OBJECTIVES: To assess recent hospital caesarean section (CS) rates in New South Wales, adjusted for case mix; to quantify the amount of variation that can be explained by case mix differences; and to examine the potential impact on the overall CS rate of reducing variation in practice. DESIGN AND SETTING: Population-based record linkage study of births in 81 hospitals in New South Wales, 2009-2010, using the Robson classification to categorise births, and multilevel logistic regression to examine variation in hospital CS rates within Robson groups. MAIN OUTCOME MEASURES: Hospital CS rates. RESULTS: The overall CS rate was 30.9%, ranging from 11.8% to 47.4% (interquartile range, 23.9%-33.1%) among hospitals. The three groups contributing most to the overall CS rate all comprised women with a single cephalic pregnancy who gave birth at term, including: those who had had a previous CS (36.4% of all CSs); nulliparous women with an elective delivery (prelabour CS or labour induction, 23.4%); and nulliparous women with spontaneous labour (11.1%). After adjustment for case mix, marked unexplained variation in hospital CS rates persisted for: nulliparous women at term; women who had had a previous CS; multifetal pregnancies; and preterm births. If variation in practice was reduced for these risk-based groups by achieving the "best practice" rate, this would lower the overall rate by an absolute reduction of 3.6%, from 30.9% to 27.3%. CONCLUSION: Understanding hospital heterogeneity in performing CS and implementing evidence-based practices may result in improved maternity care. We have identified five risk-based groups as priority targets for reducing practice variation in CS rates.
OBJECTIVES: To assess recent hospital caesarean section (CS) rates in New South Wales, adjusted for case mix; to quantify the amount of variation that can be explained by case mix differences; and to examine the potential impact on the overall CS rate of reducing variation in practice. DESIGN AND SETTING: Population-based record linkage study of births in 81 hospitals in New South Wales, 2009-2010, using the Robson classification to categorise births, and multilevel logistic regression to examine variation in hospital CS rates within Robson groups. MAIN OUTCOME MEASURES: Hospital CS rates. RESULTS: The overall CS rate was 30.9%, ranging from 11.8% to 47.4% (interquartile range, 23.9%-33.1%) among hospitals. The three groups contributing most to the overall CS rate all comprised women with a single cephalic pregnancy who gave birth at term, including: those who had had a previous CS (36.4% of all CSs); nulliparous women with an elective delivery (prelabour CS or labour induction, 23.4%); and nulliparous women with spontaneous labour (11.1%). After adjustment for case mix, marked unexplained variation in hospital CS rates persisted for: nulliparous women at term; women who had had a previous CS; multifetal pregnancies; and preterm births. If variation in practice was reduced for these risk-based groups by achieving the "best practice" rate, this would lower the overall rate by an absolute reduction of 3.6%, from 30.9% to 27.3%. CONCLUSION: Understanding hospital heterogeneity in performing CS and implementing evidence-based practices may result in improved maternity care. We have identified five risk-based groups as priority targets for reducing practice variation in CS rates.
Authors: Sally K Tracy; Alec Welsh; Bev Hall; Donna Hartz; Anne Lainchbury; Andrew Bisits; Jan White; Mark B Tracy Journal: BMC Pregnancy Childbirth Date: 2014-01-24 Impact factor: 3.007
Authors: Kathrin Schemann; Jillian A Patterson; Tanya A Nippita; Jane B Ford; Christine L Roberts Journal: BMC Pregnancy Childbirth Date: 2015-08-19 Impact factor: 3.007
Authors: Tanya A Nippita; Judy A Trevena; Jillian A Patterson; Jane B Ford; Jonathan M Morris; Christine L Roberts Journal: BMJ Open Date: 2015-09-02 Impact factor: 2.692
Authors: Christine L Roberts; Michael C Nicholl; Charles S Algert; Jane B Ford; Jonathan M Morris; Jian Sheng Chen Journal: BMC Pregnancy Childbirth Date: 2014-04-03 Impact factor: 3.007