ERS, as the leading private teleradiology provider in Switzerland and Austria, is in a strong position to support other hospitals and institutes suffering from professional shortages.

ERS currently offers its service to nearly 20 hospitals in German-speaking countries. “We are set up to cope with high capacities. It is precisely because of this that we are able to offer our staff a high caseload – the be-all and end-all for producing consistent top quality. We remain wide awake and are always growing,” confirms Gerd Schueller, founder of ERS.

A corresponding campaign was launched in October 2017. ERS learns through a multitude of personal conversations with radiological and economic decision-makers what enormous difficulties have to be mastered in the respective health markets – and offers their cooperation. “As soon as our prospective customers realise how determined we are to offer our service and which radiological and technical solutions we can provide individually, the advantages of our service become immediately clear,” adds Michael Peck, responsible for all IT services at ERS.

Innovation and technology are among the markets of hope in the health economy, as a recent study underlines.

Under the aegis of the Weitmoser Circle, of which ERS is a member, the first results of a study conducted by Deloitte among medical executives show that telemedicine is considered to be of particularly high importance in future cost optimisation and benefit enhancement in medical organisations. The first study results were presented on 17 November 2017 during the annual meeting of the Weitmoser Circle. The research was conducted to identify processes and levers for increasing efficiency in health economics among medical managers of hospitals.

The study also shows that the user-friendliness of IT applications is the lever with the greatest estimated effectiveness for increasing efficiency in the hospital sector.

For us at ERS, the study results mean,

1) we are on the right track to sustainably improve the medical landscape with our services
2) that our IT solutions are already very user-friendly. Our independently developed IT tool XTIS enables us to transfer our findings fully EDPG/eGA/ELGA-compliant into the RIS/KIS systems of our customers.

Further links:

http://www.weitmoser-kreis.at/

What if you could improve the diagnostic quality and utilization of your existing CT scanners without incurring the high cost associated with replacing them and refurbishing the CT suite? Using Deep Learning technology PixelShine can automatically enhance and harmonize the image quality of studies acquired by any CT scanner at the lowest possible dose – extending the life of older scanners and deferring costly and disruptive replacement projects. You find this exceptional opportunity on our AI platform Radailogy. It has a substantial impact on the traditional revenue stream of hospitals and imaging providers.

New deep learning CT scan processing software is now available through Radailogy that can help everyone overcome the limitations of Iterative Reconstruction. PixelShine from AlgoMedica automatically improves the quality of any CT scan by reducing image noise without reducing the conspicuity of fine details. It improves the image quality of CT studies acquired at any dose level, to make lower dose scanning possible for all CT studies. In addition, PixelShine is vendor neutral; so it works with all CT scanners, regardless of the vendor, including older and refurbished systems.

The cumulative effect of the exposure to CT imaging compounds the need to achieve the lowest per-scan patient dose possible. While low-dose CT imaging techniques exist, there is often a compromise that must be made in both image quality and cost. Lower-dose studies have higher image noise, which results in lower quality images, which are more difficult to analyze. Iterative Reconstruction (IR) is still the most used technique for improving the quality of lower-dose imaging studies. However, IR can take substantially longer to process images and is prone to producing images with a waxy or blurry appearance if applied too strongly on low-dose studies. Deep Learning CT Processing (DLCP) is the next generation in CT image noise reduction techniques. DLCP not only improves CT images acquired during typically low-dose procedures like lung screening and pediatric exams, but it also presents the ability to significantly reduce radiation exposure for other higher-risk categories such as oncology and obese patients. In addition, it can improve the image quality of ultra-low-dose abdominal, cardiac, and brain scans. Radailogy presents PixelShine by AlgoMedica in order to assist to the reduction of CT radiation dose and from now on to substantially improve image quality in low dose CT studies.

Not only trauma centres and radiology institutes, but every doctor has to deal with the diagnosis of fractures. X-rays are still the first line modality, especially for peripheral skeletal trauma. Radailogy offers you a new CE approved app from the French company AZmed: Rayvolve. Either let Rayvolve process your X-ray images always in the background, or send us selected images with a specific question. Rayvolve has been trained on data sets of one million trauma images. AZmed gives Rayvolve a sensitivity of 96% and a specificity of 86%. In our own test series, Rayvolve performed as follows: Sensitivity 93%, Specificity 86%, PPW 92%, NPW 89%, Accuracy 91%. In a multicentre study, Rayvolve provided a time saving of 36% and an increase in specificity of 8%.
Rayvolve is proving to be a valuable aid for doctors in daily practice: whether the app is used occasionally, for example in doctors’ surgeries, or whether it is used to optimise the workflow in medical centres.
The best way to request Rayvolve is with our Radailogy services Defained or Pure AI. Register, upload and get started!
Info at www.radailogy.com

Not only trauma centers and radiological institutes, but every doctor has to do with diagnosing fractures. X-rays are still the first line modality, especially in the case of trauma to the peripheral skeleton. Radailogy offers you a new, CE-approved app from AZmed in France: Rayvolve. Either let Rayvolve always process your X-ray images in the background, or you can send us selected images with a specific question. Rayvolve was trained on records from a million trauma images. AZmed shows Rayvolve a sensitivity of 96% and a specificity of 86%. In our own test series Rayvolve performed as follows: Sensitivity 93%, Specificity 86%, PPW 92%, NPW 89%, Accuracy 91%. In a multicenter study, Rayvolve achieved a time saving of 36% and an increase in specificity of 8%.

Rayvolve proves to be a valuable help for doctors in daily practice: be it that the app is used occasionally, for example in doctor’s offices, or that it is used to optimize the workflow in medical centers.

Rayvolve is best to request using our Radailogy services Defained or Pure AI. Register, upload and let’s go!