Ambulance demand: random events or predicable patterns?

Research output: Contribution to journalArticleResearchpeer-review

8 Citations (Scopus)

Abstract

Background: Occupational, social and recreational routines follow temporal patterns, as does the onset of certain acute medical diseases and injuries. It is not known if the temporal nature of injury and disease transfers into patterns that can be observed in ambulance demand. This review examines eligible study findings that reported temporal (time of day, day of week and seasonal) patterns in ambulance demand. Methods: Electronic searches of Medline and Cumulative Index of Nursing and Allied Health Literature were conducted for papers published between 1980 and 2011. In addition, hand searching was conducted for unpublished government and ambulance service documents and reports for the same period. Results: 38 studies examined temporal patterns in ambulance demand. Six studies reported trends in overall workload and 32 studies reported trends in a subset of ambulance demand, either as a specific case type or demographic group. Temporal patterns in overall demand were consistent between jurisdictions for time of day but varied for day of week and season. When analysed by case type, all jurisdictions reported similar time of day patterns, most jurisdictions had similar day of week patterns except for out-of-hospital cardiac arrest and similar seasonal patterns, except for trauma. Temporal patterns in case types were influenced by age and gender. Conclusions: Temporal patterns are present in ambulance demand and importantly these populations are distinct from those found in hospital datasets suggesting that variation in ambulance demand should not be inferred from hospital data alone. Case types seem to have similar temporal patterns across jurisdictions; thus, research where demand is broken down into case types would be generalisable to many ambulance services. This type of research can lead to improvements in ambulance service deliverables.
Original languageEnglish
Pages (from-to)883 - 887
Number of pages5
JournalEmergency Medicine Journal
Volume30
Issue number11
DOIs
Publication statusPublished - 2013

Cite this

@article{4b1f9fb9acdc48549a6ea4ffaa501d33,
title = "Ambulance demand: random events or predicable patterns?",
abstract = "Background: Occupational, social and recreational routines follow temporal patterns, as does the onset of certain acute medical diseases and injuries. It is not known if the temporal nature of injury and disease transfers into patterns that can be observed in ambulance demand. This review examines eligible study findings that reported temporal (time of day, day of week and seasonal) patterns in ambulance demand. Methods: Electronic searches of Medline and Cumulative Index of Nursing and Allied Health Literature were conducted for papers published between 1980 and 2011. In addition, hand searching was conducted for unpublished government and ambulance service documents and reports for the same period. Results: 38 studies examined temporal patterns in ambulance demand. Six studies reported trends in overall workload and 32 studies reported trends in a subset of ambulance demand, either as a specific case type or demographic group. Temporal patterns in overall demand were consistent between jurisdictions for time of day but varied for day of week and season. When analysed by case type, all jurisdictions reported similar time of day patterns, most jurisdictions had similar day of week patterns except for out-of-hospital cardiac arrest and similar seasonal patterns, except for trauma. Temporal patterns in case types were influenced by age and gender. Conclusions: Temporal patterns are present in ambulance demand and importantly these populations are distinct from those found in hospital datasets suggesting that variation in ambulance demand should not be inferred from hospital data alone. Case types seem to have similar temporal patterns across jurisdictions; thus, research where demand is broken down into case types would be generalisable to many ambulance services. This type of research can lead to improvements in ambulance service deliverables.",
author = "Cantwell, {Katharine Sophia} and Paul Dietze and Morgans, {Amee Elizabeth} and Smith, {Karen Louise}",
year = "2013",
doi = "10.1136/emermed-2012-201852",
language = "English",
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pages = "883 -- 887",
journal = "Emergency Medicine Journal",
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publisher = "BMJ Publishing Group Ltd",
number = "11",

}

Ambulance demand: random events or predicable patterns? / Cantwell, Katharine Sophia; Dietze, Paul; Morgans, Amee Elizabeth; Smith, Karen Louise.

In: Emergency Medicine Journal, Vol. 30, No. 11, 2013, p. 883 - 887.

Research output: Contribution to journalArticleResearchpeer-review

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AU - Dietze, Paul

AU - Morgans, Amee Elizabeth

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AB - Background: Occupational, social and recreational routines follow temporal patterns, as does the onset of certain acute medical diseases and injuries. It is not known if the temporal nature of injury and disease transfers into patterns that can be observed in ambulance demand. This review examines eligible study findings that reported temporal (time of day, day of week and seasonal) patterns in ambulance demand. Methods: Electronic searches of Medline and Cumulative Index of Nursing and Allied Health Literature were conducted for papers published between 1980 and 2011. In addition, hand searching was conducted for unpublished government and ambulance service documents and reports for the same period. Results: 38 studies examined temporal patterns in ambulance demand. Six studies reported trends in overall workload and 32 studies reported trends in a subset of ambulance demand, either as a specific case type or demographic group. Temporal patterns in overall demand were consistent between jurisdictions for time of day but varied for day of week and season. When analysed by case type, all jurisdictions reported similar time of day patterns, most jurisdictions had similar day of week patterns except for out-of-hospital cardiac arrest and similar seasonal patterns, except for trauma. Temporal patterns in case types were influenced by age and gender. Conclusions: Temporal patterns are present in ambulance demand and importantly these populations are distinct from those found in hospital datasets suggesting that variation in ambulance demand should not be inferred from hospital data alone. Case types seem to have similar temporal patterns across jurisdictions; thus, research where demand is broken down into case types would be generalisable to many ambulance services. This type of research can lead to improvements in ambulance service deliverables.

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