The Global Network Maternal Newborn Health Registry: a multi-country, community-based registry of pregnancy outcomes

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Study Justification:
– Accurate reporting of pregnancy outcomes is crucial for improving maternal, fetal, and newborn health in resource-limited countries.
– The Global Network Maternal Newborn Health Registry (MNHR) was developed to address the need for comprehensive data on pregnancy outcomes in low and middle-income countries (LMICs).
– The MNHR aims to assess pregnancy outcomes over time and support efforts to improve perinatal healthcare in resource-limited areas.
Study Highlights:
– From 2010 to 2018, the MNHR enrolled 579,140 pregnant women across multiple sites in Guatemala, India, Pakistan, Democratic Republic of Congo, Kenya, and Zambia.
– Delivery data were collected for 99% of enrolled women, and 42-day follow-up data were collected for 99% of those who delivered.
– The MNHR data has been analyzed in a series of 18 manuscripts, which provide insights into trends over time and differences across geographic regions.
– The MNHR has proven to be a valuable alternative registration system for collecting data on pregnancy outcomes in countries with limited health registration systems and vital records.
Study Recommendations:
– The MNHR should continue to enroll pregnant women and collect data on pregnancy outcomes to further improve perinatal healthcare in resource-limited areas.
– Efforts should be made to expand the MNHR to include more sites and clusters, allowing for a larger sample size and more comprehensive data collection.
– Collaboration and partnerships between U.S. investigators, international investigators, and local healthcare providers should be strengthened to ensure the success and sustainability of the MNHR.
Key Role Players:
– Senior site investigators and study coordinators oversee the MNHR at each site.
– Field supervisors manage daily field activities for the MNHR.
– Research administrators (RAs) collect and enter data, working closely with healthcare providers in the community.
– Data managers ensure accurate data entry and quality.
– Physicians, nurses, and other healthcare providers play a crucial role in providing healthcare services and collecting data.
Cost Items for Planning Recommendations:
– Funding for the MNHR sites, including grants for five-year periods.
– Salaries for site investigators, study coordinators, field supervisors, research administrators, and data managers.
– Training and capacity building for study staff.
– Data management systems and technology.
– Travel and logistics for site visits and meetings.
– Ethical review and approval processes.
– Community engagement and sensitization activities.
Please note that the cost items provided are general categories and may vary depending on the specific context and requirements of each site.

The strength of evidence for this abstract is 8 out of 10.
The evidence in the abstract is strong because it provides detailed information about the Global Network Maternal Newborn Health Registry (MNHR), including its objectives, methods, and results. It also mentions the number of pregnant women enrolled in the MNHR and the data collected. However, to improve the evidence, the abstract could include more specific details about the outcomes and findings of the MNHR, as well as any limitations or challenges faced during the study.

Background: The Global Network for Women’s and Children’s Health Research (Global Network) conducts clinical trials in resource-limited countries through partnerships among U.S. investigators, international investigators based in in low and middle-income countries (LMICs) and a central data coordinating center. The Global Network’s objectives include evaluating low-cost, sustainable interventions to improve women’s and children’s health in LMICs. Accurate reporting of births, stillbirths, neonatal deaths, maternal mortality, and measures of obstetric and neonatal care is critical to determine strategies for improving pregnancy outcomes. In response to this need, the Global Network developed the Maternal Newborn Health Registry (MNHR), a prospective, population-based registry of pregnant women, fetuses and neonates receiving care in defined catchment areas at the Global Network sites. This publication describes the MNHR, including participating sites, data management and quality and changes over time. Methods: Pregnant women who reside in or receive healthcare in select communities are enrolled in the MNHR of the Global Network. For each woman and her offspring, sociodemographic, health care, and the major outcomes through 42-days post-delivery are recorded. Study visits occur at enrollment during pregnancy, at delivery and at 42 days postpartum. Results: From 2010 through 2018, the Global Network MNHR sites were located in Guatemala, Belagavi and Nagpur, India, Pakistan, Democratic Republic of Congo, Kenya, and Zambia. During this period at these sites, 579,140 pregnant women were consented and enrolled in the MNHR, nearly 99% of all eligible women. Delivery data were collected for 99% of enrolled women and 42-day follow-up data for 99% of those delivered. In this supplement, the trends over time and assessment of differences across geographic regions are analyzed in a series of 18 manuscripts utilizing the MNHR data. Conclusions: Improving maternal, fetal and newborn health in countries with poor outcomes requires an understanding of the characteristics of the population, quality of health care and outcomes. Because the worst pregnancy outcomes typically occur in countries with limited health registration systems and vital records, alternative registration systems may prove to be highly valuable in providing data. The MNHR, an international, multicenter, population-based registry, assesses pregnancy outcomes over time in support of efforts to develop improved perinatal healthcare in resource-limited areas. Trial Registration The Maternal Newborn Health Registry is registered at Clinicaltrials.gov (ID# NCT01073475). Registered February 23, 2019. https://clinicaltrials.gov/ct2/show/NCT01073475

