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

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.

Clusters of Physical Frailty and Cognitive Impairment and Their Associated Comorbidities in Older Primary Care Patients

“…An assessment of the possible at-risk individuals in the clusters were described by many sociodemographic and health-related characteristics. As there is no adequate research framework for investigating multimorbidity, this method can be applied to manage older patients with multimorbidity in a more integral manner than is currently possible when chronic diseases are considered as independent entities [ 38 , 39 ].…”

A Case Study of Using Telehealth in a Rural Healthcare Facility to Expand Services and Protect the Health and Safety of Patients and Staff

“…Usage of telemedicine and advanced technologies including information processing, sensing, and artificial intelligence can help in providing support to individuals in their homes [6]. Additionally, timely access to information needed to make medical decisions, evidence based medicine and use of digital technologies and big data analytics can be help in managing health conditions of patients who suffer from two or more diseases and chronic health conditions [7].…”

A Perspective: Use of Machine Learning Models to Predict the Risk of Multimorbidity

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