Derek P Chew1, Andrew I MacIsaac2, Jeffrey Lefkovits3, Richard W Harper4, Luke Slawomirski5, David Braddock6, Matthew J Horsfall7, Heather A Buchan8, Chris John Ellis9, David B Brieger10, Tom G Briffa11. 1. Flinders University, Adelaide, SA Derek.Chew@flinders.edu.au. 2. St Vincent's Hospital, Melbourne, VIC. 3. Royal Melbourne Hospital, Melbourne, VIC. 4. Monash Health, Melbourne, VIC. 5. Health Division, Organisation for Economic Cooperation and Development, Paris, France. 6. Australian Institute of Health and Welfare, Canberra, ACT. 7. South Australian Health and Medical Research Institute, Adelaide, SA. 8. Australian Commission on Safety and Quality in Health Care, Sydney, NSW. 9. Auckland City Hospital, Auckland, New Zealand. 10. Concord Repatriation General Hospital, Sydney, NSW. 11. University of Western Australia, Perth, WA.
Abstract
BACKGROUND: Variation in the provision of coronary angiography is associated with health care inefficiency and inequity. We explored geographic, socio-economic, health service and disease indicators associated with variation in angiography rates across Australia. METHODS: Australian census and National Health Survey data were used to determine socio-economic, health workforce and service indicators. Hospital separations and coronary deaths during 2011 were identified in the National Hospital Morbidity and Mortality databases. All 61 Medicare Locals responsible for primary care were included, and age- and sex-standardised rates of acute coronary syndrome (ACS) incidence, coronary angiography, revascularisation and mortality were tested for correlations, and adjusted by Bayesian regression. RESULTS: There were 3.7-fold and 2.3-fold differences between individual Medicare Locals in the lowest and highest ACS and coronary artery disease mortality rates respectively, whereas angiography rates varied 5.3-fold. ACS and death rates within Medicare Locals were correlated (partial correlation coefficient [CC], 0.52; P < 0.001). There was modest correlation between ACS and angiography rates (CC, 0.31; P = 0.018). The proportion of patients undergoing angiography who proceeded to revascularisation was inversely correlated with the total angiogram rate (CC, -0.71; P < 0.001). Socio-economic disadvantage and remoteness were correlated with disease burden, ACS incidence and mortality, but not with angiography rate. In the adjusted analysis, the strongest association with local angiography rates was with admissions to private hospitals (71 additional angiograms [95% CI, 47-93] for every 1000 admissions). CONCLUSION: Variation in rates of coronary angiography, not related to clinical need, occurs across Australia. A greater focus on clinical care standards and better distribution of health services will be required if these variations are to be attenuated.
BACKGROUND: Variation in the provision of coronary angiography is associated with health care inefficiency and inequity. We explored geographic, socio-economic, health service and disease indicators associated with variation in angiography rates across Australia. METHODS: Australian census and National Health Survey data were used to determine socio-economic, health workforce and service indicators. Hospital separations and coronary deaths during 2011 were identified in the National Hospital Morbidity and Mortality databases. All 61 Medicare Locals responsible for primary care were included, and age- and sex-standardised rates of acute coronary syndrome (ACS) incidence, coronary angiography, revascularisation and mortality were tested for correlations, and adjusted by Bayesian regression. RESULTS: There were 3.7-fold and 2.3-fold differences between individual Medicare Locals in the lowest and highest ACS and coronary artery disease mortality rates respectively, whereas angiography rates varied 5.3-fold. ACS and death rates within Medicare Locals were correlated (partial correlation coefficient [CC], 0.52; P < 0.001). There was modest correlation between ACS and angiography rates (CC, 0.31; P = 0.018). The proportion of patients undergoing angiography who proceeded to revascularisation was inversely correlated with the total angiogram rate (CC, -0.71; P < 0.001). Socio-economic disadvantage and remoteness were correlated with disease burden, ACS incidence and mortality, but not with angiography rate. In the adjusted analysis, the strongest association with local angiography rates was with admissions to private hospitals (71 additional angiograms [95% CI, 47-93] for every 1000 admissions). CONCLUSION: Variation in rates of coronary angiography, not related to clinical need, occurs across Australia. A greater focus on clinical care standards and better distribution of health services will be required if these variations are to be attenuated.
Authors: Lee Nedkoff; Raphael Goldacre; Melanie Greenland; Michael J Goldacre; Derrick Lopez; Nick Hall; Matthew Knuiman; Michael Hobbs; Frank M Sanfilippo; F Lucy Wright Journal: Heart Date: 2019-04-04 Impact factor: 5.994
Authors: Lee K Taylor; Michael A Nelson; Marianne Gale; Judy Trevena; David B Brieger; Scott Winch; Michelle A Cretikos; Leah A Newman; Hai N Phung; Steven C Faddy; Paul M Kelly; Kerry Chant Journal: BMC Cardiovasc Disord Date: 2020-05-14 Impact factor: 2.298
Authors: Pupalan Iyngkaran; William Chan; Danny Liew; Jalal Zamani; John D Horowitz; Michael Jelinek; David L Hare; James A Shaw Journal: World J Methodol Date: 2019-01-18