The MNHR is conducted within the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) Global Network for Women’s and Children’s Health Research (Global Network). The Global Network has been funded by NICHD since 2001 as a cooperative agreement, comprising grantees representing a partnership between U.S. academic institutions with institutions based in a low or low-middle income country [6]. The Global Network conducts both interventional as well as observational studies addressing pregnancy and child outcomes. The MNHR Steering Committee, consisting of investigators from each site and a representative from the NICHD and the Data Coordination Center (DCC), guides the general conduct of the MNHR. The Steering Committee oversees the use of MNHR data, data analyses and publications. Over the study period, the sites participating in MNHR have evolved. In 2008, the MNHR was initiated at the sites based in Argentina, Guatemala, Belagavi and Nagpur, India, Pakistan, Kenya, and Zambia. In 2013, following the NICHD’s re-competition of the Global Network, the site in Argentina, which no longer met the World Bank criteria for low or low/middle income, was replaced by a site based in the DRC. The Bangladesh site joined the Global Network and began MNHR data collection in 2019 (Table ​(Table11). Sites of the global network for women’s and children’s health research At each site, the MNHR is overseen by the senior site investigator and study coordinator. One or more field supervisors at each site then manage the daily field activities for the MNHR. Each cluster employs a research administrator (RA) who is responsible for data collection, entry, and transmission of data to the DCC. Typically, the RAs are healthcare providers within the community. The RAs work closely with the existing healthcare service providers to help ensure that data describing pregnancies are comprehensive and accurate, as described elsewhere [7]. This study enrollment has been facilitated through community leaders (e.g. village elders and ministry of health officials) and the RAs may access medical charts of participating health facilities (e.g. delivery logs). In addition to field staff, each site employs a data manager to ensure accurate data entry, identifying and resolving edits to improve the data quality. The Global Network sites have been funded through five-year grants and thus the sites have changed since the Global Network’s initiation in 2001 (Fig. 1). This section describes the sites that were active as of 2019. Map of Global Network research sites. Note: Original includes those which initiated the study in 2008; current includes those sites active in MNHR as of 2019 The site comprises two sub-districts of Tangail district, located about 60 miles northwest of the capital, Dhaka, where the research coordinating center is based. Each cluster has a primary health care center, which is staffed by a Family Welfare Visitor and a Sub-Assistant Community Medical Officer. The clusters also have community clinics, the lowest tier heath facility, two in each cluster, each of which is staffed by a community health care provider. In addition to the public health facilities, the sub-districts also have private clinics/hospitals, which provide inpatient maternal and child-care services including cesarean delivery. The private clinics have general practitioners and some specialists (obstetricians and pediatricians) working mostly on an on-call basis. Years of participation: 2019—present The research site is within the northwestern corner of the southern state of Karnataka, India, with the site coordinating center located in Belagavi. Each of the clusters corresponds to the service areas of one or more primary health centers. Each is managed by a physician medical officer who works with nursing staff and auxiliary nurse midwives in associated sub-centers, the most peripheral outpost of the health care services. There are three tertiary care hospitals and eight secondary care hospitals serving the region as referral hospitals staffed by obstetricians, pediatricians and nurses. In addition to these public sector health facilities, there are several private sector maternity facilities within the site catchment area. Years of participation: 2008—present The research site is within the state of Maharashtra, India, with the coordinating center based in Nagpur. Each of the clusters corresponds to the service area of 20 primary health centers, and each is served by physician medical officers and nurses. These areas include 117 sub-centers where basic maternal and childcare services are provided. Referral care within the districts of the clusters is provided in ten tertiary hospitals (two in the public sector and eight in the private sector), and 30 secondary hospitals under public sector. In addition to these facilities, there are more than 100 private sector secondary level hospitals and nursing homes. Years of participation: 2009—present Research sites are located in two of five sub-districts within the Thatta district in the southern Sindh province. Sindh is near the city of Karachi, where the site coordinating center is located at Aga Khan University. The study clusters are served by more than 75 health facilities, both public sector and private fee-for-service, providing maternal and child health services. These include 47 primary health clinics, 25 secondary care facilities and 3 referral hospitals. Care in primary health clinics is typically provided by either paramedical staff, including nurses and lady health visitors or non-specialist physicians. Obstetricians and pediatricians provide care in secondary and referral hospitals. Years of participation: 2008—present The research site is within the western region of Kenya in the counties of Busia, Bungoma and Kakamega, with the site coordinating center located at Moi University, in Eldoret. The clusters are served by over 20 health facilities, most operated by the government and staffed by nurse-midwives and clinical officers and a single medical officer. Three hospitals in the area function as county referral hospitals. There is a one tertiary teaching and referral hospital based in Eldoret for the western region with a newly established training program in maternal fetal medicine. Most physicians are generalists, with some trained obstetricians and pediatricians. Years of participation: 2008—present The MNHR is based south and east of the capital city of Lusaka, Zambia, in four main districts (Kafue, Chilanga, Rufusa and Chongwe) where all the work is conducted. The site coordinating center is located at the University of Zambia, in Lusaka. There are ten clusters, eight of which have health posts. Care is provided primarily by nurses and midwives in the health center and posts and by traditional birth attendants for home births. Currently, there are three district hospitals and two referral hospitals in Lusaka, namely University Teaching Hospital and Levy Mwanawasa Teaching Hospital. Pediatricians and obstetricians are available only in the referral centers. Years of participation: 2008—present The research sites are in the North and South Ubangi Provinces, with the site coordinating center at Kinshasa School of Public Health, in Kinshasa. Each of the study clusters is served by a health center. Care in health centers is provided by nurses. There are two hospitals serving the study catchment area that are staffed by physicians, nurse midwives and nurses; no specialty physicians are available. Years of participation: 2013—present The Chimaltenango region is in the Western Highlands of Guatemala, with the coordinating