Evaluating the scale-up for maternal and child survival: a common framework
Related Experiment Video
Updated: May 7, 2026

Assessment of Child Anthropometry in a Large Epidemiologic Study
Published on: February 2, 2017
Jennifer Bryce1, Cesar G Victora, Ties Boerma
1Institute for International Programs, Department of International Health, Bloomberg School of Public Health, Johns Hopkins University, 625 North Wolfe Street, Baltimore, USA 20205.
Abstract:
Programs to reduce mortality among women and children are the target of new resources and redoubled commitment as the 2015 date for achieving the Millennium Development Goals approaches. The need for a common evaluation framework to guide the collection, analysis and synthesis of evidence is increasingly evident. This paper presents such a framework in four parts: (1) a conceptual model for the scale-up to MDGs 4 and 5 for maternal and child survival; (2) recommended indicators for each part of the model that bring together the work of various existing technical groups and prioritize a limited number of indicators for standardization and common use; (3) guidelines for documenting program implementation and contextual factors that may affect program implementation and its effectiveness in reducing maternal and child mortality; and (4) design considerations in evaluating the scale-up. We first present an overview of what is known and/or agreed upon within each of these areas, and in the discussion highlight areas of uncertainty or where there are gaps to be addressed.
Related Concept Videos
Scale-Up Processes
Methods Of Healthcare Delivery System
Managed Care System:
The managed care system is designed to control the cost while maintaining the quality of care. The patient's care from admission to discharge is planned by the primary care provider or the case manager, also known as the gatekeeper. In a managed care system, the number of care providers is limited...
Population Growth
Comparing the Survival Analysis of Two or More Groups
Exponential Equations for Modeling Growth
Cancer Survival Analysis
