Dataset Information

How much emergency department use by vulnerable populations is potentially preventable?: A period prevalence study of linked public hospital data in South Australia.

ABSTRACT:

Objectives

To quantify emergency department (ED) presentations by individuals within vulnerable populations compared with other adults and the extent to which these are potentially preventable.

Design

Period prevalence study from 2005-2006 to 2010-2011.

Setting

Person-linked, ED administrative records for public hospitals in South Australia.

Participants

Adults aged 20 or more in South Australia's metropolitan area presenting to ED and categorised as Refugee and Asylum Seeker Countries of birth (RASC); Aboriginal; those aged 75 years or more; or All others.

Main outcome measures

Unadjusted rates of ambulatory care sensitive condition (ACSC), general practitioner (GP)-type presentations and associated direct ED costs among mutually exclusive groups of individuals.

Results

Disparity between RASC and All others was greatest for GP-type presentations (423.7 and 240.1 persons per 1000 population, respectively) with excess costs of $A106?573 (95% CI $A98 775 to $A114 371) per 1000 population. Aboriginal had highest acute ACSC presenter rates (125.8 against 51.6 per 1000 population) with twice the risk of multiple presentations and $A108?701 (95% CI $A374 to $A123?029) per 1000 excess costs. Those aged 75 or more had highest chronic ACSC presenter rates (119.7vs21.1 per 1000), threefold risk of further presentations (incidence rate ratio 3.20, 95% CI 3.14 to 3.26) and excess cost of $A385 (95% CI $A178?160 to $A184?609) per 1000 population.

Conclusions

Vulnerable groups had excess ED presentations for a range of issues potentially better addressed through primary and community healthcare. The observed differences suggest inequities in the uptake of effective primary and community care and represent a source of excess cost to the public hospital system.

SUBMITTER: Banham D

PROVIDER: S-EPMC6340627 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Publications

How much emergency department use by vulnerable populations is potentially preventable?: A period prevalence study of linked public hospital data in South Australia.

Banham David D Karnon Jonathan J Densley Kirsten K Lynch John W JW

BMJ open 20190117 1

<h4>Objectives</h4>To quantify emergency department (ED) presentations by individuals within vulnerable populations compared with other adults and the extent to which these are potentially preventable.<h4>Design</h4>Period prevalence study from 2005-2006 to 2010-2011.<h4>Setting</h4>Person-linked, ED administrative records for public hospitals in South Australia.<h4>Participants</h4>Adults aged 20 or more in South Australia's metropolitan area presenting to ED and categorised as Refugee and Asyl ...[more]

PMID: 30782688

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Project description:IntroductionPrevention quality indicators (PQI) are a set of measures used to characterize healthcare utilization for conditions identified as being potentially preventable with high quality ambulatory care. These indicators have recently been adapted for emergency department (ED) patient presentations. In this study the authors sought to identify opportunities to potentially prevent emergency conditions and to strengthen systems of ambulatory care by analyzing patterns of ED utilization for PQI conditions.MethodsUsing multivariable logistic regression, the authors analyzed the relationship of patient demographics and neighborhood-level socioeconomic indicators with ED utilization for PQI conditions based on ED visits at an urban, academic medical center in 2017. We also used multilevel modeling to assess the contribution of these variables to neighborhood-level variation in the likelihood of an ED visit for a PQI condition.ResultsOf the included 98,522 visits, 17.5% were categorized as potentially preventable based on the ED PQI definition. On multivariate analysis, age < 18 years, Black race, and Medicare insurance had the strongest positive associations with PQI visits, with adjusted odds ratios (aOR) of 1.41 (95% confidence interval [CI], 1.29, 1.56), 1.40 (95% CI, 1.22, 1.61), and 1.40 (95% CI, 1.28, 1.54), respectively. All included neighborhood-level socioeconomic variables were significantly associated with PQI visit likelihood on univariable analysis; however; only level of education attainment and private car ownership remained significantly associated in the multivariable model, with aOR of 1.13 (95% CI, 1.10, 1.17) and 0.96 (95% CI, 0.93, 0.99) per quartile increase, respectively. This multilevel model demonstrated significant variation in PQI visit likelihood attributable to neighborhood, with interclass correlation decreasing from 5.92% (95% CI, 5.20, 6.73) in our unadjusted model to 4.12% (95% CI, 3.47, 4.87) in our fully adjusted model and median OR similarly decreasing from 1.54 to 1.43.ConclusionDemographic and local socioeconomic factors were significantly associated with ED utilization for PQI conditions. Future public health efforts can bolster efforts to target underlying social drivers of health and support access to primary care for patients who are Black, Latino, pediatric, or Medicare-dependent to potentially prevent emergency conditions (and the need for emergency care). Further research is needed to explore other factors beyond demographics and socioeconomic characteristics driving spatial variation in ED PQI visit likelihood.

