Research, Monitoring, and Evaluation

Public health policymakers and managers need sound data to guide planning, manage programs, and track performance. Countries and health institutions require systems and people that can use evidence to solve health problems and ultimately improve the lives of men, women and children around the world.

JSI examines and evaluates complex development challenges using quantitative and qualitative methods across multiple countries in close collaboration with local and international health actors. JSI strives to enable countries to respond to emerging program challenges using real time data through adaptive management practices. Analyses are designed to inform technical and organizational policy and practice at both the country and global levels, and have been conducted for USAID, the Bill & Melinda Gates Foundation, UNICEF, UNFPA, and other public and private institutions.

JSI works to improve the quality of health data, increase evidence-based decisionmaking, and respond to the growing demand for information-driven health services planning and management.

Program, Policy, and Impact Evaluations
JSI develops evaluation strategies tailored to program needs, and conducts program, policy, and impact evaluations for projects in Africa, Asia, Latin America, and Eastern Europe. JSI also conducts implementation research to assess the effectiveness of different health service delivery models and integrates continuous learning into program strategy.

Data Quality
JSI works in the U.S. and internationally to build robust health information systems that capture data in a timely and reliable manner for evidence-based decisionmaking. JSI has designed tools to assess M&E capacity including data quality audit tool (DQA), routine data quality assessment tool (RDQA), the monitoring and evaluation systems strengthening tool (MESST), and Performance of Routine Information System Management (PRISM) (many developed through the MEASURE Evaluation project).

Capacity Building
JSI is committed to strengthening the capabilities of partner organization staff in the collection, analysis and interpretation of data to make informed programmatic and policy decisions. Illustrative collaborations include RHINO (the Routine Health Information Network) and the Strategic Information for South Africa Project.

Human Centered Design
As global health challenges and new technologies evolve, public health solutions and the way we capture their effects must be creative, data-led, and most importantly, people-focused. At the heart of JSI's work is human centered design (HCD), a process that fosters innovation, prioritizes learning, and puts people at the center of public health solutions.

To learn about ongoing monitoring and evaluation work, read staff posts on JSI's blog, The Pump.


View details: Ethiopia Data Use Partnership

Ethiopia Data Use Partnership

EDUP strengthens the collection and use of high-quality routine information to improve the quality, efficiency, and availability of Ethiopia's primary health and nutrition services.

View details: Community health information system in action in Ethiopia

Community health information system in action in Ethiopia

Community Health Workers in the Southern Nations, Nationalities, and Peoples Region of Ethiopia implement an efficient community health information system at their health post after receiving training through MEASURE Evaluation HMIS Scale-Up project.

View details: MEASURE Evaluation - Strategic Information for South Africa Project

MEASURE Evaluation - Strategic Information for South Africa Project

MEval-SIFSA is building the capacity of the South African government, PEPFAR, and their implementing partners to produce information that contributes to sustainable policy, planning, and programmatic decisions.

View details: MEASURE Evaluation

MEASURE Evaluation

As a MEASURE Evaluation partner, JSI has provided technical support in developing countries to build the capacity of individuals and organizations to collect and analyze technically sound data, and use that data for health decisionmaking.

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