A combined community- and facility-based approach to improve pregnancy outcomes in low-resource settings: A Global Network cluster randomized trial

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Study Justification:
The study aimed to address the high rates of fetal and neonatal mortality in low-income countries, which are significantly higher than in high-income countries. The researchers hypothesized that a combined community- and facility-based approach involving health care providers, administrators, and local residents could improve access to quality obstetric and neonatal care and reduce perinatal mortality rates.
Highlights:
– The study was conducted in seven geographic areas in five low-income and one middle-income country, all with high perinatal mortality rates and a significant number of home deliveries.
– A package of interventions was implemented, including community mobilization, birth attendant training, and facility staff training in obstetric and neonatal emergencies.
– Despite extensive efforts, no differences were found in perinatal mortality rates between the intervention and control groups.
– The study emphasized the importance of evaluating outcomes in randomized trials, as interventions that are expected to be effective may not always produce the desired results.
Recommendations:
– The study highlights the need for substantial improvements in obstetric and neonatal care infrastructure in low-resource settings to achieve better pregnancy outcomes.
– Provider training and community mobilization alone may not be sufficient to reduce perinatal mortality rates.
– Further research and interventions should focus on strengthening healthcare infrastructure and improving access to quality care.
Key Role Players:
– Health care providers
– Administrators
– Local residents
– Researchers and study personnel
– Trainers with expertise in community mobilization, birth attendant training, and facility staff training
Cost Items for Planning Recommendations:
– Training materials and resources
– Personnel salaries and allowances
– Transportation and logistics for trainers and study personnel
– Community mobilization activities
– Facility audits and quality improvement measures
– Data collection and analysis
– Monitoring and evaluation activities
– Communication and dissemination of findings
Please note that the cost items listed above are general categories and may vary depending on the specific context and requirements of the interventions.

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is based on a cluster randomized trial conducted in multiple low-income and middle-income countries. The trial tested a package of interventions aimed at improving access to quality obstetric and neonatal care. However, the trial did not find any differences in the primary or secondary outcomes between the intervention and control clusters. The authors concluded that achieving improvement in pregnancy outcomes in these settings will require more obstetric and neonatal care infrastructure. The evidence is based on a large-scale intervention and provides valuable insights into the challenges of improving pregnancy outcomes in low-resource settings. However, the rating is not higher because the trial did not find a detectable impact on the proposed outcomes, suggesting that the interventions may not be sufficient without additional infrastructure. To improve the evidence, future studies could consider incorporating additional interventions or addressing the infrastructure gaps identified in this trial.

Background: Fetal and neonatal mortality rates in low-income countries are at least 10-fold greater than in high-income countries. These differences have been related to poor access to and poor quality of obstetric and neonatal care. Methods: This trial tested the hypothesis that teams of health care providers, administrators and local residents can address the problem of limited access to quality obstetric and neonatal care and lead to a reduction in perinatal mortality in intervention compared to control locations. In seven geographic areas in five low-income and one middle-income country, most with high perinatal mortality rates and substantial numbers of home deliveries, we performed a cluster randomized non-masked trial of a package of interventions that included community mobilization focusing on birth planning and hospital transport, community birth attendant training in problem recognition, and facility staff training in the management of obstetric and neonatal emergencies. The primary outcome was perinatal mortality at ≥28 weeks gestation or birth weight ≥1000 g. Results: Despite extensive effort in all sites in each of the three intervention areas, no differences emerged in the primary or any secondary outcome between the intervention and control clusters. In both groups, the mean perinatal mortality was 40.1/1,000 births (P = 0.9996). Neither were there differences between the two groups in outcomes in the last six months of the project, in the year following intervention cessation, nor in the clusters that best implemented the intervention. Conclusions: This cluster randomized comprehensive, large-scale, multi-sector intervention did not result in detectable impact on the proposed outcomes. While this does not negate the importance of these interventions, we expect that achieving improvement in pregnancy outcomes in these settings will require substantially more obstetric and neonatal care infrastructure than was available at the sites during this trial, and without them provider training and community mobilization will not be sufficient. Our results highlight the critical importance of evaluating outcomes in randomized trials, as interventions that should be effective may not be.Trial registration: ClinicalTrials.gov NCT01073488. © 2013 Pasha et al.; licensee BioMed Central Ltd.

