Regional and rural Australia — that is, those areas that lie outside the major capital cities — is home to over 8 million people (33% of the total population), and comprises about 98% of the Australian land mass.
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The health of regional Australians is poorer than their city counterparts. They die at a younger age, carry a higher burden of chronic disease, and are more likely to engage in unhealthy behaviours.
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Such findings are not unique to Australian regional and rural populations.
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They also have less access to and are less likely to seek medical services.
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It has recently been hypothesised that some of the misrepresentations of Aboriginal and Torres Strait Islander (Indigenous) Australians in the intensive care unit (ICU) are also due to access barriers to both primary and subspecialty care.
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Australian Bureau of Statistics. Regional population growth, Australia, 2017–18 [Cat. No. 3218.0] https://www.abs.gov.au/AUSSTATS/abs@.nsf/mf/3218.0 (viewed Sept 2020).
Trading Economics. Australia — rural land area (sq km), 2020. https://tradingeconomics.com/australia/rural-land-area-sq-km-wb-data.html (viewed Sept 2020).
Australian Institute of Health and Welfare. Rural and remote health 2017 https://www.aihw.gov.au/reports/rural-remote-australians/rural-remote-health/contents/summary (viewed Sept 2020).
Joynt KE, Harris Y, Orav EJ, Jha AK. Quality of care and patient outcomes in critical access rural hospitals. JAMA 2011; 306: 45-52.
Australian Institute of Health and Welfare. Survey of Health Care: selected findings for rural and remote Australians, 2018 [Cat. No. PHE 220]. https://www.aihw.gov.au/reports/rural-remote-australians/survey-health-care-selected-findings-rural-remote/contents/summary (viewed Sept 2020).
Secombe PJ, Brown A, Bailey MJ, Pilcher D. Equity for Indigenous Australians in intensive care. Med J Aust 2019; 211: 297-9.
Specialist medical facilities, including ICUs, are clustered in areas of high population density, mostly in and around capital cities. These tertiary and metropolitan ICUs provide highly efficient critical care services to people living in the major cities of Australia, but this aggregation of ICUs may be problematic for critically ill regional and rural Australians.
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Hicks P, Huckson S, Fenney E, et al. The financial cost of intensive care in Australia: a multicentre registry study. Med J Aust 2019; 211: 324-5.
Despite population and health service differences, comparative data on the provision of critical care services in Australia by regional and rural ICUs are lacking. A description of the characteristics and outcomes of critically ill patients admitted to regional and rural ICUs may help to identify whether equity exists in the provision of ICU care and highlight the role of regional and rural ICUs in the management of critically ill Australians. It was hypothesised that the outcomes of regional Australians admitted for critical illness would mirror the higher mortality observed in regional areas.
Methods
The Australian and New Zealand Intensive Care Society (ANZICS) Adult Patient Database (APD), one of four clinical quality registries administered by the ANZICS Centre for Outcome and Resource Evaluation (CORE), was used. The APD was used to identify all patients aged 16 years or older admitted to an Australian public ICU between 1 January 2009 and 30 June 2019. Over 90% of ICU admissions in Australia are reported to the APD.
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ICUs are classified by the type of hospital to which they provide services (tertiary, metropolitan, regional/rural or private).
Australian and New Zealand Intensive Care Society Centre for Outcomes and Resource Evaluation. ANZICS CORE annual report 2017. https://www.anzics.com.au/wp-content/uploads/2018/10/ANZICS-CORE-Annual-Report-2017.pdf (viewed Sept 2020).
Admissions were excluded if there was no admission diagnosis, no in-hospital mortality outcome listed, or if the admission was to a private ICU. To avoid double-counting patient outcomes, ICU readmissions during the same hospital episode were excluded, as were episodes where the admission source was the ICU of another hospital (ie, an interhospital transfer [IHT] defined by the receiving ICU). Patients readmitted to ICU at the same hospital in a separate hospital episode were included and considered as two distinct episodes. It was not possible to identify subsequent ICU admissions at a different hospital. The study was approved by the Central Australian Human Research Ethics Committee (CA-19-3516) and was conducted following the Strengthening the Reporting of Observational studies in Epidemiology (STROBE) standards (Online Appendix, table 1).