center based in Guatemala City. The study clusters are served by one referral hospital, 30 health centers, and 42 health posts. Maternal and infant care in the hospital is provided mainly by obstetricians, pediatricians, and general physicians, in health centers by physicians and nurses, and in health posts by auxiliary nurses. Years of participation: 2008—present The objective of the MNHR is to register each pregnant woman residing within the designated communities, also referred to as clusters, and to collect data on these pregnancies and their outcomes. Each cluster is defined by a geographic area including all households within the area. For a cluster to be eligible for the MNHR, generally it needs to be based on a population with approximately 300 to 500 deliveries annually, although the specific numbers may differ. The clusters usually correspond to existing healthcare service delivery areas, such as an area or zone defined by the ministry of health in the participating country. Each site currently has between 8 to 10 active study clusters, but in prior years, some sites have had up to 24 clusters. Altogether, the MNHR enrolls approximately 60,000 pregnant women annually [5]. Pregnant women, and their newborns, who are residents of the study clusters are eligible to participate in the MNHR. Study staff created and maintain detailed maps of the health facilities serving each cluster and a log of all providers (e.g. traditional birth attendants) who attend deliveries outside of facilities. A variety of surveillance methods have been utilized to identify pregnant women as early as possible. The study RAs proactively identify women at or prior to antenatal care (ANC) through sensitization activities. In addition, they engage all active birth attendants in the clusters in order to facilitate the documentation of facility as well as home deliveries. On a routine basis, the RAs review hospital and clinic logs for enrollment at ANC as well as for facility births. The study team monitors cluster-level monthly data to identify trends that may indicate missed enrollments. Use of mobile phones is one strategy that has proven effective to facilitate identification and tracking of women at several sites [8]. In addition, sites conduct household surveys to help identify women who are eligible for the MNHR [4]. Data are formally collected at three time-points, at enrollment during pregnancy, within 72 h of delivery and at 42-days post-partum. Additional contacts are made between these formal data collection visits to maintain connection with the pregnant woman and her family. The RA collects data on socio-economic, demographic, health care characteristics and pregnancy outcomes. Standard definitions are used to classify certain outcomes and characteristics. For example, gestational age is estimated using ultrasound, last menstrual period (LMP), or clinical data such as physical examination, and other available information when LMP is unknown. An algorithm, based on recommendations from the American College of Obstetrics and Gynecology, then assigns the gestational age and estimated delivery date for the study [21]. With introduction of ultrasound at many sites, the use of ultrasound-based gestational age has increased over the study period [14]. In addition, the objective is to measure birth weight within 48 h of delivery using weighing scales provided by the study. When birth weight is not obtained, weight is estimated by the RA to distinguish infants weighing less than and greater than 1000 g and 2500 g. Birth attendants are classified as physicians, nurses or equivalent, traditional birth attendants (TBA) or equivalent, family or unattended, while the delivery location is defined as hospital, health center or home (including the TBA’s home or in-transit). Finally, receipt of ANC is defined as having at least one health care visit with a skilled health provider, but the specific number of visits is also documented. The clinical conditions are recorded by RAs, using the WHO definitions, whenever possible [22]. The major outcomes include stillbirths (fetal demise after 20 weeks gestation and prior to delivery), neonatal death (death at < 28 days), and maternal mortality (death of mother during pregnancy or up to 6-weeks postpartum). These standardized definitions are used to collect the data across the sites, with a manual of operations and training materials used to reinforce the definitions across study sites [9]. The causes of maternal, stillbirth and neonatal deaths are assigned by physicians at each site based on their evaluation of the available clinical information for each case. Prior to 2014, the Global Network did not have a methodology for assigning cause of death systematically across sites, resulting in potential inconsistency across the sites. In 2014, an additional data form was added to collect supplemental data about the deaths and a hierarchal computer-based system to assign cause of death using a prospectively defined methodology was implemented for maternal and neonatal deaths as well as stillbirths [23, 24]. In 2019, a more in-depth socio-economic status data collection tool was added to the MNHR to obtain more granular assessment of the women’s status [25]. Study staff collect all data for women within each cluster; a supervisor then reviews the forms for completeness and accuracy. The computerized data management system also contains basic inter- and intra-form checks. Each site transmits data to the DCC for central analyses and additional data edits to ensure quality [9]. Routine monitoring reports are reviewed at least monthly by each site team to resolve data errors. The RAs receive training on the completion of data forms, schedule of data collection and the process for editing data forms [9]. Birth attendants are trained to collect data and assess basic clinical variables and outcomes, including differentiation of stillbirths from early neonatal deaths, birth weight and assessment of gestational age. Birth attendants are also taught to distinguish macerated from fresh stillbirths using pictures depicting levels of maceration. At each site, the RAs have monthly meetings to review their data collection and have refresher training on study definitions on an annual basis, with specific training held more frequently as needed. Each site develops a monitoring plan to ensure the quality of the data. The monitoring plan has several components, including a timetable for responding to edits and an assessment of responsibility for completeness of data collection, data quality, data accuracy and data entry [7, 9]. The compliance with the plan is also tracked centrally. To assist site staff with monitoring activities, the DCC prepares monthly monitoring reports that document trends in study data for key variables. Site-specific programs are also deployed to assist each site in monitoring data locally. Additionally, site visits are conducted routinely by the DCC, NICHD and the core investigator to review the overall study progress as well as the quality of the data collection. The appropriate institutional review boards or ethics research committees of the participating institutions and the ministries of health of the respective countries approve the activities of the MNHR. Initially, approval was sought from the appropriate leader of the participating community. Informed consent for study participation is requested from each pregnant woman (and her partner when available). The Global Network Data Monitoring Committee, appointed by the NICHD, oversees and reviews activities of the MNHR at bi-annual meetings.

