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2.
Med J Aust ; 218(3): 120-125, 2023 02 20.
Article in English | MEDLINE | ID: mdl-36567660

ABSTRACT

OBJECTIVES: To assess emergency department (ED) presentation numbers in Queensland during the coronavirus disease 2019 (COVID-19) pandemic to mid-2021, a period of relatively low COVID-19 case numbers. DESIGN: Interrupted time series analysis. SETTING: All 105 Queensland public hospital EDs. MAIN OUTCOME MEASURES: Numbers of ED presentations during the COVID-19 lockdown period (11 March 2020 - 30 June 2020) and the period of easing restrictions (1 July 2020 - 30 June 2021), compared with pre-pandemic period (1 January 2018 - 10 March 2020), overall (daily numbers) and by Australasian Triage Scale (ATS; daily numbers) and selected diagnostic categories (cardiac, respiratory, mental health, injury-related conditions) and conditions (stroke, sepsis) (weekly numbers). RESULTS: During the lockdown period, the mean number of ED presentations was 19.4% lower (95% confidence interval, -20.9% to -17.9%) than during the pre-pandemic period (predicted mean number: 5935; actual number: 4786 presentations). The magnitudes of the decline and the time to return to predicted levels varied by ATS category and diagnostic group; changes in presentation numbers were least marked for ATS 1 and 2 (most urgent) presentations, and for presentations with cardiac conditions or stroke. Numbers remained below predicted levels during the 12-month post-lockdown period for ATS 5 (least urgent) presentations and presentations with mental health problems, respiratory conditions, or sepsis. CONCLUSIONS: The COVID-19 pandemic and related public restrictions were associated with profound changes in health care use. Pandemic plans should include advice about continuing to seek care for serious health conditions and health emergencies, and support alternative sources of care for less urgent health care needs.


Subject(s)
COVID-19 , Stroke , Humans , Pandemics , Queensland , Interrupted Time Series Analysis , Communicable Disease Control , Emergency Service, Hospital , Stroke/epidemiology , Retrospective Studies
4.
Crim Behav Ment Health ; 29(2): 85-93, 2019 Apr.
Article in English | MEDLINE | ID: mdl-30697841

ABSTRACT

BACKGROUND: Adults released from prison often have complex health needs. They are at high risk of poor health outcomes and reincarceration, with health service use unlikely to be planned. AIMS/HYPOTHESES: To determine the incidence of emergency health service (EHS) use, ambulance attendance and/or emergency department presentation, among 1,181 adults released from Australian prisons. We hypothesised that EHS contact would be associated with increased reincarceration risk. METHODS: Baseline surveys were conducted within 6 weeks before release. Postrelease EHS contacts and reincarceration were identified through prospective data linkage. For each participant, EHS contacts within a 24-hour period were combined to make an episode. We used Cox proportional hazards regression to examine the relationship between EHS episodes and reincarceration, controlling for covariates. RESULTS: More than half (53.3%) of participants had at least one EHS contact over a median of 25.6-month follow-up. In adjusted analyses, compared to those with no EHS contacts, the hazard of reincarceration was greater for participants who had one to three EHS episodes (hazard ratio [HR] = 1.84; 95% confidence interval [CI] [1.48, 2.29]) or four or more (HR = 2.35; 95% CI [1.67, 3.29]). CONCLUSIONS/IMPLICATIONS FOR PRACTICE: Emergency department attendance by people with a history of imprisonment may be indicative of wider decompensation. Improved management of such patients may improve health outcomes and have collateral benefits for reducing reincarceration.


Subject(s)
Ambulatory Care/statistics & numerical data , Emergency Medical Services/statistics & numerical data , Primary Health Care/statistics & numerical data , Prisoners/psychology , Prisons , Adult , Australia/epidemiology , Emergency Service, Hospital , Female , Humans , Incidence , Male , Middle Aged , Prisoners/statistics & numerical data , Proportional Hazards Models , Prospective Studies , Time Factors
5.
Qual Manag Health Care ; 24(4): 169-76, 2015.
Article in English | MEDLINE | ID: mdl-26426317

