If you don't know what works, there can be an understandable temptation to try to create a picture that more closely resembles things that work. In some of his presentations on the dire state of student learning around the world, Lant Pritchett invokes the zoological concept of isomorphic mimicry: the adoption of the camouflage of organizational forms that are successful elsewhere to hide their actual dysfunction. (Think, for example, of a harmless snake that has the same size and coloring as a very venomous snake -- potential predators might not be able to tell the difference, and so they assume both have the same deadly qualities.) For our illustrative purposes here, this could mean in practice that some leaders believe that, since good schools in advanced countries have lots of computers, it will follow that, if computers are put into poor schools, they will look more like the good schools. The hope is that, in the process, the poor schools will somehow (magically?) become good, or at least better than they previously were. Such inclinations can nicely complement the "edifice complex" of certain political leaders who wish to leave a lasting, tangible, physical legacy of their benevolent rule. Where this once meant a gleaming monument soaring towards the heavens, in the 21st century this can mean rows of shiny new computers in shiny new computer classrooms.
That's from this EduTech post by Michael Trucano. It's about the recent evaluations showing no impact from the One Laptop per Child (OLPC) program, but I think the broader idea can be applied to health programs as well. For a moment let's apply it to interventions designed to prevent maternal mortality. Maternal mortality is notoriously hard to measure because it is -- in the statistical sense -- quite rare. While many 'rates' (which are often not actual rates, but that's another story) in public health are expressed with denominators of 1,000 (live births, for example), maternal mortality uses a denominator of 100,000 to make the numerators a similar order of magnitude.
That means that you can rarely measure maternal mortality directly -- even with huge sample sizes you get massive confidence intervals that make it difficult to say whether things are getting worse, staying the same, or improving. Instead we typically measure indirect things, like the coverage of interventions that have been shown (in more rigorous studies) to reduce maternal morbidity or mortality. And sometimes we measure health systems things that have been shown to affect coverage of interventions... and so forth. The worry is that at some point you're measuring the sort of things that can be improved -- at least superficially -- without having any real impact.
All that to say: 1) it's important to measure the right thing, 2) determining what that 'right thing' is will always be difficult, and 3) it's good to step back every now and then and think about whether the thing you're funding or promoting or evaluating is really the thing you care about or if you're just measuring "organizational forms" that camouflage the thing you care about.