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Optimizing inpatient bed management in a rural community-based hospital: a quality improvement initiative

BACKGROUND: Appropriate use of available inpatient beds is an ongoing challenge for US hospitals. Historical capacity goals of 80% to 85% may no longer serve the intended purpose of maximizing the resources of space, staff, and equipment. Numerous variables affect the input, throughput, and output o...

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Autores principales: Bartlett, Brian N., Vanhoudt, Nadine N., Wang, Hanyin, Anderson, Ashley A., Juliar, Danielle L., Bartelt, Jennifer M., Lanz, April D., Bhandari, Pawan, Anil, Gokhan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10506333/
https://www.ncbi.nlm.nih.gov/pubmed/37723528
http://dx.doi.org/10.1186/s12913-023-10008-6
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author Bartlett, Brian N.
Vanhoudt, Nadine N.
Wang, Hanyin
Anderson, Ashley A.
Juliar, Danielle L.
Bartelt, Jennifer M.
Lanz, April D.
Bhandari, Pawan
Anil, Gokhan
author_facet Bartlett, Brian N.
Vanhoudt, Nadine N.
Wang, Hanyin
Anderson, Ashley A.
Juliar, Danielle L.
Bartelt, Jennifer M.
Lanz, April D.
Bhandari, Pawan
Anil, Gokhan
author_sort Bartlett, Brian N.
collection PubMed
description BACKGROUND: Appropriate use of available inpatient beds is an ongoing challenge for US hospitals. Historical capacity goals of 80% to 85% may no longer serve the intended purpose of maximizing the resources of space, staff, and equipment. Numerous variables affect the input, throughput, and output of a hospital. Some of these variables include patient demand, regulatory requirements, coordination of patient flow between various systems, coordination of processes such as bed management and patient transfers, and the diversity of departments (both inpatient and outpatient) in an organization. METHODS: Mayo Clinic Health System in the Southwest Minnesota region of the US, a community-based hospital system primarily serving patients in rural southwestern Minnesota and part of Iowa, consists of 2 postacute care and 3 critical access hospitals. Our inpatient bed usage rates had exceeded 85%, and patient transfers from the region to other hospitals in the state (including Mayo Clinic in Rochester, Minnesota) had increased. To address these quality gaps, we used a blend of Agile project management methodology, rapid Plan-Do-Study-Act cycles, and a proactive approach to patient placement in the medical-surgical units as a quality improvement initiative. RESULTS: During 2 trial periods of the initiative, the main hub hospital (Mayo Clinic Health System hospital in Mankato) and other hospitals in the region increased inpatient bed usage while reducing total out-of-region transfers. CONCLUSION: Our novel approach to proactively managing bed capacity in the hospital allowed the region’s only tertiary medical center to increase capacity for more complex and acute cases by optimizing the use of historically underused partner hospital beds.
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spelling pubmed-105063332023-09-19 Optimizing inpatient bed management in a rural community-based hospital: a quality improvement initiative Bartlett, Brian N. Vanhoudt, Nadine N. Wang, Hanyin Anderson, Ashley A. Juliar, Danielle L. Bartelt, Jennifer M. Lanz, April D. Bhandari, Pawan Anil, Gokhan BMC Health Serv Res Research BACKGROUND: Appropriate use of available inpatient beds is an ongoing challenge for US hospitals. Historical capacity goals of 80% to 85% may no longer serve the intended purpose of maximizing the resources of space, staff, and equipment. Numerous variables affect the input, throughput, and output of a hospital. Some of these variables include patient demand, regulatory requirements, coordination of patient flow between various systems, coordination of processes such as bed management and patient transfers, and the diversity of departments (both inpatient and outpatient) in an organization. METHODS: Mayo Clinic Health System in the Southwest Minnesota region of the US, a community-based hospital system primarily serving patients in rural southwestern Minnesota and part of Iowa, consists of 2 postacute care and 3 critical access hospitals. Our inpatient bed usage rates had exceeded 85%, and patient transfers from the region to other hospitals in the state (including Mayo Clinic in Rochester, Minnesota) had increased. To address these quality gaps, we used a blend of Agile project management methodology, rapid Plan-Do-Study-Act cycles, and a proactive approach to patient placement in the medical-surgical units as a quality improvement initiative. RESULTS: During 2 trial periods of the initiative, the main hub hospital (Mayo Clinic Health System hospital in Mankato) and other hospitals in the region increased inpatient bed usage while reducing total out-of-region transfers. CONCLUSION: Our novel approach to proactively managing bed capacity in the hospital allowed the region’s only tertiary medical center to increase capacity for more complex and acute cases by optimizing the use of historically underused partner hospital beds. BioMed Central 2023-09-18 /pmc/articles/PMC10506333/ /pubmed/37723528 http://dx.doi.org/10.1186/s12913-023-10008-6 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://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
Bartlett, Brian N.
Vanhoudt, Nadine N.
Wang, Hanyin
Anderson, Ashley A.
Juliar, Danielle L.
Bartelt, Jennifer M.
Lanz, April D.
Bhandari, Pawan
Anil, Gokhan
Optimizing inpatient bed management in a rural community-based hospital: a quality improvement initiative
title Optimizing inpatient bed management in a rural community-based hospital: a quality improvement initiative
title_full Optimizing inpatient bed management in a rural community-based hospital: a quality improvement initiative
title_fullStr Optimizing inpatient bed management in a rural community-based hospital: a quality improvement initiative
title_full_unstemmed Optimizing inpatient bed management in a rural community-based hospital: a quality improvement initiative
title_short Optimizing inpatient bed management in a rural community-based hospital: a quality improvement initiative
title_sort optimizing inpatient bed management in a rural community-based hospital: a quality improvement initiative
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10506333/
https://www.ncbi.nlm.nih.gov/pubmed/37723528
http://dx.doi.org/10.1186/s12913-023-10008-6
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