Delirium Bibliography

Reference Information

Title

Using anchors from free text in electronic health records to diagnose postoperative delirium.

Authors

Mikalsen, K. Ø Soguero-Ruiz, C. Jensen, K. Hindberg, K. Gran, M. Revhaug, A. Lindsetmo, R. O. Skrøvseth, S. O. Godtliebsen, F. Jenssen, R.

Year

2017

Journal

Computer Methods and Programs in Biomedicine

Abstract

Objectives Postoperative delirium is a common complication after major surgery among the elderly. Despite its potentially serious consequences, the complication often goes undetected and undiagnosed. In order to provide diagnosis support one could potentially exploit the information hidden in free text documents from electronic health records using data-driven clinical decision support tools. However, these tools depend on labeled training data and can be both time consuming and expensive to create. Methods The recent learning with anchors framework resolves this problem by transforming key observations (anchors) into labels. This is a promising framework, but it is heavily reliant on clinicians knowledge for specifying good anchor choices in order to perform well. In this paper we propose a novel method for specifying anchors from free text documents, following an exploratory data analysis approach based on clustering and data visualization techniques. We investigate the use of the new framework as a way to detect postoperative delirium. Results By applying the proposed method to medical data gathered from a Norwegian university hospital, we increase the area under the precision-recall curve from 0.51 to 0.96 compared to baselines. Conclusions The proposed approach can be used as a framework for clinical decision support for postoperative delirium.

PMID

29054250

Keywords

haloperidol
article
classifier
electronic health record
human
major clinical study
medical information
medical information system
postoperative delirium
psychiatric diagnosis
psychopharmacotherapy

Page(s)

105-114

Volume

152

Issue