Entity embedding of high-dimensional claims data for hospitalized exacerbation prediction

Cordier, J.;, Geissler, A.; and Vogel, J.;

Health, Econometrics and Data Group (HEDG) Working Papers from HEDG, c/o Department of Economics, University of York

Abstract: This study addresses the challenges of using high-dimensional claims data, typically represented by categorical features, for prediction tasks. Traditional one-hot encoding methods lead to computational inefficiencies and sparse data issues. To overcome these challenges, we propose using entity embedding, a technique that has shown promise in natural language processing, to transform categorical claims data into dense, low-dimensional vectors as input for downstream prediction tasks. Our study focuses on predicting hospitalizations for patients with Chronic Obstructive Pulmonary Disease using the Word2Vec Continuous Bag-of-Words model. Our findings indicate that entity embedding enhances model performance, achieving an AUC of 0.92 compared to 0.91 with one-hot encoding, and improves specificity from 0.55 to 0.60 for a recall of 0.95. Additionally, entity embedding significantly reduces required computation power. These results suggest that entity embedding not only captures the dynamics of medical events more effectively but also enhances the efficiency of training predictive models, making it a valuable tool for healthcare and insurance analytics.

Date: 2024-08
New Economics Papers: this item is included in nep-big
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.york.ac.uk/media/economics/documents/h ... papers/2024/2409.pdf Main text (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:yor:hectdg:24/09

Access Statistics for this paper

More papers in Health, Econometrics and Data Group (HEDG) Working Papers from HEDG, c/o Department of Economics, University of York HEDG/HERC, Department of Economics and Related Studies, University of York, York, YO10 5DD, United Kingdom. Contact information at EDIRC.
Bibliographic data for series maintained by Jane Rawlings ().