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Implementation of a Physician-Based Stroke Unit in a Remote Hospital of North-East India-Tezpur Model

Objective  The study aims to determine the effects of implementing stroke unit (SU) care in a remote hospital in North-East India. Materials and Methods  This before-and-after implementation study was performed at the Baptist Christian Mission Hospital, Tezpur, Assam between January 2015 and Decembe...

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Autores principales: John, Lydia, William, Akanksha, Dawar, Dimple, Khatter, Himani, Singh, Pratibha, Andrias, Anjana, Mochahari, Christina, Langhorne, Peter, Pandian, Jeyaraj
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Thieme Medical and Scientific Publishers Pvt. Ltd. 2021
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8064833/
https://www.ncbi.nlm.nih.gov/pubmed/33927525
http://dx.doi.org/10.1055/s-0041-1723099
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author John, Lydia
William, Akanksha
Dawar, Dimple
Khatter, Himani
Singh, Pratibha
Andrias, Anjana
Mochahari, Christina
Langhorne, Peter
Pandian, Jeyaraj
author_facet John, Lydia
William, Akanksha
Dawar, Dimple
Khatter, Himani
Singh, Pratibha
Andrias, Anjana
Mochahari, Christina
Langhorne, Peter
Pandian, Jeyaraj
author_sort John, Lydia
collection PubMed
description Objective  The study aims to determine the effects of implementing stroke unit (SU) care in a remote hospital in North-East India. Materials and Methods  This before-and-after implementation study was performed at the Baptist Christian Mission Hospital, Tezpur, Assam between January 2015 and December 2017. Before the implementation of stroke unit care (pre-SU), we collected information on usual stroke care and 1-month outcome of 125 consecutive stroke admissions. Staff was then trained in the delivery of SU care for 1 month, and the same information was collected in a second (post-SU) cohort of 125 patients. Statistical Analysis  Chi-square and Mann–Whitney U test were used to compare group differences. The loss to follow-up was imputed by using multiple imputations using the Markov Chain Monto Carlo method. The sensitivity analysis was also performed by using propensity score matching of the groups for baseline stroke severity (National Institute of Health Stroke Scale) using the nearest neighbor approach to control for confounding, and missing values were imputed by using multiple imputations. The adjusted odds ratio was calculated in univariate and multivariate regression analysis after adjusting for baseline variables. All the analysis was done by using SPSS, version 21.0., IBM Corp and R version 4.0.0., Armonk, New York, United States. Results  The pre-SU and post-SU groups were age and gender matched. The post-SU group showed higher rates of swallow assessment (36.8 vs. 0%, p < 0.001), mobility assessment, and re-education (100 vs. 91.5%, p = 0.037). The post-SU group also showed reduced complications (28 vs. 45%, p = 0.006) and a shorter length of hospital stay (4 ± 2.16 vs. 5 ± 2.68 days, p = 0.026). The functional outcome (modified ranking scale) at 1-month showed no difference between the groups, good outcome in post-SU (39.6%) versus pre-SU (35.7%), p = 0.552. Conclusion  The implementation of this physician-based SU care model in a remote hospital in India shows improvements in quality measures, complications, and possibly patient outcomes.
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spelling pubmed-80648332021-04-28 Implementation of a Physician-Based Stroke Unit in a Remote Hospital of North-East India-Tezpur Model John, Lydia William, Akanksha Dawar, Dimple Khatter, Himani Singh, Pratibha Andrias, Anjana Mochahari, Christina Langhorne, Peter Pandian, Jeyaraj J Neurosci Rural Pract Objective  The study aims to determine the effects of implementing stroke unit (SU) care in a remote hospital in North-East India. Materials and Methods  This before-and-after implementation study was performed at the Baptist Christian Mission Hospital, Tezpur, Assam between January 2015 and December 2017. Before the implementation of stroke unit care (pre-SU), we collected information on usual stroke care and 1-month outcome of 125 consecutive stroke admissions. Staff was then trained in the delivery of SU care for 1 month, and the same information was collected in a second (post-SU) cohort of 125 patients. Statistical Analysis  Chi-square and Mann–Whitney U test were used to compare group differences. The loss to follow-up was imputed by using multiple imputations using the Markov Chain Monto Carlo method. The sensitivity analysis was also performed by using propensity score matching of the groups for baseline stroke severity (National Institute of Health Stroke Scale) using the nearest neighbor approach to control for confounding, and missing values were imputed by using multiple imputations. The adjusted odds ratio was calculated in univariate and multivariate regression analysis after adjusting for baseline variables. All the analysis was done by using SPSS, version 21.0., IBM Corp and R version 4.0.0., Armonk, New York, United States. Results  The pre-SU and post-SU groups were age and gender matched. The post-SU group showed higher rates of swallow assessment (36.8 vs. 0%, p < 0.001), mobility assessment, and re-education (100 vs. 91.5%, p = 0.037). The post-SU group also showed reduced complications (28 vs. 45%, p = 0.006) and a shorter length of hospital stay (4 ± 2.16 vs. 5 ± 2.68 days, p = 0.026). The functional outcome (modified ranking scale) at 1-month showed no difference between the groups, good outcome in post-SU (39.6%) versus pre-SU (35.7%), p = 0.552. Conclusion  The implementation of this physician-based SU care model in a remote hospital in India shows improvements in quality measures, complications, and possibly patient outcomes. Thieme Medical and Scientific Publishers Pvt. Ltd. 2021-04 2021-02-22 /pmc/articles/PMC8064833/ /pubmed/33927525 http://dx.doi.org/10.1055/s-0041-1723099 Text en Association for Helping Neurosurgical Sick People. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial-License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/). https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License, which permits unrestricted reproduction and distribution, for non-commercial purposes only; and use and reproduction, but not distribution, of adapted material for non-commercial purposes only, provided the original work is properly cited.
spellingShingle John, Lydia
William, Akanksha
Dawar, Dimple
Khatter, Himani
Singh, Pratibha
Andrias, Anjana
Mochahari, Christina
Langhorne, Peter
Pandian, Jeyaraj
Implementation of a Physician-Based Stroke Unit in a Remote Hospital of North-East India-Tezpur Model
title Implementation of a Physician-Based Stroke Unit in a Remote Hospital of North-East India-Tezpur Model
title_full Implementation of a Physician-Based Stroke Unit in a Remote Hospital of North-East India-Tezpur Model
title_fullStr Implementation of a Physician-Based Stroke Unit in a Remote Hospital of North-East India-Tezpur Model
title_full_unstemmed Implementation of a Physician-Based Stroke Unit in a Remote Hospital of North-East India-Tezpur Model
title_short Implementation of a Physician-Based Stroke Unit in a Remote Hospital of North-East India-Tezpur Model
title_sort implementation of a physician-based stroke unit in a remote hospital of north-east india-tezpur model
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8064833/
https://www.ncbi.nlm.nih.gov/pubmed/33927525
http://dx.doi.org/10.1055/s-0041-1723099
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