Resources

Clinical decision support algorithms (CDSAs) are digitized tools that combine an individual’s health information with the health worker’s knowledge and clinical protocols to assist in making diagnosis and treatment decisions. They analyze patient data, providing prompts and reminders that help health care workers deliver a range of services within a continuum of care.Despite several initiatives underway around the use of these digital tools in low-resource settings, there remains a lack of awareness of their impact and cost-effectiveness at the national level, as well as a growing need to streamline how health data is collected and used for decision-making. Though more research is needed, initial evidence suggests that CDSAs can reduce barriers to quality of care and, ultimately, health disparities, leading to greater health impact.This fact sheet summarizes key considerations that countries, implementing partners, and donors should keep in mind when planning for CDSA implementation. It also describes the work PATH, as part of its Tools for Integrated Management of Childhood Illness initiative, is leading to adapt CDSAs for country context and incorporate them into health systems to enable better and more targeted patient care.

PATH is working with state governments in India to improve access to COVID-19 testing by building a cost effective, sustainable, and scalable model for testing strategy and capacity.

The Prospective Country Evaluation (PCE) is an embedded mixed-methods evaluation platform designed to examine the Global Fund business model, investments, and contribution to disease program outcomes and impact in eight countries. The PCE generates timely evidence to support program improvements and accelerate progress towards the objectives of the Global Fund 2017-2022 Strategy.This report presents findings synthesized across the eight PCE countries in 2020 presenting a comprehensive look at the Global Fund grant cycle. The PCE assessed how business model factors have facilitated or hindered the achievement of objectives during implementation of grants approved during the 2017-19 funding cycle, including around Resilient and Sustainable Systems for Health (RSSH), sustainability and equity, and whether lessons learned during current grants have informed the next funding cycle. The objective of this grant cycle analysis was to understand what, when, why, and how grant investments change over time, including significant factors that influenced the implementation of and changes to the original grant.

This brief provides a landscape of glucose-6-phosphate dehydrogenase (G6PD) deficiency in Myanmar. The brief provides information about how G6PD is measured, and collates all accessible data from gray and peer-reviewed literature to offer a comprehensive view of the situation in Myanmar.

In a world with dynamic population movements, outbreaks with cross-border implications, and increasingly politicized health issues, linear and inflexible approaches to global health programs are ineffective. Adaptive management has emerged as one possible approach that embodies iteration and adaptability in program design and implementation to help with navigating complex and dynamic environments. It entails iterative program timelines, funding mechanisms, monitoring and evaluation plans, and implementation strategies that allow for a process of continuous “learning by doing.” It builds in explicit processes of testing, learning, and iteration throughout the project lifecycle and calls for an organizational culture that embraces flexibility and learns from its failures. Real-time data systems can strengthen adaptive management by generating data that can more rapidly inform tactical adaptations, changes, and future planning. This white paper challenges traditional project management in the global development sector. It encourages donors, policymakers, implementers, and ministries of health to set a new precedent of adaptive programming.