Hospitals around the world are facing increasing care shortages, with the World Health Organization estimated that the organization will reach 4.5 million by 20301if the current mode continues. The causes of nurse shortages are burnout, safety issues and poor salary.
Furthermore, frustration among nursing communities is increasing as more and more tasks prevent them from spending enough time in face-to-face patient care. A study found that nurses reported spending only 54%2 They have time on direct patient care and hope to spend more time on this.
In particular, administrative tasks account for a large portion of nurses’ time, but these tasks have the potential to be removed from the nurse’s burden by using AI-powered assistants. Incorporating technology into care can free up about 20% of nurses’ time, allowing them to spend more time on their patients.
7 Ways to Help Nurse With AI-powered Assistant
1. Enhance clinical decision-making
AI is increasingly used to help healthcare professionals make diagnosis. AI can combine data from different sources, including genetic and lifestyle data, to improve diagnostic accuracy. Therefore, AI can provide nurses with more insights and provide nursing advice to achieve a completely wise decision about patient care services. In this case, AI helps identify patterns that humans miss because they are not able to analyze large amounts of data and can help nurses avoid “information fatigue”3.
2. Predictive analysis
The use of AI in predictive analytics further helps nurses provide optimal patient care. AI can analyze large amounts of patient data and compare it with previous patients, allowing patterns to be identified and treated or cared for. AI algorithms can be used to analyze real-time, subtle changes in a patient’s condition, which may indicate worsening or adverse outcomes.
3. Simplify management tasks
Administrative tasks are a large part of the non-target work performed by nurses, thus reducing the time spent on patient care. One study found that only 21% of nurses spend on direct patient care4. Documentation can consume most of the nurse’s time, estimated to be up to 60%5 Shifts absorbed in patient care were recorded. Document automation and patient record updates can save a lot of time.
4. Simplify clinical documentation
Natural language processing can speed up nursing documents by converting voice or handwritten notes into electronic health records and assisting in writing nurse narratives.
5. Arrangement and staffing
AI algorithms can be used to optimize personnel adjustment plans and have the ability to produce and optimize schedules while taking into account constraints, workloads, and service needs.
6. Task priority
AI tools can be used to prioritize and assign tasks, calculate time sensitivity, workload, staffing level, patient complexity, and available resources.
7. Strengthen communication
Virtual healthcare assistants are increasingly used to reduce the burden on nurses and give them more time to direct patient care. These can be in the form of chatbots, using natural language processing to understand patients’ queries and come up with accurate answers.
Challenges and risks of AI implementation in nursing
Nurse adopts and trusts AI tools
One of the most important considerations for using AI tools is how to ensure nurses interact with tools. AI tools should be developed in collaboration with nurses, as nurses will be able to inform developers about what their needs are and whether the tool can incorporate them into their workflow. AI tools must be trained adequately. In a survey conducted by the Health Foundation, 54% of registered nurses said they “expected” to use AI at work6.
Technical Challenges
Effective integration of AI assistants into hospitals requires compatibility with pre-existing IT systems to ensure sufficient data access. Interoperability between different IT systems is a common problem, and 61% of clinicians in a survey believe this is a critical barrier to implementing digital tools, such as AI7.
Ethical and regulatory issues
To play a role in healthcare, AI requires access to a large amount of patient data. Therefore, data privacy and confidentiality regulations (such as HIPAA) must be incorporated into any AI implemented in the hospital. Other problems may arise because the risks of using AI will permanently exist in their systems.
AI Assistant Nursing Cases
The possibility of incorporating AI assistants into patient care has the potential to alleviate the global nursing crisis. One contributing factor to nurses leaving the job is limited job satisfaction, as other tasks lead to limited in-person patient exposure. By simplifying administrative tasks, assisting clinical decision-making, optimizing care through predictive analytics, and reducing cognitive burden, AI can provide nurses with more time to focus on direct patient care. To learn more about AI’s implementation in care, download IT Medical’s latest white paper, which discusses it in more detail.
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2. Solutions to address the nursing shortage gap | McKinsey. Visited on December 16, 2024.
3. Walsh University. Technology Impacts Nursing in 2022 | Walsh University Online. November 22, 2022. Visited on December 16, 2024.
4. Solve the shortage of technology care. Visited on December 16, 2024.
5.GESNER E, GAZAIRAR P, DYKES P. Recording the burden and burnout of patient care: a comprehensive literature review. Stud Health Technol Information. 2019; 264:1194-1198. doi: 10.3233/shti19041
6. Survey: Nurse is cautiously optimistic about AI | Nursing time. Visited on December 17, 2024.
7. Addressing the technology’s nursing shortage. Visited on December 16, 2024.
