Please use this identifier to cite or link to this item: https://dora.health.qld.gov.au/qldresearchjspui/handle/1/235
Title: Risk-adjusted hospital mortality rates for stroke: evidence from the Australian Stroke Clinical Registry (AuSCR)
Authors: Middleton, Sandy
Herkes, Geoffrey K.
Castley, Helen
Crompton, Douglas
Faux, Steven G.
Hill, Kelvin
Lannin, Natasha A.
Wong, Andrew 
Kim, Joosup
Dewey, Helen M.
Grabsch, Brenda
Gill, Melissa
Thrift, Amanda G.
Churilov, Leonid
Cadilhac, Dominique A.
Donnan, Geoffrey A.
Grimley, Rohan 
Levi, Christopher R.
Hand, Peter J.
Kilkenny, Monique F.
Issue Date: 2017
Source: 206, (8), 2017, p. 345-350
Pages: 345-350
Journal: Medical Journal of Australia
Abstract: Objectives: Hospital data used to assess regional variability in disease management and outcomes, including mortality, lack information on disease severity. We describe variance between hospitals in 30-day risk-adjusted mortality rates (RAMRs) for stroke, comparing models that include or exclude stroke severity as a covariate.Design: Cohort design linking Australian Stroke Clinical Registry data with national death registrations. Multivariable models using recommended statistical methods for calculating 30-day RAMRs for hospitals, adjusted for demographic factors, ability to walk on admission, stroke type, and stroke recurrence.Setting: Australian hospitals providing at least 200 episodes of acute stroke care, 2009-2014.Main Outcome Measures: Hospital RAMRs estimated by different models. Changes in hospital rank order and funnel plots were used to explore variation in hospital-specific 30-day RAMRs; that is, RAMRs more than three standard deviations from the mean.Results: In the 28 hospitals reporting at least 200 episodes of care, there were 16 218 episodes (15 951 patients; median age, 77 years; women, 46%; ischaemic strokes, 79%). RAMRs from models not including stroke severity as a variable ranged between 8% and 20%; RAMRs from models with the best fit, which included ability to walk and stroke recurrence as variables, ranged between 9% and 21%. The rank order of hospitals changed according to the covariates included in the models, particularly for those hospitals with the highest RAMRs. Funnel plots identified significant deviation from the mean overall RAMR for two hospitals, including one with borderline excess mortality.Conclusions: Hospital stroke mortality rates and hospital performance ranking may vary widely according to the covariates included in the statistical analysis.Biomedical; Double Blind Peer Reviewed; Peer Reviewed. Instrumentation: Clinical Decision Making in Nursing Scale (CDMNS) (Jenkins). NLM UID: 0400714.PMID: 28446116.
DOI: 10.5694/mja16.00525
Resources: http://search.ebscohost.com/login.aspx?direct=true&AuthType=ip,athens&db=ccm&AN=122804791&site=ehost-live
Keywords: Quality of Health Care -- StandardsHospital Mortality;Hospitals -- Statistics and Numerical Data;Stroke -- Mortality;Prospective Studies;Models, Statistical;Aged, 80 and Over;Male;Data Collection;Outcome Assessment;Australia;Human;Risk Assessment;Aged;Middle Age;Female;Validation Studies;Comparative Studies;Evaluation Research;Multicenter Studies;Scales
Type: Article
Appears in Sites:Sunshine Coast HHS Publications

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