Advantages and limitations of using national administrative data on obstetric blood transfusions to estimate the frequency of obstetric hemorrhages

J Public Health (Oxf). 2013 Mar;35(1):147-56. doi: 10.1093/pubmed/fds057. Epub 2012 Jul 24.

Abstract

Background: Obstetric hemorrhages are a frequent cause of maternal death all over the world, but are not routinely monitored. Health systems administrative databases could be used for this purpose, but data quality needs to be assessed.

Objectives: Using blood transfusion data recorded in administrative databases to estimate the frequency of obstetric hemorrhages. Research design A population-based study. Subjects Validation sub-sample: all mothers who gave birth in a French region in 2006-07 (35 123 pregnancies). Main study: all mothers who gave birth in France in 2006-07 (1 629 537 pregnancies).

Method: Linkage and comparison of administrative data on blood transfusions with data from the French blood agency ('gold standard'), and, based on this validation, the construction of a multivariable regression model to correct the number of pregnant women identified as having received a transfusion in the national administrative database.

Results: The blood transfusion rate observed in the gold standard was 7.12‰. The sensitivity of the administrative data was estimated at 66.3% and the positive predictive value at 91.3%. The estimated total number of pregnant women who received blood transfusions in France in 2006-07 was 10 941 (6.71‰).

Conclusions: The administrative data, available in most countries, can be used to estimate the frequency of obstetric hemorrhages.

MeSH terms

  • Blood Transfusion / statistics & numerical data*
  • Data Collection
  • Databases as Topic / standards*
  • Databases as Topic / statistics & numerical data
  • Feasibility Studies
  • Female
  • France / epidemiology
  • Humans
  • Infant, Newborn
  • Logistic Models
  • Postpartum Hemorrhage / epidemiology*
  • Postpartum Hemorrhage / therapy
  • Pregnancy
  • Reproducibility of Results