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Trajectories of Disease Accumulation Using Electronic Health Records

Planell-Morell, P; Bajekal, M; Denaxas, S; Raine, R; Alexander, DC; (2020) Trajectories of Disease Accumulation Using Electronic Health Records. Studies in Health Technology and Informatics , 270 pp. 469-473. 10.3233/SHTI200204. Green open access

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Abstract

Multimorbidity is a major problem for patients and health services. However, we still do not know much about the common trajectories of disease accumulation that patients follow. We apply a data-driven method to an electronic health record dataset (CPRD) to analyse and condense the main trajectories to multimorbidity into simple networks. This analysis has never been done specifically for multimorbidity trajectories and using primary care based electronic health records. We start the analysis by evaluating temporal correlations between diseases to determine which pairs of disease appear significantly in sequence. Then, we use patient trajectories together with the temporal correlations to build networks of disease accumulation. These networks are able to represent the main pathways that patients follow to acquire multiple chronic conditions. The first network that we find contains the common diseases that multimorbid patients suffer from and shows how diseases like diabetes, COPD, cancer and osteoporosis are crucial in the disease trajectories. The results we present can help better characterize multimorbid patients and highlight common combinations helping to focus treatment to prevent or delay multimorbidity progression.

Type: Article
Title: Trajectories of Disease Accumulation Using Electronic Health Records
Location: Netherlands
Open access status: An open access version is available from UCL Discovery
DOI: 10.3233/SHTI200204
Publisher version: https://doi.org/10.3233/SHTI200204
Language: English
Additional information: This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0). https://creativecommons.org/licenses/by-nc/4.0/
Keywords: multimorbidity, electronic health records, disease trajectory, multiple disease progression model
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Epidemiology and Health
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Epidemiology and Health > Applied Health Research
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics > Clinical Epidemiology
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10103491
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