Emergency department crowding in Singapore: Insights from a systems thinking approach.

Published

Journal Article

Emergency Department crowding is a serious and international health care problem that seems to be resistant to most well intended but often reductionist policy approaches. In this study, we examine Emergency Department crowding in Singapore from a systems thinking perspective using causal loop diagramming to visualize the systemic structure underlying this complex phenomenon. Furthermore, we evaluate the relative impact of three different policies in reducing Emergency Department crowding in Singapore: introduction of geriatric emergency medicine, expansion of emergency medicine training, and implementation of enhanced primary care.The construction of the qualitative causal loop diagram is based on consultations with Emergency Department experts, direct observation, and a thorough literature review. For the purpose of policy analysis, a novel approach, the path analysis, is applied.The path analysis revealed that both the introduction of geriatric emergency medicine and the expansion of emergency medicine training may be associated with undesirable consequences contributing to Emergency Department crowding. In contrast, enhancing primary care was found to be germane in reducing Emergency Department crowding; in addition, it has apparently no negative side effects, considering the boundary of the model created.Causal loop diagramming was a powerful tool for eliciting the systemic structure of Emergency Department crowding in Singapore. Additionally, the developed model was valuable in testing different policy options.

Full Text

Duke Authors

Cited Authors

  • Schoenenberger, LK; Bayer, S; Ansah, JP; Matchar, DB; Mohanavalli, RL; Lam, SS; Ong, ME

Published Date

  • January 2016

Published In

Volume / Issue

  • 4 /

Start / End Page

  • 2050312116671953 -

PubMed ID

  • 27757231

Pubmed Central ID

  • 27757231

Electronic International Standard Serial Number (EISSN)

  • 2050-3121

International Standard Serial Number (ISSN)

  • 2050-3121

Digital Object Identifier (DOI)

  • 10.1177/2050312116671953

Language

  • eng