The Child Health and Mortality Prevention Surveillance (CHAMPS) network is an ambitious global project that seeks to reduce childhood mortality around the world by identifying what exactly is killing children under five. Project partners have established surveillance sites in seven countries across south Asia and sub-Saharan Africa to determine causes of death for children in those catchment areas. Informatics is crucial to this project, as the informatics office provides the core infrastructure for transporting and housing key health data. My colleage, Senior Manager for Information Technology Patrick Caneer, recently sat down with me to walk me through how PHII and its partners manage data for CHAMPS.

CHAMPS partners include the CDC, Emory Global Health Institute, the International Association of Public Health Institutes, Deloitte, and numerous ministries of health. The project is funded by the Bill & Melinda Gates Foundation.

If you haven’t subscribed to Inform Me, Informatics, you can do so on iTunes or Soundcloud. We’re also now on Google Play and Like the podcast? Please consider rating us on iTunes! This will help other listeners find out about the show.

Patrick Caneer



Hi, this is Piper Hale, and you’re listening to Inform Me, Informatics. A quick note before we dive into the show this time: this episode deals with the potentially distressing topic of infant mortality in some level of detail. It’s a difficult topic to discuss, and if that’s a subject you or those around you may find difficult to listen to, you may want to skip this one.

PHII runs the CHAMPS informatics office. I recently spoke to Patrick Caneer, the Senior Manager for Information Technology. He explained the purpose of the project and the key role informatics plays in understanding the lead causes of death for children under five across the globe.


The kind of problem statement is that childhood mortality, especially with children under five, is a huge global burden. There’s been great strides made in the last several decades. It’s almost been cut in half. However, it’s still atrociously high and especially in some third world countries.

So, the challenge is to cut that in half again, but in order to do that, there needs to be more precision information and that information needs to be a little more timely so that action can be taken. So, really, the challenge was how do we get more definitive causes of death and kind of hotspots or regions that are representative of the continent and begin working in those locations to start gathering that information and try to get it in the hands of people who can use it either with innovation or to take action.

It’s not just the Gates Foundation. We’re working very closely with ministries of health and local public health agencies referring to this data to action.

So, we wanna try to get that information to people locally as well as people globally to start making a difference both at a grassroots level but also at a country or a continent level. Well, our first big challenge in the beginning was just trying to figure out what exactly are we going to set out to do to accomplish this.


CHAMPS is based on the idea that multiple kinds of data are necessary in order to determine what causes a child’s death. For each reported death, the project assembles data from biological samples, pathological reports, other health records and information from family members. CHAMPS then packages this information so that expert panels can review it and determine the cause of death. In this way, we can learn more about what drives infant mortality. Additionally, the information is sent back to Ministries of Health and health care providers in the communities where CHAMPS is operating so they have a better picture of their population’s health, and ultimately, so they can develop interventions that will prevent future deaths.

I asked Patrick to walk me through how that information is collected. He will mention a few specific data collection tools that I wanted to take a moment to explain. First, Patrick will mention MITS, which stands for Minimally Invasive Tissue Samples, which is a term for a kind of non-invasive autopsy. He also talks about TAQman Array Cards, which are rapid diagnostic kits that allow biological samples to be simultaneously tested for multiple diseases.


So, our role is to facilitate and kind of orchestrate and coordinate this exchange of information. So, it begins with a death notification. So, a child has passed away either in a hospital or somewhere in the community. So, we need to facilitate people calling the local CHAMPS team or texting the local CHAMPS team or bumping into the CHAMPS practitioner in the hospital and saying, “Hey, there’s been a child that may qualify for this surveillance.” So, we gotta manage the notification and then we need to determine if that child is truly eligible. So, do they live in the area that we’re studying? Are they really under five years old? You know, things like that to kind of pre-screen, are they qualified to participate?


From there, we need to get consent from the family to do the procedures as well as to follow up with verbal autopsies and also to get consent from the mother if we’re going to look at her medical records. That information all has to be managed and coordinated. Once we have consent, then begins the gauntlet of data collection. So, it’s all the laboratory values that are done, which includes TaqMan Array, which is a kind of innovative new test that we’re doing, as well as all the clinical abstractions that I spoke about as well as the verbal autopsy, bringing all that together and finally presenting that information to a panel of experts. We refer to them as a “decode panel.” They’re decoding the cause of death. And we present all this information to them, and they debate and review the case, and make a final judgment using all the information we’ve put together to say, “This was the definitive cause of death.”