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The Global Network Maternal Newborn Health Registry (MNHR) is an innovative approach to improving access to maternal health. It is a multi-country, community-based registry that aims to accurately report and track pregnancy outcomes in resource-limited countries. Here are some key innovations of the MNHR:

1. Prospective, population-based registry: The MNHR enrolls pregnant women residing in or receiving healthcare in select communities. It collects data on sociodemographic factors, healthcare utilization, and major outcomes throughout the pregnancy and up to 42 days post-delivery.

2. Collaboration and partnerships: The MNHR is conducted through partnerships between U.S. investigators, international investigators, and a central data coordinating center. This collaboration allows for the pooling of resources, expertise, and data to improve maternal and newborn health outcomes.

3. Use of existing healthcare infrastructure: The MNHR utilizes existing healthcare facilities and providers within the communities. Research administrators (RAs), who are often healthcare providers themselves, work closely with healthcare service providers to ensure comprehensive and accurate data collection.

4. Mobile phone technology: Mobile phones have been used as an effective tool for identifying and tracking pregnant women in some MNHR sites. This technology helps facilitate timely data collection and communication with study participants.

5. Continuous monitoring and quality assurance: The MNHR has a robust monitoring plan to ensure data quality and accuracy. Monthly monitoring reports, site visits, and regular training sessions help maintain the integrity of the data collected.

