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Prospective stratification of patients at risk for emergency department revisit: resource utilization and population management strategy implications

BACKGROUND: Estimating patient risk of future emergency department (ED) revisits can guide the allocation of resources, e.g. local primary care and/or specialty, to better manage ED high utilization patient populations and thereby improve patient life qualities. METHODS: We set to develop and valida...

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Autores principales: Jin, Bo, Zhao, Yifan, Hao, Shiying, Shin, Andrew Young, Wang, Yue, Zhu, Chunqing, Hu, Zhongkai, Fu, Changlin, Ji, Jun, Wang, Yong, Zhao, Yingzhen, Jiang, Yunliang, Dai, Dorothy, Culver, Devore S., Alfreds, Shaun T., Rogow, Todd, Stearns, Frank, Sylvester, Karl G., Widen, Eric, Ling, Xuefeng B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4739399/
https://www.ncbi.nlm.nih.gov/pubmed/26842066
http://dx.doi.org/10.1186/s12873-016-0074-5
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author Jin, Bo
Zhao, Yifan
Hao, Shiying
Shin, Andrew Young
Wang, Yue
Zhu, Chunqing
Hu, Zhongkai
Fu, Changlin
Ji, Jun
Wang, Yong
Zhao, Yingzhen
Jiang, Yunliang
Dai, Dorothy
Culver, Devore S.
Alfreds, Shaun T.
Rogow, Todd
Stearns, Frank
Sylvester, Karl G.
Widen, Eric
Ling, Xuefeng B.
author_facet Jin, Bo
Zhao, Yifan
Hao, Shiying
Shin, Andrew Young
Wang, Yue
Zhu, Chunqing
Hu, Zhongkai
Fu, Changlin
Ji, Jun
Wang, Yong
Zhao, Yingzhen
Jiang, Yunliang
Dai, Dorothy
Culver, Devore S.
Alfreds, Shaun T.
Rogow, Todd
Stearns, Frank
Sylvester, Karl G.
Widen, Eric
Ling, Xuefeng B.
author_sort Jin, Bo
collection PubMed
description BACKGROUND: Estimating patient risk of future emergency department (ED) revisits can guide the allocation of resources, e.g. local primary care and/or specialty, to better manage ED high utilization patient populations and thereby improve patient life qualities. METHODS: We set to develop and validate a method to estimate patient ED revisit risk in the subsequent 6 months from an ED discharge date. An ensemble decision-tree-based model with Electronic Medical Record (EMR) encounter data from HealthInfoNet (HIN), Maine’s Health Information Exchange (HIE), was developed and validated, assessing patient risk for a subsequent 6 month return ED visit based on the ED encounter-associated demographic and EMR clinical history data. A retrospective cohort of 293,461 ED encounters that occurred between January 1, 2012 and December 31, 2012, was assembled with the associated patients’ 1-year clinical histories before the ED discharge date, for model training and calibration purposes. To validate, a prospective cohort of 193,886 ED encounters that occurred between January 1, 2013 and June 30, 2013 was constructed. RESULTS: Statistical learning that was utilized to construct the prediction model identified 152 variables that included the following data domains: demographics groups (12), different encounter history (104), care facilities (12), primary and secondary diagnoses (10), primary and secondary procedures (2), chronic disease condition (1), laboratory test results (2), and outpatient prescription medications (9). The c-statistics for the retrospective and prospective cohorts were 0.742 and 0.730 respectively. Total medical expense and ED utilization by risk score 6 months after the discharge were analyzed. Cluster analysis identified discrete subpopulations of high-risk patients with distinctive resource utilization patterns, suggesting the need for diversified care management strategies. CONCLUSIONS: Integration of our method into the HIN secure statewide data system in real time prospectively validated its performance. It promises to provide increased opportunity for high ED utilization identification, and optimized resource and population management. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12873-016-0074-5) contains supplementary material, which is available to authorized users.
