Integrating AHP in an FMECA framework for ranking Down syndrome tests
Rachel Ravid, Emil Bashkansky, Shuki Dror · IIE Transactions on Healthcare Systems Engineering · 2011
Many have argued that good quality health care includes involving patients in decisions about their care. In the case of genetic consultation women make decisions that also concern the next generation. Today, tests for detection of fetal Down syndrome (DS) are readily available. These tests are either diagnostic or screening tests. The result of a diagnostic test is certain, however, it involves the risk of hurting the fetus. The results of a screening test are less certain but do not involve a risk to the fetus. Pregnant women have their own preferences concerning possible losses based on their own beliefs. We developed a model similar to the failure mode, effects, and criticality analysis (FMECA) model to support the pregnant woman's decision making process. The model takes into account information about DS statistics, the risk of hurting the fetus, false diagnostic rates, and possible losses. Analytic hierarchy process (AHP) is used for scaling the subjective scores of the losses. A case study demonstrates the model.