This trial was undertaken by the Global Network for Women’s and Children’s Health Research (GN) supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development [28]. The GN, a multi-country research network with seven research sites in six countries, conducts research to evaluate interventions to reduce maternal and perinatal mortality and morbidity. All seven GN sites participated in the trial, including two in India (Belgaum and Nagpur), and sites in Pakistan, Kenya, Zambia, Guatemala and Argentina. Descriptions of the site populations and resources have been published [28,29]. Details of the trial methods have been described [30]. Briefly, we conducted a community-based, two-arm cluster-randomized trial, including all pregnancies of residents in 106 clusters. A cluster is a distinct geographic area with approximately 500 births per year. Intervention start dates ranged from March to August 2009 and the project intervention period was terminated for all sites on 30 September 2011. Data for the first six months of the implementation were not included in the analysis data set. Thus, the primary outcome period was 18 months (two sites) to 24 months (five sites). We also present outcome data for the last six months of the intervention period and, because a pregnancy registry is ongoing, the full year following cessation of the intervention. Each site had a pre-existing, independent maternal-newborn health registry system to screen, enroll, and track all pregnant women in the study clusters [28]. Registry administrators enrolled women during pregnancy, obtained informed consent for the trial, and recorded all intervention and control cluster delivery outcomes, including stillbirths and neonatal deaths, and all deaths of pregnant women through 42 days post-delivery or pregnancy termination. Outcomes for all women with births ≥1000 grams and or ≥28 weeks residing within the study cluster for at least four weeks prior to delivery and who consented were included in study. Study site ethics/institutional review boards, partnering US institutions, and RTI International approved the protocol. The trial was registered at ClinicalTrials.gov (NCT ID# {“type”:”clinical-trial”,”attrs”:{“text”:”NCT01073488″,”term_id”:”NCT01073488″}}NCT01073488). Based on previously collected data, the 106 study clusters had a mean perinatal death <7 days of age of 40 to 50 per 1,000 deliveries and an intra-class correlation coefficient between 0.005 and 0.01 [26]. Using a two-sided hypothesis test at 5% significance, these 106 clusters, with a minimum of 18 month outcome data, provided a power of at least 80% to detect a 25% reduction in perinatal mortality. Randomization was performed at the cluster level, stratifying by rates of the primary outcome (stillbirth and early neonatal death) and number of deliveries. The data coordinating center (Research Triangle Institute) produced a computer-generated randomization algorithm which assigned clusters at a 1:1 ratio within each stratum. Because of the nature of the intervention, there was no masking. Under direction of the GN Steering Committee, a team of GN investigators, trainers with expertise in community mobilization, TBA training and facility quality improvement designed the intervention and provided study oversight (See Figure 1). At each international site, an intervention team of senior health, health system and study personnel, meeting at least monthly, oversaw the project implementation. Trainers with extensive experience in community mobilization, others with experience in training community birth attendants and physicians with expertise in facility staff training were part of the country intervention team and participated in training in the individual clusters. In each study cluster, a cluster team comprising health care providers, local residents and study personnel was formed to develop and implement comprehensive interventions to improve the quality of obstetric and neonatal care. These cluster teams worked within their community and the local health care system to introduce these interventions. Maternal and perinatal mortality audits, facility-level provider training and facility reviews were conducted as quality improvement activities at the facility level. In addition, at the community level, village-level core groups were formed which facilitated community meetings of mothers, family and community birth attendants over the course of the trial. In summary, the cluster teams facilitated a multi-faceted intervention which included the following: EmONC Study Organization. •Community mobilization to establish village-level core groups and to strengthen community capacity to identify and address barriers to obstetric and neonatal care such as recognition of complications and transportation to a facility to manage the complication [18]. Each village-level core group was trained to move through a cycle to organize, plan, explore, act, and to evaluate maternal and perinatal outcomes within their community. •Home-based Life Savings Skills (HBLSS) training was provided for birth attendants and families to recognize prolonged labor, infection, preeclampsia and hemorrhage, and the use of appropriate stabilization methods that can be employed