Patients admitted to Australian intensive care units: impact of remoteness and distance travelled on patient outcome.
ABSTRACT To use a geographical information system (GIS) to explore the impact of (i) patient remoteness and (ii) distance travelled to an Australian public-hospital intensive care unit on patient outcomes.
We conducted a retrospective study over the period 2002-2008 linking intensive care unit resource and clinical datasets with Australian population postcode data and using a GIS for analysis. Data from the Australian and New Zealand Intensive Care Society Centre for Outcome and Resource Evaluation (ANZICS CORE) critical care resources survey (2007), the ANZICS CORE adult patient database (2002- 2008) and the Australian Bureau of Statistics were used. Only public-hospital ICUs were included in the study. Classification of remoteness was based on the extended version of the Accessibility/Remoteness Index of Australia (ARIA+). Distance was the distance between centroids of the patient's residential postcode and the postcode of the area in which the admitting ICU was located. ICU admissions were divided into three categories: "direct other-hospital ICU admission" (patient transferred directly from another hospital), "indirect other-hospital ICU admission" (patient admitted from a ward, emergency department or operating room after being transferred from another hospital) or "home ICU admission" (patient not transferred from another hospital).
There were 218 709 ICU admissions to 76 Australian publichospital ICUs. Of these admissions, 49 674 (22.7%) were in the "indirect" group and 19 494 (8.9%) in the "direct" group. Over the period of the study, for the indirect and direct groups, remoteness (measured by median ARIA+ rating) increased (from 0.25 to 0.55 [P < 0.01] and from 0.12 to 0.25 [P < 0.01], respectively) as did median distance travelled to the admitting ICU (from 36.4 to 42.5 km [P < 0.01] and from 27.1 to 36.7 km [P < 0.01], respectively), while mortality decreased (from 18.2% to 15.8% [P = 0.01] and from 22.7% to 18.7% [P = 0.01], respectively). ICU length of stay (LOS) and hospital LOS correlated with ARIA+ rating for both the indirect group (R = 0.018, P < 0.01; and R = 0.013, P < 0.01, respectively) and the direct group (R = 0.038, P < 0.01; and R = 0.036, P < 0.01, respectively). The median distance travelled by survivors compared with non-survivors was similar in the direct group (30.8 v 32.1 km [P = 0.66]) but longer in the indirect group (42.8 v 33.8 km [P < 0.01]) and the home admission group (11.5 v 7.6 km [P < 0.01]).
For patients who were admitted to the ICU after being transferred from another hospital, greater remoteness and greater distance travelled were not associated with increased mortality, but LOS in the hospital and the ICU was longer.
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ABSTRACT: Background & Aims: An increased liver disease burden has been reported in Aboriginal and Torres Strait Islanders (ATSI) in Australia, however, only few proceed to liver transplantation (LT). We aimed to compare overall and graft survival after LT between ATSI and non-ATSI population, assess the factors influencing survival within ATSI and finally to examine the proportion of ATSI having LT.Methods: Retrospective review of Australia and New Zealand Liver Transplant Registry (ANZLTR) from 1985-2012 examining consecutive primary LT performed in Australia. Overall and graft survival was compared between ATSI and non-ATSI groups. Accessibility/Remoteness Index of Australia (ARIA) score was used to calculate the remoteness of individuals.Results: 3493 primary LT were performed and 45 (14 children and 31 adults) were ATSI (1.3%). The median (range) ages of ATSI children and adults at the time of LT were 9.6 (0.2-15.3) and 44.5 (19.5-65.5) years, respectively. There were 10 deaths in the ATSI cohort. Median overall (range) survival was similar between ATSI and non-ATSI children [6.5 (0.1-23.5) vs. 9.0 (0-28.2) years, p=0.9] and adults [7.1 (0.1-15.7) v 6.3 (0-26.7) years, p=0.8]. Cumulative graft survival was similar between ATSI and non-ATSI children (p=0.8) and adults (p=0.8). High ARIA score [HR (95% CI) = 1.2 (1.01-1.53), p=0.03] in children and blood group O [HR (95% CI) = 3.8 (1.1-12.7), p=0.03] in adults predicted a worse outcome in ATSI. Although ATSI account for 4.7% and 1.8% of the Australian paediatric and adult populations respectively, they represent only 2.2% of paediatric (χ2 =8.2, p=0.004) and 1.1% of adult (χ2=7.9, p=0.005) LT recipients.Conclusion: Overall and graft survival post-LT in ATSI is comparable to non-ATSI. There was a trend towards increased death/re-transplantation in ATSI from remote areas. ATSI children and adults appear under-represented in the Australian LT population. Liver Transpl , 2014. © 2014 AASLD.Liver Transplantation 07/2014; 20(7). DOI:10.1002/lt.23894 · 3.79 Impact Factor
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ABSTRACT: Background:Planning for mass critical care in resource poor or constrained settings (developing or undeveloped countries) has been largely ignored despite their large populations that are prone to suffer disproportionately from natural disasters. Addressing mass critical care in these settings has the potential to help vast numbers of people and also to inform planning for better-resourced areas. Methodology:The Resource Poor Settings panel developed 5 key question domains; defining the term resource poor and using the traditional phases of disaster (mitigation/preparedness/response/recovery), literature searches were conducted to identify evidence on which to answer the key questions in these areas. Given a lack of data upon which to develop evidenced-based recommendations, expert-opinion suggestions were developed and consensus was achieved using a modified Delphi process. Results:The 5 key questions were then separated as follows: definition, infrastructure and capacity building, resources, response, and reconstitution/recovery of host nation critical care capabilities and research. Addressing these questions led the panel to offer 33 suggestions. Due to the large number of suggestions the results have been separated into two sections, part I: Infrastructure/Capacity in this manuscript, and part II, Response/Recovery/Research in the accompanying manuscript. Conclusions:Lack of, or presence of, rudimentary Intensive Care Unit resources and limited capacity to enhance services further challenge resource poor and constrained settings. Hence, capacity building entails preventative strategies and strengthening of primary health services. Assistance from other countries and organizations is needed to mount a surge response. Moreover, planning should include when to disengage and how the host nation can provide capacity beyond the mass casualty care event.Chest 08/2014; 146(4). DOI:10.1378/chest.14-0744 · 7.13 Impact Factor