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Predicting hospital visits from geo-tagged Internet search logs

The steady rise in healthcare costs has deprived over 45 million Americans of healthcare services (1, 2) and has encouraged healthcare providers to look for opportunities to improve their operational efficiency. Prior studies have shown that evidence of healthcare seeking intent in Internet searches...

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Detalles Bibliográficos
Autores principales: Agarwal, Vibhu, Han, Lichy, Madan, Isaac, Saluja, Shaurya, Shidham, Aaditya, Shah, Nigam H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Medical Informatics Association 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5001755/
https://www.ncbi.nlm.nih.gov/pubmed/27570641
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author Agarwal, Vibhu
Han, Lichy
Madan, Isaac
Saluja, Shaurya
Shidham, Aaditya
Shah, Nigam H.
author_facet Agarwal, Vibhu
Han, Lichy
Madan, Isaac
Saluja, Shaurya
Shidham, Aaditya
Shah, Nigam H.
author_sort Agarwal, Vibhu
collection PubMed
description The steady rise in healthcare costs has deprived over 45 million Americans of healthcare services (1, 2) and has encouraged healthcare providers to look for opportunities to improve their operational efficiency. Prior studies have shown that evidence of healthcare seeking intent in Internet searches correlates well with healthcare resource utilization. Given the ubiquitous nature of mobile Internet search, we hypothesized that analyzing geo-tagged mobile search logs could enable us to machine-learn predictors of future patient visits. Using a de-identified dataset of geo-tagged mobile Internet search logs, we mined text and location patterns that are predictors of healthcare resource utilization and built statistical models that predict the probability of a user’s future visit to a medical facility. Our efforts will enable the development of innovative methods for modeling and optimizing the use of healthcare resources—a crucial prerequisite for securing healthcare access for everyone in the days to come.
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spelling pubmed-50017552016-08-26 Predicting hospital visits from geo-tagged Internet search logs Agarwal, Vibhu Han, Lichy Madan, Isaac Saluja, Shaurya Shidham, Aaditya Shah, Nigam H. AMIA Jt Summits Transl Sci Proc Articles The steady rise in healthcare costs has deprived over 45 million Americans of healthcare services (1, 2) and has encouraged healthcare providers to look for opportunities to improve their operational efficiency. Prior studies have shown that evidence of healthcare seeking intent in Internet searches correlates well with healthcare resource utilization. Given the ubiquitous nature of mobile Internet search, we hypothesized that analyzing geo-tagged mobile search logs could enable us to machine-learn predictors of future patient visits. Using a de-identified dataset of geo-tagged mobile Internet search logs, we mined text and location patterns that are predictors of healthcare resource utilization and built statistical models that predict the probability of a user’s future visit to a medical facility. Our efforts will enable the development of innovative methods for modeling and optimizing the use of healthcare resources—a crucial prerequisite for securing healthcare access for everyone in the days to come. American Medical Informatics Association 2016-07-20 /pmc/articles/PMC5001755/ /pubmed/27570641 Text en ©2016 AMIA - All rights reserved. This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose
spellingShingle Articles
Agarwal, Vibhu
Han, Lichy
Madan, Isaac
Saluja, Shaurya
Shidham, Aaditya
Shah, Nigam H.
Predicting hospital visits from geo-tagged Internet search logs
title Predicting hospital visits from geo-tagged Internet search logs
title_full Predicting hospital visits from geo-tagged Internet search logs
title_fullStr Predicting hospital visits from geo-tagged Internet search logs
title_full_unstemmed Predicting hospital visits from geo-tagged Internet search logs
title_short Predicting hospital visits from geo-tagged Internet search logs
title_sort predicting hospital visits from geo-tagged internet search logs
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5001755/
https://www.ncbi.nlm.nih.gov/pubmed/27570641
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