loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Anima Singh and John Guttag

Affiliation: Massachusetts Institute of Technology, United States

Keyword(s): Machine Learning, Collaborative Filtering, Latent Factor Models, Intensive Care Units, Prescription Omissions.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Business Analytics ; Clinical Problems and Applications ; Data Engineering ; Data Mining ; Databases and Information Systems Integration ; Datamining ; Decision Support Systems ; Enterprise Information Systems ; Health Information Systems ; Pattern Recognition and Machine Learning ; Sensor Networks ; Signal Processing ; Soft Computing

Abstract: Medication errors in critical care are frequent and can lead to adverse consequences. One important category of errors is prescription omission, i.e., failure to prescribe a potentially useful medication. Studies have shown that failure to prescribe a medication can result in adverse consequences leading to patient morbidity or even patient mortality (Aspden et al., 2007; Olsen et al., 2007). In this paper, we present a machine learning based approach to building a system that can be used to provide physicians with an ordered list of possible omissions. We investigated three different collaborative filtering approaches as well as simple prevalence and co-occurrence methods. When evaluated on over 19,000 ICU admissions, each of the CF approaches outperformed both prevalence and co-occurrence based methods. This work highlights the importance of capturing a multi-scale view of the prescription data for the task of identifying omissions. Our results suggest that latent factor models and neighborhood models are better at capturing different kinds of omissions. Latent factor models demonstrated improved performance on identifying omission of rarely prescribed medications while neighborhood models were slightly better at identifying omissions of commonly prescribed medications. (More)

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.97.14.83

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Singh, A. and Guttag, J. (2013). Collaborative Filtering for Identifying Prescription Omissions in an ICU. In Proceedings of the International Conference on Health Informatics (BIOSTEC 2013) - HEALTHINF; ISBN 978-989-8565-37-2; ISSN 2184-4305, SciTePress, pages 58-64. DOI: 10.5220/0004233900580064

@conference{healthinf13,
author={Anima Singh and John Guttag},
title={Collaborative Filtering for Identifying Prescription Omissions in an ICU},
booktitle={Proceedings of the International Conference on Health Informatics (BIOSTEC 2013) - HEALTHINF},
year={2013},
pages={58-64},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004233900580064},
isbn={978-989-8565-37-2},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the International Conference on Health Informatics (BIOSTEC 2013) - HEALTHINF
TI - Collaborative Filtering for Identifying Prescription Omissions in an ICU
SN - 978-989-8565-37-2
IS - 2184-4305
AU - Singh, A.
AU - Guttag, J.
PY - 2013
SP - 58
EP - 64
DO - 10.5220/0004233900580064
PB - SciTePress