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.
- 1. National Stroke Foundation. Clinical guidelines for stroke management 2010. Melbourne: Stroke Foundation, 2010. https://informme.org.au/guidelines/clinical-guidelines-for-stroke-management-2010 (accessed Sept 2016).
- 2. Katzan IL, Spertus J, Bettger JP, et al. Risk adjustment of ischemic stroke outcomes for comparing hospital performance: a statement for healthcare professionals from the American Heart Association/American Stroke Association. Stroke 2014; 45: 918-944.
- 3. Scott I, Youlden D, Coory M. Are diagnosis specific outcome indicators based on administrative data useful in assessing quality of hospital care? Qual Saf Health Care 2004; 13: 32-39.
- 4. Saposnik G, Hill MD, O’Donnell M, et al. Variables associated with 7-day, 30-day, and 1-year fatality after ischemic stroke. Stroke 2008; 39: 2318-2324.
- 5. Hankey GJ. Long-term outcome after ischaemic stroke/transient ischaemic attack. Cerebrovasc Dis 2003; 16 Suppl 1: 14-19.
- 6. Bureau of Health Information. Healthcare in focus 2012. How well does NSW perform? Looking out and looking in. Annual performance report: December 2012. Sydney: BHI, 2012. http://www.bhi.nsw.gov.au/?a=177202 (accessed Sept 2016).
- 7. National Health Performance Authority. Towards public reporting of standardised hospital mortality in Australia: Progress report. Feb 2016. http://www.aihw.gov.au/WorkArea/DownloadAsset.aspx?id=60129555679 (accessed Sept 2016).
- 8. Cadilhac DA, Lannin NA, Anderson CS, et al. Protocol and pilot data for establishing the Australian Stroke Clinical Registry. Int J Stroke 2010; 5: 217-226.
- 9. Counsell C, Dennis M, McDowall M, Warlow C. Predicting outcome after acute and subacute stroke: development and validation of new prognostic models. Stroke 2002; 33: 1041-1047.
- 10. Cadilhac D, Kilkenny M, Churilov L, et al. Identification of a reliable subset of process indicators for clinical audit in stroke care: an example from Australia. Clinical Audit 2010; 2: 67-77.
- 11. Katzenellenbogen JM, Vos T, Somerford P, et al. Burden of stroke in indigenous Western Australians: a study using data linkage. Stroke 2011; 42: 1515-1521.
- 12. Dassanayake J, Gurrin L, Payne WR, et al. Is country of birth a risk factor for acute hospitalization for cardiovascular disease in Victoria, Australia? Asia Pac J Public Health 2011; 23: 280-287.
- 13. Kapral MK, Wang H, Mamdani M, Tu JV. Effect of socioeconomic status on treatment and mortality after stroke. Stroke 2002; 33: 268-273.
- 14. Australian Bureau of Statistics. 2033.0.55.001. Census of population and housing: Socio-Economic Indexes for Areas (SEIFA), Australia, 2011. http://www.abs.gov.au/ausstats/abs@.nsf/mf/2033.0.55.001 (accessed Sept 2016).
- 15. Hardie K, Hankey GJ, Jamrozik K, et al. Ten-year risk of first recurrent stroke and disability after first-ever stroke in the Perth Community Stroke Study. Stroke 2004; 35: 731-735.
- 16. Ali SF, Singhal AB, Viswanathan A, et al. Characteristics and outcomes among patients transferred to a regional comprehensive stroke center for tertiary care. Stroke 2013; 44: 3148-3153.
- 17. Fonarow GC, Smith EE, Reeves MJ, et al. Hospital-level variation in mortality and rehospitalization for Medicare beneficiaries with acute ischemic stroke. Stroke 2011; 42: 159-166.
- 18. Feigin VL, Lawes CM, Bennett DA, et al. Worldwide stroke incidence and early case fatality reported in 56 population-based studies: a systematic review. Lancet Neurol 2009; 8: 355-369.
- 19. Spiegelhalter DJ. Funnel plots for comparing institutional performance. Stat Med 2005; 24: 1185-1202.
- 20. McCormick N, Bhole V, Lacaille D, Avina-Zubieta JA. Validity of diagnostic codes for acute stroke in administrative databases: a systematic review. PLoS One 2015; 10: e0135834.
- 21. Appelros P, Jonsson F, Asberg S, et al. Trends in stroke treatment and outcome between 1995 and 2010: observations from Riks-Stroke, the Swedish stroke register. Cerebrovasc Dis 2014; 37: 22-29.
- 22. Preen DB, Holman CDAJ, Lawrence DM, et al. Hospital chart review provided more accurate comorbidity information than data from a general practitioner survey or an administrative database. J Clin Epidemiol 2004; 57: 1295-1304.
- 23. Fonarow GC, Pan W, Saver JL, et al. Comparison of 30-day mortality models for profiling hospital performance in acute ischemic stroke with vs without adjustment for stroke severity. JAMA 2012; 308: 257-264.
- 24. Sim J, Teece L, Dennis MS, et al. Validation and recalibration of two multivariable prognostic models for survival and independence in acute stroke. PLoS One 2016; 11: e0153527.
- 25. Xian Y, Holloway RG, Pan W, Peterson ED. Challenges in assessing hospital-level stroke mortality as a quality measure: comparison of ischemic, intracerebral hemorrhage, and total stroke mortality rates. Stroke 2012; 43: 1687-1690.
Publication of your online response is subject to the Medical Journal of Australia's editorial discretion. You will be notified by email within five working days should your response be accepted.