Anatomy of a demand shock: Quantitative analysis of crowding in hospital emergency departments in Victoria, Australia during the 2009 influenza pandemic
Identifieur interne : 000379 ( Main/Exploration ); précédent : 000378; suivant : 000380Anatomy of a demand shock: Quantitative analysis of crowding in hospital emergency departments in Victoria, Australia during the 2009 influenza pandemic
Auteurs : Peter Sivey [Australie] ; Richard Mcallister [Australie] ; Hassan Vally [Australie] ; Anna Burgess [Australie] ; Anne-Maree Kelly [Australie]Source :
- PLoS ONE [ 1932-6203 ] ; 2019.
Descripteurs français
- KwdFr :
- Besoins et demandes de services de santé (), Charge de travail (), Durée du séjour (), Facteurs temps, Flambées de maladies (), Grippe humaine (), Grippe humaine (diagnostic), Grippe humaine (épidémiologie), Hospitalisation (), Humains, Impressions de foule, Pandémies (), Service hospitalier d'urgences ().
- MESH :
English descriptors
- KwdEn :
- Crowding, Disease Outbreaks (statistics & numerical data), Emergency Service, Hospital (statistics & numerical data), Health Services Needs and Demand (statistics & numerical data), Hospitalization (statistics & numerical data), Humans, Influenza, Human (diagnosis), Influenza, Human (epidemiology), Influenza, Human (therapy), Length of Stay (statistics & numerical data), Pandemics (statistics & numerical data), Time Factors, Workload (statistics & numerical data).
- MESH :
- diagnosis : Influenza, Human.
- epidemiology : Influenza, Human.
- statistics & numerical data : Disease Outbreaks, Emergency Service, Hospital, Health Services Needs and Demand, Hospitalization, Length of Stay, Pandemics, Workload.
- therapy : Influenza, Human.
- Crowding, Humans, Time Factors.
Abstract
An infectious disease outbreak such as the 2009 influenza pandemic is an unexpected demand shock to hospital emergency departments (EDs). We analysed changes in key performance metrics in (EDs) in Victoria during this pandemic to assess the impact of this demand shock.
Descriptive time-series analysis and longitudinal regression analysis of data from the Victorian Emergency Minimum Dataset (VEMD) using data from the 38 EDs that submit data to the state’s Department of Health and Human Services.
Daily number of presentations, influenza-like-illness (ILI) presentations, daily mean waiting time (time to first being seen by a doctor), daily number of patients who did-not-wait and daily number of access-blocked patients (admitted patients with length of stay >8 hours) at a system and hospital-level.
During the influenza pandemic, mean waiting time increased by up to 25%, access block increased by 32% and did not wait presentations increased by 69% above pre-pandemic levels. The peaks of all three crowding variables corresponded approximately to the peak in admitted ILI presentations. Longitudinal fixed-effects regression analysis estimated positive and statistically significant associations between mean waiting times, did not wait presentations and access block and ILI presentations.
This pandemic event caused excess demand leading to increased waiting times, did-not-wait patients and access block. Increases in admitted patients were more strongly associated with crowding than non-admitted patients during the pandemic period, so policies to divert or mitigate low-complexity non-admitted patients are unlikely to be effective in reducing ED crowding.
