Data-driven Temporal Prediction of Surgical Site Infection.

Journal: AMIA ... Annual Symposium proceedings. AMIA Symposium
Published Date: Nov 5, 2015

Abstract

Analysis of data from Electronic Health Records (EHR) presents unique challenges, in particular regarding nonuniform temporal resolution of longitudinal variables. A considerable amount of patient information is available in the EHR - including blood tests that are performed routinely during inpatient follow-up. These data are useful for the design of advanced machine learning-based methods and prediction models. Using a matched cohort of patients undergoing gastrointestinal surgery (101 cases and 904 controls), we built a prediction model for post-operative surgical site infections (SSIs) using Gaussian process (GP) regression, time warping and imputation methods to manage the sparsity of the data source, and support vector machines for classification. For most blood tests, wider confidence intervals after imputation were obtained in patients with SSI. Predictive performance with individual blood tests was maintained or improved by joint model prediction, and non-linear classifiers performed consistently better than linear models.

Authors

  • Cristina Soguero-Ruiz
    Department of Signal Theory and Communications, Telematics and Computing Systems, Rey Juan Carlos University, Madrid, Spain. Electronic address: cristina.soguero@urjc.es.
  • Wang M E Fei
    Department of Computer Science and Engineering, University of Connecticut, Storrs, CT, USA.
  • Robert Jenssen
    Department of Physics and Technology, University of Tromsø - The Arctic University of Norway, Tromsø, Norway; Norwegian Centre for Integrated Care and Telemedicine, University Hospital of North Norway, Tromsø, Norway.
  • Knut Magne Augestad
    Norwegian Centre for Integrated Care and Telemedicine, University Hospital of North Norway, Tromsø, Norway; Department of Surgery, Hammerfest Hospital, Hammerfest, Norway.
  • José-Luis Rojo Álvarez
    Department of Signal Theory and Communications, Telematics and Computing, Rey Juan Carlos University, Madrid, Spain.
  • Inmaculada Mora Jiménez
    Department of Signal Theory and Communications, Telematics and Computing, Rey Juan Carlos University, Madrid, Spain.
  • Rolv-Ole Lindsetmo
    Department of Gastrointestinal Surgery, University Hospital of North Norway, Tromsø, Norway; Department of Clinical Medicine, University of Tromsø - The Arctic University of Norway, Tromsø, Norway.
  • Stein Olav Skrøvseth
    Norwegian Centre for Integrated Care and Telemedicine, University Hospital of North Norway, Tromsø, Norway; Department of Mathematics and Statistics, University of Tromsø - The Arctic University of Norway, Tromsø, Norway.

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