If you’re a scientist, and you have to have an answer, even in the absence of data, you’re not going to be a good scientist. –Neil deGrasse Tyson @neiltyson
Data can do a lot. It is an essential component in reaching global health equity. It provides the tools for the mapping of where diseases are and how they affect communities (spatial epidemiology). It creates an understanding of where funding allocations are best spent to further strengthen health programs and increase effectiveness. And it allows for solutions to be catered towards community needs through impact evaluation. Despite these advantages, it has been made clear by a growing concern for the collection of data by NGOs, private institutions, and the global healthcare workforce, that problems exist with evaluation and essential feedback mechanisms that will improve efforts and initiatives. Many organizations that provide health services do not have the resources to quantitatively analyze the impact of their intervention and determine what influence their work has on the health of a community. How effective are the vaccines administered at combating disease? Are maternal health services truly improving infant and maternal mortality rates? Continuous evaluation of programs and initiatives is vital to understand health outcomes and positively change them.
In 2012 The Children’s Prize launched an open call for it’s one million dollar prize to fund the most impactful, credible, and cost-effective action plans for reducing child mortality. After reviewing the 565 applications, it became clear that that many of the applications lacked any sound data to back up the impact of their solutions and relied on anecdotal evidence to validate the success of their interventions. Of the 50 most comprehensive applicants only twenty presented evidence of both suitable data usage and evaluation of their proposed intervention. Applicants used limited health monitoring techniques including baseline and endline surveys, third party evaluation, and consultation. Monitoring techniques that if implored could increase the success and scope of a given project. For example many organizations would collect data on patient interventions (200 children under five were given X treatment during 2013) however, without baseline data to corroborate the effectiveness of health interventions, or comparisons of surrounding populations that did not receive the given intervention, substantiating evidence was impossible.
Data for Life, a new $100,000 initiative that expands the focus of the earlier $1 million Caplow Children’s Prize, was created to increase the impact of data for sound project evaluation. It provides mechanisms to increase capacity, while simultaneously rolling out life saving interventions. Data for Life is a steppingstone for successful solutions that must come from a data driven understanding of community and individual health needs. Populations around the globe possess differing qualities that can influence the success of a program including age, gender, income levels, and the prevalence of diseases, among others. These socioeconomic conditions all play a role into which solutions should be implemented and in what communities. Properly using data can help prevent costly and ineffective programs from evolving and ensuring that evidence-based successful interventions can be scaled up. To better structure implementation plans, effective evaluation of datasets is a must. After all, you cannot improve want you do not measure.