ABSTRACT

STUDY OBJECTIVES: To evaluate the implementation of a Patient Admission Prediction Tool (PAPT) in terms of patient flow outcomes and decision-making strategies. SETTING: The PAPT was implemented in 2 Australian public teaching hospitals during October-December 2010 (hospital A) and October-December 2011 (hospital B). DESIGN: A multisite prospective, comparative (before and after) design was used. Patient flow outcomes measured included access block and hospital occupancy. Daily and weekly data were collected from patient flow reports and routinely collected emergency department information by the site champion and researchers. RESULTS: Daily decision-making strategies ranged from business as usual to use of overcensus beds. Weekly strategies included advanced approval to use of overcensus beds and prebooking nursing staff. These strategies resulted in improved weekend discharges to manage incoming demand for the following week. Following the introduction of the PAPT and workflow guidelines, patient access and hospital occupancy levels could be maintained despite increases in patient presentations (hospital A). CONCLUSIONS: The use of a PAPT, embedded in patient flow management processes and championed by a manager, can benefit bed and staff management. Further research that incorporates wider evaluation of the use of the tool at other sites is warranted.


Subject(s)
Decision Support Systems, Clinical , Hospitals, Public/statistics & numerical data , Patient Admission/statistics & numerical data , Australia , Bed Occupancy/statistics & numerical data , Emergency Service, Hospital/statistics & numerical data , Humans , Prospective Studies
6.
Aust Health Rev ; 38(3): 278-87, 2014 Jun.
Article in English | MEDLINE | ID: mdl-24869756

ABSTRACT

OBJECTIVES: The aims of the present study were to identify predictors of admission and describe outcomes for patients who arrived via ambulance to three Australian public emergency departments (EDs), before and after the opening of 41 additional ED beds within the area. METHODS: The present study was a retrospective comparative cohort study using deterministically linked health data collected between 3 September 2006 and 2 September 2008. Data included ambulance offload delay, time to see doctor, ED length of stay (LOS), admission requirement, access block, hospital LOS and in-hospital mortality. Logistic regression analysis was undertaken to identify predictors of hospital admission. RESULTS: Almost one-third of all 286037 ED presentations were via ambulance (n=79196) and 40.3% required admission. After increasing emergency capacity, the only outcome measure to improve was in-hospital mortality. Ambulance offload delay, time to see doctor, ED LOS, admission requirement, access block and hospital LOS did not improve. Strong predictors of admission before and after increased capacity included age >65 years, Australian Triage Scale (ATS) Category 1-3, diagnoses of circulatory or respiratory conditions and ED LOS >4h. With additional capacity, the odds ratios for these predictors increased for age >65 years and ED LOS >4h, and decreased for ATS category and ED diagnoses. CONCLUSIONS: Expanding ED capacity from 81 to 122 beds within a health service area impacted favourably on mortality outcomes, but not on time-related service outcomes such as ambulance offload time, time to see doctor and ED LOS. To improve all service outcomes, when altering (increasing or decreasing) ED bed numbers, the whole healthcare system needs to be considered.


Subject(s)
Capacity Building/organization & administration , Emergency Service, Hospital , Adolescent , Adult , Aged , Child , Child, Preschool , Female , Humans , Infant , Longitudinal Studies , Male , Middle Aged , Retrospective Studies , Young Adult
7.
Med J Aust ; 195(11-12): 690-3, 2011 Dec 19.
Article in English | MEDLINE | ID: mdl-22171867

ABSTRACT

OBJECTIVE: To measure alcohol-related harms to the health of young people presenting to emergency departments (EDs) of Gold Coast public hospitals before and after the increase in the federal government "alcopops" tax in 2008. DESIGN, SETTING AND PARTICIPANTS: Interrupted time series analysis over 5 years (28 April 2005 to 27 April 2010) of 15-29-year-olds presenting to EDs with alcohol-related harms compared with presentations of selected control groups. MAIN OUTCOME MEASURES: Proportion of 15-29-year-olds presenting to EDs with alcohol-related harms compared with (i) 30-49-year-olds with alcohol-related harms, (ii)15-29-year-olds with asthma or appendicitis, and (iii) 15-29-year-olds with any non-alcohol and non-injury related ED presentation. RESULTS: Over a third of 15-29-year-olds presented to ED with alcohol-related conditions, as opposed to around a quarter for all other age groups. There was no significant decrease in alcohol-related ED presentations of 15-29-year-olds compared with any of the control groups after the increase in the tax. We found similar results for males and females, narrow and broad definitions of alcohol-related harms, under-19s, and visitors to and residents of the Gold Coast. CONCLUSIONS: The increase in the tax on alcopops was not associated with any reduction in alcohol-related harms in this population in a unique tourist and holiday region. A more comprehensive approach to reducing alcohol harms in young people is needed.


