The PRECISE (PREgnancy Care Integrating translational Science, Everywhere) database: Open-access data collection in maternal and newborn health

  • Reproductive Health, Volume 17, Year 2020

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Study Justification:
– Adverse pregnancy outcome rates are unacceptably high in less-resourced settings.
– Accurate epidemiological data is needed to understand rates of death and morbidity, as well as social determinants of health and processes of care.
– Contextualized strategies are necessary to improve maternal and newborn health.
Highlights:
– The PRECISE database is a unique core infrastructure of a generic, unified data collection platform.
– It builds on previous work in data harmonization, outcome and data field standardization, and open-access software.
– The database contains globally-recommended indicators and key outcomes for maternal and perinatal health.
– It also includes additional modules for social determinants of health, maternal co-morbidities, mental health, violence against women, and health systems.
– The database enables high-quality epidemiological research integrated with clinical care and discovery bioscience.
Recommendations:
– Utilize the PRECISE database to collect accurate and comprehensive data on maternal and newborn health in less-resourced settings.
– Use the data to inform and contextualize strategies for improving pregnancy outcomes.
– Promote collaboration between researchers, healthcare providers, and policymakers to leverage the database for evidence-based decision-making.
Key Role Players:
– Researchers and epidemiologists for data collection and analysis.
– Healthcare providers for data input and utilization.
– Policy makers for decision-making based on the data.
– IT professionals for database maintenance and technical support.
Cost Items for Planning Recommendations:
– Database infrastructure development and maintenance.
– Training and capacity building for data collection and analysis.
– IT support and software updates.
– Collaboration and communication expenses for stakeholders.
– Dissemination of research findings and policy recommendations.

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In less-resourced settings, adverse pregnancy outcome rates are unacceptably high. To effect improvement, we need accurate epidemiological data about rates of death and morbidity, as well as social determinants of health and processes of care, and from each country (or region) to contextualise strategies. The PRECISE database is a unique core infrastructure of a generic, unified data collection platform. It is built on previous work in data harmonisation, outcome and data field standardisation, open-access software (District Health Information System 2 and the Baobab Laboratory Information Management System), and clinical research networks. The database contains globally-recommended indicators included in Health Management Information System recording and reporting forms. It comprises key outcomes (maternal and perinatal death), life-saving interventions (Human Immunodeficiency Virus testing, blood pressure measurement, iron therapy, uterotonic use after delivery, postpartum maternal assessment within 48 h of birth, and newborn resuscitation, immediate skin-to-skin contact, and immediate drying), and an additional 17 core administrative variables for the mother and babies. In addition, the database has a suite of additional modules for ‘deep phenotyping’ based on established tools. These include social determinants of health (including socioeconomic status, nutrition and the environment), maternal co-morbidities, mental health, violence against women and health systems. The database has the potential to enable future high-quality epidemiological research integrated with clinical care and discovery bioscience.

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The PRECISE (PREgnancy Care Integrating translational Science, Everywhere) database is an innovative solution that aims to improve access to maternal health. It is a unified data collection platform that provides accurate epidemiological data on rates of death and morbidity, social determinants of health, and processes of care related to maternal and newborn health. The database includes globally-recommended indicators and key outcomes such as maternal and perinatal death, life-saving interventions, and core administrative variables for mothers and babies. It also offers additional modules for ‘deep phenotyping’ based on established tools, including social determinants of health, maternal co-morbidities, mental health, violence against women, and health systems. This database has the potential to facilitate high-quality epidemiological research, integrated clinical care, and discovery bioscience in the field of maternal health.
AI Innovations Description
The PRECISE (PREgnancy Care Integrating translational Science, Everywhere) database is a recommendation for developing an innovation to improve access to maternal health. This database serves as a core infrastructure for a unified data collection platform. It is designed to gather accurate epidemiological data on rates of death and morbidity, social determinants of health, processes of care, and other relevant factors in less-resourced settings.

The database is built upon previous work in data harmonization, outcome and data field standardization, and open-access software. It includes globally-recommended indicators found in Health Management Information System recording and reporting forms. Key outcomes such as maternal and perinatal death, as well as life-saving interventions like HIV testing, blood pressure measurement, and newborn resuscitation, are included. Additionally, there are 17 core administrative variables for both mothers and babies.

The PRECISE database also offers additional modules for “deep phenotyping” based on established tools. These modules cover social determinants of health, maternal co-morbidities, mental health, violence against women, and health systems. This comprehensive approach allows for future high-quality epidemiological research integrated with clinical care and discovery bioscience.

By providing a standardized and open-access platform for data collection, the PRECISE database has the potential to improve access to maternal health information and enable evidence-based strategies to address adverse pregnancy outcomes in different countries or regions.
AI Innovations Methodology
In order to improve access to maternal health, the PRECISE (PREgnancy Care Integrating translational Science, Everywhere) database has been developed as an innovative solution. This database serves as a core infrastructure for a unified data collection platform, aiming to provide accurate epidemiological data on rates of death and morbidity, social determinants of health, processes of care, and contextualized strategies for each country or region.

The methodology to simulate the impact of recommendations on improving access to maternal health using the PRECISE database can be outlined as follows:

1. Data Collection: The first step involves collecting data from various sources, including health management information systems, clinical research networks, and established tools for deep phenotyping. This data collection process should ensure the inclusion of globally-recommended indicators, key outcomes, life-saving interventions, and core administrative variables for both mothers and babies.

2. Data Harmonization: Once the data is collected, it needs to be harmonized to ensure consistency and compatibility across different sources. This involves standardizing outcome and data fields, using open-access software like the District Health Information System 2 and the Baobab Laboratory Information Management System.

3. Analysis and Modeling: With the harmonized data, statistical analysis and modeling techniques can be applied to simulate the impact of recommendations on improving access to maternal health. This can involve assessing the current state of maternal health, identifying gaps and challenges, and exploring potential interventions or strategies to address them.

4. Impact Assessment: The simulated impact of recommendations can be evaluated by comparing the projected outcomes with the current situation. This assessment can provide insights into the potential benefits and effectiveness of the proposed recommendations in improving access to maternal health.

5. Iterative Improvement: Based on the impact assessment, the recommendations can be refined and adjusted to optimize their effectiveness. This iterative process allows for continuous improvement and refinement of strategies to ensure better access to maternal health.

By utilizing the PRECISE database and following this methodology, researchers and policymakers can gain valuable insights into the current state of maternal health, identify areas for improvement, and simulate the impact of recommendations to enhance access to maternal health services.

Statistics:
Citations: 5
Authors: 71
Identifiers:
DOI: 10.1186/s12978-020-0873-8
Research Areas:
Community Interventions, Disparities, Food Security, Health System and Policy, Maternal and Child Health, Mental Health, Noncommunicable Diseases, Quality of Care, Sexual and Reproductive Health, Social Determinants
Study Design:
Grounded Theory
Participants Gender:
Female
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