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von Elm E, Altman DG, Egger M, et al. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Lancet 2007; 370: 1453-7.
Baseline characteristics (age and sex), demographic features (home postcode, regional status), the presence of comorbidities, the need for mechanical ventilation, and outcomes were extracted.
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Illness severity was described using the Acute Physiology and Chronic Health Evaluation (APACHE) II and III scoring systems and the Australian and New Zealand Intensive Care Risk of Death (ANZROD) model.
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ANZROD is derived from locally collected variables and components of the APACHE scoring system. It accounts for individual admission diagnoses and applies separate predictive equations for each major physiological system. It provides highly discriminatory mortality prediction for admissions to Australian and New Zealand ICUs.
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The reason for ICU admission was taken from the ANZICS modification of the APACHE III diagnostic coding system.
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Individual admission diagnoses were grouped into eight major system-based categories.
Australian and New Zealand Intensive Care Society Centre for Outcomes and Resource Evaluation. APD data dictionary: ANZICS CORE — Adult patient database, version 5.10. Melbourne, VIC: ANZCIS CORE, 2017. https://www.anzics.com.au/wp-content/uploads/2018/08/ANZICS-APD-Dictionary.pdf (viewed Sept 2020).
Knaus WA, Wagner DP, Draper EA, et al. The APACHE III prognostic system. Risk prediction of hospital mortality for critically ill hospitalized adults. Chest 1991; 100: 1619-36.
Pilcher D, Paul E, Bailey M, Huckson S. The Australian and New Zealand Risk of Death (ANZROD) model: getting mortality prediction right for intensive care units. Crit Care Resusc 2014; 16: 3-4.
Paul E, Bailey M, Kasza J, Pilcher D. The ANZROD model: better benchmarking of ICU outcomes and detection of outliers. Crit Care Resusc 2016; 18: 25-36.
Paul E, Bailey M, Kasza J, Pilcher D. The ANZROD model: better benchmarking of ICU outcomes and detection of outliers. Crit Care Resusc 2016; 18: 25-36.
Australian and New Zealand Intensive Care Society Centre for Outcomes and Resource Evaluation. APD data dictionary: ANZICS CORE — Adult patient database, version 5.10. Melbourne, VIC: ANZCIS CORE, 2017. https://www.anzics.com.au/wp-content/uploads/2018/08/ANZICS-APD-Dictionary.pdf (viewed Sept 2020).
Remoteness and socio-economic status were determined respectively by the 2011 iteration of the Accessibility and Remoteness Index of Australia (ARIA+) and the 2011 iteration of the Index of Relative Socio-Economic Advantage and Disadvantage (IRSAD) linked to each patient’s postcode.
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ARIA+ is an objective process for classifying remoteness and values vary between 0 (high accessibility) and 15 (high remoteness) based on road distance measurements, population size, and accessibility.
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IRSAD is a general socio-economic index that summarises the economic and social conditions within an area. Lower numbers indicate areas of relative greater socio-economic disadvantage and lack of advantage.
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Australian Bureau of Statistics. Technical paper: Socio-Economic Indexes for Areas (SEIFA) 2011. Canberra: Commonwealth Government of Australia; 2013.
Hugo Centre for Population and Housing, University of Adelaide. Accessibility/Remoteness Index of Australia (ARIA) 2018. https://www.adelaide.edu.au/hugo-centre/spatial_data/aria/ (viewed Sept 2020).
Hugo Centre for Population and Housing, University of Adelaide. Accessibility/Remoteness Index of Australia (ARIA) 2018. https://www.adelaide.edu.au/hugo-centre/spatial_data/aria/ (viewed Sept 2020).
Australian Bureau of Statistics. Technical paper: Socio-Economic Indexes for Areas (SEIFA) 2011. Canberra: Commonwealth Government of Australia; 2013.
The primary outcome was in-hospital mortality. Secondary outcomes included in-ICU mortality, measures of resource use (ICU and hospital length of stay, need for mechanical ventilation, need for IHT), and ICU readmissions rate in subsequent hospital admissions.
