How Precision Medicine Can Save More Lives and Waste Less Money (Part 2 of 2)

Posted on August 10, 2016 I Written By

Andy Oram is an editor at O'Reilly Media, a highly respected book publisher and technology information provider. An employee of the company since 1992, Andy currently specializes in open source, software engineering, and health IT, but his editorial output has ranged from a legal guide covering intellectual property to a graphic novel about teenage hackers. His articles have appeared often on EMR & EHR and other blogs in the health IT space. Andy also writes often for O'Reilly's Radar site ( and other publications on policy issues related to the Internet and on trends affecting technical innovation and its effects on society. Print publications where his work has appeared include The Economist, Communications of the ACM, Copyright World, the Journal of Information Technology & Politics, Vanguardia Dossier, and Internet Law and Business. Conferences where he has presented talks include O'Reilly's Open Source Convention, FISL (Brazil), FOSDEM, and DebConf.

The previous section of this article looked at how little help we get from genetic testing. Admittedly, when treatments have been associated with genetic factors, testing has often been the difference between life and death. Sometimes doctors can hone in with laser accuracy on a treatment that works for someone because a genetic test shows that he or she will respond to that treatment. Hopefully, the number of treatments that we can associate with tests will grow over time.

So genetics holds promise, but behavioral and environmental data are what we can use right now. One sees stories in the trade press all the time such as these:

These studies usually depend on straightforward combinations of data that are easy to get, either from the health care system (clinical or billing data) or from the patient (reports of medication adherence, pain level, etc.).

And we’ve only scratched the surface of the data available to us. Fitness devices, sensors in our neighborhoods, and other input will give us much more. We can also find new applications for data: for instance, to determine whether one institution is overprescribing certain high-cost drugs, or whether an asthma victim is using an inhaler too often, meaning the medication isn’t strong enough. We know that social factors, notably poverty (LGBTQ status is not mentioned in the article, but is another a huge contributor to negative health outcomes, due to discrimination and clinician ignorance) must be incorporated into models for diagnosis, prediction, and care.

President Obama promises that Precision Medicine features both genetics and personal information. One million volunteers are sought for DNA samples and information on age, race, income, education, sexual orientation, and gender identity.

There are other issues that critics have brought up with the Precision Medicine initiative. For instance, its focus on cure instead of prevention weakens its value for long-term public health improvements. We must also remember the large chasm between knowing what’s good for you and doing it. People don’t change notoriously unhealthy behaviors, such as smoking, even when told they are at increased risk. Some experts think people shouldn’t be told their DNA results.

Meanwhile, those genetic database can be used against you. But let’s consider our context, once again, in order to assess the situation responsibly. The data is being mined by police, but it’s probably not very useful because the DNA segments collected are different from what the police are looking for. Behavioral data, if abused, is probably more damning than genetic data.

Just as there are powerful economic forces biasing us toward genetics, social and political considerations weigh against behavioral and environmental data. We all know the weaknesses in the government’s dietary guidelines, heavily skewed by the food industry. And the water disaster in Flint, Michigan showed how cowardice and resistance by the guardians of public health to admitting changes raised the costs in public health measures. Industry lobbying and bureaucratic inertia work together to undermine the simplest and most effective ways of improving health. But let’s get behavioral and environmental measures on the right track before splurging on genetic testing.