World hospitals1If the current model continues. The reason for nurses’ shortages, among many things, is professional exhaustion, security problems and bad wages.
In addition, frustration among the nursing community increases on an increasing number of tasks preventing them from spending enough time for face -to -face patient care. A study revealed that nurses said they had spent only 54%2 of their time on the direct care of patients and wanted to spend more time on this.
Administrative tasks in particular take a significant proportion of nurses, however, these tasks have the potential to be removed from the charges of nurses thanks to the use of assistants supplied by AI. This incorporation of technology in nursing could release around 20% of nurses, allowing them to spend more time with patients.
7 ways how assistants fueled by AI can help nurses
1. Improve clinical decision -making
AI is used more and more to help healthcare professionals with diagnostics. AI can combine data from different sources, including genetic and lifestyle data, to improve diagnostic accuracy. The AI can therefore provide nurses increased information and provide care recommendations to allow fully informed decisions concerning patient care. In these circumstances, AI helps to identify the models that could be missed by humans because of not having the capacity to analyze large volumes of data, and can help nurses to avoid “information fatigue”3.
2. Predictive analytics
The use of AI in predictive analysis also helps nurses provide optimal care to patients. The AI can analyze large amounts of data on patients and compare it to previous patients, to identify models and treatments or care to be paid accordingly. AI algorithms can be used to analyze subtle changes in real time in the condition of a patient, which could be indicative of a deterioration or an unfavorable result.
3. Ration to rationalize administrative tasks
Administrative tasks represent a large part of the work not intended for patients carried out by nurses, which reduces the time available to devote to patient care. A study revealed that 21% of the time of nurses is spent on the direct care of patients4. Documentation can consume a large part of the time of nurses, with estimates of up to 60%5 of the offset absorbed by the documentation of care for patients. Automation of documentation and updating the patients’ files could allow nurses to have an important time.
4. Rationalization of clinical documentation
Natural language treatment can be used to speed up nursing documentation by converting discourse notes or handwritten into electronic health files and helping to write nursing stories.
5. Planning and endowment
AI algorithms can be used to optimize staff planning, with the possibility of producing and optimizing a calendar while taking into account the constraints, the workload and the demand for services.
6. Proritization of the task
AI tools can be used to prioritize and assign tasks, taking into account time sensitivity, workload, personnel levels, patients’ complexity and available resources.
7. Improve communication
Virtual health assistants are increasingly used to reduce the load placed on nurses and give them more time for direct care to patients. These can take the form of chatbots, using natural language treatment to understand patient queries and formulate specific responses.
Challenges and risks surrounding the implementation of AI in nursing care
Nurse adoption and confidence in AI tools
One of the most important considerations with the use of AI tools is how to ensure the commitment of nurses with the tool. AI tools should be developed in collaboration with nurses, because nurses will be able to inform developers what their needs are and if the tool could be integrated into their workflows. Nurses must receive sufficient training on AI tools. In a survey carried out by the Health Foundation, 54% of authorized nurses said that they “impatiently awaited” the use of AI in their work6.
Technological challenges
The effective integration of AI assistants into hospitals requires compatibility with pre -existing IT systems to ensure sufficient access to data. Interoperability between different computer systems is a common problem, with 61% of clinicians of a survey, citing this as a key obstacle to the implementation of digital tools, such as AI7.
Ethical and regulatory concerns
To carry out its roles in health care, AI requires access to large amounts of data on patients. Confidentiality and confidentiality regulations, such as HIPAA, must therefore be taken into account in any IA implemented in hospitals. Other concerns may arise regarding the use of AI due to the risk of perpetuating biases in its systems.
The case for AI assistants in nursing care
The integration of AI assistants into patient care has the potential to relieve the global nursing crisis. A factor contributing to nurses leaving their job is a satisfaction limited to work, for which contact limited in the face of patients due to other tasks is partially responsible. By rationalizing administrative tasks, helping clinical decision -making, optimizing care by predictive analysis and reducing cognitive load, AI can provide nurses for more time to focus on the direct care of patients. To find out more about the implementation of AI in nursing, download the latest white paper from IT Medical which discusses it in more detail.
1. Nurse and midwife. Accessed December 13, 2024. Https://www.who.int/news-room/fact-sheets/datail/nursing-and-midwifery
2. Solutions to fill the nursing shortage gap | MCKINSEY. Accessed December 16, 2024. Https://www.mckinsey.com/industries/healthcare/our-insights/reimagining-the-nursing-Workload-findting-time-To-Close–HeworkForce-gap
3. WALSH University. 7 ways whose technology has an impact on nursing care in 2022 | Online walsh university. November 22, 2022. Accessed December 16, 2024. https://online.walsh.edu/news/technology-in-nursing
4. To solve the nurses’ shortage with technology. Accessed December 16, 2024. Https://www.accentre.com/us-en/insights/health/solving-nursing-shortage
5.Sesges E, Gazarian P, Dykes P. burden and professional exhaustion in patient care documentation: a review of integrative literature. Stud Health Technol Inform. 2019; 264: 1194-1198. DOI: 10.3233 / SHTI19041
6. Investigation: Carefully optimistic nurses on AI | Nurse. Accessed December 17, 2024. Https://www.nursingtimes.net/digital-and-technology/survey-nurses-cautious-optimit-about-ai-01-08-2024/
7. To solve the nursing shortage with technology. Accessed December 16, 2024. Https://www.accentre.com/us-en/insights/health/solving-nursing-shortage
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