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spelling pubmed-47393992016-02-04 Prospective stratification of patients at risk for emergency department revisit: resource utilization and population management strategy implications Jin, Bo Zhao, Yifan Hao, Shiying Shin, Andrew Young Wang, Yue Zhu, Chunqing Hu, Zhongkai Fu, Changlin Ji, Jun Wang, Yong Zhao, Yingzhen Jiang, Yunliang Dai, Dorothy Culver, Devore S. Alfreds, Shaun T. Rogow, Todd Stearns, Frank Sylvester, Karl G. Widen, Eric Ling, Xuefeng B. BMC Emerg Med Research Article BACKGROUND: Estimating patient risk of future emergency department (ED) revisits can guide the allocation of resources, e.g. local primary care and/or specialty, to better manage ED high utilization patient populations and thereby improve patient life qualities. METHODS: We set to develop and validate a method to estimate patient ED revisit risk in the subsequent 6 months from an ED discharge date. An ensemble decision-tree-based model with Electronic Medical Record (EMR) encounter data from HealthInfoNet (HIN), Maine’s Health Information Exchange (HIE), was developed and validated, assessing patient risk for a subsequent 6 month return ED visit based on the ED encounter-associated demographic and EMR clinical history data. A retrospective cohort of 293,461 ED encounters that occurred between January 1, 2012 and December 31, 2012, was assembled with the associated patients’ 1-year clinical histories before the ED discharge date, for model training and calibration purposes. To validate, a prospective cohort of 193,886 ED encounters that occurred between January 1, 2013 and June 30, 2013 was constructed. RESULTS: Statistical learning that was utilized to construct the prediction model identified 152 variables that included the following data domains: demographics groups (12), different encounter history (104), care facilities (12), primary and secondary diagnoses (10), primary and secondary procedures (2), chronic disease condition (1), laboratory test results (2), and outpatient prescription medications (9). The c-statistics for the retrospective and prospective cohorts were 0.742 and 0.730 respectively. Total medical expense and ED utilization by risk score 6 months after the discharge were analyzed. Cluster analysis identified discrete subpopulations of high-risk patients with distinctive resource utilization patterns, suggesting the need for diversified care management strategies. CONCLUSIONS: Integration of our method into the HIN secure statewide data system in real time prospectively validated its performance. It promises to provide increased opportunity for high ED utilization identification, and optimized resource and population management. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12873-016-0074-5) contains supplementary material, which is available to authorized users. BioMed Central 2016-02-03 /pmc/articles/PMC4739399/ /pubmed/26842066 http://dx.doi.org/10.1186/s12873-016-0074-5 Text en © Jin et al. 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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.
spellingShingle Research Article
Jin, Bo
Zhao, Yifan
Hao, Shiying
Shin, Andrew Young
Wang, Yue
Zhu, Chunqing
Hu, Zhongkai
Fu, Changlin
Ji, Jun
Wang, Yong
Zhao, Yingzhen
Jiang, Yunliang
Dai, Dorothy
Culver, Devore S.
Alfreds, Shaun T.
Rogow, Todd
Stearns, Frank
Sylvester, Karl G.
Widen, Eric
Ling, Xuefeng B.
Prospective stratification of patients at risk for emergency department revisit: resource utilization and population management strategy implications
title Prospective stratification of patients at risk for emergency department revisit: resource utilization and population management strategy implications
title_full Prospective stratification of patients at risk for emergency department revisit: resource utilization and population management strategy implications
title_fullStr Prospective stratification of patients at risk for emergency department revisit: resource utilization and population management strategy implications
title_full_unstemmed Prospective stratification of patients at risk for emergency department revisit: resource utilization and population management strategy implications
title_short Prospective stratification of patients at risk for emergency department revisit: resource utilization and population management strategy implications
title_sort prospective stratification of patients at risk for emergency department revisit: resource utilization and population management strategy implications
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4739399/
https://www.ncbi.nlm.nih.gov/pubmed/26842066
http://dx.doi.org/10.1186/s12873-016-0074-5
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