Url:
DOI: 10.1371/journal.pone.0222851
PubMed: 31550288
PubMed Central: 6759189
Affiliations:
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pandemic</title><author><name sortKey="Sivey, Peter" sort="Sivey, Peter" uniqKey="Sivey P" first="Peter" last="Sivey">Peter Sivey</name><affiliation wicri:level="1"><nlm:aff id="aff001"><addr-line>School of Economics, Finance and Marketing, RMIT University, Melbourne, Victoria, Australia</addr-line></nlm:aff><country xml:lang="fr">Australie</country><wicri:regionArea>School of Economics, Finance and Marketing, RMIT University, Melbourne, Victoria</wicri:regionArea><wicri:noRegion>Victoria</wicri:noRegion></affiliation></author><author><name sortKey="Mcallister, Richard" sort="Mcallister, Richard" uniqKey="Mcallister R" first="Richard" last="Mcallister">Richard Mcallister</name><affiliation wicri:level="1"><nlm:aff id="aff002"><addr-line>Department of Education and Training, Australian Government, Canberra, ACT, Australia</addr-line></nlm:aff><country xml:lang="fr">Australie</country><wicri:regionArea>Department of Education and Training, Australian Government, Canberra, ACT</wicri:regionArea><wicri:noRegion>ACT</wicri:noRegion></affiliation></author><author><name sortKey="Vally, Hassan" sort="Vally, Hassan" uniqKey="Vally H" first="Hassan" last="Vally">Hassan Vally</name><affiliation wicri:level="1"><nlm:aff id="aff003"><addr-line>Department of Public Health, La Trobe University, Melbourne, Victoria, Australia</addr-line></nlm:aff><country xml:lang="fr">Australie</country><wicri:regionArea>Department of Public Health, La Trobe University, Melbourne, Victoria</wicri:regionArea><wicri:noRegion>Victoria</wicri:noRegion></affiliation></author><author><name sortKey="Burgess, Anna" sort="Burgess, Anna" uniqKey="Burgess A" first="Anna" last="Burgess">Anna Burgess</name><affiliation wicri:level="1"><nlm:aff id="aff004"><addr-line>Department of Health and Human Services (Victoria), Melbourne, Victoria, Australia</addr-line></nlm:aff><country xml:lang="fr">Australie</country><wicri:regionArea>Department of Health and Human Services (Victoria), Melbourne, Victoria</wicri:regionArea><wicri:noRegion>Victoria</wicri:noRegion></affiliation></author><author><name sortKey="Kelly, Anne Maree" sort="Kelly, Anne Maree" uniqKey="Kelly A" first="Anne-Maree" last="Kelly">Anne-Maree Kelly</name><affiliation wicri:level="4"><nlm:aff id="aff005"><addr-line>Joseph Epstein Centre for Emergency Medicine Research at Western Health and School of Medicine-Western Clinical School, The University of Melbourne, Parkville, Victoria, Australia</addr-line></nlm:aff><country xml:lang="fr">Australie</country><wicri:regionArea>Joseph Epstein Centre for Emergency Medicine Research at Western Health and School of Medicine-Western Clinical School, The University of Melbourne, Parkville, Victoria</wicri:regionArea><orgName type="university">Université de Melbourne</orgName><placeName><settlement type="city">Melbourne</settlement><region type="état">Victoria (État)</region></placeName></affiliation></author></analytic><series><title level="j">PLoS ONE</title><idno type="eISSN">1932-6203</idno><imprint><date when="2019">2019</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Crowding</term><term>Disease Outbreaks (statistics & numerical data)</term><term>Emergency Service, Hospital (statistics & numerical data)</term><term>Health Services Needs and Demand (statistics & numerical data)</term><term>Hospitalization (statistics & numerical data)</term><term>Humans</term><term>Influenza, Human (diagnosis)</term><term>Influenza, Human (epidemiology)</term><term>Influenza, Human (therapy)</term><term>Length of Stay (statistics & numerical data)</term><term>Pandemics (statistics & numerical data)</term><term>Time Factors</term><term>Workload (statistics & numerical data)</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Besoins et demandes de services de santé ()</term><term>Charge de travail ()</term><term>Durée du séjour ()</term><term>Facteurs temps</term><term>Flambées de maladies ()</term><term>Grippe humaine ()</term><term>Grippe humaine (diagnostic)</term><term>Grippe humaine (épidémiologie)</term><term>Hospitalisation ()</term><term>Humains</term><term>Impressions de foule</term><term>Pandémies ()</term><term>Service hospitalier d'urgences ()</term></keywords><keywords scheme="MESH" qualifier="diagnosis" xml:lang="en"><term>Influenza, Human</term></keywords><keywords