So, they look at what we refer to as a causal chain. So, they try to determine the immediate cause of death, but also look at underlying factors or maternal factors that may have contributed to the death and other morbid conditions.

So, an example might be, a child may have died of malaria that might have been the immediate cause of death. However, through testing, we found that they were exposed to HIV and tuberculosis, and they may have been malnourished. So, there’s a lot of compounding factors. It may just be that one particular…say, malaria during the summer was the tipping point, but there were a lot of other things going on that made the child more susceptible to malaria that season. So, it’s a kind of a richness of data that we’re bringing that tells a little deeper story, but it also is backed by, you know, laboratory results.


Great. So, what are some innovations within CHAMPS that you’re particularly excited about or proud of? You mentioned TaqMan. Do you wanna say more about that and also any other innovations?


Sure. First and foremost, I think it’s just the overall standardization.

I mean, we’re running now in five countries. We hope to be soon up in two more. So, actually just bringing consistent information in a very timely fashion. It’s not fancy technology, but the fact that we’re working with the local people in each of these countries to turn this data around so quickly, that in and of itself, is an innovation even though, again, the technology is not that hard.

My colleague, Wais Said has done a great job in the last couple of years working with the Centers for Disease Control experts and the World Health Organization to come up with a way to organize version control and translate the WHO standard verbal autopsy instrument. Again, it’s not fancy technology, it’s not highly innovative, but it’s a consistent process that Wais has put in place. And that’s really sped up the time, but it’s also provided a really efficient way, provide local language versions of a standard document. 

The TaqMan Array work which Tim Morris and Joanna Boyles and Greco Johnson have worked closely with one of our vendors on is coming up with an algorithm. So it’ll say, “These combinations of diseases or this disease was positive or negative,” for those that are very straightforward. For others that are very complex, so it may be a combination, if test A and B are positive and test C is negative, it’s this disease, but if tests A and B are negative and C is positive, it’s this disease. So, there is a decision logic that has to take place.

It runs through that logic and provides a result and also cues all that information up for a human to then review it one more time.

So, it allows experts in the CDC to double check those results or override results or invalidate or validate those results. And that’s been a tremendous innovation to speed up how that works, but also to kinda make a standardized way for all these sites to provide this data and us to provide quality answers back. We just rolled that out to our CDC colleagues actually just about a week ago, and in our discussions, you know, they mentioned that they’ve had some very large for-profit contract groups trying to solve this problem for a number of years since the early 2000s. And our team, I think, has kind of cracked the code and I think, you know, the proof’s in the pudding. We’ll see.

One other innovation — again, not horribly difficult, but I’m excited about — is the data quality efforts being led by Joanna Boyles and Tim Morris and myself, and that’s working with the sites.

We’ve been receiving data for almost a year and we’ve been running data quality checks and looking at the information providing queries back to the sites. But we’re getting to the point now where we’re starting to empower and provide tools to the sites where they can do the data quality checks themselves first. So, we kinda have a double quality loop where they look at it first and it comes to us and we look at it again or we’ll take some of the harder queries, things that may go across different data sets to provide queries, and we’re really starting to see the data quality that’s coming from those locations begin to improve. And it’s a little nerdy, but it’s… The higher quality information we get, the faster we are able to put it to work.


So what do the data flows and the data capture process look like from a technical perspective for CHAMPS?


So the flow is really from time of death to a panel that makes the decision. Along that route, we’re using case report forms. So at most of our sites, we’re facilitating case report form data capture in REDCap, which is software developed out of Vanderbilt University.

The verbal autopsy, which is a standard we’re working with the World Health Organization on, is exclusively done on ODK, Open Data Kit, so our primary toolset is REDCap and ODK. That information is collected at each of the stages. So death notification, eligibility, consent, laboratory information, verbal autopsy, again on the ODK, and that is stored locally on their own servers at each of the sites. We provide a set of API scripts that will extract the information out of REDCap, capture the data in a format that then can be used by the data managers to send us what we refer to as packaged data files, or grouped data files.