Statistical analysis
Data were analysed with STATA version 15.1 (Statacorp, Texas, USA). All data were initially assessed for normality. Group comparisons were performed using χ2 tests, Student t test for normally distributed data, and Wilcoxon rank sum tests for non-normally distributed data. Results are reported as n (%), mean (standard deviation [SD]) or median (interquartile range [IQR]) respectively. Hierarchical logistic regression was used to account for baseline severity of illness using ANZROD methodology, adjusting for hospital type, region, year of admission (treated as a continuous variable) and socio-economic status, with patients clustered by site, and site treated as a random effect.
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To reduce the risk of confounding due to an IHT (since attribution of mortality may be transferred from the regional or rural ICU to a tertiary ICU), further sensitivity analyses were undertaken excluding patients who had an ICU discharge destination of another ICU and also without excluding any IHT. For comparative analyses, P values are provided for perspective rather than for statistical significance; and for regression, results were considered significant at P < 0.05.
Paul E, Bailey M, Kasza J, Pilcher D. The ANZROD model: better benchmarking of ICU outcomes and detection of outliers. Crit Care Resusc 2016; 18: 25-36.
Results
Patient characteristics
Between January 2009 and July 2019, there were nearly 1.4 million admissions to adult ICUs within Australia reported to the ANZICS APD. After exclusions (Figure 1), the study dataset comprised 876 522 episodes of care in 103 distinct ICUs, of which 172 444 (19.7%) occurred in one of 36 regional/rural units (Table 1). The proportion of admissions to regional/rural units over the sampling period was relatively stable (Figure 2). Patients admitted to regional/rural units were less likely to originate from a major city, had a higher ARIA+ score, indicating a residential postcode from more remote centres, and were more likely to come from areas that were relatively disadvantaged and had less advantage.
Patients admitted to a regional/rural ICU had a similar age (62.5 ν 63.9 ν 64.6 years for tertiary, metropolitan and regional/rural ICUs respectively), and were more frequently admitted emergently (64.5% ν 81.7% ν 81.1% respectively). They more frequently had chronic cardiovascular or chronic respiratory disease and less frequently had metastatic cancer, leukaemia, or were immunosuppressed (Table 1).
Illness severity was lower in regional/rural units, with lower APACHE II and III scores and lower risk of death as measured by ANZROD. Admission diagnoses for cardiovascular, respiratory or gastrointestinal reasons predominated in regional/rural units, while an admission following cardiac surgery was rare.
Outcomes
Unadjusted hospital mortality was lower in regional/rural ICUs (10.7% ν 10.5% ν 8.0% for tertiary, metropolitan and regional/rural ICUs respectively) (Table 2), a finding that persisted after adjustment for illness acuity, socio-economic disadvantage, jurisdiction, and year of admission (odds ratio [OR], 0.73; 95% CI, 0.66–0.80; P < 0.001) (Figure 3). The full model is outlined in Table 3. Sensitivity analysis excluding patients who had an ICU discharge destination of another ICU (an IHT defined by the referring unit) and including all patients irrespective of retrieval status revealed similar results (Online Appendix, tables 2 and 3).
Unadjusted ICU mortality was lowest in regional/rural ICUs (7.0% ν 6.5% ν 5.0% of tertiary, metropolitan and regional/rural ICUs respectively). There were very small differences in ICU length of stay, with the longest seen for patients admitted to metropolitan ICUs (Table 2). Hospital length of stay was shorter in regional/rural hospitals (10.0 ν 7.4 ν 6.0 days for tertiary, metropolitan and regional/rural ICUs respectively). Patients admitted to regional/rural ICUs had lower rates of mechanical ventilation (51.7% ν 30.5% ν 19.9% for tertiary, metropolitan and regional/rural respectively), although about one-third of ventilated patients were elective ICU admissions (Online Appendix, table 4). Admissions to regional/rural ICUs were more likely to result in an IHT from the unit to which they presented to a unit that offered a higher level of care. There were significantly more admissions to regional/rural ICUs that represented an ICU episode during a subsequent hospital admission; indeed, this was nearly twice as likely compared with tertiary hospitals.