Predicting Care Needs of Older Adults in the Healthcare System through AI-enabled Analysis of Patient-Monitoring Data

As more people are living longer, we need more healthcare services, especially for urgent health problems. This puts a lot of pressure on our healthcare system, which includes care at home, nursing homes, local clinics, and hospitals. To make sure we can take care of everyone in the future, we need to find ways to help older people stay healthy and avoid needing a lot of care. The PAI project is working on this problem. The project uses artificial intelligence (AI) to predict what kind of care older people might need by looking at health data. By spotting health problems early, we can take steps to prevent them from getting worse. This could mean preventing falls in nursing homes or changing a person’s medication at their local clinic. This helps to avoid hospital stays, which can be expensive and stressful. However, predicting healthcare needs is tricky because the data we have can vary a lot. It can be different depending on where the person lives and what kind of health problems they have. To tackle this, the PAI project is working with people who receive care and healthcare workers to develop AI tools. These tools are tested in real-life situations in Spain, Sweden, and Norway. The project uses a mix of methods to collect and analyze data. This includes both numbers (quantitative data) and people’s experiences and opinions (qualitative data). The goal is to help older people by giving them the right care at the right time, preventing injuries and illnesses from getting worse. It also helps healthcare workers by making sure resources are used effectively and creating a good working environment. The solutions they find can be used in many different places.

As the population ages, the demand for healthcare services increases, including acute care. This puts a strain on healthcare resources, making efficient care management crucial at all levels - home, nursing homes, primary care, and hospitals. The PAI project aims to address this challenge by using artificial intelligence (AI) to predict the care needs of older individuals. By analyzing patient monitoring data, the project can detect early signs of health or functional decline. This allows for preventive measures to be taken, reducing the need for costly acute care and aftercare. For example, hospitalizations can be prevented by avoiding falls in nursing homes or adjusting medication in primary care. However, predicting the care needs of older patients is not straightforward. It involves dealing with varying data availability, quality, and potential interventions across different care levels and diagnoses. To tackle this, the PAI project uses a design science approach and a multiple case study design. It develops analytics in collaboration with care recipients and healthcare practitioners and implements them in real-life settings in Spain, Sweden, and Norway. The project uses a mixed-methods strategy for data collection and analysis, combining quantitative and qualitative elements. This includes the thematic interpretative analysis of meeting notes, interviews, and observations, as well as the statistical longitudinal trend analysis of Key Performance Indicators in the respective healthcare systems. The benefits of the PAI project are twofold. Older individuals receive adequate early care, preventing injuries and the worsening of diseases. Healthcare staff can use their resources more effectively, creating a sustainable and satisfying work environment. The outcomes of the project are scalable and can be applied in various contexts, making it a valuable contribution to the future of European healthcare.