Subject(s)
Alcohol-Related Disorders/prevention & control , Alcoholic Beverages/economics , Emergency Service, Hospital/statistics & numerical data , Taxes , Adolescent , Adult , Alcohol-Related Disorders/epidemiology , Case-Control Studies , Federal Government , Female , Humans , Male , Models, Statistical , New South Wales/epidemiology , Queensland/epidemiology , Wounds and Injuries/epidemiology , Wounds and Injuries/etiology , Wounds and Injuries/prevention & control , Young Adult
8.
Med J Aust ; 194(4): S28-33, 2011 Feb 21.
Article in English | MEDLINE | ID: mdl-21401485

ABSTRACT

OBJECTIVE: To describe the use of surveillance and forecasting models to predict and track epidemics (and, potentially, pandemics) of influenza. METHODS: We collected 5 years of historical data (2005-2009) on emergency department presentations and hospital admissions for influenza-like illnesses (International Classification of Diseases [ICD-10-AM] coding) from the Emergency Department Information System (EDIS) database of 27 Queensland public hospitals. The historical data were used to generate prediction and surveillance models, which were assessed across the 2009 southern hemisphere influenza season (June-September) for their potential usefulness in informing response policy. Three models are described: (i) surveillance monitoring of influenza presentations using adaptive cumulative sum (CUSUM) plan analysis to signal unusual activity; (ii) generating forecasts of expected numbers of presentations for influenza, based on historical data; and (iii) using Google search data as outbreak notification among a population. RESULTS: All hospitals, apart from one, had more than the expected number of presentations for influenza starting in late 2008 and continuing into 2009. (i) The CUSUM plan signalled an unusual outbreak in December 2008, which continued in early 2009 before the winter influenza season commenced. (ii) Predictions based on historical data alone underestimated the actual influenza presentations, with 2009 differing significantly from previous years, but represent a baseline for normal ED influenza presentations. (iii) The correlation coefficients between internet search data for Queensland and statewide ED influenza presentations indicated an increase in correlation since 2006 when weekly influenza search data became available. CONCLUSION: This analysis highlights the value of health departments performing surveillance monitoring to forewarn of disease outbreaks. The best system among the three assessed was a combination of routine forecasting methods coupled with an adaptive CUSUM method.


Subject(s)
Epidemics , Influenza, Human/epidemiology , Population Surveillance/methods , Forecasting/methods , Hospitalization/statistics & numerical data , Humans , Queensland/epidemiology
9.
Med J Aust ; 194(4): S34-7, 2011 Feb 21.
Article in English | MEDLINE | ID: mdl-21401486

ABSTRACT

OBJECTIVE: To assess the accuracy of data linkage across the spectrum of emergency care in the absence of a unique patient identifier, and to use the linked data to examine service delivery outcomes in an emergency department (ED) setting. DESIGN: Automated data linkage and manual data linkage were compared to determine their relative accuracy. Data were extracted from three separate health information systems: ambulance, ED and hospital inpatients, then linked to provide information about the emergency journey of each patient. The linking was done manually through physical review of records and automatically using a data linking tool (Health Data Integration) developed by the CSIRO (Commonwealth Scientific and Industrial Research Organisation). Match rate and quality of the linking were compared. SETTING: 10,835 patient presentations to a large, regional teaching hospital ED over a 2-month period (August - September 2007). RESULTS: Comparison of the manual and automated linkage outcomes for each pair of linked datasets demonstrated a sensitivity of between 95% and 99%; a specificity of between 75% and 99%; and a positive predictive value of between 88% and 95%. CONCLUSIONS: Our results indicate that automated linking provides a sound basis for health service analysis, even in the absence of a unique patient identifier. The use of an automated linking tool yields accurate data suitable for planning and service delivery purposes and enables the data to be linked regularly to examine service delivery outcomes.


Subject(s)
Ambulances/statistics & numerical data , Emergency Service, Hospital/statistics & numerical data , Hospitalization/statistics & numerical data , Data Collection , Emergency Medical Services/statistics & numerical data , Hospitals, Teaching/statistics & numerical data , Humans , Outcome Assessment, Health Care/methods , Outcome Assessment, Health Care/statistics & numerical data , Patient Identification Systems , Queensland
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