in homes and in first level care facilities [31-36]; and, improvement of quality of care in existing health facilities through a combination of facility staff Emergency Obstetric and Newborn Care (EMONC) training for clinical care of the major causes of maternal and newborn mortality [37], perinatal and maternal death audits [38,39] and health facility audits [29]. The EmONC trial used a train-the-trainer model for the three main components (HBLSS, community mobilization and facility EMONC training) and the modules which were focused on the major causes of maternal, fetal and neonatal mortality (Table 1). Experienced trainers for each of the three components were identified and these 'master trainers’ with input from other experts, selected and modified the existing curriculum and led the train-the-trainer training as described below: Training For HBLSS and community mobilization, the training was combined and consisted of two in-country train-the-trainer sessions (an initial two-week period with approximately 70 hours of course work and practicum utilizing the home-based life-saving skills curriculum. The community mobilization/HBLSS training emphasized the Community Action Cycle and the relevant HBLSS modules to identify and perform life-saving measures for the conditions associated with maternal and early newborn mortality (for example, post-partum hemorrhage, preeclampsia/eclampsia, low birth weight newborn care). A second one-week in-country training of trainers and cluster coordinators was held after 12 months. The in-country trainers then trained all of the community birth attendants in the curriculum; these training sessions included an initial three-day training followed by ongoing (minimal of monthly) training and community meetings. Additionally, the in-country EMONC trainer, usually an experienced obstetric physician, received a three-day course using a train-the-trainer model at a central location utilizing a modified version of the Jhpeigo EMONC curriculum (37). This three-day training emphasized the curriculum addressing post-partum hemorrhage, preeclampsia/eclampsia and emergency preparedness. The in-country trainers then carried out training for the hospitals serving their intervention clusters with the amount of training, including an initial three to five day session to cover the essential elements with additional time dedicated to follow-up training, varying based on local assessment of facility needs. For each of these components, the master trainers participated in central training, followed by in-country training every six months during the 24-month trial period. Each of the training sessions included pre and post-tests to assess knowledge and skills acquisition. In anticipation that the package of interventions would be better introduced in some clusters than others, we a priori created a system for measuring the integrity of the intervention, with credit given for reaching the targets for four intervention measures including monthly cluster team meetings, death audits, village-level core group activities and village-level core groups reaching the 'act’ phase of the community action cycle. The primary outcome was perinatal mortality, defined as the composite of stillbirth and seven-day neonatal mortality per 1,000 births among births occurring at ≥28 weeks gestation or birth weight ≥1000 g. Secondary outcomes included rates of stillbirth (both fresh and macerated), seven-day neonatal mortality, 28-day neonatal mortality and maternal death. Process measures, such as rates of transport to hospital of mothers and newborns and facility delivery, were also determined. Each of these measures was assessed in both intervention and control clusters through the registries, with registry teams distinct from those implementing the interventions. We also collected extensive data on the intervention itself including number and type of cluster and community meetings, death audits and providers trained. Data were entered at each study site with inter- and intra-data edits and consistency checks performed. The Data Monitoring Committee reviewed the data for safety and efficacy. Generalized estimating equations (GEE) extensions of a log-binomial for multivariate logistic regression model that accounted for the study design strata and correlation between outcomes in the same cluster tested for differences in the primary outcome. Secondary outcome analyses were conducted using GEE extensions of either log-binomial or robust Poisson regression models for binary outcomes and clustered multinomial logistic regression model extensions for ordinal outcomes. All analyses were performed using SAS version 9.3 (SAS Institute, Cary, NC), with the exception of the multinomial logistic regression models, which were performed using SUDAAN 11. The Ethics Review Committees of each participating institution and the data coordinating center (RTI International) all approved the study protocol. Informed consent was obtained from all women who participated in the study. This trial was funded by grants from the US National Institutes of Health (NIH). The NIH program officers (LLW, MKT) participated in the protocol development and study monitoring, and reviewed the manuscript.

