Hybrid Collaborative Filtering Methods for Recommending Search Terms to Clinicians

If you need an accessible version of this item, please submit a remediation request.
Date
2021
Language
American English
Embargo Lift Date
Committee Members
Degree
Degree Year
Department
Grantor
Journal Title
Journal ISSN
Volume Title
Found At
Elsevier
Abstract

With increasing and extensive use of electronic health records (EHR), clinicians are often challenged in retrieving relevant patient information efficiently and effectively to arrive at a diagnosis. While using the search function built into an EHR can be more useful than browsing in a voluminous patient record, it is cumbersome and repetitive to search for the same or similar information on similar patients. To address this challenge, there is a critical need to build effective recommender systems that can recommend search terms to clinicians accurately. In this study, we developed a hybrid collaborative filtering model to recommend search terms for a specific patient to a clinician. The model draws on information from patients' clinical encounters and the searches that were performed during them. To generate recommendations, the model uses search terms which are (1) frequently co-occurring with the ICD codes recorded for the patient and (2) highly relevant to the most recent search terms. In one variation of the model (Hybrid Collaborative Filtering Method for Healthcare, or HCFMH), we use only the most recent ICD codes assigned to the patient, and in the other (Co-occurrence Pattern based HCFMH, or cpHCFMH), all ICD codes. We have conducted comprehensive experiments to evaluate the proposed model. These experiments demonstrate that our model outperforms state-of-the-art baseline methods for top-N search term recommendation on different data sets.

Description
item.page.description.tableofcontents
item.page.relation.haspart
Cite As
Ren Z, Peng B, Schleyer TK, Ning X. Hybrid collaborative filtering methods for recommending search terms to clinicians. J Biomed Inform. 2021;113:103635. doi:10.1016/j.jbi.2020.103635
ISSN
Publisher
Series/Report
Sponsorship
Major
Extent
Identifier
Relation
Journal
Journal of Biomedical Informatics
Source
PMC
Alternative Title
Type
Article
Number
Volume
Conference Dates
Conference Host
Conference Location
Conference Name
Conference Panel
Conference Secretariat Location
Version
Author's manuscript
Full Text Available at
This item is under embargo {{howLong}}