Expertise and Leadership from Local Partners: A Q&A on data collection strategies and lessons learned in Bangladesh and Tanzania In 2023, Data for Impact (D4I) published an assessment report entitled High Impact Practices (HIPs) in Family Planning (FP): A qualitative assessment of quality and scale of implementation for three service delivery HIPs in Bangladesh and Tanzania.
Enhancing Private Sector Engagement: Introducing the Private Sector Engagement Self-Assessment Monitoring Tool On Tuesday, August 6, 2024, D4I hosted a webinar introducing the new Private Sector Engagement (PSE) Self-Assessment Monitoring (SAM) Tool.
EN-MINI: Finally, tools for combating newborn deaths are here! External link to the Ifakara Health Institute blog post published on May 27, 2024: EN-MINI: Finally, tools for combating newborn deaths are here!
D4I at the International Maternal Newborn Health Conference (IMNHC) 2023 D4I at the International Maternal Newborn Health Conference (IMNHC) 2023 Join Data for Impact (D4I) at the International Maternal Newborn Health Conference (IMNHC) 2023 happening May 8–11, 2023 in Cape … Read More "D4I at the International Maternal Newborn Health Conference (IMNHC) 2023 "
Every Newborn-Measurement Improvement for Newborn & Stillbirth Indicators (EN-MINI) Tools for Routine Health Information Systems On May 17, 2022, D4I hosted a webinar on the Every Newborn-Measurement Improvement for Newborn & Stillbirth Indicators (EN-MINI) Tools for Routine Health Information Systems. The EN-MINI tools MAP newborn data in routine health information systems, explore current USE of newborn data for decision-making, and identify how to IMPROVE newborn data quality.
Lessons learned in using the ripple effects mapping (REM) method for evaluation On February 20, 2020, Data for Impact (D4I) hosted the third webinar in a series sharing lessons learned in applying complexity-aware methods in evaluation. Today, evaluations require methods that are flexible; allow for the complexity of current public health programming in low-resource settings; and address field challenges such as strict budget and time constraints, limited baseline data, and lack of access to comparison groups. Under these circumstances, the Ripple Effects Mapping (REM) method is a useful tool for evaluators.
