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Predictive model of multiple emergency department visits among adults: analysis of the data from the National Survey of Drug Use and Health (NSDUH)
BACKGROUND: In this methodological paper, we use a novel, predictive approach to examine how demographics, substance use, mental and other health indicators predict multiple visits (≥3) to emergency departments (ED) within a year. METHODS: State-of-the-art predictive methods were used to evaluate pr...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7995604/ https://www.ncbi.nlm.nih.gov/pubmed/33766009 http://dx.doi.org/10.1186/s12913-021-06221-w |
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author | Bobashev, Georgiy Warren, Lauren Wu, Li-Tzy |
author_facet | Bobashev, Georgiy Warren, Lauren Wu, Li-Tzy |
author_sort | Bobashev, Georgiy |
collection | PubMed |
description | BACKGROUND: In this methodological paper, we use a novel, predictive approach to examine how demographics, substance use, mental and other health indicators predict multiple visits (≥3) to emergency departments (ED) within a year. METHODS: State-of-the-art predictive methods were used to evaluate predictive ability and factors predicting multiple visits to ED within a year and to identify factors that influenced the strength of the prediction. The analysis used public-use datasets from the 2015–2018 National Surveys on Drug Use and Health (NSDUH), which used the same questionnaire on the variables of interest. Analysis focused on adults aged ≥18 years. Several predictive models (regressions, trees, and random forests) were validated and compared on independent datasets. RESULTS: Predictive ability on a test set for multiple ED visits (≥3 times within a year) measured as the area under the receiver operating characteristic (ROC) reached 0.8, which is good for a national survey. Models revealed consistency in predictive factors across the 4 survey years. The most influential variables for predicting ≥3 ED visits per year were fair/poor self-rated health, being nervous or restless/fidgety, having a lower income, asthma, heart condition/disease, having chronic obstructive pulmonary disease (COPD), nicotine dependence, African-American race, female sex, having diabetes, and being of younger age (18–20). CONCLUSIONS: The findings reveal the need to address behavioral and mental health contributors to ED visits and reinforce the importance of developing integrated care models in primary care settings to improve mental health for medically vulnerable patients. The presented modeling approach can be broadly applied to national and other large surveys. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-021-06221-w. |
format | Online Article Text |
id | pubmed-7995604 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-79956042021-03-26 Predictive model of multiple emergency department visits among adults: analysis of the data from the National Survey of Drug Use and Health (NSDUH) Bobashev, Georgiy Warren, Lauren Wu, Li-Tzy BMC Health Serv Res Research Article BACKGROUND: In this methodological paper, we use a novel, predictive approach to examine how demographics, substance use, mental and other health indicators predict multiple visits (≥3) to emergency departments (ED) within a year. METHODS: State-of-the-art predictive methods were used to evaluate predictive ability and factors predicting multiple visits to ED within a year and to identify factors that influenced the strength of the prediction. The analysis used public-use datasets from the 2015–2018 National Surveys on Drug Use and Health (NSDUH), which used the same questionnaire on the variables of interest. Analysis focused on adults aged ≥18 years. Several predictive models (regressions, trees, and random forests) were validated and compared on independent datasets. RESULTS: Predictive ability on a test set for multiple ED visits (≥3 times within a year) measured as the area under the receiver operating characteristic (ROC) reached 0.8, which is good for a national survey. Models revealed consistency in predictive factors across the 4 survey years. The most influential variables for predicting ≥3 ED visits per year were fair/poor self-rated health, being nervous or restless/fidgety, having a lower income, asthma, heart condition/disease, having chronic obstructive pulmonary disease (COPD), nicotine dependence, African-American race, female sex, having diabetes, and being of younger age (18–20). CONCLUSIONS: The findings reveal the need to address behavioral and mental health contributors to ED visits and reinforce the importance of developing integrated care models in primary care settings to improve mental health for medically vulnerable patients. The presented modeling approach can be broadly applied to national and other large surveys. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-021-06221-w. BioMed Central 2021-03-25 /pmc/articles/PMC7995604/ /pubmed/33766009 http://dx.doi.org/10.1186/s12913-021-06221-w Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Bobashev, Georgiy Warren, Lauren Wu, Li-Tzy Predictive model of multiple emergency department visits among adults: analysis of the data from the National Survey of Drug Use and Health (NSDUH) |
title | Predictive model of multiple emergency department visits among adults: analysis of the data from the National Survey of Drug Use and Health (NSDUH) |
title_full | Predictive model of multiple emergency department visits among adults: analysis of the data from the National Survey of Drug Use and Health (NSDUH) |
title_fullStr | Predictive model of multiple emergency department visits among adults: analysis of the data from the National Survey of Drug Use and Health (NSDUH) |
title_full_unstemmed | Predictive model of multiple emergency department visits among adults: analysis of the data from the National Survey of Drug Use and Health (NSDUH) |
title_short | Predictive model of multiple emergency department visits among adults: analysis of the data from the National Survey of Drug Use and Health (NSDUH) |
title_sort | predictive model of multiple emergency department visits among adults: analysis of the data from the national survey of drug use and health (nsduh) |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7995604/ https://www.ncbi.nlm.nih.gov/pubmed/33766009 http://dx.doi.org/10.1186/s12913-021-06221-w |
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