Zhecheng Zhu1, Bee Hoon Heng2, Kiok Liang Teow2. 1. Health Services & Outcomes Research, National Healthcare Group, Singapore. Electronic address: zhecheng_zhu@nhg.com.sg. 2. Health Services & Outcomes Research, National Healthcare Group, Singapore.
Abstract
INTRODUCTION: Comorbidity is common in elderly patients and it imposes heavy burden on both individual and the whole healthcare system. This study aims to gain insights of comorbidity development by simulating the lifetime trajectory of disease progression from single chronic disease to comorbidity. METHODS: Eight health states spanning from no chronic condition to comorbidity are considered in this study. Disease progression network is constructed based on the seven-year retrospective data of around 700,000 residents living in Singapore central region. Microsimulation is applied to simulate the process of aging and disease progression of a synthetic new-born cohort for the entire lifetime. RESULTS: Among the 40 unique trajectories observed from the simulation, the top 10 trajectories covers 60% of the cohort. Timespan of most trajectories from birth to death is 80 years. Most people progress to at risk at late 30 s, develop the first chronic condition at 50 s or 60 s, and then progress to complications at 70 s. It is also observed that the earlier one person develops chronic conditions, the more life-year-lost is incurred. DISCUSSION: The lifetime disease progression trajectory constructed for each person in the cohort describes how a person starts healthy, becomes at risk, then progresses to one or more chronic conditions, and finally deteriorates to various complications over the years. This study may help us have a better understanding of chronic disease progression and comorbidity development, hence add values to chronic disease prevention and management.
INTRODUCTION: Comorbidity is common in elderly patients and it imposes heavy burden on both individual and the whole healthcare system. This study aims to gain insights of comorbidity development by simulating the lifetime trajectory of disease progression from single chronic disease to comorbidity. METHODS: Eight health states spanning from no chronic condition to comorbidity are considered in this study. Disease progression network is constructed based on the seven-year retrospective data of around 700,000 residents living in Singapore central region. Microsimulation is applied to simulate the process of aging and disease progression of a synthetic new-born cohort for the entire lifetime. RESULTS: Among the 40 unique trajectories observed from the simulation, the top 10 trajectories covers 60% of the cohort. Timespan of most trajectories from birth to death is 80 years. Most people progress to at risk at late 30 s, develop the first chronic condition at 50 s or 60 s, and then progress to complications at 70 s. It is also observed that the earlier one person develops chronic conditions, the more life-year-lost is incurred. DISCUSSION: The lifetime disease progression trajectory constructed for each person in the cohort describes how a person starts healthy, becomes at risk, then progresses to one or more chronic conditions, and finally deteriorates to various complications over the years. This study may help us have a better understanding of chronic disease progression and comorbidity development, hence add values to chronic disease prevention and management.