Q: I see many one-off research projects, which may work in one country or one clinic or one disease. how do we break down these silos ?
A: I think it is very easy to fool oneself to think something works. What system will help people take their drugs? It is a good problem to work on since the scale of the problem is gigantic. There are problems which affect millions of people. These include vaccines, Tb diagnosis, Tb treatment. The lens of “did it work” needs to be a tough one. There are many variables, including infrastructure, etc. One thing about taxonomy: rich vs. developing world is sometimes appropriate but usually not. The middle income countries such as China, Brazil, South Africa, parts of India, Indonesia are where the most health innovation is occurring. The rich countries are very conservative — unless you work in an HMO, prevention is not reimbursed. Many of these things will work first in middle income countries. Do it there first and then scale it up.
Q: It is clear that much funding goes to high end things. What is the value proposition to get people to target lower income populations, even in America ?
A: What the health care system does wrong for the poor in America is different than in poorer countries. There will definitely be a market for people who already want to work on their health and but want to do more. Some people want to go from 95% rate of exercising to 98%. I hope you make a ton off of those people (laughter).
But will it affect the person who exercises 0% of the time ? Maybe the phone won’t make any phone calls until you do some pushups (laughter). There may be incentives for employers to affect behavior of employees. The ability for a phone to monitor activity and track old people may help seniors stay out of long term care. I dont think it is good to narrow down solutions to a very small population, these may not scale.
Q: What will keep this investment going once philanthropy scales back
A: It helps to have patients pay for this. If apps change behavior, money will flow. Where incentives are aligned, payment will occur. We don’t yet have that kind of exemplary thing. Microsoft and Google are both developing personal health records, this is part of the solution. If there is a benefit, people will pay for this.
Q: Education and health are linked. Can you speak about the Foundation’s efforts in education and its effect on health ?
A: I considered getting a college degree (laughter). My friend had a simpler method for dealing with health and education. He heard that exercising led to longer life. Also, longer living parents were correlated with longer life. So, he made his parents exercise (laughter). A lot of what you do depends on your time horizon. In South Africa, we partnered with the Kaiser Foundation to combat AIDS. We found that awareness of AIDS was very low in teens, which is often when the diseases was acquired. So we raised awareness. We were the biggest billboard buyer in the country. People could then explain how AIDS was caused but there was still no behavior change. The problem was the time horizon, the effect of AIDS was 7-8 years out from its acquisition. if it killed immediately, it would be better because there would be piles of bodies outside of bars, people would think twice before going in (laughter). The discontinuities are the problem. We should invest in both education and health. Women literacy and health care are tightly correlated but the effect seems to be that better health leads to better education. Lower birth rates lead to more education.
Q: What’s the next technology, after mobile phones
A: If you want to pick one thing, it would be robots. If you don’t want to go to a convention send a robot (laughter). If we look at mortality, there is a certain level below which you can’t go below without technology, if you can’t do a c-section, for example. Computers are going from just sitting there to where they can see, perform high end visual applications, like in the military. The computer is learning to move around, this has advanced a lot in the last 5 years. Dexterity is about 5 years behind. The hardest thing is to lift an elderly patient, humans are surprisingly good at this. But, once the robot knows how to do it, it doesn’t forget and the price goes down.
Also, increases in biological knowledge are important. We can find receptors and develop small molecules to block them. There are phenomenal advances in store in the next 10 years, as drug discovery becomes rational. Discovery has been low in the last 10 years which seems paradoxical. Discovering drugs by computation instead of manually is changing that, in 10-15 years it will be utterly different. If we are smart about it, it will benefit the poor as well as the rich.
