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The COVID-19 pandemic has marked a shortage of nursing resources worldwide. They represent more than half of the world's health personnel and provide essential services in the health system. A report, prepared by the World Health Organization (WHO), reveals that in 2020 there was a world deficit of 5.9 million professionals(1). On the other hand, the aging of the world population is a phenomenon present in many countries of the European Union (EU) and will increase in the coming decades. According to data from Eurostat, in just over 20 years the percentage of the population over 65 in the EU will go from the current 18.9% to 27%2. Likewise, aging also threatens the nursing staff: it is expected that one in six nursing professionals will retire in the next 10 years1. So we will have even more retired people to care for and fewer nursing resources to assist them.
To address this current problem we must consider different types of resources that we have available, including technological ones, that allow us to assist patients, without the need to increase the number of nursing professionals. That is, optimizing staff resources and automating tasks through the use of technology. In this way we allocate human resources to tasks that are not simple and cannot be automated, we do it with the simple ones, and consequently, we reduce health costs, which have been increasing in recent years, presenting a great problem for the health system.
Within the technological resources, we must highlight artificial intelligence (AI). This has the potential to improve the quality of nursing care through greater productivity and efficiency in patient care at a lower cost(3). One of the ways in which it can collaborate is in the automation of simple tasks, for example in the follow-up of patients at home.
Patients at home follow-up through the use of the telephone has been used for patient education, symptom control, anticipation of complications, prevention of readmissions, and providing patient care. Home hospitalization units, like other cases, use human-based telephone monitoring as a follow-up tool. This generates work overload in the nursing team where only a small percentage of patients undergo interventions, leading one to think that these tasks could be performed automatically and only in that percentage where the patient required intervention from the health team, using health resources, optimizing them and reducing the professional's work overload.
Artificial intelligence has been defined as “an intelligent setup” that performs human-like tasks in a more efficient manner. These include investigating, consolidating, learning, forecasting, and decision-making. Over the last decade, artificial intelligence has made a major transformation in nursing care delivery and has been shown to facilitate clinical decision-making so that nurses can focus on developing a more seamless and individualized plan of care. AI has also been shown to assist in daily nursing care activities, such as monitoring patient vital signs, and to reduce the time required for documentation while increasing its accuracy and completeness. This gives them more time to engage in quality nurse-patient interaction to better understand their preferences and needs3. Therefore, the integration of artificial intelligence among professionals can improve healthcare processes while adhering to the fundamental values of nursing: providing emotional care and concern for the patient's needs3.
From Tucuvi, we propose the use of LOLA, the virtual medical assistant that employs artificial intelligence and natural language processing (NLP) to follow up and accompany patients at home through a phone call, without the need to use an app or computer. Engineered to be used by all age groups, LOLA reduces the technological gap, since only a telephone is needed. The health team can configure the questions and alerts that LOLA will ask. Likewise, when LOLA asks a question, and the patient responds with a warning parameter, the health team receives an alert, informing the professional that the patient needs to be contacted in the short term. After that call, the professional will decide what type of intervention is performed on the patient. In this way, follow-up calls are automated, and the health team only needs to intervene in a small percentage of patients, optimizing the professionals' working time.
In 2022, in one of the largest hospitals in Spain where LOLA is used for the follow-up of patients with chronic obstructive pulmonary disease (COPD), heart and/or respiratory failure, an observational study was carried out for 5 months, with the aim of evaluating the impact of the use of LOLA, both in patients and in health professionals. The results showed that only 7-10% of the patients required intervention from the health team. Regarding user satisfaction, the patients scored 4.31/5, this being a positive result. On the other hand, a third reported that LOLA facilitated their clinical follow-up and increased their empowerment over their pathology. They also rated the effort generated by the patient when talking to LOLA as “simple”. The feedback from the professional that was collected through the Technology Acceptance model (TAM) questionnaire was 4.5/5, a positive result. Ultimately, the users considered that the use of LOLA improved productivity, facilitated the prioritization of patients, and allowed them to have more information about the patient for decision-making. It was concluded that automated patient follow-up using LOLA had a great impact, allowing the team to prioritize care, increase their work capacity, and improve the continuity of patient care4.
Given the progressive aging of the population, where there will be fewer and fewer people in productive age, added to an increase in life expectancy and fewer nursing resources, the automation of simple patient care tasks offers great solutions. Among them, we can highlight the increase in the productivity of the health team and the prioritization of patients for medical care. I believe that the use of AI can offer great solutions to current and complex problems with which we nowadays live.
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