Why data is the key to better medicine — and maybe a cure for cancer — Data | GigaOM

Some good examples on how big data is being used in healthcare and how its further use in improved understanding of cancer genetics is hampered by lack of more data and related infrastructure. Quote:

He [University of California Santa Cruz researcher David Haussler] — along with others in the field — thinks cloud computing could be the solution because it gives genetic researchers a central location where they can access and perform computations on the data. Haussler and his team that house the Cancer Genome Atlas and a couple other projects currently have more than 400 terabytes of data and expect to have around 5 petabytes of data eventually. Downloading that is infeasible save for access to high-speed research networks, so “we need a place where people can experiment with these big data problems,” Haussler said.

In the meantime, Haussler and his peers will keep on collecting and accessing genome data however they can. And they’ll keep building software packages and algorithms that analyze that data better and faster than ever before. However, he lamented, “If we had the big data out there in an unrestricted setting, then all the best minds in the world would already be crunching on it.”

Why data is the key to better medicine — and maybe a cure for cancer — Data | GigaOM.

Data-Driven Discovery Is Tech’s New Wave – Unboxed – NYTimes.com

For those of you interested in some of the earlier posts on big data and its possible implications for healthcare and other sectors, an interesting piece on how technology is driving the costs down, and the potential for more widespread use. As in a lot of similar cases, the balance between privacy protection and trend analysis will be a hard issue to resolve.

Data-Driven Discovery Is Tech’s New Wave – Unboxed – NYTimes.com.

A marriage of data and caregivers gives Dr. Atul Gawande hope for health care – O’Reilly Radar

A good interview with Atul Gawande on how good data can improve healthcare, suing the police experience with ‘hotspots’ to identify community issues and problems, ending up on the challenge of how to use it to change individual behaviour. Quote:

That’s where the art comes in. There are problems because you lack information, but when you have information like “you shouldn’t drink three cans of Coke a day — you’re going to put on weight,” then having that information is not sufficient for most people.

Understanding what is sufficient to be able to either change the care or change the behaviors that we’re concerned about is the crux of what we’re trying to figure out and discover.

When the information is presented in a really interesting way, people have gradually discovered — for example, having a little ball on your dashboard that tells you when you’re accelerating too fast and burning off extra fuel — how that begins to change the actual behavior of the person in the car.

No amount of presenting the information that you ought to be driving in a more environmentally friendly way ends up changing anything. It turns out that change requires the psychological nuance of presenting the information in a way that provokes the desire to actually do it.

We’re at the very beginning of understanding these things. There’s also the same sorts of issues with clinician behavior — not just information, but how you are able to foster clinicians to actually talk to one another and coordinate when five different people are involved in the care of a patient and they need to get on the same page.

That’s why I’m fascinated by the police work, because you have the data people, but they’re married to commanders who have responsibility and feel responsibility for looking out on their populations and saying, “What do we do to reduce the crime here? Here’s the kind of information that would really help me.” And the data people come back to them and say, “Why don’t you try this? I’ll bet this will help you.”

A marriage of data and caregivers gives Dr. Atul Gawande hope for health care – O’Reilly Radar.

Physicians May Not Be Social, But They are Interactive – Forbes

While written largely from a business development perspective, the application of big data and business intelligence to looking for patterns of behaviour has both positive (accountability) and scary (big brother) implications. I expect that many of us might be surprised what analysis of our purchasing and other patterns would show. Quote:

The key is to design and deploy solutions that mine the ever-increasing data noise to identify relevant interactions. A hospital may not need to care about every $15 lunch that a physician forgets to report if it has a solution to systematically identify medical anomalies that may be the result of unhealthy industry payments. Pharmaceutical companies may not need to hire multiple resources to manage the many complaints of physicians concerned about mis-attribution of payments if it deploys a portal to communicate and adjudicate those interactions directly with their physician consultants. Companies that leverage Big Data effectively will not only out-compete their peers in realizing value from their interactions with physicians but could actually create more engaging and valuable relationships.

Physicians May Not Be Social, But They are Interactive – Forbes.

How Big Data Became So Big – Unboxed – NYTimes.com

How big data became the new marketing term for businesses, in contrast to some of the dryer terminology like ‘data mining’, ‘business intelligence’ and ‘data analytics’. Quote:

IT may seem marketing gold, but Big Data also carries a darker connotation, as a linguistic cousin to the likes of Big Brother, Big Oil and Big Government.

“If only inadvertently, it does have a sinister flavor to it,” says Fred R. Shapiro, editor of the Yale Book of Quotations.

Big Data’s enthusiasts say the rewards far outweigh the risks. Still, smart technologies that promise to observe, record and make inferences about human behavior as never before should prompt some second thoughts — both from the people building those technologies and from the people using them.

How Big Data Became So Big – Unboxed – NYTimes.com.

Esther Dyson on health data, “preemptive healthcare” and the next big thing – O’Reilly Radar

A thoughtful interview with Esther Dyson, and the need for focus on prevention (health, not healthcare). Well worth reading. Two of my favourite quotes:

Then there’s the market for bad health, which people don’t talk about a lot, at least not in those terms, but it’s huge. It’s the products and all of the advertising around everything from sugared soft drinks to cigarettes to recreational drugs to things that keep you from going to bed, going to sleep, keep you on the couch, and keep you immobile. I mentioned cigarettes and alcohol, I think. That’s a huge market. People are being encouraged to engage in unhealthy behaviors, whether it’s stuff that might be healthy in moderation or stuff that just isn’t healthy at all…..

The biggest myth is that any single thing is the solution. The biggest need is for long-term thinking, which is everything from an individual thinking long-term about the impact of behavior to a financial institution thinking long-term and having the incentive to think long-term.

Individuals need to be influenced by psychology. Institutions, and the individuals in them, are employees that can be motivated or not. As an institution, they need financial incentives that are aligned with the long-term rather than the short-term.

That, again, goes back to having a vested interest in the health of people rather than in the cost of care.

Esther Dyson on health data, “preemptive healthcare” and the next big thing – O’Reilly Radar.

Better medicine, brought to you by big data — Cloud Computing News

Some concrete examples of how ‘big data’ is improving medicine and healthcare:

  1. Genomics
  2. Business intelligence for doctors to analyse hospital-wide data
  3. Semantic search to improve search results (more plain language search)
  4. Hadoop (?) for everything – identifying unsuspected adverse side effects from multi-drug combinations, or analysing medical images
  5. IMB’s Watson diagnostic tool
  6. Getting ahead of disease by identifying predictors
  7. Data scientist in residence
  8. Crowdsourced science – see PatientsLikeMe website

Worth a quick read.

Better medicine, brought to you by big data — Cloud Computing News.