Medical Information Service via mobile Telephone (m-MIST TM) Provider Support to Improve Pregnancy Outcomes

项目摘要 全世界几乎所有孕产妇和围产期死亡都发生在低收入国家。访问延迟 接受适当的优质孕期护理，特别是在分娩和分娩期间，是 这些结果。减少不良妊娠结局是当前的全球高度优先事项。大学 伯明翰的亚拉巴马（UAB）母婴医学和生殖医学小组是主要的转诊中心 在服务不足的亚拉巴马州为高危妊娠和新生儿提供服务。通过UAB的高度 有价值的，忙碌和开拓性的免费电话24/7医疗信息服务通过电话（MISTTM），及时，和 农村孕妇护理提供者通常可以获得救命的护理点咨询和指导， 妇女和新生儿。虽然这种提供者支持服务现在是护理标准的一部分， 在美国，它们的执行情况和对执行情况的评估往往是不可用的， 孕产妇和围产期结局最差的低收入国家。低收入国家移动的电话拥有量迅速增加 提供了一个巨大的机会，以适应，实施和评估创新，可能挽救生命 例如MISTTM。移动的平台可以帮助减少结构性障碍， 通过为远程提供者提供临床支持，满足患者的医疗保健访问需求， 医疗紧急情况-同时也在资源有限的情况下加强地方护理系统。因此 本研究的目的是适应和评估基于移动电话的MIST（mMIST）的实施， 改善低收入国家产妇和新生儿的结局。拟议的mMIST干预措施将根据我们的 喀麦隆的孕产妇死亡率排名第九， 也是世界上围产期死亡率最高的国家之一。我们提出了三个具体目标：1）适应和 为向孕妇提供医疗保健的外围提供者开发一个24/7移动医疗支持系统 2）在喀麦隆西北部的一个卫生区测试mMIST的可行性和可接受性， 3)使用阶梯式楔形分组随机试验设计评价全量表 实施mMIST以减少孕产妇和围产期死亡以及严重孕产妇和新生儿死亡 在喀麦隆西北部的19个地区（集群），每年有65，000名产妇分娩。参与性 利益攸关方和一个有代表性的工作队参与的方法将为制定和交付 干预。三个框架将为这项研究提供信息，WHO护理质量模型，ADAPT-ITT， 干预适应性，实施科学探索，准备，实施， 可持续发展（EPIS）模式。其他功能包括计划通过参与确保可持续性， 政府和移动的服务提供商，并在这一严格的范围内关注移动卫生能力建设 调查研究。如果证明有效，扩大mMIST干预将改善孕产妇和 类似LIC环境中的新生儿结局。

PROJECT SUMMARY Almost all maternal and perinatal deaths worldwide are in low-income countries (LICs). Delays in accessing and receiving appropriate quality pregnancy care, particularly during labor and delivery, is a major reason for these outcomes. Reducing adverse pregnancy outcomes is a current and high global priority. The University of Alabama at Birmingham's (UAB) maternal and fetal medicine and neonatology groups are the primary referral services for high-risk pregnancies and newborns statewide in underserved Alabama. Through UAB's highly valued, busy and pioneering toll-free 24/7 Medical Information Service via Telephone (MISTTM), timely, and often life-saving point-of-care consultation and guidance is available to rural providers caring for pregnant women and newborns. Although such provider support services are now part of standard-of-care in the United States, their implementation and assessment of that implementation are often unavailable in LICs with the worst maternal and perinatal outcomes. The rapid rise in mobile phone ownership in LICs provides a tremendous opportunity to adapt, implement, and evaluate innovative, potentially life-saving interventions such as MISTTM. The mobile platform can help mitigate structural barriers and enhance healthcare access needs of the patient by providing clinical support for remotely-located providers facing medical emergencies -- while also enhancing local care systems in resource-constrained settings. Thus, the purpose of this study is to adapt and evaluate the implementation of mobile-phone based MIST (mMIST) to improve maternal and newborn outcomes in a LIC. The proposed mMIST intervention will be adapted from our ongoing experience at UAB and implemented in Cameroon, which has the 9th highest maternal mortality ratio and one of the highest rates of perinatal mortality in the world. We propose three Specific Aims: 1) Adapt and develop a 24/7 mHealth support system for peripheral providers who provide healthcare to pregnant women and newborns; 2) Test mMIST's feasibility and acceptability in one health district in northwest Cameroon, and 3) Evaluate the effectiveness - using a stepped wedge cluster randomized trial design - of full-scale implementation of mMIST in reducing maternal and perinatal deaths, and serious maternal and newborn morbidities in 19 districts (clusters) of northwest Cameroon with 65,000 deliveries per year. A participatory approach involving stakeholders and a representative task force will inform the development and delivery of the intervention. Three frameworks will inform this study, WHO Model for Quality of Care, ADAPT-ITT for intervention adaptation, and the implementation science Exploration, Preparation, Implementation, Sustainment (EPIS) model. Additional features include plans to ensure sustainability by engaging the government and mobile service providers, and attention to m-health capacity building within this rigorous research study. If demonstrated effective, scaling-up the mMIST intervention will improve maternal and newborn outcomes across similar LIC settings.