Helping Mothers Select Better Childbirth Hospitals
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 发起方
- 入组人数
- 120,621
- 试验地点
- 2
- 主要终点
- Hospital Selection
研究概览
简要总结
The investigators aim to conduct a randomized controlled trial of women who are pregnant or considering pregnancy to understand whether women provided with specific data on hospital-level cesarean delivery rates are more likely to select higher quality hospitals, defined as hospitals with cesarean delivery rates below the Federal HealthyPeople 2020 target of 23.9%.
详细描述
The choice of a childbirth provider is one of the most consequential decisions a pregnant woman makes. The hospital she delivers at is a better predictor of many treatment decisions than her own risks or preferences. For example, choosing the wrong hospital can increase the risk of cesarean delivery up to 10-fold. Cumulatively, avoidable cesarean deliveries are estimated to cause 20,000 major surgical complications, $5 billion in spending, and unmeasured pain each year in the United States.
The proposed project aims to prevent these harms by empowering women to choose hospitals with risk-appropriate cesarean delivery rates. Preliminary research indicates that the majority of women may not understand how hospital-level quality data applies to them personally. In a test sample of 1,000 demographically diverse pregnant mothers, over half do not know if hospital-level cesarean delivery rates are important, and the overwhelming majority do not know if obstetrical infection rates, maternal or neonatal birth trauma rates, or hospital quality metrics are important when selecting their hospital. The investigators will conduct a randomized controlled trial of women using Ovia Health mobile applications to track their fertility or pregnancy to understand whether women provided with location-specific cesarean delivery rate data along with education about the importance of hospital-level cesarean delivery rates are more likely to select higher quality hospitals than women provided with education alone.
The study is labeled double blind, but the investigators recognize uncertainty on this framework. Though subjects will be exposed to different information they do not know they were in a trial. At the point that outcomes are collected, researchers will not know which group the subject was randomized because outcomes are self-reported.
研究设计
- 研究类型
- Interventional
- 分配方式
- Randomized
- 干预模型
- Parallel
- 主要目的
- Health Services Research
- 盲法
- Double (Participant, Investigator)
入排标准
- 年龄范围
- 18 Years 至 —(Adult, Older Adult)
- 性别
- Female
- 接受健康志愿者
- 否
入选标准
- •Ovia Fertility users that are trying to conceive and are not infertile or Ovia Pregnancy users within the United States in their first trimester who have NOT chosen a delivery hospital or provider.
排除标准
- •People who do not use Ovia Health mobile applications, Ovia Pregnancy users beyond the first trimester of their pregnancy, Ovia Fertility users that are not infertile (as defined by women under 35 that have been trying for more than 12 months, and women over 35 that have been trying for over 6 months) and Ovia Pregnancy/Fertility users who have selected their delivering hospital or provider.
结局指标
主要结局
Hospital Selection
时间窗: Up to 12 months
Enrollees will be asked to self-report the hospital where they delivered. Hospitals will be categorized into a five-star quality rating scale based on the corresponding quintile of their cesarean section rate at the state level, as reported to the Leapfrog Group and other state data sources. Our primary outcome will be the average star rating of hospitals selected by control and intervention group enrollees. We will also report the proportion of enrollees in each group selecting hospitals of each star rating, as well as selecting hospitals that do not report their cesarean section rate.
次要结局
- Knowledge of Hospital-Level Differences(Up to 12 months)
- Use of Rates in Hospital Selection(Up to 12 months)
- Hospital Impact on Cesarean Delivery Risk(Up to 12 months)
研究者
Neel Shah
Principal Investigator
Harvard School of Public Health (HSPH)
