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Effects of Telemedicine ICU Intervention on Care Standardization and Patient Outcomes: An Observational Study

OBJECTIVES: Given the numerous recent changes in ICU practices and protocols, we sought to confirm whether favorable effects of telemedicine ICU interventions on ICU mortality and length of stay can be replicated by a more recent telemedicine ICU intervention. DESIGN, SETTING AND PATIENTS: Observati...

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Autores principales: Becker, Christian D., Fusaro, Mario V., Al Aseri, Zohair, Millerman, Konstantin, Scurlock, Corey
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer Health 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7365711/
https://www.ncbi.nlm.nih.gov/pubmed/32766561
http://dx.doi.org/10.1097/CCE.0000000000000165
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author Becker, Christian D.
Fusaro, Mario V.
Al Aseri, Zohair
Millerman, Konstantin
Scurlock, Corey
author_facet Becker, Christian D.
Fusaro, Mario V.
Al Aseri, Zohair
Millerman, Konstantin
Scurlock, Corey
author_sort Becker, Christian D.
collection PubMed
description OBJECTIVES: Given the numerous recent changes in ICU practices and protocols, we sought to confirm whether favorable effects of telemedicine ICU interventions on ICU mortality and length of stay can be replicated by a more recent telemedicine ICU intervention. DESIGN, SETTING AND PATIENTS: Observational before-after telemedicine ICU intervention study in seven adult ICUs in two hospitals. The study included 1,403 patients in the preintervention period (October 2014 to September 2015) and 14,874 patients in the postintervention period (January 2016 to December 2018). INTERVENTION: Telemedicine ICU implementation. MEASUREMENTS AND MAIN RESULTS: ICU and hospital mortality and length of stay, best practice adherence rates, and telemedicine ICU performance metrics. Unadjusted ICU and hospital mortality and lengths of stay were not statistically significantly different. Adjustment for Acute Physiology and Chronic Health Evaluation Version IVa score, ICU type, and ICU admission time via logistic regression yielded significantly lower ICU and hospital mortality odds ratios of 0.58 (95% CI, 0.45–0.74) and 0.66 (95% CI, 0.54–0.80), respectively. When adjusting for acuity by comparing observed-over-expected length of stay ratios through Acute Physiology and Chronic Health Evaluation IVa methodology, we found significantly lower ICU and hospital length of stay in the postintervention group. ICU mortality improvements were driven by nighttime ICU admissions (odds ratio 0.45 [95% CI, 0.33–0.61]) as compared to daytime ICU admissions (odds ratio 0.81 [95% CI, 0.55–1.20]), whereas hospital mortality improvements were seen in both subgroups but more prominently in nighttime ICU admissions (odds ratio 0.57 [95% CI, 0.44–0.74]) as compared to daytime ICU admissions (odds ratio 0.73 [95% CI, 0.55–0.97]), suggesting that telemedicine ICU intervention can effectively supplement low intensity bedside staffing hours (nighttime). CONCLUSIONS: In this pre-post observational study, telemedicine ICU intervention was associated with improvements in care standardization and decreases in ICU and hospital mortality and length of stay. The mortality benefits were mediated in part through telemedicine ICU supplementation of low intensity bedside staffing hours.
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spelling pubmed-73657112020-08-05 Effects of Telemedicine ICU Intervention on Care Standardization and Patient Outcomes: An Observational Study Becker, Christian D. Fusaro, Mario V. Al Aseri, Zohair Millerman, Konstantin Scurlock, Corey Crit Care Explor Observational Study OBJECTIVES: Given the numerous recent changes in ICU practices and protocols, we sought to confirm whether favorable effects of telemedicine ICU interventions on ICU mortality and length of stay can be replicated by a more recent telemedicine ICU intervention. DESIGN, SETTING AND PATIENTS: Observational before-after telemedicine ICU intervention study in seven adult ICUs in two hospitals. The study included 1,403 patients in the preintervention period (October 2014 to September 2015) and 14,874 patients in the postintervention period (January 2016 to December 2018). INTERVENTION: Telemedicine ICU implementation. MEASUREMENTS AND MAIN RESULTS: ICU and hospital mortality and length of stay, best practice adherence rates, and telemedicine ICU performance metrics. Unadjusted ICU and hospital mortality and lengths of stay were not statistically significantly different. Adjustment for Acute Physiology and Chronic Health Evaluation Version IVa score, ICU type, and ICU admission time via logistic regression yielded significantly lower ICU and hospital mortality odds ratios of 0.58 (95% CI, 0.45–0.74) and 0.66 (95% CI, 0.54–0.80), respectively. When adjusting for acuity by comparing observed-over-expected length of stay ratios through Acute Physiology and Chronic Health Evaluation IVa methodology, we found significantly lower ICU and hospital length of stay in the postintervention group. ICU mortality improvements were driven by nighttime ICU admissions (odds ratio 0.45 [95% CI, 0.33–0.61]) as compared to daytime ICU admissions (odds ratio 0.81 [95% CI, 0.55–1.20]), whereas hospital mortality improvements were seen in both subgroups but more prominently in nighttime ICU admissions (odds ratio 0.57 [95% CI, 0.44–0.74]) as compared to daytime ICU admissions (odds ratio 0.73 [95% CI, 0.55–0.97]), suggesting that telemedicine ICU intervention can effectively supplement low intensity bedside staffing hours (nighttime). CONCLUSIONS: In this pre-post observational study, telemedicine ICU intervention was associated with improvements in care standardization and decreases in ICU and hospital mortality and length of stay. The mortality benefits were mediated in part through telemedicine ICU supplementation of low intensity bedside staffing hours. Wolters Kluwer Health 2020-07-15 /pmc/articles/PMC7365711/ /pubmed/32766561 http://dx.doi.org/10.1097/CCE.0000000000000165 Text en Copyright © 2020 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of the Society of Critical Care Medicine. This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND) (http://creativecommons.org/licenses/by-nc-nd/4.0/) , where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.
spellingShingle Observational Study
Becker, Christian D.
Fusaro, Mario V.
Al Aseri, Zohair
Millerman, Konstantin
Scurlock, Corey
Effects of Telemedicine ICU Intervention on Care Standardization and Patient Outcomes: An Observational Study
title Effects of Telemedicine ICU Intervention on Care Standardization and Patient Outcomes: An Observational Study
title_full Effects of Telemedicine ICU Intervention on Care Standardization and Patient Outcomes: An Observational Study
title_fullStr Effects of Telemedicine ICU Intervention on Care Standardization and Patient Outcomes: An Observational Study
title_full_unstemmed Effects of Telemedicine ICU Intervention on Care Standardization and Patient Outcomes: An Observational Study
title_short Effects of Telemedicine ICU Intervention on Care Standardization and Patient Outcomes: An Observational Study
title_sort effects of telemedicine icu intervention on care standardization and patient outcomes: an observational study
topic Observational Study
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7365711/
https://www.ncbi.nlm.nih.gov/pubmed/32766561
http://dx.doi.org/10.1097/CCE.0000000000000165
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