# AI and Big Data in Healthcare: Towards a More Comprehensive Research Framework for Multimorbidity

## TL;DR

The paper proposes using AI and big data to better address the complex needs of patients with multiple chronic diseases.

## Contribution

The paper introduces an interactive research framework using AI and big data to improve care for patients with multimorbidity.

## Key findings

- Current healthcare systems are not well-suited for managing multiple chronic diseases in one patient.
- AI and big data analytics can provide an integrated platform for multimorbidity research tasks.
- Integration of electronic health data and AI into clinical workflows is essential for this new approach.

## Abstract

Multimorbidity refers to the coexistence of two or more chronic diseases in one person. Therefore, patients with multimorbidity have multiple and special care needs. However, in practice it is difficult to meet these needs because the organizational processes of current healthcare systems tend to be tailored to a single disease. To improve clinical decision making and patient care in multimorbidity, a radical change in the problem-solving approach to medical research and treatment is needed. In addition to the traditional reductionist approach, we propose interactive research supported by artificial intelligence (AI) and advanced big data analytics. Such research approach, when applied to data routinely collected in healthcare settings, provides an integrated platform for research tasks related to multimorbidity. This may include, for example, prediction, correlation, and classification problems based on multiple interaction factors. However, to realize the idea of this paradigm shift in multimorbidity research, the optimization, standardization, and most importantly, the integration of electronic health data into a common national and international research infrastructure is needed. Ultimately, there is a need for the integration and implementation of efficient AI approaches, particularly deep learning, into clinical routine directly within the workflows of the medical professionals.