Based on the information provided, it seems that the trial did not result in a detectable impact on the proposed outcomes. The interventions tested in the trial included community mobilization, birth planning, hospital transport, community birth attendant training, and facility staff training in the management of obstetric and neonatal emergencies. However, despite extensive efforts, no differences emerged in the primary or secondary outcomes between the intervention and control clusters.

The trial highlights the importance of evaluating outcomes in randomized trials and suggests that achieving improvement in pregnancy outcomes in low-resource settings may require more obstetric and neonatal care infrastructure than was available during the trial. It also emphasizes the need for provider training and community mobilization to be accompanied by substantial improvements in healthcare infrastructure.

In summary, the trial did not identify specific innovations or recommendations for improving access to maternal health. Further research and evaluation are needed to identify effective interventions in low-resource settings.
AI Innovations Description
The recommendation from the study is to implement a combined community- and facility-based approach to improve access to maternal health in low-resource settings. This approach involves several interventions, including community mobilization, birth planning, hospital transport, community birth attendant training, and facility staff training in the management of obstetric and neonatal emergencies. The goal of these interventions is to address the problem of limited access to quality obstetric and neonatal care and reduce perinatal mortality rates. However, the study found that despite extensive efforts, there were no significant differences in perinatal mortality rates between the intervention and control groups. The study suggests that achieving improvement in pregnancy outcomes in these settings will require substantial investment in obstetric and neonatal care infrastructure.
AI Innovations Methodology
Based on the information provided, the trial described aimed to address the problem of limited access to quality obstetric and neonatal care in low-income countries. The trial tested a package of interventions that included community mobilization, birth attendant training, and facility staff training. However, the trial did not result in a detectable impact on the proposed outcomes.

To improve access to maternal health, here are some potential recommendations:

1. Strengthening healthcare infrastructure: This could involve improving the availability and quality of healthcare facilities, ensuring access to essential medical equipment and supplies, and increasing the number of skilled healthcare providers.

2. Enhancing community engagement: Engaging communities in maternal health initiatives can help raise awareness, promote healthy behaviors, and address cultural and social barriers to accessing care. This can be done through community mobilization, education programs, and involving community health workers.

3. Improving transportation and referral systems: Developing efficient transportation systems and referral networks can help ensure that pregnant women can access healthcare facilities in a timely manner, especially in remote or rural areas.

4. Implementing telemedicine and mobile health solutions: Utilizing technology, such as telemedicine and mobile health applications, can help overcome geographical barriers and provide remote access to healthcare services, including prenatal care and consultations.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could include the following steps:

1. Define the target population: Identify the specific population or geographic area that will be the focus of the simulation.

2. Collect baseline data: Gather relevant data on the current state of maternal health access in the target population, including indicators such as healthcare facility availability, healthcare provider-to-patient ratios, transportation infrastructure, and community engagement levels.

3. Define intervention scenarios: Develop different scenarios that represent the potential recommendations mentioned above. Each scenario should outline the specific changes or improvements that would be implemented.

4. Model the impact: Use mathematical or statistical models to simulate the impact of each intervention scenario on improving access to maternal health. This could involve estimating changes in key indicators such as the number of healthcare facilities, healthcare provider availability, transportation access, and community engagement.

5. Analyze and compare results: Evaluate the simulated outcomes of each intervention scenario and compare them to the baseline data. Assess the potential impact of each recommendation on improving access to maternal health, considering factors such as cost-effectiveness, feasibility, and scalability.

6. Refine and iterate: Based on the analysis, refine the intervention scenarios and repeat the simulation process to further optimize the recommendations for improving access to maternal health.

It is important to note that simulation methodologies may vary depending on the specific context and available data. The methodology described above provides a general framework for simulating the impact of recommendations on improving access to maternal health.

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