Hi there. This is producer, Piper Hale. We’re working hard for you on the October episode of Inform Me, Informatics. But in the meantime, here’s a special bonus episode. You may remember Task Force for Global Health President, Dr. Dave Ross from previous episodes, including the call-in show and this podcast’s very first episode about his journey from rocket scientist to informatician. A couple of years ago, I had a conversation with Dave about public health informatics. He explained to me that the field is ultimately about getting information to the people who need it in order to improve health outcomes. And informatics doesn’t have to involve high-tech information systems, or even any technology at all. To help me understand, he told me a story about a project he’d worked on with the Sierra Leone Ministry of Health almost 20 years ago, a little after the country’s decade-long civil war had ended in 2002. This conversation was recorded, and I wanted to share it with you today.
People often ask me if public health informatics means using information technologies. And my answer is, “not necessarily so.” It means that we can produce information that informs action, so we’re giving information to the people who need it in a timely way, when they need it, and in a way that leads them to take actions that produce outcomes in health that matter. Does that mean that you have to use electronic technologies to do that? Not necessarily so.
So let me tell you a story. So this was around the time that the Bill and Melinda Gates Foundation had funded the World Health Organization to create the Health Metrics Network. And in that effort, they were reaching out to a number of countries in Africa and Asia to help them conceptualize what a national information system might look like. But in the course of this, the staff that worked with the Health Metrics Network came to know Dr. Clifford Kamara, who was the Minister of Health in Sierra Leone, and began a conversation about what some of his problems were.
So his biggest problem was that he needed some facts about infant and maternal mortality, about how many babies were dying, and how many mothers were dying or having complications that led to additional medical care. And that was clearly one of their major national health priorities. But he had no facts, and he had to get them. So how do you get them? That was his challenge.
So this ensued then conversations that uncovered what were the essential requirements? And what were the conditions in which his information solution had to function?
The medical care often, that was available, was a traditional birth attendant. And often these traditional birth attendants were illiterate. So you had a minimally trained workforce that weren’t able to take on traditional, kind of, training materials or use systems that required reading and writing. So that’s a big constraint. So how do you develop an information solution that produces timely information, that’s granular and accurate to the level of the village or the district that would tell you how high the mortality is? And do that in a way that would produce information to the district level, provincial level, and ministerial level officials fast enough to help them start to make decisions of where they allocate the limited dollars they did have to posting nurses, a few physicians, building a facility?
Where do you do that? How do you do that? That was the problem. So we helped Dr. Kamara. He had these constraints of limited time, limited money, limited workforce, absence of electricity. And so the information solution then has to be workable in that context. And that led down to the really creative thinking, and I think, and in fact the credit goes to the people of that country who worked in the ministry, who came up with the answer.
And the essence was, did the baby live? Was it stillborn? Or did the baby die? Did the mother live or did the mother die? And if mother lived, maybe she had complications and they had to carry her off to a hospital. So they ended up concluding that if they had those five data points…so basically, choose between, for the baby, alive, stillborn, dead. The mother, alive, death. If you knew that and you knew it in a very timely way, like every week, you could start to see if there were patterns emerging and if you’re getting hotspots in fact, right?
So how would you do that? The answer became this, what you’ve called the box of rocks. But it was a counting box, it was a counting device. Essentially they said, “Well, best way if somebody can’t read, is look at the picture.” So you have icons that describe each one of those states. And the instruction then, the training, is pretty straightforward. You teach the birth attendant that after the birth, and you know what’s the disposition of the baby and the mother, go out into the courtyard and pick up a stone for the baby and another stone for the mother, and come in and you’ve got this box. And there’s a trapdoor with a hole in each cell, if you will, underneath each icon and you put the rock in the right box. If the baby’s alive, drop it in that cell. If the baby was stillborn, drop it in that cell. If the baby died, drop it in that one. Similarly, for the mother.
And at the end of the week, open up your trapdoors, count the number of rocks and put hash marks on a piece of paper that has the same icons. And then keep that piece of paper, and a man from the district health office will come by on a motorbike and pick up your sheet of paper. And you start to see the accumulation of basic statistics, basic data counts, that allow you to know that, within a given population, with an estimate of how many people live there, you start to get a birth rate. You get a death rate. You get maternal mortality rates. And then these data show you the picture at the village level, at the district level, the provincial level, and the national level.
And very quickly the Minister of Health then had his map of the country on his wall with pins, basically what we would call an intensity map, that started to show where the hotspots were. Where the highest mortality was for kids and moms. Which led them, within matter of months, and I think it was like six months they started to have enough data, to start to say, “Look. We ought to put our nurses here. We ought to put our facilities here.” So that information led directly to the allocation of resources, and those resources started to change mortality patterns. So I would challenge that anybody who’s developing public health informatic solutions, use this kind of case as a way to say, “Does our solution produce timely data that’s as good as what they did in Sierra Leone? Does it produce granular data? And will those data get used and translated into an action that changes health outcomes?”
To me that’s kind of the gold standard. The country Sierra Leone, in my view, built one of the best information solutions I have ever seen. And guess what? It doesn’t plug into a wall. It doesn’t have blinking lights. It’s not electronic, but it’s an information solution that produces real health outcomes. And I think that should be, kind of, one of our gold standards.
Many thanks to Dr. Dave Ross for sitting down with me back in 2015 to record this conversation. Even without a plan for how we’d end up using that audio. Dave is unfailingly generous with his time, which I’m continually grateful for. This podcast is a project of the Public Health Informatics Institute and the Informatics Academy. Visit www.phii.org to learn more about all of our informatics work. You can also find us on Facebook and follow us on Twitter, @PHInformatics. Thank you to Michole Kemp, PHII’s former video production intern for recording this conversation. Thanks also go to my rockstar co-producer and this podcast’s host, Jessica Hill. I’m Piper Hale, and you’ve been informed.
No, that’s not a big deal. You stick a pencil around it and you roll the worm out.
Yeah! Like a fishing line.