The BID Initiative has released midline and endline monitoring and evaluation (M&E) reports for Tanzania. This report presents the evaluation findings from Arusha Region and Tanga Region based on data that were collected between 2015 and 2018. In Arusha Region, data were collected at baseline (pre-intervention), midline (about four months post-intervention), and endline (12 months… >
This report presents the evaluation findings from data collected at baseline and midline of BID implementation in sampled health facilities from the first six implementation districts in Southern Province—Choma, Kazungula, Kalomo, Livingstone, Mazabuka, and Zimba. Data collection took place between November 2016 and March 2018. Read the full report.
A theory of change (TOC) defines the activities, outputs, outcomes, evidence and assumptions on the pathway to achieve a long-term goal. For the BID Initiative, this pathway is based on the principal hypothesis that better information plus better decisions will lead to the long-term goal of better health outcomes. The TOC describes in detail the types of activities the BID Initiative is conducting to bring about the outputs and outcomes depicted in the pathway.
The BID Initiative has four primary outcomes:
Improved overall immunization data quality at scale in two demonstration countries by 2017
Increased use of immunization data for decision making across all levels of the health system at scale in two demonstration countries by 2018.
Achieved implementation of relevant components of the BID solution at scale in two demonstration countries, and commitment toward implementation by 5-8 other country governments within Sub-Saharan Africa by 2018.
Significant additional resources are committed from donors, multilateral agencies, implementation organizations, or other innovative sources for financial and technical support to countries adopting and improving the BID solution by 2018.
There are a broad range of activities supporting the achievement of these outcomes, with the activities for primary outcomes 1 and 2 focused at the country level in Tanzania and Zambia (our two initial demonstration countries) and the activities for primary outcomes 3 and 4 focused mainly at the regional and global levels to expand and scale with additional resources. For this reason, we developed two separate but related TOCs – one for outcomes 1 and 2 and one for outcomes 3 and 4. In addition, there is a supporting document that summarizes a thorough review of the literature supporting the design of the BID Initiative activities and TOC related to outcomes 3 and 4.
The December Discussion Meeting held in Arusha, Tanzania is designed to be hands on and highly participatory events that become a rich learning experience for all attendees. In this report and the presentations, we share some of the discussions around strategies and approaches to improving data, quality, and use among participating countries and include highlights around the progress made in BID demonstration countries (Tanzania and Zambia), the successes and challenges they have had, and the way forward.
A selection of presentations from the meeting are available below.
Advances in information and communications technology (ICT) have increased exponentially the amount of data that health information systems can collect, synthesize, and report. Expansion of these technologies promises to revolutionize the global health sector’s response to most pressing health issues. Even though health program managers are increasingly expected to use and invest in such strategies, many lack information about how the strategies work and how they can benefit the management of health programs. To address this problem, MEASURE Evaluation developed a glossary of eHealth strategies most likely to enhance data access, synthesis, and communication for health program managers at all levels of a health system who are eHealth novices. The complete set consists of fact sheets on: dashboards, hackathons, open data, big data & data science, geospatial analysis, integration & interoperability, and crowdsourcing.
The following summary tables represent the best estimates of WHO for a broad range of key public health indicators – based on evidence available in 2011. These best estimates have wherever possible been computed by WHO using standardized categories and methods in order to enhance crossnational comparability. This approach may result in some cases in differences between the estimates presented here and the official national statistics prepared and endorsed by individual Member States.
Community health workers (CHWs) have and continue to play a pivotal role in health services delivery in many resource-constrained environments. The data routinely generated through these programs are increasingly relied upon for providing information for program management, evaluation and quality assurance. However, there are few published results on the quality of CHW-generated data, and what information exists suggests quality is low. An ongoing challenge is the lack of routine systems for CHW data quality assessments (DQAs). In this paper, we describe a system developed for CHW DQAs and results of the first formal assessment in southern Kayonza, Rwanda, May-June 2011. We discuss considerations for other programs interested in adopting such systems. While the results identified gaps in the current data quality, the assessment also identified opportunities for strengthening the data to ensure suitable levels of quality for use in management and evaluation.
Articles in this issue show clearly the enormous impact that the use of health information technology can have on the quality of health care for children. However, they also point out the challenges that need to be overcome to realize fully the potential of health information technology to improve the quality and efficiency of health care.
Health priorities since the UN Millennium Declaration have focused strongly on children younger than 5 years. The health of older children (age 5–9 years) and younger adolescents (age 10–14 years) has been neglected until recently, especially in low-income and middle-income countries, and mortality measures for these age groups have often been derived from overly flexible models. We report global and regional empirical mortality estimates for children aged 5–14 years in low-income and middle-income countries, and compare them with ones from existing models.