Understanding the factors associated with differences in caesarean section rates at hospital level: the case of Latin America.
As in many other regions of the world, caesarean section (CS) rates in Latin America are increasing. Studies elsewhere have shown that providing feedback to caregivers regarding their own performance relative to their peers can significantly reduce the rates. Our objectives are to calculate risk-adjusted CS rates for hospitals in Latin America and to identify factors associated with differences among risk-adjusted rates. We included 120 randomly selected institutions in eight countries of Latin America, representing 97 095 pregnancies. We used random-effects models to calculate a risk-adjusted rate for each hospital and to identify hospitals significantly higher or lower than a benchmark rate. We conducted a regression analysis to identify characteristics of hospitals associated with differences among risk-adjusted rates. The overall CS rate was 35%, ranging from 0% to 85%. Risk-adjusted CS rates ranged from 11% to 78%. Three-quarters of hospitals had risk-adjusted rates significantly above the previously identified benchmark of 20%. Characteristics of institutions explained 48% of the variability among risk-adjusted rates, including being a private as opposed to a public institution, having some economic incentive for CS as opposed to no incentive, and having > or = 50 maternity beds. Strategies to halt further increases in CS rates and reduce rates to levels that reflect the best quality of care, are urgently needed worldwide. The involvement of local quality control departments is an essential component in achieving success. Our results can be used to identify institutions that can be targets for further interventions to reduce CS rates.
Taljaard
Monica
M
Ottawa Health Research Institute and University of Ottawa, Ottawa, Canada. mtaljaard@ohri.ca
Donner
Allan
A
Villar
José
J
Wojdyla
Daniel
D
Faundes
Anibal
A
Zavaleta
Nelly
N
Acosta
Arnaldo
A
D002585:Cesarean Section / Q000191:economics / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D007843:Latin America; D016017:Odds Ratio; D011247:Pregnancy; D011248:Pregnancy Complications / Q000517:prevention & control*; D012044:Regression Analysis; D012307:Risk Factors