Online Program

Systematic error in the measurement of unsafe abortion related mortality: A multiple bias analysis

Wednesday, November 6, 2013 : 1:15 p.m. - 1:30 p.m.

Caitlin Gerdts, MHS, PhD, Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California, San Francisco, Oakland, CA
Background: Without accurate measurement we cannot effectively target programs to reduce the dangerous consequences of unsafe abortion. Here we undertook a multiple-bias analysis approach to quantify the effect of systematic error on abortion-related maternal mortality estimates and outline a simple framework for investigators interested in replicating a multiple-bias analysis in their own data. Methods: This analysis employed Monte-Carlo based, probabilistic, multiple bias-analysis techniques to evaluate the influence of selection bias and misclassification in three studies of abortion related mortality. The prior distributions chosen for selection bias and misclassification differed by study, but a common analysis plan was followed. Results: For each study, the proportion of abortion related deaths (median) increased significantly after multiple bias analysis. Conclusions: These findings have broad reaching implications for the way we understand the distribution of cause of maternal death. If, as our data suggest, abortion related deaths account for a larger proportion of maternal deaths than previously thought, these methods can be used to more accurately determine the range of potential burden of abortion related mortality, and can also be used to help target funds towards increasing access to family planning and safe abortion.

Learning Areas:

Biostatistics, economics
Public health or related research
Social and behavioral sciences

Learning Objectives:
Describe biases that exist in current measures of unsafe abortion related mortality. Demonstrate a quantitative technique (Mutlitple Bias Analysis) to correct for existing biases.

Keyword(s): Abortion, Epidemiology

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I am an Epidemiologist by training, and my methodologic expertise lies in study design, quantitative bias analysis, and causal inference approaches. I employ a combination of epidemiologic methods and biostatistical techniques to pursue a research agenda that focuses on the causes and consequences of illegal and/or unsafe abortion.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.