea,” said Bogner.
“The major equipment plan is to blame,” said Frühwald. Here it is decided between social security and the state government “where something goes,” the doctor said, making politicians responsible. The decision criteria are “very difficult to understand”. The result is that outside of hospitals there is a “dramatic” lack of equipment “that would be needed, especially in the MRI crisis, to deal with this situation,” said Frühwald.
Not regulated in the major equipment plan
Private MRI and CT machines are not covered by the large-scale equipment plan, but the examination costs for these are not covered by social insurance either. “The goal is by no means to ensure that patients have to pay something extra or even cover the costs,” emphasized Frühwald. However, it can be observed that the offer is increasingly private and those affected pay for the MRI themselves if they are seriously ill, said the specialist.
The innovations in medical technology primarily concern speed, explained Bogner from Siemens Healthineers. Existing devices can sometimes also be upgraded with updates. For example, AI helps to minimize “noise” during recording and thus improve image quality. Bogner reported that more research and development is still needed in the area of artificial intelligence as a “support technology” in making diagnoses. “The number of radiologists is increasing for whom AI technologies are playing an increasingly important role in their everyday work,” he observes.
“You have to see through it, almost like a film”
When examining the chest, for example, image series are created from 3,000 to 4,000 individual images, explained Frühwald. “You have to see through it, almost like a film.” It is difficult to capture everything. Algorithms can help “at least rule out big things”. For example, in AI-supported mammography for early breast cancer detection, there are systems with a high false positive rate. The diagnosing doctor is still ultimately responsible, emphasized the radiologist.
The radiation exposure from CT machines has also been reduced over the years, as has all other X-ray machines. That’s why the professional association for radiology technology in Austria recently launched a campaign to inform people that the classic lead apron for protection once morest radiation has largely become obsolete. Except for X-rays at dentists, this is largely avoided in radiological examinations. People have been used to lead aprons for 50 years, now it’s regarding making it clear to them that this is no longer necessary, said Frühwald.
Today’s reduced radiation exposure from new devices, for example through the use of special tin filters, might also enable further examinations for the early detection of diseases, such as with mammography. Lung cancer screenings using CT are particularly being discussed or demanded by specialist societies, which would allow such carcinomas to be detected in earlier stages and treated better. However, it is difficult for the general public and many doctors to understand why screening for a type of cancer that is 99 percent caused by smoking should be financed, explained Frühwald. According to Bogner, from a technical perspective, full-body screenings, for example, are also conceivable in the more distant future.
