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Repeat hospital transfers among long stay nursing home residents: a mixed methods analysis of age, race, code status and clinical complexity
BACKGROUND: Nursing home residents are at increased risk for hospital transfers resulting in emergency department visits, observation stays, and hospital admissions; transfers that can also result in adverse resident outcomes. Many nursing home to hospital transfers are potentially avoidable. Reside...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9087933/ https://www.ncbi.nlm.nih.gov/pubmed/35538575 http://dx.doi.org/10.1186/s12913-022-08036-9 |
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author | Vogelsmeier, Amy Popejoy, Lori Fritz, Elizabeth Canada, Kelli Ge, Bin Brandt, Lea Rantz, Marilyn |
author_facet | Vogelsmeier, Amy Popejoy, Lori Fritz, Elizabeth Canada, Kelli Ge, Bin Brandt, Lea Rantz, Marilyn |
author_sort | Vogelsmeier, Amy |
collection | PubMed |
description | BACKGROUND: Nursing home residents are at increased risk for hospital transfers resulting in emergency department visits, observation stays, and hospital admissions; transfers that can also result in adverse resident outcomes. Many nursing home to hospital transfers are potentially avoidable. Residents who experience repeat transfers are particularly vulnerable to adverse outcomes, yet characteristics of nursing home residents who experience repeat transfers are poorly understood. Understanding these characteristics more fully will help identify appropriate intervention efforts needed to reduce repeat transfers. METHODS: This is a mixed-methods study using hospital transfer data, collected between 2017 and 2019, from long-stay nursing home residents residing in 16 Midwestern nursing homes who transferred four or more times within a 12-month timeframe. Data were obtained from an acute care transfer tool used in the Missouri Quality Initiative containing closed- and open-ended questions regarding hospital transfers. The Missouri Quality Initiative was a Centers for Medicare and Medicaid demonstration project focused on reducing avoidable hospital transfers for long stay nursing home residents. The purpose of the analysis presented here is to describe characteristics of residents from that project who experienced repeat transfers including resident age, race, and code status. Clinical, resident/family, and organizational factors that influenced transfers were also described. RESULTS: Findings indicate that younger residents (less than 65 years of age), those who were full-code status, and those who were Black were statistically more likely to experience repeat transfers. Clinical complexity, resident/family requests to transfer, and lack of nursing home resources to manage complex clinical conditions underlie repeat transfers, many of which were considered potentially avoidable. CONCLUSIONS: Improved nursing home resources are needed to manage complex conditions in the NH and to help residents and families set realistic goals of care and plan for end of life thus reducing potentially avoidable transfers. |
format | Online Article Text |
id | pubmed-9087933 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-90879332022-05-11 Repeat hospital transfers among long stay nursing home residents: a mixed methods analysis of age, race, code status and clinical complexity Vogelsmeier, Amy Popejoy, Lori Fritz, Elizabeth Canada, Kelli Ge, Bin Brandt, Lea Rantz, Marilyn BMC Health Serv Res Research BACKGROUND: Nursing home residents are at increased risk for hospital transfers resulting in emergency department visits, observation stays, and hospital admissions; transfers that can also result in adverse resident outcomes. Many nursing home to hospital transfers are potentially avoidable. Residents who experience repeat transfers are particularly vulnerable to adverse outcomes, yet characteristics of nursing home residents who experience repeat transfers are poorly understood. Understanding these characteristics more fully will help identify appropriate intervention efforts needed to reduce repeat transfers. METHODS: This is a mixed-methods study using hospital transfer data, collected between 2017 and 2019, from long-stay nursing home residents residing in 16 Midwestern nursing homes who transferred four or more times within a 12-month timeframe. Data were obtained from an acute care transfer tool used in the Missouri Quality Initiative containing closed- and open-ended questions regarding hospital transfers. The Missouri Quality Initiative was a Centers for Medicare and Medicaid demonstration project focused on reducing avoidable hospital transfers for long stay nursing home residents. The purpose of the analysis presented here is to describe characteristics of residents from that project who experienced repeat transfers including resident age, race, and code status. Clinical, resident/family, and organizational factors that influenced transfers were also described. RESULTS: Findings indicate that younger residents (less than 65 years of age), those who were full-code status, and those who were Black were statistically more likely to experience repeat transfers. Clinical complexity, resident/family requests to transfer, and lack of nursing home resources to manage complex clinical conditions underlie repeat transfers, many of which were considered potentially avoidable. CONCLUSIONS: Improved nursing home resources are needed to manage complex conditions in the NH and to help residents and families set realistic goals of care and plan for end of life thus reducing potentially avoidable transfers. BioMed Central 2022-05-10 /pmc/articles/PMC9087933/ /pubmed/35538575 http://dx.doi.org/10.1186/s12913-022-08036-9 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/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/ (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 Vogelsmeier, Amy Popejoy, Lori Fritz, Elizabeth Canada, Kelli Ge, Bin Brandt, Lea Rantz, Marilyn Repeat hospital transfers among long stay nursing home residents: a mixed methods analysis of age, race, code status and clinical complexity |
title | Repeat hospital transfers among long stay nursing home residents: a mixed methods analysis of age, race, code status and clinical complexity |
title_full | Repeat hospital transfers among long stay nursing home residents: a mixed methods analysis of age, race, code status and clinical complexity |
title_fullStr | Repeat hospital transfers among long stay nursing home residents: a mixed methods analysis of age, race, code status and clinical complexity |
title_full_unstemmed | Repeat hospital transfers among long stay nursing home residents: a mixed methods analysis of age, race, code status and clinical complexity |
title_short | Repeat hospital transfers among long stay nursing home residents: a mixed methods analysis of age, race, code status and clinical complexity |
title_sort | repeat hospital transfers among long stay nursing home residents: a mixed methods analysis of age, race, code status and clinical complexity |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9087933/ https://www.ncbi.nlm.nih.gov/pubmed/35538575 http://dx.doi.org/10.1186/s12913-022-08036-9 |
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