Please use this identifier to cite or link to this item: https://ahro.austin.org.au/austinjspui/handle/1/16859
Title: Identification and assessment of potentially high-mortality intensive care units using the ANZICS Centre for Outcome and Resource Evaluation clinical registry
Austin Authors: McClean, K;Mullany, D;Huckson, S;Lint, AV;Chavan, S;Hicks, P;Hart, G ;Paul, Eldho;Pilcher, David V
Affiliation: Centre for Outcome and Resource Evaluation, Australian and New Zealand Intensive Care Society, Melbourne, Victoria, Australia
Critical Care Research Group, Adult Intensive Care Services, Prince Charles Hospital and University of Queensland, Brisbane, Queensland, Australia
Department of Intensive Care, Austin Health, Heidelberg, Victoria, Australia
Australian and New Zealand Intensive Care Research Centre, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
Issue Date: Sep-2017
Publication information: Critical Care and Resuscitation 2017; 19(3): 230-238
Abstract: PURPOSE: A hospital's highest-risk patients are managed in the intensive care unit. Outcomes are determined by patients' severity of illness, existing comorbidities and by processes of care delivered. The Australian and New Zealand Intensive Care Society (ANZICS) Centre for Outcome and Resource Evaluation (CORE) manages a binational clinical registry to benchmark performance, and report and assess ICUs which appear to have worse outcomes than others. METHODS: A descriptive retrospective cohort study was undertaken to detail processes, outcomes, limitations and practical lessons learnt from monitoring ICU performance throughout Australia and New Zealand. All ICUs contributing to the ANZICS Adult Patient Database between 2009 and 2014 were included. A potential outlier ICU was defined as one with a statistically significantly higher standardised mortality ratio (SMR) than its peer group. RESULTS: There were 757 188 admissions to 168 ICUs. Of these, 27 ICUs (16%) were identified as potential outlier ICUs at least once. Data quality problems led to inaccurate or artificially elevated SMRs at 16/27 ICUs. Variation in diagnostic casemix partly or completely explained the elevated SMR at 15/27 ICUs. At nine ICUs where data quality and casemix differences did not explain the elevated SMR, process-of-care problems were identified. CONCLUSIONS: A combination of routine monitoring techniques, statistical analysis and contextual interpretation of findings is required to ensure potential outlier ICUs are appropriately identified. This ensures engagement and understanding from clinicians and jurisdictional health departments, while contributing to the improvement of ICU practices throughout Australia and New Zealand.
URI: http://ahro.austin.org.au/austinjspui/handle/1/16859
PubMed URL: https://pubmed.ncbi.nlm.nih.gov/28866973
Type: Journal Article
Appears in Collections:Journal articles

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