Among women who give birth in industrialized countries maternal age, obesity, twin or triplet pregnancy, and presence of chronic diseases such as diabetes and hypertension continue to increase. For example, 34% of mothers in Canada today are overweight or obese, and approximately 20% of births are to women over 34 years. These demographic trends highlight the need for increasingly complex obstetric care with careful prenatal monitoring and timely obstetric intervention if necessary.
Dr. Lisonkova's research will quantify the risk of severe maternal morbidity by developing a score system that will accurately distinguish between high, moderate, and low risk women. This score calculator will help, for example, women in rural areas to decide about transport to higher-level obstetric care, as these women may face geographical barriers to timely transfer. Determinants of these elevated risks will be examined, as well as whether these risks increase with distance to maternity care, seasonally (for example in winter), or occur only among women in selected geographically specific areas.
The results of this research will provide information to women who are contemplating delaying childbirth, who are overweight or obese, or have chronic health problems. This information will also help health care providers in pre-pregnancy and pregnancy counselling, and health care administrators to identify maternal care needs with respect to maternal-fetal medicine specialists and intensive care units. The maternal morbidity risk score calculator can also be used to adjust for baseline risks (maternal comorbidity, etc.) when comparing hospital performance and evaluating new safety measures in maternal care.
This project will be conducted in collaboration with the Society of Obstetricians and Gynaecologists of Canada, Public Health Agency of Canada, and the Department of Family Medicine & Midwifery, University of British Columbia. The collaboration between midwifery, family physicians and obstetricians will be beneficial especially for women in rural areas, for whom accurate risk identification is crucial.