6. Standardized definitions and protocols: The MNHR follows standardized definitions and protocols for data collection, ensuring consistency across sites. This allows for meaningful comparisons and analysis of data across different geographic regions.

7. Ethical considerations: The MNHR obtains informed consent from each pregnant woman and adheres to the ethical guidelines set by institutional review boards and ethics research committees. The privacy and confidentiality of study participants are prioritized.

These innovations of the MNHR contribute to improving access to maternal health by providing valuable data on pregnancy outcomes, identifying areas for improvement in healthcare delivery, and informing the development of targeted interventions to reduce maternal and neonatal mortality and morbidity.
AI Innovations Description
The recommendation to improve access to maternal health based on the described innovation, the Maternal Newborn Health Registry (MNHR), is to expand the implementation of the registry to more resource-limited countries. This would involve establishing partnerships between U.S. investigators, international investigators based in low and middle-income countries (LMICs), and a central data coordinating center.

The MNHR is a prospective, population-based registry that collects data on pregnant women, fetuses, and neonates receiving care in defined catchment areas. It aims to accurately report births, stillbirths, neonatal deaths, maternal mortality, and measures of obstetric and neonatal care. By collecting comprehensive and accurate data, the MNHR provides valuable information for improving pregnancy outcomes and developing improved perinatal healthcare in resource-limited areas.

Expanding the MNHR to more countries would help address the lack of health registration systems and vital records in countries with poor pregnancy outcomes. Alternative registration systems like the MNHR can provide crucial data for understanding population characteristics, quality of healthcare, and outcomes in these countries.

To implement the MNHR in new countries, partnerships can be established with local investigators and institutions in LMICs. These partnerships would facilitate the enrollment of pregnant women residing in or receiving healthcare in select communities. The MNHR data collection process, including enrollment during pregnancy, data collection at delivery, and follow-up at 42 days postpartum, would be implemented in these new sites.

To ensure the quality of data collection, each site would have a team consisting of a senior site investigator, study coordinator, field supervisors, research administrators, and data managers. These teams would be responsible for comprehensive and accurate data collection, entry, and transmission to the central data coordinating center.

Ethical considerations, such as obtaining informed consent from pregnant women and obtaining approval from institutional review boards and ethics research committees, would be followed in each participating country.

Overall, expanding the MNHR to more resource-limited countries would contribute to improving access to maternal health by providing valuable data for developing evidence-based interventions and strategies to enhance pregnancy outcomes in these areas.
AI Innovations Methodology
The Maternal Newborn Health Registry (MNHR) is a multi-country, community-based registry that aims to improve access to maternal health by collecting data on pregnant women, fetuses, and neonates receiving care in defined catchment areas. The MNHR is conducted within the Global Network for Women’s and Children’s Health Research, which conducts clinical trials and studies in resource-limited countries.

To simulate the impact of recommendations on improving access to maternal health, a methodology can be developed using the MNHR data. Here is a brief description of a possible methodology:

1. Identify the recommendations: Start by identifying specific recommendations that can improve access to maternal health. These recommendations can be based on evidence-based practices, guidelines, or innovative approaches. For example, recommendations could include increasing the number of skilled health providers, improving transportation infrastructure, or implementing telemedicine services.

2. Define indicators: Determine the indicators that will be used to measure the impact of the recommendations on improving access to maternal health. These indicators can include the number of pregnant women receiving antenatal care, the percentage of facility-based deliveries, or the maternal mortality rate.

3. Collect baseline data: Use the existing MNHR data to establish a baseline for the selected indicators. This will provide a starting point for comparison and evaluation.

4. Simulate the impact: Use statistical modeling techniques to simulate the impact of the recommendations on the selected indicators. This can involve creating different scenarios based on the implementation of the recommendations and estimating the potential changes in the indicators.

5. Analyze the results: Analyze the simulated results to assess the potential impact of the recommendations on improving access to maternal health. This can involve comparing the indicators between different scenarios and identifying the most effective recommendations.

6. Validate the findings: Validate the simulated results by comparing them with real-world data, if available. This can help ensure the accuracy and reliability of the simulation methodology.

7. Communicate the findings: Present the findings of the simulation study in a clear and concise manner. This can include visualizations, reports, or presentations to stakeholders and policymakers to inform decision-making and prioritize interventions.

By following this methodology, the impact of recommendations on improving access to maternal health can be simulated using the MNHR data. This can provide valuable insights for policymakers and stakeholders to make informed decisions and prioritize interventions to improve maternal health outcomes.

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