Cesarean delivery (CD) accounts for one-third of all births in the US, representing an increase of approximately 50% in the last decade. Elective repeat CDs (ERCD) are a significant contributor to the rising cesarean rate, resulting from the combination of an increasing rate of primary CD and a decreasing rate of vaginal birth after cesarean (VBAC). A primary driver of the decreased frequency of VBAC is the decline in frequency with which eligible women elect a trial of labor after cesarean (TOLAC). The reasons for this decline are unclear;in particular, little is known about the extent to which patient preferences have contributed to this decrease. In addition, tools to help patients and providers engage in patient-preference driven, shared decision making regarding approach to delivery after cesarean are lacking. We propose to 1) identify patient preference drivers of delivery approach (TOLAC or ERCD) and mode (VBAC or CD) among 240 English- or Spanish-speaking TOLAC-eligible women;2) use this data to create an innovative, personalized decision support mHealth app (Prior CD Decision App) that integrates values clarification exercises with a validated VBAC prediction tool;and 3) conduct a randomized trial of the Prior CD Decision App versus usual care among 1650 English- or Spanish-speaking women to assess its effect on TOLAC and VBAC rates and decision quality. Our hypotheses are that compared to women who receive only usual care, women who are randomized to use the Prior CD Decision App will be more likely to undergo TOLAC and have a VBAC and will experience less decisional conflict, be more knowledgeable about TOLAC and ERCD and experience more optimal shared decision making.
Our study will address the gap in knowledge regarding the role of patient preferences in decision making regarding delivery approach after prior cesarean, and combine the newly gained information with a validated VBAC risk calculator and state-of-the art mobile health technology to create an innovative decision tool for women who are facing the TOLAC decision. Our study also will generate evidence on the effectiveness of this app in increasing TOLAC rates and improving decision quality. As such, we believe that our project will lead to a more individualized, patient-centered, informed shared decision-making approach to this critical decision in obstetrics, leading to an increased TOLAC rate, improved maternal and neonatal outcomes, and higher quality of obstetric care.
