Mining Major Transitions of Chronic Conditions in Patients with Multiple Chronic Conditions.

ABSTRACT:

Objectives

Evolution of multiple chronic conditions (MCC) follows a complex stochastic process, influenced by several factors including the inter-relationship of existing conditions, and patient-level risk factors. Nearly 20% of citizens aged 18 years and older are burdened with two or more (multiple) chronic conditions (MCC). Treatment for people living with MCC currently accounts for an estimated 66% of the Nation's healthcare costs. However, it is still not known precisely how MCC emerge and accumulate among individuals or in the general population. This study investigates major patterns of MCC transitions in a diverse population of patients and identifies the risk factors affecting the transition process.

Methods

A Latent regression Markov clustering (LRMCL) algorithm is

SUBMITTER: Alaeddini A 

PROVIDER: S-EPMC5875179 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature