Disease Trajectories from Healthcare Data: Methodologies, Key Results, and Future Perspectives

Disease trajectories, defined as sequential, directional disease associations, have become an intense research field driven by the availability of electronic population-wide healthcare data and sufficient computational power. Here, we provide an overview of disease trajectory studies with a focus on...

Full description

Saved in:
Bibliographic Details
Published in:Annual review of biomedical data science 2024-08, Vol.7 (1), p.251-276
Main Authors: Jørgensen, Isabella Friis, Haue, Amalie Dahl, Placido, Davide, Hjaltelin, Jessica Xin, Brunak, Søren
Format: Article
Language:English
Subjects:
Delivery of Health Care
disease co-occurrence
Disease Progression
disease trajectories
Europe - epidemiology
healthcare data
Humans
Machine Learning - trends
multimorbidity
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Disease trajectories, defined as sequential, directional disease associations, have become an intense research field driven by the availability of electronic population-wide healthcare data and sufficient computational power. Here, we provide an overview of disease trajectory studies with a focus on European work, including ontologies used as well as computational methodologies for the construction of disease trajectories. We also discuss different applications of disease trajectories from descriptive risk identification to disease progression, patient stratification, and personalized predictions using machine learning. We describe challenges and opportunities in the area that eventually will benefit from initiatives such as the European Health Data Space, which, with time, will make it possible to analyze data from cohorts comprising hundreds of millions of patients.
ISSN:2574-3414
2574-3414
DOI:10.1146/annurev-biodatasci-110123-041001