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Impact of Care Initiation Model on Emergency Department Orders and Operational Metrics: Cohort Study

INTRODUCTION: Emergency departments (ED) employ many strategies to address crowding and prolonged wait times. They include front-end Care Initiation and clinician-in-triage models that start the diagnostic and therapeutic process while the patient waits for a care space in the ED. The objective of t...

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Autores principales: Lee, Andy Hung-Yi, Cash, Rebecca E., Bukhman, Alice, Im, Dana, Baymon, Damarcus, Sanchez, Leon D., Chen, Paul C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Department of Emergency Medicine, University of California, Irvine School of Medicine 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10393454/
https://www.ncbi.nlm.nih.gov/pubmed/37527374
http://dx.doi.org/10.5811/westjem.59340
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author Lee, Andy Hung-Yi
Cash, Rebecca E.
Bukhman, Alice
Im, Dana
Baymon, Damarcus
Sanchez, Leon D.
Chen, Paul C.
author_facet Lee, Andy Hung-Yi
Cash, Rebecca E.
Bukhman, Alice
Im, Dana
Baymon, Damarcus
Sanchez, Leon D.
Chen, Paul C.
author_sort Lee, Andy Hung-Yi
collection PubMed
description INTRODUCTION: Emergency departments (ED) employ many strategies to address crowding and prolonged wait times. They include front-end Care Initiation and clinician-in-triage models that start the diagnostic and therapeutic process while the patient waits for a care space in the ED. The objective of this study was to quantify the impact of a Care Initiation model on resource utilization and operational metrics in the ED. METHODS: We performed a retrospective analysis of ED visits at our institution during October 2021. Baseline characteristics were compared with Chi-square and quantile regression. We used t-tests to calculate unadjusted difference in outcome measures, including number of laboratory tests ordered and average time patients spent in the waiting room and the ED treatment room, and the time from arrival until ED disposition. We performed propensity score analysis using matching and inverse probability weighting to quantify the direct impact of Care Initiation on outcome measures. RESULTS: There were 2,407 ED patient encounters, 1,191 (49%) of whom arrived during the hours when Care Initiation was active. A total of 811 (68%) of these patients underwent Care Initiation, while the remainder proceeded directly to the main treatment area. Patients were more likely to undergo Care Initiation if they had lower acuity and lower risk of admission, and if the ED was busier as measured by the number of recent arrivals and percentage of occupied ED beds. After adjusting for patient-specific and department-level covariates, Care Initiation did not increase the number of diagnostic laboratory tests ordered. Care Initiation was associated with increased waiting room time by 1.8 hours and longer time from arrival until disposition by 1.3 hours, but with decreased time in the main treatment area by 0.6 hours, which represents a 15% reduction. CONCLUSION: Care Initiation was associated with a 15% reduction in time spent in the main ED treatment area but longer waiting room time and longer time until ED disposition without significantly increasing the number of laboratory studies ordered. While previous studies produced similar results with Care Initiation models accessing all diagnostic modalities including imaging, our study demonstrates that a more limited Care Initiation model can still result in operational benefits for EDs.
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spelling pubmed-103934542023-08-02 Impact of Care Initiation Model on Emergency Department Orders and Operational Metrics: Cohort Study Lee, Andy Hung-Yi Cash, Rebecca E. Bukhman, Alice Im, Dana Baymon, Damarcus Sanchez, Leon D. Chen, Paul C. West J Emerg Med ED Operations INTRODUCTION: Emergency departments (ED) employ many strategies to address crowding and prolonged wait times. They include front-end Care Initiation and clinician-in-triage models that start the diagnostic and therapeutic process while the patient waits for a care space in the ED. The objective of this study was to quantify the impact of a Care Initiation model on resource utilization and operational metrics in the ED. METHODS: We performed a retrospective analysis of ED visits at our institution during October 2021. Baseline characteristics were compared with Chi-square and quantile regression. We used t-tests to calculate unadjusted difference in outcome measures, including number of laboratory tests ordered and average time patients spent in the waiting room and the ED treatment room, and the time from arrival until ED disposition. We performed propensity score analysis using matching and inverse probability weighting to quantify the direct impact of Care Initiation on outcome measures. RESULTS: There were 2,407 ED patient encounters, 1,191 (49%) of whom arrived during the hours when Care Initiation was active. A total of 811 (68%) of these patients underwent Care Initiation, while the remainder proceeded directly to the main treatment area. Patients were more likely to undergo Care Initiation if they had lower acuity and lower risk of admission, and if the ED was busier as measured by the number of recent arrivals and percentage of occupied ED beds. After adjusting for patient-specific and department-level covariates, Care Initiation did not increase the number of diagnostic laboratory tests ordered. Care Initiation was associated with increased waiting room time by 1.8 hours and longer time from arrival until disposition by 1.3 hours, but with decreased time in the main treatment area by 0.6 hours, which represents a 15% reduction. CONCLUSION: Care Initiation was associated with a 15% reduction in time spent in the main ED treatment area but longer waiting room time and longer time until ED disposition without significantly increasing the number of laboratory studies ordered. While previous studies produced similar results with Care Initiation models accessing all diagnostic modalities including imaging, our study demonstrates that a more limited Care Initiation model can still result in operational benefits for EDs. Department of Emergency Medicine, University of California, Irvine School of Medicine 2023-07 2023-07-12 /pmc/articles/PMC10393454/ /pubmed/37527374 http://dx.doi.org/10.5811/westjem.59340 Text en © 2023 Lee et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) License. See: http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/)
spellingShingle ED Operations
Lee, Andy Hung-Yi
Cash, Rebecca E.
Bukhman, Alice
Im, Dana
Baymon, Damarcus
Sanchez, Leon D.
Chen, Paul C.
Impact of Care Initiation Model on Emergency Department Orders and Operational Metrics: Cohort Study
title Impact of Care Initiation Model on Emergency Department Orders and Operational Metrics: Cohort Study
title_full Impact of Care Initiation Model on Emergency Department Orders and Operational Metrics: Cohort Study
title_fullStr Impact of Care Initiation Model on Emergency Department Orders and Operational Metrics: Cohort Study
title_full_unstemmed Impact of Care Initiation Model on Emergency Department Orders and Operational Metrics: Cohort Study
title_short Impact of Care Initiation Model on Emergency Department Orders and Operational Metrics: Cohort Study
title_sort impact of care initiation model on emergency department orders and operational metrics: cohort study
topic ED Operations
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10393454/
https://www.ncbi.nlm.nih.gov/pubmed/37527374
http://dx.doi.org/10.5811/westjem.59340
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