The nursing shortage in Germany is acute. Nursing staff struggle daily with overwork and staff shortages, while demand for services is constantly increasing. In this tense situation, artificial intelligence (AI) could offer the decisive solution. Find out in this article how AI could revolutionize some areas of nursing and thus mitigate the effects of the staff shortage.
5 examples of how AI in nursing is counteracting staff shortages
Whether nurses or nursing staff in old people's homes and care facilities: they are all desperately needed. High levels of workload and stress, staff shortages and little appreciation due to low salaries are some of the reasons why more and more employees are leaving the industry and the emergency is worsening.
Good remuneration, measures to encourage employee retention and the creation of a pleasant working environment would be the first steps to counteract this. However, the conditions for this are becoming increasingly difficult, as can be seen, for example, in the ongoing privatization of the health care system, which is increasingly putting profit first.
Nevertheless, there is hope for improvement: the establishment of artificial intelligence could also have a positive impact on the care sector. Here are 5 examples:
1) Predictive analytics for demand planning
Through predictive analytics, AI can help to accurately predict care needs. Based on extensive data analysis of health data and historical care histories, care facilities can better plan how many nurses they need, where and at what time. This enables more efficient resource allocation and helps to avoid bottlenecks.
2) AI takes over repetitive care tasks
AI-powered systems can take over repetitive tasks in nursing, such as monitoring vital signs, administering medications on a schedule, or monitoring patient data. This relieves nurses of routine tasks and gives them more time to focus on direct patient care.
3) AI-supported robots for assistive tasks
Robots equipped with artificial intelligence can be used in care facilities to perform supportive tasks. For example, they can help with mobility assistance for patients, transport objects or even carry out simple rehabilitation exercises under the guidance of a care expert. Such AI robots have already been successfully tested in some nursing homes in Germany, the best known model is “Peppers”.
4) Care planning and decision support
Artificial intelligence can support nurses in making complex decisions by providing evidence-based information and suggestions for best care practices. By analyzing large amounts of data, AI can support diagnoses, optimize therapies, and create individualized care plans tailored to the specific needs of each patient. Artificial intelligence can also be used to create shift schedules that take into account the needs of both nurses and patients.
5) Recruiting with AI tools
Artificial intelligence is also increasingly being used in recruiting staff in the nursing sector. Our recruiting tool flynne, for example, is based on AI to identify candidates who are suitable for nursing staff. We also deliberately include target groups that are difficult or impossible to reach using traditional recruiting methods. For example, career changers or people who are not actively looking for a job but would be interested in working in this field.
Can ChatGPT help combat the nursing shortage?
The most well-known AI tool in the world is undoubtedly ChatGPT. Can the chatbot also be helpful in addressing the shortage of staff in Healthcare industry to counteract?
It would be conceivable that it could assist nursing staff with everyday tasks. ChatGPT could, for example, create nutrition and action plans, explain why and how a medication should be taken, or structure patient records in a clear manner. Of course, information that directly affects those in need of care must always be checked with a critical eye by nursing staff.
If ChatGPT is not only used as a pure chatbot, but is integrated into an external system designed specifically for care facilities, much more is conceivable. ChatGPT could, for example, take over this automatically and thus relieve the burden on nursing staff:
- Making appointments with patients
- Communication with patients
- Automatic sending of appointment reminders
- Waiting list management
- Documentation and management of patient data
- Support with medication management
- Emotional support (e.g. communication with relatives of patients)
However, since integrating ChatGPT into existing systems is comparatively laborious and requires corresponding technical know-how, the chatbot is currently only suitable for assisting with smaller tasks in the care sector.
If you want AI to automate larger processes, you have to use other tools. For example, flynne can completely take over the recruitment process for nursing staff, from sourcing to the pre-selection of suitable talent. Those responsible in nursing facilities are presented with candidates who match their requirements "ready-made" and can send their invitations to interviews directly - also via flynne.
Risks of using artificial intelligence in care
Despite the promising potential and advantages, the use of artificial intelligence in the care sector also entails risks – concerns are raised, especially from an ethical point of view.
A key issue is the risk of dehumanization. While AI can take over repetitive tasks, it is not able to replace the human interaction and empathy that are so crucial to the quality of care. Overuse of technology could lead to the neglect of personal contact between caregivers and patients, which in turn could affect the well-being of those in need of care.
Another risk is the privacy and security of sensitive health data, as already mentioned in the section above. AI-powered systems need access to extensive data to perform their analyses. It is crucial that this is stored securely and protected from unauthorized access to avoid data breaches and maintain patient trust.
The handling of data is also a sensitive issue when it comes to AI recruiting in the care sector. HR managers should therefore only work with tools such as flynne that comply with data protection regulations in Germany. Here, candidates retain control over their data and information is processed and protected securely.
In addition, the dependence on technology presents a challenge. If AI systems make mistakes or make incorrect predictions, this can have serious consequences for patient safety.
It is therefore important that nurses always maintain control over decision-making processes and see AI as a supporting tool, not as a replacement for human expertise and experience.
