Our Work

MEASURE Evaluation’s mandate was to strengthen health systems in low-resource countries to enable collection, analysis, and use of health data; improve capacity to manage health information systems; engage countries with useful methods, tools, and approaches to address health information challenges and gaps; and increase their capacity for rigorous evaluation. We worked within existing systems and address the most pressing health needs as we improve health information overall.

Under optimum conditions, public health relies upon a network of facilities staffed with competent providers, a ready supply of essential medicines, and a governance structure supported by managers who understand the health issues of the population and are equipped to make good policy and program decisions based on evidence.

To learn how this work is continuing after the MEASURE Evaluation project, please visit Data for ImpactPMI Measure Malaria, and TB DIAH.

This optimum scenario is built, top to bottom, on data—data about each patient; data about provider performance; data about disease prevalence; data about best treatments; data about supply chain and proper medicines; data about health trends; data about health program performance; and data about health policy and resources. Said simply, behind good health for every person is a system reliant on information that is shared and used.

MEASURE Evaluation worked in this arena in low- and middle-income countries to strengthen health systems to perform this role. We researched health system performance; we built human capacity to do this work; and we built evidence of what works. To achieve the greatest health, public health practitioners and policy makers must be able to use data to perform these six essential functions:

  1. Monitor trends in health outcomes and services. Data should provide information on disease prevalence and health service delivery to show what services are needed, how they perform, and if they reach the people who need them. We assist countries to develop or adapt data software that perform this role.
     
  2. Ensure that data are trustworthy. Health programs and health policies overall will be off-base if data can’t be trusted. Data give the picture of what is happening; data that can’t be trusted calls the entire system into question. We conduct data quality assessments and build capacity to generate and use high quality data.
     
  3. Make decisions quickly and efficiently. Data must be responsive to the “now.” If data are weeks, months, or even years late in arriving, they give a false picture at best and, at worst, are useless and ignored. Current data safeguard against epidemics or crucial gaps in health services. We work with information and communications technologies that make possible real-time data collection, analysis, and use.
     
  4. Identify what works. Health systems are particular to local contexts. What works in one place may not perform as well in another. Data should show what programs and policies are yielding good results in a particular place. We conduct rigorous evaluations to find out what works; we help design “fixes” for under-performance; and we feed our learning into the global understanding of what strengthens health information systems.
     
  5. Ensure the coordination and equity of health services. Health services in low- and middle-income countries are typically provided through a mix of government, private, and donor interventions. Data should show if geographic coverage is unequal, or if some diseases are getting more funding; or if there is an inequity in health services for different populations. We help assess if there are gaps in health services or inequities in who is served.
     
  6. Manage resources for the greatest benefit. Data need to show what resource constraints exist in a given health system and, correspondingly, show managers what needs are most urgent. Resources in health systems are usually limited and data are essential to make good decisions on how to allocate them. We assist in research, data analysis and use, and building staff capacity to interpret data to manage scarce resources.