Dominique A Cadilhac1, Monique F Kilkenny2, Christopher R Levi3, Natasha A Lannin4, Amanda G Thrift2, Joosup Kim2, Brenda Grabsch5, Leonid Churilov5, Helen M Dewey6, Kelvin Hill7, Steven G Faux8, Rohan Grimley9, Helen Castley10, Peter J Hand11, Andrew Wong12, Geoffrey K Herkes13, Melissa Gill14, Douglas Crompton15, Sandy Middleton16, Geoffrey A Donnan5, Craig S Anderson17. 1. Monash University, Melbourne, VIC dominique.cadilhac@monash.edu. 2. Monash University, Melbourne, VIC. 3. John Hunter Hospital Campus, Newcastle, NSW. 4. La Trobe University, Melbourne, VIC. 5. Florey Institute of Neuroscience and Mental Health, Melbourne, VIC. 6. Eastern Health Clinical School, Monash University, Melbourne, VIC. 7. Stroke Foundation, Melbourne, VIC. 8. St Vincent's Hospital, Sydney, NSW. 9. Sunshine Coast Clinical School, University of Queensland, Birtinya, QLD. 10. Royal Hobart Hospital, Hobart, TAS. 11. Royal Melbourne Hospital, Melbourne, VIC. 12. Royal Brisbane and Women's Hospital, Brisbane, QLD. 13. Royal North Shore Hospital, Sydney, NSW. 14. Armidale Rural Referral Hospital, Hunter New England Local Health District, Armidale, NSW. 15. Northern Health, Melbourne, VIC. 16. St Vincent's Health Australia (Sydney), Sydney, NSW. 17. The George Institute for Global Health, Sydney, NSW.
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.
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.
Authors: Richard Ofori-Asenso; Ella Zomer; Ken Lee Chin; Si Si; Peter Markey; Mark Tacey; Andrea J Curtis; Sophia Zoungas; Danny Liew Journal: Int J Environ Res Public Health Date: 2018-11-12 Impact factor: 3.390
Authors: Rasa Ruseckaite; Claire Bavor; Lucy Marsh; Joanne Dean; Oliver Daly; Dora Vasiliadis; Susannah Ahern Journal: Qual Life Res Date: 2022-02-03 Impact factor: 3.440