Thank you very much for inviting me.
Last year $8 trillion was spent for health care globally, with $2 trillion to lower- and middle-income countries. As well, $30 billion, a massive number that sounds small only when you compare it with these huge numbers, was spent on global health by the aid community, including USAID, UKaid, us, the Gates Foundation, and the Global Fund. About two billion contact points between people and a health care system occurred last year, meaning contacts between a patient and a doctor, a nurse, or a health worker.
At the heart of this massively expensive and complex system touching so many lives is a damaging dysfunction that I want to tell you about and that I think Canada can address as a theme. For people spending all of that money and managing all of those health care systems, there is next to no data going to them about how that money was actually spent and the kind of care that was actually delivered.
You hear that and you wonder how that can be. There are electronic health record systems, and health care IT systems, so how can there be no data? But when you're thinking about that, you're really thinking about hospitals and major medical centres. Those are the guys with that technology. But only about 5% of all of the two billion health care interactions I just mentioned occur in hospitals, while 95% occur in decentralized health care facilities—clinics, offices, and little health posts. Even in the U.S. it's no more than 15%. The vast majority of health care is delivered in decentralized facilities and the vast amount of money is spent there. Yet only approximately 5% of the data we have about health care comes from there, and 95% of all health care data we have over the last decade comes from about the 5% of where our health care happens.
It's not possible for any system organized like that to be spending the money wisely. There's a big data disconnect between where the vast majority of health care is delivered and the vast amount of money being spent. How can that be? Why isn't there more data coming out of clinics?
To understand the answer to that, just picture a clinic. You will picture, probably, hundreds of patients waiting to see a couple of health workers whose supervisors, by definition, are somewhere else, because that's the definition of decentralized health care. Now let's picture the health worker seeing patient number 22. In that short conversation, a tremendous amount of valuable information occurs about how the whole system works and the demographic needs of the population. At the end of that session, when patient 22 leaves, there's a data dilemma. This busy health worker can either stop and record all of what just happened with patient 22, or she—it's mostly a she—can go on to see patient 23. They go on to see patient 23 because there's no time to capture the data. In that moment, multiplied by several hundred times a day in that clinic and in millions of clinics, all of that golden, valuable information is gone.
If the health worker doesn't capture the data at the moment of care, no one gets the data—not their supervisors, not their funders, and not the World Health Organization. The result is a mind-boggling situation where you have trillions of dollars being spent and we don't know exactly how, and you have millions of health workers being very busy but we don't actually know what they're doing.
Fio Corporation is a Canadian company that has solved this problem and is scaling this solution globally. It's a solution that I'll describe briefly and then get back to the main problem. It's simple, it's sustainable, and it's scalable. Instead of the arrangement where delivering health care competes with capturing data, there's a technological way of having the delivery of health care drive, in an automatic way, large-scale data capture so that the result is unprecedented amounts of data for people responsible for the health care system and their funders and other stakeholders.
I have a visual aid here. This is a rapid diagnostic test. We don't make these things. Last year 800 million of these were sold, and that's growing at 20% a year. You squeeze a little blood out of a finger, put a couple of drops there, put in a little buffer, and then in some time, if this thing changes colour, it means you have tested positive for the Zika virus. That little test on the spot can tell you if you have Zika.
This is for malaria. It's the same thing for HIV, dengue, and so on. There are hundreds of millions of these a year. Health workers do this. Do they do this accurately? Nobody really knows. We've created a set of mobile smart devices that go into the hands of health workers. This is an example. It has a little drawer. After you prepare the test, you pop it in and it will read this test with a level of accuracy equal to that of a centralized laboratory. It's highly accurate.
It will guide the health worker. How do they even know which test to give? Well, there's a whole bunch of Q&A involved, and it will guide the health worker through that, and by offering questions and having answers that the health worker just touches as soon as the patient speaks, basically, as the health worker is delivering care, it is automatically entered as a by-product of that process. It is uploaded to a cloud from which managers overseeing these supervisors can be looking at their tablets or smartphones, and it is as if they are hovering over all of the thousands of clinics they're responsible for and they can actually see what's going on. It's a new level of accountability and transparency. It interconnects a continuum of care.
Cellphones became smartphones when they fused data and email with calls. These devices are fusing data with diagnostics and other care delivery. It's the same thing, and once they're together they won't be pulled apart.
The results from the field are a ten-fold reduction in diagnostic errors made by health workers within weeks. There's been a ten-fold increase in the accuracy of the care they give. Just because somebody gets the right diagnosis doesn't mean you get the right drug necessarily.
There has been a twenty-fold reduction in unnecessary patient visits. If you misdiagnose a patient and they're still sick, they're smart, and they're going to come back. If you give them the right diagnosis, the right treatment, they have better things to do than to come back.
There's been a twenty-fold increase in epidemiologic accuracy. For example, in a certain region of Kenya, they believed that malaria incidence was 17%. Think of all the drugs and tests the government must order for 17%. They installed our devices and found it was 0.7%. All those people with fevers didn't have malaria.
Africa spends approximately $1 billion per year on anti-malarial drugs for people who do not have malaria.
We're scaling this technology in a number of countries, and I guess this begins to get at the question that was posed. We're in Colombia. We're in Brazil, where we're working on the Zika problem. We're talking with Honduras and Ecuador. In west Africa we're in Ghana. We just entered Nigeria, where ExxonMobil—and this is a very interesting opportunity in which dollars are matched by the private sector—is doing a pilot in the Niger Delta.
In east Africa we're in Kenya, Tanzania, Uganda, and Ethiopia. In central Africa we just launched in the Democratic Republic of the Congo where people who are literally in the middle of nowhere to the rest of us are getting laboratory-quality care delivered with clinical expertise through these devices. We are in South Africa and Lesotho, and we are about to start a pilot in India with the largest private health care provider.
We are working in Europe with the largest diagnostic company, and the same in the United States. In the United States, the U.S. Department of Defense has us in about a half-dozen projects. We also work with the Gates Foundation and the Global Fund. We're in programs that deal with malaria, HIV, maternal and child health, and primary care. I tell you this list because we started relatively recently, and yet we have had such a response with this business of health care data from decentralized places and not hospitals that we're on to something.
You're contemplating a strategy of selected countries versus themes. When Fio came into being and started from scratch on this in 2010, we were in a world that had, to use a well-known phrase, “separate solitudes”. There was data and there was care delivery. You had to choose. It was data versus care. Our solution is based on realizing that there's a way to make it data and care—the fusion of care and data. Global health care data is a theme that can result in profound leverage when it's added to selected countries, because it's a sector that impacts all other sectors.
We always fly the Canadian flag whenever we do business anywhere. Canadians are known for being a measured people. Let's be known for measuring health care data. It's a wide open field. It's estimated that in the next five years there will be fifty times more health care data than today. It's a field in which tens or hundreds of millions of dollars of spending can impact hundreds of billions of dollars, or trillions of dollars, of other spending and outcomes. It's a very big bang for a very little buck when it's combined with selected countries.
Thank you very much.