SD.20.010 – RIsk-based triaGe to improve tHe quality of care at birTh: RIGHT study
Introduction: Ensuring that the right woman receives the right care at the right time during delivery is an essential strategy to improve maternal and newborn survival – especially in low-resource settings with persistent shortages in ‘staff, stuff and systems’.
Aim: To develop, implement and evaluate risk-based triage approaches to cradle a breakthrough in the quality of delivery care in diverse low- and middle-income settings worldwide.
Methods: Prediction models to triage women between low, moderate and high risk for adverse maternal and perinatal outcomes will be developed. These models will be externally validated in cohorts of women giving birth in participating health facilities across sub-Saharan Africa, Latin America and South-East Asia. The prediction models will be developed by the novel combination of three strategies: epidemiological methodologies, artificial intelligence and the introduction of frugal diagnostic technologies to identify health risks in pregnant women. Through co-creation involving relevant stakeholders from targeted communities, practice, research and policy, the triage implementation strategy will be developed and the models subsequently implemented. The interdisciplinary evaluation will include impact on health outcomes, women’s experiences of care, their families and health professionals, and health systems’ functioning including socioeconomic inequalities, cost-effectiveness, sustainability and scalability to other settings.
Expected impact: This project will be the cradle of a breakthrough in care at birth, ensuring the right care at the right time for the right woman through development, implementation and evaluation of risk prediction-driven triage. High-income countries may benefit from the results of this project, as they do suffer increasingly from shortage of staff. Guidance to improve the quality of care during birth in low-resource settings will contribute to achieving the maternal and perinatal mortality and morbidity targets of Sustainable Development Goals.
birth, clinical decision support, low- and middle-income countries, low-resource settings, maternal health, perinatal death, Risk prediction, triage
Academic Hospital, Action on Preeclampsia Ghana (patient organization). Suriname: Anton de Kom University, Anthropology Department & Amsterdam Institute for Social Science research, Center Frugal Innovation: International Institute of Social Studies in the Hague, College of Physicians and Surgeons, Denmark: The PartoMa Project, Department of Public Health, Department of Radiology and Nuclear Medicine, Dutch knowledge institutions: UMC Utrecht, East Africa, Effective, Erasmus Universiteit (EUR), Global Health Economics Erasmus School of Health Policy & Management, Global Health Section, Kenya: African Population and Health Research Center, KorleBu Teaching Hospital, Labour Monitoring-to-Action (SELMA) tool for Better Outcomes in Labour Difficulty (BOLD)., Leiden University (LEI) and Erasmus University Rotterdam (EUR). International collaborators: Ghana: Greater Accra Regional Hospital, Nijmegen, Radboud Medical Center (RUMC), Royal Tropical Institute KIT and Share-Net international, Tanzania, Tanzania: Aga Khan University, Thailand: Mahidol Oxford tropical medicine Research Unit, the Netherlands, Together For Her: app based intervention to improve quality of delivery care, University of Amsterdam, University of Copenhagen, University of Ghana, Utrecht University (UU), UU): Department of Obstetrics and Julius Centre (Global Maternal and Childhealth Core team project) https:, Working Party for International Safe Motherhood and Reproductive Health, World Health Organisation: WHO BOLD Research Group: Simplified, www.globalhealth.eu
|Organisation||UMC Utrecht (UMCU), The Netherlands|
|Name||Prof. dr. K.W.M. (Kitty) Bloemenkamp|