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Improving Hospital Discharge Time: A successful Implementation of Six Sigma Methodology
Delays in discharging patients can impact hospital and emergency department (ED) throughput. The discharge process is complex and involves setting specific challenges that limit generalizability of solutions. The aim of this study was to assess the effectiveness of using Six Sigma methods to improve...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer Health
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4554014/ https://www.ncbi.nlm.nih.gov/pubmed/25816029 http://dx.doi.org/10.1097/MD.0000000000000633 |
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author | El-Eid, Ghada R. Kaddoum, Roland Tamim, Hani Hitti, Eveline A. |
author_facet | El-Eid, Ghada R. Kaddoum, Roland Tamim, Hani Hitti, Eveline A. |
author_sort | El-Eid, Ghada R. |
collection | PubMed |
description | Delays in discharging patients can impact hospital and emergency department (ED) throughput. The discharge process is complex and involves setting specific challenges that limit generalizability of solutions. The aim of this study was to assess the effectiveness of using Six Sigma methods to improve the patient discharge process. This is a quantitative pre and post-intervention study. Three hundred and eighty-six bed tertiary care hospital. A series of Six Sigma driven interventions over a 10-month period. The primary outcome was discharge time (time from discharge order to patient leaving the room). Secondary outcome measures included percent of patients whose discharge order was written before noon, percent of patients leaving the room by noon, hospital length of stay (LOS), and LOS of admitted ED patients. Discharge time decreased by 22.7% from 2.2 hours during the preintervention period to 1.7 hours post-intervention (P < 0.001). A greater proportion of patients left their room before noon in the postintervention period (P < 0.001), though there was no statistical difference in before noon discharge. Hospital LOS dropped from 3.4 to 3.1 days postintervention (P < 0.001). ED mean LOS of patients admitted to the hospital was significantly lower in the postintervention period (6.9 ± 7.8 vs 5.9 ± 7.7 hours; P < 0.001). Six Sigma methodology can be an effective change management tool to improve discharge time. The focus of institutions aspiring to tackle delays in the discharge process should be on adopting the core principles of Six Sigma rather than specific interventions that may be institution-specific. |
format | Online Article Text |
id | pubmed-4554014 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Wolters Kluwer Health |
record_format | MEDLINE/PubMed |
spelling | pubmed-45540142015-10-27 Improving Hospital Discharge Time: A successful Implementation of Six Sigma Methodology El-Eid, Ghada R. Kaddoum, Roland Tamim, Hani Hitti, Eveline A. Medicine (Baltimore) 3900 Delays in discharging patients can impact hospital and emergency department (ED) throughput. The discharge process is complex and involves setting specific challenges that limit generalizability of solutions. The aim of this study was to assess the effectiveness of using Six Sigma methods to improve the patient discharge process. This is a quantitative pre and post-intervention study. Three hundred and eighty-six bed tertiary care hospital. A series of Six Sigma driven interventions over a 10-month period. The primary outcome was discharge time (time from discharge order to patient leaving the room). Secondary outcome measures included percent of patients whose discharge order was written before noon, percent of patients leaving the room by noon, hospital length of stay (LOS), and LOS of admitted ED patients. Discharge time decreased by 22.7% from 2.2 hours during the preintervention period to 1.7 hours post-intervention (P < 0.001). A greater proportion of patients left their room before noon in the postintervention period (P < 0.001), though there was no statistical difference in before noon discharge. Hospital LOS dropped from 3.4 to 3.1 days postintervention (P < 0.001). ED mean LOS of patients admitted to the hospital was significantly lower in the postintervention period (6.9 ± 7.8 vs 5.9 ± 7.7 hours; P < 0.001). Six Sigma methodology can be an effective change management tool to improve discharge time. The focus of institutions aspiring to tackle delays in the discharge process should be on adopting the core principles of Six Sigma rather than specific interventions that may be institution-specific. Wolters Kluwer Health 2015-03-27 /pmc/articles/PMC4554014/ /pubmed/25816029 http://dx.doi.org/10.1097/MD.0000000000000633 Text en Copyright © 2015 Wolters Kluwer Health, Inc. All rights reserved. http://creativecommons.org/licenses/by-nc/4.0 This is an open access article distributed under the Creative Commons Attribution-NonCommercial License, where it is permissible to download, share and reproduce the work in any medium, provided it is properly cited. The work cannot be used commercially. http://creativecommons.org/licenses/by-nc/4.0 |
spellingShingle | 3900 El-Eid, Ghada R. Kaddoum, Roland Tamim, Hani Hitti, Eveline A. Improving Hospital Discharge Time: A successful Implementation of Six Sigma Methodology |
title | Improving Hospital Discharge Time: A successful Implementation of Six Sigma Methodology |
title_full | Improving Hospital Discharge Time: A successful Implementation of Six Sigma Methodology |
title_fullStr | Improving Hospital Discharge Time: A successful Implementation of Six Sigma Methodology |
title_full_unstemmed | Improving Hospital Discharge Time: A successful Implementation of Six Sigma Methodology |
title_short | Improving Hospital Discharge Time: A successful Implementation of Six Sigma Methodology |
title_sort | improving hospital discharge time: a successful implementation of six sigma methodology |
topic | 3900 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4554014/ https://www.ncbi.nlm.nih.gov/pubmed/25816029 http://dx.doi.org/10.1097/MD.0000000000000633 |
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