We then use a set of scripts here in Atlanta, or locally, that then review and validate those files, so to make sure, is it the right file type? Is it what we were expecting? Does it have the right columns? Does it have the right variables? Is the data within the columns—does it makes sense? Do we have dates where we’re supposed to have dates? Do we have flags where we’re supposed to have flags? That’s then evaluated, transformed, processed, and stored in a relational database using Microsoft SQL. So that is stored here in Atlanta in a large data repository, a server. Here in Atlanta, we can then use that relational database to generate reports, transfer information, generate dashboards, etc. So that’s our global repository for that information. As I stated earlier, that same information is stored locally.


That’s terrific. So, what outcomes have you already seen in CHAMPS, and what outcomes do you anticipate in the future?


I think the biggest thing that we’ve seen in the last couple of weeks that’s been exciting is we were really slow to ramp up, but in the last couple of months we’ve seen, of our five locations that are doing the MITS procedure, we had all five locations within the matter of a two- to three-week period, actually do a decode panel at the same time.

We’ve been doing them one by one, but to have them all kind of happen simultaneously in different countries and kind of see it all come together where everyone’s in a cadence so there’s enough cases, there’s enough data flowing and they’re getting in the rhythm of doing their decodes on a regular basis, that was a huge accomplishment for our team.

The first couple were with our initial or flagship sites that started out and they were…everybody was focused on the first one and then everybody was focused on the second one and they were staggered. But then in the last couple of weeks, we’ve really seen the network kind of come together and were able to handle all that simultaneous data flow and decisions. So, it’s really starting to see it all come together and mature to a point where, you know, we’re ready to kind of take on the growth.


Great. And for future outcomes, I don’t know how much you want to speculate on those, but what do you see this data doing down the road in terms of how it will be used, you know, to combat childhood mortality?


Sure. I think, as I mentioned earlier, we were kind of slow to start. So, we’re just really getting that first kind of wave of information, and so that in turn is we’re just now facing the opportunity to turn and share that information back. There’s some anecdotal stories of, you know, information being provided back to facilities about some infections that may be occurring. There’s, you know, small things here and there that are starting to work. There’s, you know, things that we’ve found on an individual basis, like someone may have had tuberculosis exposure or HIV exposure and that’s, you know, giving that information back to the family.

But on a broader scale, I think that’s yet to come, simply because we’re just getting the volume to make it necessary and to be able to start sharing that data back with the ministries of health. Some of our locations have only done five or six cases that have reached the end of the line. Others have gotten to the 100-150 range. So, we’re starting to reach that volume where it starts to make sense.


I do think a lot of listeners will be wondering about, you know, going in and working in these developing countries and dealing with a sensitive topic. How does CHAMPS operate within these five catchment sites in a way that they can ensure is culturally sensitive, takes into account family needs, you know, maybe grieving families? Like, what sort of protocols do you guys have in place to account for those needs?


Sure. We have a social behavioral research group that’s led on both by our colleagues from the Centers for Disease Control and Emory Rollins School of Public Health and the Emory Global Health Institute. And they really are kind of our pre-arrival team. So, they do a lot of work. And I’m simplifying it, but they do a tremendous amount of work of identifying and working with community leaders, having community meetings, and really taking a pulse of the community and asking questions and preparing for, would the community accept these practices? Would an autopsy of a child be acceptable? What to expect if they were to occur. Religious concerns.


It’s an ongoing process, so it’s not the social behavioral team comes in, provides a report and leaves. It’s an ongoing, ever-present theme to CHAMPS and it is constantly, as we provide feedback on the death, making sure that families understand the information that’s being provided back to them and make sure expectations are met.


So, we have a lot of listeners from different backgrounds, you know, public health agencies, public health organizations, some of them are public health students. Is there a lesson or success story from CHAMPS that you think our listeners could think about replicating in their own work?


Sure. I really think, first, it’s kind of simple stuff. It’s universal, but first is keep the end goal in mind.

