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EMS utilization predictors in a Mobile Integrated Health (MIH) program

BACKGROUND: The provision of unnecessary Emergency Medical Services care remains a challenge throughout the US and contributes to Emergency Department overcrowding, delayed services and lower quality of care. New EMS models of care have shown promise in improving access to health services for patien...

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Autores principales: Pinet-Peralta, Luis M., Glos, Lukas J., Sanna, Evan, Frankel, Brian, Lindqvist, Ernest
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7863316/
https://www.ncbi.nlm.nih.gov/pubmed/33541350
http://dx.doi.org/10.1186/s12911-021-01409-w
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author Pinet-Peralta, Luis M.
Glos, Lukas J.
Sanna, Evan
Frankel, Brian
Lindqvist, Ernest
author_facet Pinet-Peralta, Luis M.
Glos, Lukas J.
Sanna, Evan
Frankel, Brian
Lindqvist, Ernest
author_sort Pinet-Peralta, Luis M.
collection PubMed
description BACKGROUND: The provision of unnecessary Emergency Medical Services care remains a challenge throughout the US and contributes to Emergency Department overcrowding, delayed services and lower quality of care. New EMS models of care have shown promise in improving access to health services for patients who do not need urgent care. The goals of this study were (1) to identify factors associated with EMS utilization (911) and (2) their effects on total EMS calls and transports in an MIH program. METHODS: The study sample included 110 MIH patients referred to the program or considered high-users of EMS services between November 2016 and September 2018. The study employed descriptive statistics and Poisson regressions to estimate the effects of covariates on total EMS calls and transports. RESULTS: The typical enrollee is a 60-year-old single Black male living with two other individuals. He has a PCP, takes 12 medications and is compliant with his treatment. The likelihood of calling and/or being transported by EMS was higher for males, patients at high risk for falls, patients with asthma/COPD, psychiatric or behavioral illnesses, and longer travel times to a PCP. Each prescribed medication increased the risk for EMS calls or transports by 4%. The program achieved clear reductions in 911 calls and transports and savings of more than 140,000 USD in the first month. CONCLUSIONS: This study shows that age, marital status, high fall risk scores, the number of medications, psychiatric/behavioral illness, asthma/COPD, CHF, CVA/stroke and medication compliance may be good predictors of EMS use in an MIH setting. MIH programs can help control utilization of EMS care and reduce both EMS calls and transports.
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spelling pubmed-78633162021-02-05 EMS utilization predictors in a Mobile Integrated Health (MIH) program Pinet-Peralta, Luis M. Glos, Lukas J. Sanna, Evan Frankel, Brian Lindqvist, Ernest BMC Med Inform Decis Mak Research Article BACKGROUND: The provision of unnecessary Emergency Medical Services care remains a challenge throughout the US and contributes to Emergency Department overcrowding, delayed services and lower quality of care. New EMS models of care have shown promise in improving access to health services for patients who do not need urgent care. The goals of this study were (1) to identify factors associated with EMS utilization (911) and (2) their effects on total EMS calls and transports in an MIH program. METHODS: The study sample included 110 MIH patients referred to the program or considered high-users of EMS services between November 2016 and September 2018. The study employed descriptive statistics and Poisson regressions to estimate the effects of covariates on total EMS calls and transports. RESULTS: The typical enrollee is a 60-year-old single Black male living with two other individuals. He has a PCP, takes 12 medications and is compliant with his treatment. The likelihood of calling and/or being transported by EMS was higher for males, patients at high risk for falls, patients with asthma/COPD, psychiatric or behavioral illnesses, and longer travel times to a PCP. Each prescribed medication increased the risk for EMS calls or transports by 4%. The program achieved clear reductions in 911 calls and transports and savings of more than 140,000 USD in the first month. CONCLUSIONS: This study shows that age, marital status, high fall risk scores, the number of medications, psychiatric/behavioral illness, asthma/COPD, CHF, CVA/stroke and medication compliance may be good predictors of EMS use in an MIH setting. MIH programs can help control utilization of EMS care and reduce both EMS calls and transports. BioMed Central 2021-02-04 /pmc/articles/PMC7863316/ /pubmed/33541350 http://dx.doi.org/10.1186/s12911-021-01409-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
Pinet-Peralta, Luis M.
Glos, Lukas J.
Sanna, Evan
Frankel, Brian
Lindqvist, Ernest
EMS utilization predictors in a Mobile Integrated Health (MIH) program
title EMS utilization predictors in a Mobile Integrated Health (MIH) program
title_full EMS utilization predictors in a Mobile Integrated Health (MIH) program
title_fullStr EMS utilization predictors in a Mobile Integrated Health (MIH) program
title_full_unstemmed EMS utilization predictors in a Mobile Integrated Health (MIH) program
title_short EMS utilization predictors in a Mobile Integrated Health (MIH) program
title_sort ems utilization predictors in a mobile integrated health (mih) program
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7863316/
https://www.ncbi.nlm.nih.gov/pubmed/33541350
http://dx.doi.org/10.1186/s12911-021-01409-w
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