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Modelling Granular Process Flow Information to Reduce Bottlenecks in the Emergency Department

Increasing demand and changing case-mix have resulted in bottlenecks and longer waiting times in emergency departments (ED). However, many process improvement efforts addressing the bottlenecks have limitations, as they lack accurate models of the real system as input accounting for operational comp...

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Autores principales: Amissah, Marian, Lahiri, Sudakshina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9140672/
https://www.ncbi.nlm.nih.gov/pubmed/35628079
http://dx.doi.org/10.3390/healthcare10050942
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author Amissah, Marian
Lahiri, Sudakshina
author_facet Amissah, Marian
Lahiri, Sudakshina
author_sort Amissah, Marian
collection PubMed
description Increasing demand and changing case-mix have resulted in bottlenecks and longer waiting times in emergency departments (ED). However, many process improvement efforts addressing the bottlenecks have limitations, as they lack accurate models of the real system as input accounting for operational complexities. To understand the limitations, this research modelled granular procedural information, to analyse processes in a Level-1 ED of a 1200-bed teaching hospital in the UK. Semi-structured interviews with 21 clinicians and direct observations provided the necessary information. Results identified Majors as the most crowded area, hence, a systems modelling technique, role activity diagram, was used to derive highly granular process maps illustrating care in Majors which were further validated by 6 additional clinicians. Bottlenecks observed in Majors included awaiting specialist input, tests outside the ED, awaiting transportation, bed search, and inpatient handover. Process mapping revealed opportunities for using precedence information to reduce repeat tests; informed alerting; and provisioning for operational complexity into ED processes as steps to potentially alleviate bottlenecks. Another result is that this is the first study to map care processes in Majors, the area within the ED that treats complex patients whose care journeys are susceptible to variations. Findings have implications on the development of improvement approaches for managing bottlenecks.
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spelling pubmed-91406722022-05-28 Modelling Granular Process Flow Information to Reduce Bottlenecks in the Emergency Department Amissah, Marian Lahiri, Sudakshina Healthcare (Basel) Article Increasing demand and changing case-mix have resulted in bottlenecks and longer waiting times in emergency departments (ED). However, many process improvement efforts addressing the bottlenecks have limitations, as they lack accurate models of the real system as input accounting for operational complexities. To understand the limitations, this research modelled granular procedural information, to analyse processes in a Level-1 ED of a 1200-bed teaching hospital in the UK. Semi-structured interviews with 21 clinicians and direct observations provided the necessary information. Results identified Majors as the most crowded area, hence, a systems modelling technique, role activity diagram, was used to derive highly granular process maps illustrating care in Majors which were further validated by 6 additional clinicians. Bottlenecks observed in Majors included awaiting specialist input, tests outside the ED, awaiting transportation, bed search, and inpatient handover. Process mapping revealed opportunities for using precedence information to reduce repeat tests; informed alerting; and provisioning for operational complexity into ED processes as steps to potentially alleviate bottlenecks. Another result is that this is the first study to map care processes in Majors, the area within the ED that treats complex patients whose care journeys are susceptible to variations. Findings have implications on the development of improvement approaches for managing bottlenecks. MDPI 2022-05-19 /pmc/articles/PMC9140672/ /pubmed/35628079 http://dx.doi.org/10.3390/healthcare10050942 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Amissah, Marian
Lahiri, Sudakshina
Modelling Granular Process Flow Information to Reduce Bottlenecks in the Emergency Department
title Modelling Granular Process Flow Information to Reduce Bottlenecks in the Emergency Department
title_full Modelling Granular Process Flow Information to Reduce Bottlenecks in the Emergency Department
title_fullStr Modelling Granular Process Flow Information to Reduce Bottlenecks in the Emergency Department
title_full_unstemmed Modelling Granular Process Flow Information to Reduce Bottlenecks in the Emergency Department
title_short Modelling Granular Process Flow Information to Reduce Bottlenecks in the Emergency Department
title_sort modelling granular process flow information to reduce bottlenecks in the emergency department
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9140672/
https://www.ncbi.nlm.nih.gov/pubmed/35628079
http://dx.doi.org/10.3390/healthcare10050942
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