This is a very complicated project, and there’s lots of moving parts and lots of information coming from different places at different times, but I think one of the things that kept us grounded is, at the end of the day, what are we looking to accomplish? We’re looking to provide a definitive cause of death for children under five in these locations using all the data we’ve collected. But the end result is really 10 to 15 fields of information that are backed by all the expertise and all the testing that went into making that decision, and so, kind of keeping focus. There’s lots of opportunities for scientific exploration or exploration or let’s use this method or let’s try this test, but really trying to stay focused on does that contribute at the end of the day? Is it the information that this panel of experts needs or is it something that would be nice to have later?

So, really keeping the end in mind, that’s something that, to me, always benefits any kind of large problem or objective you’re trying to accomplish. I think the other thing is other simple stuff. It’s just listen, observe, and understand the problem.

Really focus on trying to figure out what it is people are trying to do and as an informatician or as someone who’s trying to, you know, move information from one place to another, is don’t jump in immediately with, “Hey, you can put this on your phone. There’s an app for that.” You know, kind of solution is to really listen, watch what’s happening, observe. So, it’s about a methodology. Technology will change over time, but kind of a problem-solving methodology or approach, that’s really the skill set and the discipline that we bring to the table to help find the solutions. 


We’re providing through our processes and the data collection instruments that are being facilitated a large amount of information that’s not usually available to people considering what the cause of death was in the context of day-to-day life. This is what makes CHAMPS special, is that we’re bringing together a considerable amount of evidence, it’s being brought before a group of experts that then have the time to consider that evidence, discuss that evidence, and say based on what we’ve been presented, we have, to the best of our ability, to determine this is the definitive cause or underlying cause of death is, based on the evidence we’ve been provided.

It’s that richness of data and that discussion, and that brain power that’s happening in discussing that information, that makes CHAMPS data a little different. There’s no way that anyone could do this for every child death around the world. The hope is that the sample sizes that we’re providing and the contributions these groups make over time will inform other instruments or other similar cases with less information, form algorithms that may help us use small sample sizes of data with this level of specificity to make projections in the future. At the granular level for the individual cases in the local communities, it provides a very definitive cause of death and some, I would guess, relief to some of these families, that we determined it was this that caused your child’s death, and this is how this death may or may not have been prevented, and by the way, because of what we learned, from the gift, if you will, that you gave of allowing our teams to research the death of your child, we were able to make these small or large or impactful changes, either in our current community or our hospital, or perhaps our country, depending on how that plays out.

One more thing. I think that it’s important to know that it takes a huge effort. It takes not just myself or a team of three or four people that are informatics people. It takes a huge team. We have software developers in Wisconsin and there’s a team of people there. We have our informatics team, but we can’t do it without all the skilled scientists and public health workers and epidemiologists and community leaders. It’s really a huge amount of people to make all this work, and we’re just a small part of it. CHAMPS is, again, kind of a monumental effort, but it takes everyone working together in concert for it to work.


At the end of our discussion, I asked Patrick the question we ask all our guests on the podcast: how do you define informatics?


I kinda think of it as getting the right information to the right people at the right time in really the most efficient or pragmatic way. I said earlier in our interview that I kind of felt like the technology changes frequently, but usually, people’s needs for information don’t. It’s just the speed and the precision which they need it may change. So, I think it’s really being able to step back, observe, listen, and like I said, get the right information to the right people. Determine what that is and get it to them at the right time.


Many thanks to Patrick Caneer for taking the time to speak with me about CHAMPS! I’m also grateful to Tim Morris, Joanna Boyles, Andie Tucker and Ellen Whitney of the CHAMPS team, who all helped me out with background information for the show.

This podcast is a project of the Public Health Informatics Institute and the Informatics Academy. Visit to learn more about all of our informatics work! You can also find us on Facebook and follow us on Twitter @PHInformatics.

If you enjoy the podcast, please consider leaving us a rating on iTunes! Thank you to those listeners who have already written in!

The music used throughout our show was composed by Kevin MacLeod. Thanks also go to Jessica Hill, my co-producer on the show. Statistics used in this episode were sourced from the WHO, CDC and UNICEF.

I’m Piper Hale, and you’ve been informed.



Should I use my real voice?


What is your not real voice? Can I get a preview of that, see which one I like better?

Copyright © 2021 Public Health Information Institute | All rights reserved