scheme="MESH" qualifier="diagnostic" xml:lang="fr"><term>Grippe humaine</term></keywords><keywords scheme="MESH" qualifier="epidemiology" xml:lang="en"><term>Influenza, Human</term></keywords><keywords scheme="MESH" qualifier="statistics & numerical data" xml:lang="en"><term>Disease Outbreaks</term><term>Emergency Service, Hospital</term><term>Health Services Needs and Demand</term><term>Hospitalization</term><term>Length of Stay</term><term>Pandemics</term><term>Workload</term></keywords><keywords scheme="MESH" qualifier="therapy" xml:lang="en"><term>Influenza, Human</term></keywords><keywords scheme="MESH" qualifier="épidémiologie" xml:lang="fr"><term>Grippe humaine</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Crowding</term><term>Humans</term><term>Time Factors</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Besoins et demandes de services de santé</term><term>Charge de travail</term><term>Durée du séjour</term><term>Facteurs temps</term><term>Flambées de maladies</term><term>Grippe humaine</term><term>Hospitalisation</term><term>Humains</term><term>Impressions de foule</term><term>Pandémies</term><term>Service hospitalier d'urgences</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><sec id="sec001"><title>Objective</title><p>An infectious disease outbreak such as the 2009 influenza pandemic is an unexpected demand shock to hospital emergency departments (EDs). We analysed changes in key performance metrics in (EDs) in Victoria during this pandemic to assess the impact of this demand shock.</p></sec><sec id="sec002"><title>Design and setting</title><p>Descriptive time-series analysis and longitudinal regression analysis of data from the Victorian Emergency Minimum Dataset (VEMD) using data from the 38 EDs that submit data to the state’s Department of Health and Human Services.</p></sec><sec id="sec003"><title>Main outcome measures</title><p>Daily number of presentations, influenza-like-illness (ILI) presentations, daily mean waiting time (time to first being seen by a doctor), daily number of patients who did-not-wait and daily number of access-blocked patients (admitted patients with length of stay >8 hours) at a system and hospital-level.</p></sec><sec id="sec004"><title>Results</title><p>During the influenza pandemic, mean waiting time increased by up to 25%, access block increased by 32% and did not wait presentations increased by 69% above pre-pandemic levels. The peaks of all three crowding variables corresponded approximately to the peak in admitted ILI presentations. Longitudinal fixed-effects regression analysis estimated positive and statistically significant associations between mean waiting times, did not wait presentations and access block and ILI presentations.</p></sec><sec id="sec005"><title>Conclusions</title><p>This pandemic event caused excess demand leading to increased waiting times, did-not-wait patients and access block. Increases in admitted patients were more strongly associated with crowding than non-admitted patients during the pandemic period, so policies to divert or mitigate low-complexity non-admitted patients are unlikely to be effective in reducing ED crowding.</p></sec></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Schull, M J" uniqKey="Schull M">M.J. Schull</name></author><author><name sortKey="Mamdani, M M" uniqKey="Mamdani M">M.M. 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Guttmann</name></author></analytic></biblStruct></listBibl></div1></back></TEI><affiliations><list><country><li>Australie</li></country><region><li>Victoria (État)</li></region><settlement><li>Melbourne</li></settlement><orgName><li>Université de Melbourne</li></orgName></list><tree><country name="Australie"><noRegion><name sortKey="Sivey, Peter" sort="Sivey, Peter" uniqKey="Sivey P" first="Peter" last="Sivey">Peter Sivey</name></noRegion><name sortKey="Burgess, Anna" sort="Burgess, Anna" uniqKey="Burgess A" first="Anna" last="Burgess">Anna Burgess</name><name sortKey="Kelly, Anne Maree" sort="Kelly, Anne Maree" uniqKey="Kelly A" first="Anne-Maree" last="Kelly">Anne-Maree Kelly</name><name sortKey="Mcallister, Richard" sort="Mcallister, Richard" uniqKey="Mcallister R" first="Richard" last="Mcallister">Richard Mcallister</name><name sortKey="Vally, Hassan" sort="Vally, Hassan" uniqKey="Vally H" first="Hassan" last="Vally">Hassan Vally</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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