Localized Data for Decision-Making: Implementing a Nurse-Led Data System for Maternal and Newborn Health in Tanzania
Nurse-Led Data System for Maternal and Newborn Health in Tanzania
Keywords:
maternal and newborn health, health management information systems (HMIS), quality improvement, TanzaniaAbstract
Background: Health information systems are integral tools that strengthen (and ideally drive) decision-making related to delivery of healthcare services and health outcomes in lower-income countries. However, often these data systems remain underutilized in local healthcare facilities. In sub-Saharan Africa, many countries are seeing an increasing number of facility-based births but not necessarily a corresponding improvement in outcomes, indicating that maternal and newborn health is an area in which better health information is needed to inform quality improvement initiatives. The purpose of this project was to design, implement, and evaluate a localized HIS to build capacity for quality improvement and research in maternal and newborn health at Muhimbili National Hospital in Dar es Salaam, Tanzania.
Methods: Through a collaborative partnership between Muhimbili National Hospital and Emory University, a data collection system using REDCap was developed to provide sustainable, high-quality data on in-patient maternal and newborn health services. Called the Obstetric and Neonatal Database, this project was led and implemented by nurses at MNH with support from staff obstetricians, IT personnel, and the hospital’s Training, Research, and Consultancy Unit. Four months after its launch, we conducted a mixed-methods evaluation that used quantitative methods to assess data capture and quality, and qualitative methods to elicit perceptions and experiences of users.
Results: The project demonstrated significant successes overall and continues to be used as a means of assessing quality on the maternity wards today. Although data accuracy was high, the evaluation revealed large discrepancies in data capture; specifically, data from labor and surgical wards were >97% complete versus only about 20% complete in postnatal and newborn wards. This inconsistency is attributed to differing degrees of hands-on training and efforts to promote ownership and investment among nursing staff. On the other hand, most nurses overwhelmingly reported positive experiences with the database, describing unanticipated benefits that ranged from enhanced workflow efficiency to improved data security to updated technology-related skills.
Conclusion: To effectively provide local health facilities with critical information for evaluating and improving outcomes, health management information systems must be closely tailored to the needs of specific contexts and for the benefit of all users.
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