Learning prevalent patterns of co-morbidities in multichronic patients using population-based healthcare data.

ABSTRACT: The prevalence of longstanding chronic diseases has increased worldwide, along with the average age of the population. As a result, an increasing number of people is affected by two or more chronic conditions simultaneously, and healthcare systems are facing the challenge of treating multimorbid patients effectively. Current therapeutic strategies are suited to manage each chronic condition separately, without considering the whole clinical condition of the patient. This approach may lead to suboptimal clinical outcomes and system inefficiencies (e.g. redundant diagnostic tests and inadequate drug prescriptions). We develop a novel methodology based on the joint implementation of data reduction and clustering algorithms to identify patterns of chronic diseases that are likely to co-occur i

SUBMITTER: Seghieri C 

PROVIDER: S-EPMC10810806 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature