Network-medicine framework for studying disease trajectories in U.S. veterans

Italo Faria do Valle, Brian Ferolito, Hanna Gerlovin, Lauren Costa, Serkalem Demissie, Franciel Linares, Jeremy Cohen, David R. Gagnon, J. Michael Gaziano, Edmon Begoli, Kelly Cho, Albert László Barabási

Research output: Contribution to journalArticlepeer-review

Abstract (may include machine translation)

A better understanding of the sequential and temporal aspects in which diseases occur in patient’s lives is essential for developing improved intervention strategies that reduce burden and increase the quality of health services. Here we present a network-based framework to study disease relationships using Electronic Health Records from > 9 million patients in the United States Veterans Health Administration (VHA) system. We create the Temporal Disease Network, which maps the sequential aspects of disease co-occurrence among patients and demonstrate that network properties reflect clinical aspects of the respective diseases. We use the Temporal Disease Network to identify disease groups that reflect patterns of disease co-occurrence and the flow of patients among diagnoses. Finally, we define a strategy for the identification of trajectories that lead from one disease to another. The framework presented here has the potential to offer new insights for disease treatment and prevention in large health care systems.

Original languageEnglish
Article number12018
JournalScientific Reports
Volume12
Issue number1
DOIs
StatePublished - Dec 2022
Externally publishedYes

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