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

IC-CSRisk 研究：引产期间计算剖腹产风险的实施，一项多站点阶梯式楔形随机推广试验

• 批准号: 10776163
• 负责人: Rebecca Feldman Hamm
• 金额: $ 191.89万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-22 至 2026-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10776163
• 关键词: Affect; Biometry; Birth; Black race; Black, Indigenous, People of Color; Body mass index; Caring; Catalogs; Cervical; Cesarean section; Child Development; Child Health; Clinical; Clinical effectiveness; Color; Consolidated Framework for Implementation Research; Data; Decision Making; Discipline of obstetrics; Disparity; Epidemiology; Equation; Equity; Evidence based intervention; Evidence based practice; Foundations; Future; Geography; Gestational Age; Goals; Health; Height; Hemorrhage; Induced Labor; Intervention; Interview; Maps; Maternal Health; Maternal health equity; Methodology; Methods; Mission; Morbidity - disease rate; Outcome; Patients; Penetration; Persons; Population; Pregnancy Outcome; Prospective, cohort study; Race; Randomized; Reduce health disparities; Research; Research Design; Research Personnel; Risk; Risk Reduction; Site; Standardization; Surgical Wound Infection; Surveys; System; Testing; United States; Variant; Vision; Woman; Work; clinically significant; demographics; design; disparity reduction; effectiveness evaluation; effectiveness study; effectiveness/implementation hybrid; effectiveness/implementation trial; ethnic diversity; experience; explicit bias; falls; high risk; implementation determinants; implementation evaluation; implementation outcomes; implementation research; implementation science; implementation strategy; implicit bias; improved; innovation; interest; maternal morbidity; mortality; novel; obstetric outcomes; parity; personalized risk prediction; racial disparity; response; risk prediction; risk prediction model; success

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.

项目总结