Analysis of free text in electronic health records for identification of cancer patient trajectories
Author(s)
Jensen, Kasper
Soguero-Ruiz, Cristina
Mikalsen, Karl Oyvind
Lindsetmo, Rolv-Ole
Kouskoumvekaki, Irene
Type
Journal Article
Abstract
With an aging patient population and increasing complexity in patient disease trajectories, physicians are often met with complex patient histories from which clinical decisions must be made. Due to the increasing rate of adverse events and hospitals facing financial penalties for readmission, there has never been a greater need to enforce evidence-led medical decision-making using available health care data. In the present work, we studied a cohort of 7,741 patients, of whom 4,080 were diagnosed with cancer, surgically treated at a University Hospital in the years 2004–2012. We have developed a methodology that allows disease trajectories of the cancer patients to be estimated from free text in electronic health records (EHRs). By using these disease trajectories, we predict 80% of patient events ahead in time. By control of confounders from 8326 quantified events, we identified 557 events that constitute high subsequent risks (risk > 20%), including six events for cancer and seven events for metastasis. We believe that the presented methodology and findings could be used to improve clinical decision support and personalize trajectories, thereby decreasing adverse events and optimizing cancer treatment.
Date Issued
2017-04-07
Date Acceptance
2017-03-13
Citation
Scientific Reports, 2017, 7
ISSN
2045-2322
Publisher
Nature Publishing Group
Journal / Book Title
Scientific Reports
Volume
7
Copyright Statement
© 2017 The Authors. This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000398551300001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Subjects
Science & Technology
Multidisciplinary Sciences
Science & Technology - Other Topics
GOODNESS-OF-FIT
SURGICAL COMPLICATIONS
FEATURE-SELECTION
CLINICAL-DATA
RISK-FACTORS
SURGERY
STRATIFICATION
CLASSIFICATION
READMISSIONS
COHORT
Publication Status
Published
Article Number
46226
Date Publish Online
2017-04-07