Project description:IntroductionOntario ambulances are restricted from patient transportation to sub-acute levels of care when these facilities may be more suitable than emergency departments for non-emergent conditions. There is no known patient classification specifically constructed to inform ED diversion protocols and guidance for sub-acute centre transportation for primary care-like patient conditions.ObjectiveTo construct a novel patient classification of potentially preventable emergency department visits following transport by ambulance, and analyse patient-level characteristic associations with this classification based in Ontario secondary data.Methods and analysisThe Primary Care-like Ambulance transports following Response for 911-Emergencies (PriCARE) patient classification will be constructed using a two-phase RAND/UCLA modified Delphi design. All experts included are physicians with relevant experience in emergency and/or primary care in Ontario. The first phase of the study will determine consensus of the expert committee on which ED interventions performed on patients with non-emergent acuities could be conducted in sub-acute healthcare centres. The second phase will assess consensus of which patient, hospital and acuity factors are most appropriate to be incorporated into a PriCARE classification. We will also investigate secondary outcomes on consensus of which ED interventions could be transferred to a paramedic context given an expanded scope of practice and patient-level characteristics of PriCARE classified individuals.Ethics and disseminationThis study received a research ethics board exemption waiver from the Hamilton Integrated Research Ethics Board; review reference 2020-11451-GRA. Results will be submitted for publication in a peer-reviewed journal and presented at relevant conferences. The results will be shared with Ontario paramedic services and governing institutions. This study will be used to inform patient classification protocols and clinical decision tools for ambulances to transport to sub-acute healthcare centres.Trial registration numberISRCTN22901977.

Project description:ObjectivesTo determine disparities in rates, length of stay (LOS) and hospital costs of potentially preventable hospitalisations (PPH) for selected chronic conditions among Aboriginal and non-Aboriginal South Australians (SA), then examine associations with area-level socioeconomic disadvantage and remoteness.SettingPeriod prevalence study using linked, administrative public hospital records.ParticipantsParticipants included all SA residents in 2005-2006 to 2010-2011. Analysis focused on those individuals experiencing chronic PPH as defined by the Australian Institute of Health and Welfare.Primary outcome measuresNumber and rates (unadjusted, then adjusted for sex and age) of chronic PPH, total LOS and direct hospital costs by Aboriginality.ResultsAboriginal SAs experienced higher risk of index chronic PPH compared with non-Aboriginals (11.5 and 6.2 per 1000 persons per year, respectively) and at younger ages (median age 48 vs 70 years). Once hospitalised, Aboriginal people experienced more chronic PPH events, longer total LOS with higher costs than non-Aboriginal people (2.6 vs 1.9 PPH per person; 11.7 vs 9.0 days LOS; at $A17 928 vs $A11 515, respectively). Compared with population average LOS, the standardised rate ratio of LOS among Aboriginal people increased by 0.03 (95% CI 0.00 to 0.07) as disadvantage rank increased and 1.04 (95% CI 0.63 to 1.44) as remoteness increased. Non-Aboriginal LOS also increased as disadvantage increased but at a lower rate (0.01 (95% CI 0.01 to 0.01)). Costs of Aboriginal chronic PPH increased by 0.02 (95% CI 0.00 to 0.06) for each increase in disadvantage and 1.18 (95% CI 0.80 to 1.55) for increased remoteness. Non-Aboriginal costs also increased as disadvantage increased but at lower rates (0.01 (95% CI 0.01 to 0.01)).ConclusionAboriginal people's heightened risk of chronic PPH resulted in more time in hospital and greater cost. Systematic disparities in chronic PPH by Aboriginality, area disadvantage and remoteness highlight the need for improved uptake of effective primary care. Routine, regional reporting will help monitor progress in meeting these population needs.

Dataset Information

How much emergency department use by vulnerable populations is potentially preventable?: A period prevalence study of linked public hospital data in South Australia.

Objectives

Design

Setting

Participants

Main outcome measures

Results

Conclusions

Publications

How much emergency department use by vulnerable populations is potentially preventable?: A period prevalence study of linked public hospital data in South Australia.

Similar Datasets

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