The German healthcare system has not only been a critical focus since the corona pandemic. The aging population requires more and more health care, which, however, has to be managed by fewer and fewer staff.
Digitization and automation are two approaches to reduce the workload in nursing. Less administration, more care – this is the motto for the use of automation technologies in hospitals. AmdoSoft is at the forefront and will continue to expand our efforts to make the healthcare system work more efficiently in the future.
The basic problem: Overburdened hospitals
The high workload in hospitals results not only from the time-consuming patient care or the sheer number of patients, but also from the many administrative tasks for doctors and nurses. Various studies have shown that the burden of automation, especially in the back office and document management, as well as the processing of billing and benefit claims, can be significantly reduced. Although this does not necessarily solve the structural problems in the health system, it does noticeably reduce the acute burden.
RPA enables efficient processes
As already known and explained several times, RPA software robots like AmdoSoft’s b4 Virtual Client can imitate the actions of humans on the computer and thus carry out rule-based and repetitive tasks flawlessly and without a break. Thanks to the latest improvements in data entry and symbol recognition, many more documents can now be read and edited than just a few years ago. Robotic Process Automation (RPA) in the hospital can therefore take over many repetitive processes in the back office and thus free up capacities for patient care. This also saves a lot of costs. According to a McKinsey study, automatic processes, paperless data and the possibility of online interaction with citizens can save more than 34 billion euros per year in Germany.
Connection problem: overloaded network operators
The internal network of a hospital is already highly complex even without RPA optimization and is therefore naturally error-prone. However, network errors can have extremely serious consequences, especially in a hospital environment. The larger and more extensive the network becomes, the heavier the workload of the often small network teams that work either in-house or externally. As a result, the automation solution also brings new problems with it. The small teams can simply no longer guarantee that the network works without errors – or errors cannot be found or not found quickly enough, because any manual intervention is always associated with a great deal of time and work.
RPA enables real-time, end-to-end monitoring
If RPA technologies are bloating networks, then it’s only logical that RPA also provides the solution. RPA bots are able to maintain constant monitoring of the individual processes in real time and thus pinpoint errors. Network automation is therefore not just an optimization step in itself, but also the prerequisite for RPA to be able to intervene in the hospital system across the board. Advanced software systems can not only recognize and localize errors, but often also fix them automatically. This also relieves the small network teams.
In association with providers of RPA software, hospitals can set up their networks in such a way that they come as close as possible to the great efficiency role models such as Amazon, Google or Microsoft. These hyperscalers process huge amounts of data and still eliminate errors in the shortest possible time because they use a homogeneous network structure and a few, universal automation tools that harmonize perfectly. RPA tools can help design networks from the start to harmonize with perfectly matched solutions.
Other advantages of RPA solutions
From the user side, it is important that RPA software works and is easy to understand and use. Simple functions operated via a neat graphical interface are key to the acceptance of RPA bots in the hospital work environment. If necessary, these functions should be scalable at any time. Last but not least, modern RPA solutions also manage to meet the high compliance requirements that are required when dealing with sensitive patient data.