Abstract
A key prerequisite for precision medicine is the estimation of disease progression from the current patient state. Disease correlations and temporal disease progression (trajectories) have mainly been analysed with focus on a small number of diseases or using large-scale approaches without time consideration, exceeding a few years. So far, no large-scale studies have focused on defining a comprehensive set of disease trajectories. Here we present a discovery-driven analysis of temporal disease progression patterns using data from an electronic health registry covering the whole population of Denmark. We use the entire spectrum of diseases and convert 14.9 years of registry data on 6.2 million patients into 1,171 significant trajectories. We group these into patterns centred on a small number of key diagnoses such as chronic obstructive pulmonary disease (COPD) and gout, which are central to disease progression and hence important to diagnose early to mitigate the risk of adverse outcomes. We suggest such trajectory analyses may be useful for predicting and preventing future diseases of individual patients.
Highlights
A key prerequisite for precision medicine is the estimation of disease progression from the current patient state
This example stands out as one of the strongest correlations between diagnoses and encounter type, but our analysis demonstrates that this trend holds true for most ICD-10 chapters
An important consideration in the subsequent analyses was to make use of this aspect to stratify diagnosis assignments into more precisely matched groups. We enable both the discovery of statistically significant correlations that would have been otherwise masked and the removal of statistically significant correlations that are trivially explained by encounter types
Summary
A key prerequisite for precision medicine is the estimation of disease progression from the current patient state. We use the entire spectrum of diseases and convert 14.9 years of registry data on 6.2 million patients into 1,171 significant trajectories We group these into patterns centred on a small number of key diagnoses such as chronic obstructive pulmonary disease (COPD) and gout, which are central to disease progression and important to diagnose early to mitigate the risk of adverse outcomes. Mandatory reporting from all Danish hospitals to the NPR is likely to severely limit the influence of population bias This data set covers 6.2 million patients with a total of 65 million total clinical encounters, comprising 16 million hospital inpatient events (24.5% of total), 35 million outpatient clinic events (53.6% of total) and 14 million emergency department events (21.9% of total). The data analyses presented here may be more useful, as they exhibit trajectories that are amenable to interruption at various stages and they point out those stages
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