Artificial intelligence for care

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Nursing is involved in many digital processes – which makes it all the more important that it takes a serious look at how the digital transformation can serve nursing professionals so that it benefits boththem and their patients

The nursing profession is involved in many digital processes due to its central position in healthcare. It is time for nursing to take a serious look at how the digital transformation can and must serve the profession. It is crucial that digitalisation is designed in such a way that a clearly defined and perceptible benefit can be created in nursing care and support, both for nursing itself and for the people being cared for. Artificial intelligence – AI – is on everyone’s lips and it is therefore worth taking a closer look at this digital tool. What is often overlooked is that the development of AI began back in the 1950s. The seemingly “meteoric” rise of AI into everyone’s everyday lives is due to its improved performance. AI has been able to develop this because it uses access to large amounts of data, computing power has improved, statistical analysis methods have been optimised and high storage capacity can now be found

However, it must also be said that the ChatGPT application has certainly also contributed to AI applications becoming part of people’s everyday lives. It can be assumed that ChatGPT is another milestone in human-driven technological evolution. Just like the development of writing, the wheel, printing, electricity, radio, the telephone, the computer, the World Wide Web or the iPhone, which in turn is the ancestor of a plethora of smart wearables

What can AI really do?

To date, AI applications in nursing have been developed primarily for direct patient care, i.e. for intensive care units and intermediate care units, for wound care, for delirium or discharge management and for the areas of falls, health emergencies or infections, primarily in the care of older people. However, AI also already plays a role in the application areas of specialised care languages and documentation, management (personnel), education and administration (skills). Despite these relevant areas of application, the literature reveals two serious limitations that we will have to address in the coming months and years: Firstly, the nursing profession has so far hardly developed, tested and piloted any AI applications, well understood in the required interdisciplinary collaboration. Other disciplines are currently still in the lead. Secondly, there is a lack of studies that demonstrate the impact of AI applications in everyday clinical practice, such as improved patient outcomes or improved clinical decision-making. However, this can be explained by the fact that the focus to date has been on the data-based development and testing of AI applications, without sufficient implementation in daily clinical practice

Utilisation options to support practice

Werner Hackl, assistant professor at the Tyrolean private university Umit Tirol, discussed with ChatGPT the question of what practical uses AI applications have or can have in nursing

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AI applications are designed to support carers, providing them with additional information and insights that help and relieve their work at the bedside.

Here are some of their ideas

  1. Patient monitoring: AI applications can monitor vital signs in real time and alert carers when deviations occur. This can help patients receive help more quickly and avoid potential complications.
  2. Care planning and documentation: AI applications can support carers in creating personalised care plans and documenting care interventions, saving time and ensuring a more accurate and comprehensive record of care services.
  3. Patient education: AI applications can be used as an interactive tool to educate patients and their families about diseases, treatments and care practices. This can help patients better understand what is happening during their stay in the care facility and actively involve them in the care process
  4. Data collection and analysis: AI applications can automatically collect and analyse data to identify trends and patterns that help improve care practices and increase the quality of care services.

However, AI will never replace care. It will be a new tool that carers will use. And, of course, they will need the appropriate skills to do so. Two things are therefore very important: helping to shape the care provided by AI applications and scientifically supported introduction into care practice

  • The more care professionals engage with the topic, set requirements for AI applications and test, assess and improve AI applications or communicate clearly when AI applications remain unsuitable, the more care professionals can build up competences and skills through these measures. The introduction of AI into nursing practice must be done carefully and ethically, taking into account the concerns and perspectives of nurses and experts Training and education are crucial to ensure that nurses have the understanding and skills to effectively use and critically evaluate AI applications.

Reliability of AI applications

The reliability of AI applications depends on various factors, including the quality of the data used, the accuracy of the algorithms and the type of application. Experts are aware that AI systems are not error-free and that misinterpretations can occur. It is therefore important to consider AI applications as supporting tools that provide additional information and insights to care professionals, but not as the exclusive basis for medical and care decisions

Challenges of AI applications

The biggest challenges for AI in healthcare and nursing include data protection, transparency of decisions, ethical implications, integration into workflows, regulatory frameworks, patient acceptance and resource inequality. It is crucial to strengthen data protection measures, ensure transparent AI decisions, establish and implement ethical guidelines to complement, not replace, human care. Finally, access to AI applications should be guaranteed for all population groups

A robust data infrastructure is also particularly important. Existing health data must be stored in a structured and secure environment to enable effective use by AI applications. It is also essential to ensure the quality and integrity of this data, as it directly influences the performance of the AI. It is therefore important that the data is prepared accordingly in order to meet the requirements of the AI applications

Co-create to do a better job

It is clear: AI must serve the carer. AI provides a starting point or a specific snapshot, but the carer brings their specialist and contextual knowledge, patient preference, scientific evidence and available resources to the decision. AI can then support the carer in doing an even better job
The nursing profession must actively shape the present and future of digital transformation. This does not just require digital solutions such as AI applications, but rather a combination of a willingness to take risks and precise communication of requirements. It is therefore essential to test and thoroughly assess imperfect digital tools in daily use. This enables the formulation of precise requirements that must be met in order for both carers and patients to derive real benefit from the digital tools. A digital solution should not be legitimised without meeting these requirements

This article appeared on pages 12-14 of the January 2024 issue of the professional journal “Krankenpflege”. “Krankenpflege” is the official publication of the Swiss Professional Association of Nurses (SBK).

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AUTHOR: Friederike J. S. Thilo

Prof. Dr Friederike Thilo is Head of Innovation Field "Digital Health", aF&E Nursing, BFH Health. Her research focuses are: Design collaboration human and machine; technology acceptance; need-driven development, testing and evaluation technologies in the context of health/disease; data-based care (artificial intelligence).

AUTHOR: Renate Ranegger

Dr Renate Ranegger is a qualified nurse, member of the SBK eHealth and Care Commission and Head of Research and Development at LEP AG, St. Gallen.

AUTHOR: Werner Hackl

Werner Hackl is an assistant professor, medical IT specialist and expert in information processing in care at UMIT TIROL, Division for Digital Health & Telemedicine, Hall in Tirol.

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