IC-CSRisk Study: Implementation of Calculated Cesarean Section Risk during labor induction, a multi-site stepped-wedge randomized rollout trial

项目总结 在美国，每年有400多万妇女分娩，其中超过20%的妇女正在分娩 归纳法。三分之一的引产以剖腹产告终，这与产妇产程增加有关。 发病率。在美国，黑人、土著、 彩色(BIPOC)和非BIPOC分娩者的剖宫产率和孕产妇发病率。在产科之外， 增加客观性和决策标准化的干预措施已被证明限制了效果 对健康结果的偏见。作为回应，我们小组创建了一个剖腹产风险预测模型，其中 进行诱导，这为临床医生和患者提供了个性化的剖宫产风险百分比 对于给定的病人的引产。在一项单部位前瞻性队列研究中，使用这种剖腹产风险 计算器与剖宫产率和产妇发病率的显著改善有关。 通过混合方法的工作，我们阐明了计算器的成功机制：可信地辅助 临床医生的客观决策，特别是对于剖腹产风险很低或很高的患者， 这一提议的中心假设是，在执行科学的基础上， 在美国各地不同的劳动单位实施剖腹产风险计算器可能会产生深远的影响 关于所有分娩人群的关键产科结局，特别关注有色人种患者。这项建议 利用产妇健康公平方面的经验丰富的调查人员(PI Hamm、Co-is Levine、Howell、Clark和 实施科学(Pi Hamm，Co-I Lane-Fall，Delgado，Stephens)，生物统计学/流行病学 实施(Co-I Stephens)和混合方法(Pi Hamm，Co-I Lane-Fall)。 我们计划通过研究剖腹产风险计算器的有效性来检验我们的假设，同时 在I型混合有效性中同时收集实施数据.随机化实施 跨14个承诺劳动单位的阶梯式楔形铺设设计。在部署开始之前，目标1将评估 以及所包括的所有地点的上下文决定因素目录，以便绘制实施战略图 而工作流程计划最有可能导致成功的本地实施。然后Aim 2将决定 剖宫产风险计算器在阶梯形楔形设计中的有效性，按计划分层分析 耐心地评估计算器对差异的影响。最后，目标3将决定计算器的可接受性， 渗透性，以及混合方法中的公平覆盖。 通过这项工作的结论，我们将有新的，临床上重要的信息关于影响 关于分娩结果的剖腹产风险计算器，以及广泛实施的在线工具包。结果是 建议的R01还将产生可推广到未来许多大规模实施工作的数据 旨在改善产妇健康。

PROJECT SUMMARY In the United States, over four million women give birth annually, with more than 20% undergoing labor induction. One-third of inductions end in cesarean delivery, which are associated with increased maternal morbidity. In the US, there are also significant, unacceptable disparities between Black, Indigenous, People of Color (BIPOC) and non-BIPOC birthing people in cesarean rates and maternal morbidity. Outside obstetrics, interventions that increase objectivity and decision-making standardization have been shown to limit the effects of bias on health outcomes. In response, our group created a risk prediction model for cesarean among those undergoing induction, which provides clinicians and patients with an individualized percentage risk of cesarean for a given patient’s labor induction. In a single-site prospective cohort study, use of this cesarean risk calculator was associated with substantial improvements in cesarean delivery rate and maternal morbidity. Through mixed-methods work, we elucidated the calculator’s mechanisms of success: plausibly assisting clinicians in objective decision-making, particularly for patients at very low or very high risk of cesarean, The central hypothesis of this proposal is that, with a foundation in implementation science, implementation of the cesarean risk calculator at diverse labor units across the US can have a profound impact on critical obstetric outcomes for all birthing people, with a particular focus on patients of color. This proposal leverages experienced investigators in maternal health equity (PI Hamm, Co-Is Levine, Howell, Clark, and Hussey), implementation science (PI Hamm, Co-I Lane-Fall, Delgado, Stephens), biostatistics/epidemiology of implementation (Co-I Stephens), and mixed methods (PI Hamm, Co-I Lane-Fall). We plan to test our hypothesis by studying the effectiveness of the cesarean risk calculator, while simultaneously collecting implementation data in a type I hybrid effectiveness-implementation, randomized stepped-wedge rollout design across 14 committed labor units. Before the rollout begins, Aim 1 will evaluate and catalogue contextual determinants at all included sites included in order to map implementation strategies and workflow plans most likely to result in successful local implementation. Aim 2 will then determine effectiveness of the cesarean risk calculator in the stepped wedge design, with planned stratified analysis by patient race to evaluate calculator impact on disparities. Finally, Aim 3 will determine calculator acceptability, penetration, and equitable reach in a mixed-methods approach. By the conclusion of this work, we will have novel, clinically important information on the impact of the cesarean risk calculator on labor outcomes, and an online toolkit for widespread implementation. The results of this proposed R01 will also produce data generalizable to many future large-scale implementation endeavors designed to improve maternal health.