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|Title:||Patients admitted to Australian intensive care units: impact of remoteness and distance travelled on patient outcome|
|Citation:||Critical care and Resuscitation, 2012; 14(4):256-267|
|Publisher:||Australasian Academy of Critical Care Medicine|
|Arthas Flabouris, Graeme K Hart and Angela Nicholls|
|Abstract:||OBJECTIVE: 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. DESIGN, SETTING AND SUBJECTS: 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). MAIN OUTCOME MEASURE: Hospital mortality. RESULTS: There were 218 709 ICU admissions to 76 Australian public hospital 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]). CONCLUSION: 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.|
|Keywords:||Humans; Transportation of Patients; Length of Stay; Patient Transfer; Severity of Illness Index; Hospital Mortality; Logistic Models; Retrospective Studies; Geographic Information Systems; Adult; Middle Aged; Intensive Care Units; Medically Underserved Area; Health Services Accessibility; Outcome Assessment (Health Care); Australia; New Zealand; Female; Male|
|Rights:||Copyright status unknown|
|Appears in Collections:||Anaesthesia and Intensive Care publications|
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