Background Overcrowding occurs when the identified need for emergency services outweighs the available resources in the emergency department (ED). Literature shows that ED overcrowding impacts the overall quality of the entire hospital production system, as confirmed by the recent COVID-19 pandemic. This study aims to identify the most relevant variables that cause ED overcrowding using the input-process-output model with the aim of providing managers and policy makers with useful hints for how to effectively redesign ED operations. Methods A mixed-method approach is used, blending qualitative inquiry with quantitative investigation in order to: i) identifying and operationalizing the main components of the model that can be addressed by hospital operation management teams and ii) testing and measuring how these components can influence ED LOS. Results With a dashboard of indicators developed following the input-process-output model, the analysis identifies the most significant variables that have an impact on ED overcrowding: the type (age and complexity) and volume of patients (input), the actual ED structural capacity (in terms of both people and technology) and the ED physician-to-nurse ratio (process), and the hospital discharging process (output). Conclusions The present paper represents an original contribution regarding two different aspects. First, this study combines different research methodologies with the aim of capturing relevant information that by relying on just one research method, may otherwise be missed. Second, this study adopts a hospitalwide approach, adding to our understanding of ED overcrowding, which has thus far focused mainly on single aspects of ED operations.

Operations management solutions to improve ED patient flows: evidence from the Italian NHS / M. Marsilio, E.T. Roldan, L. Salmasi, S. Villa. - In: BMC HEALTH SERVICES RESEARCH. - ISSN 1472-6963. - 22:1(2022 Jul 30), pp. 974.1-974.14. [10.1186/s12913-022-08339-x]

Operations management solutions to improve ED patient flows: evidence from the Italian NHS

M. Marsilio
Primo
;
2022-07-30

Abstract

Background Overcrowding occurs when the identified need for emergency services outweighs the available resources in the emergency department (ED). Literature shows that ED overcrowding impacts the overall quality of the entire hospital production system, as confirmed by the recent COVID-19 pandemic. This study aims to identify the most relevant variables that cause ED overcrowding using the input-process-output model with the aim of providing managers and policy makers with useful hints for how to effectively redesign ED operations. Methods A mixed-method approach is used, blending qualitative inquiry with quantitative investigation in order to: i) identifying and operationalizing the main components of the model that can be addressed by hospital operation management teams and ii) testing and measuring how these components can influence ED LOS. Results With a dashboard of indicators developed following the input-process-output model, the analysis identifies the most significant variables that have an impact on ED overcrowding: the type (age and complexity) and volume of patients (input), the actual ED structural capacity (in terms of both people and technology) and the ED physician-to-nurse ratio (process), and the hospital discharging process (output). Conclusions The present paper represents an original contribution regarding two different aspects. First, this study combines different research methodologies with the aim of capturing relevant information that by relying on just one research method, may otherwise be missed. Second, this study adopts a hospitalwide approach, adding to our understanding of ED overcrowding, which has thus far focused mainly on single aspects of ED operations.
Emergency department; Healthcare operations management; Length of stay (LOS); Patient flow logistics; COVID-19; Emergency Service, Hospital; Humans; Length of Stay; Patient Discharge; Crowding; Pandemics;
Settore SECS-P/07 - Economia Aziendale
https://bmchealthservres.biomedcentral.com/articles/10.1186/s12913-022-08339-x
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2434/938087
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