"StrataRX" entries

Strata Rx is a wrap

Watch live keynotes from this week's Strata Rx Conference in San Francisco.

The intersection of big data and health care was explored at the O’Reilly Strata Rx Conference. The event has concluded, but you can still access an archive of videos, photos, and speaker slides. Read more…

How we can consumerize health care

The Zero Overhead Principle can bring lessons from the consumer space to health care.

Operating room in the Elliot Community Hospital by Keene and Cheshire County (NH) Historical Photos, on FlickrRecently I wrote about one of my key product principles that is particularly relevant for designing software for the enterprise. The principle is called the Zero Overhead Principle, and it states that no feature may add training costs to the user.

The essence of the Zero Overhead Principle is that consumer products have figured out how to turn the “how-to manual” into a relic. They’ve focused on creating a glide path for the user to quickly move from newbie to proficient in minimal time. Put another way, the products must teach the user how they should be used.

Just this weekend, I downloaded a new game for my son on the iPad, and he was a pro in a matter of minutes (or at least proficient enough to kick my butt). No manual required. In fact, he didn’t even read anything before starting to play. This highly optimized glide path is exactly what we need to focus on when we talk about the consumerization of the enterprise.

This week, the first Strata RX conference will focus on bringing data and health together. Just as in national security (the place where we came up with the Zero Overhead Principle to help combat the lack of tech adoption by overloaded security analysts), there is tremendous opportunity to apply lessons learned in the consumer space to the health care sector. We know the space needs disruption and it is a way to make constructive disruption with a rapid adoption cycle. Read more…

Want an NIH grant to build a better mobile health app? Connect your code to the research

The United States National Institutes of Health (NIH) wants to tie development of mobile health apps to evidence-based research, and it hopes to do that with a new grant program. The imperative to align developers with research is urgent, given the strong interest in health IT, mobile health and health data. There are significant challenges for the space, from consumer concerns over privacy and mobile applications to the broader question of balancing health data innovation with patient rights.

To learn more about what’s happening with mobile health apps, health data, behavioral change and cancer research, I recently interviewed Dr. Abdul Sheikh. Our interview, lightly edited for content and clarity, follows.

What led you to your current work at NIH?

Dr. Abdul SheikhDr. Abdul Sheikh: I’ve always had a strong grounding in public health and population health, but I also have a real passion for technology and informatics. What’s beautiful is, in my current position here as a program director at the National Cancer Institute (NCI), I have a chance to meld these worlds of public health, behavior and communication science with my passion for technology and informatics. Some of the work I did before coming to the NIH was related to the early telemedicine and web-based health promotion efforts that the government of Canada was involved in.

At NCI, I direct a portfolio of research on technology-mediated communication. I’ve also had the chance to get involved and provide leadership on two very cool efforts. One of them is leadership for our division’s Small Business Innovation Research Program (SBIR). I’ve led the first NIH developer challenge competitions as well.

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When data disrupts health care

The convergence of data, privacy and cost have created a unique opportunity to reshape health care.

Health care appears immune to disruption. It’s a space where the stakes are high, the incumbents are entrenched, and lessons from other industries don’t always apply.

Yet, in a recent conversation between Tim O’Reilly and Roger Magoulas it became evident that we’re approaching an unparalleled opportunity for health care change. O’Reilly and Magoulas explained how the convergence of data access, changing perspectives on privacy, and the enormous expense of care are pushing the health space toward disruption.

As always, the primary catalyst is money. The United States is facing what Magoulas called an “existential crisis in health care costs” [discussed at the 3:43 mark]. Everyone can see that the current model is unsustainable. It simply doesn’t scale. And that means we’ve arrived at a place where party lines are irrelevant and tough solutions are the only options.

“Who is it that said change happens when the pain of not changing is greater than the pain of changing?” O’Reilly asked. “We’re now reaching that point.” [3:55]

(Note: The source of that quote is hard to pin down, but the sentiment certainly applies.)

This willingness to change is shifting perspectives on health data. Some patients are making their personal data available so they and others can benefit. Magoulas noted that even health companies, which have long guarded their data, are warming to collaboration.

At the same time there’s a growing understanding that health data must be contextualized. Simply having genomic information and patient histories isn’t good enough. True insight — the kind that can improve quality of life — is only possible when datasets are combined.

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Open science will be a key part of the health data equation

Dr. Stephen Friend on open science and the need for a "GitHub for scientists."

To unlock the potential of health data for the public good, balancing health privacy with innovation will rely on improving informed consent. If the power of big data is to be applied to scientific inquiry in health care, unlocking genetic secrets, finding a cure for breast cancer or “preemptive health care,” changes in scientific culture and technology will both need to occur.

Dr. Stephen FriendOne element of that change could include a health data commons. Another is open access in the research community. Dr. Stephen Friend, the founder of Sage Bionetworks, is one of the foremost advocates of what I think of as “open science.” Earlier in his career, Dr. Friend was a senior vice president at Merck & Co., Inc., where he led the pharmaceutical company’s basic cancer research program.

In a recent interview, Dr. Friend explained what open science means to him and what he’s working on today. For more on the synthesis of open source with genetics, watch Andy Oram’s interview with Dr. Friend and read his series on recombinant research and Sage Congress.

Read more…

Solving the Wanamaker problem for health care

Data science and technology give us the tools to revolutionize health care. Now we have to put them to use.

By Tim O’Reilly, Julie Steele, Mike Loukides and Colin Hill

“The best minds of my generation are thinking about how to make people click ads.” — Jeff Hammerbacher, early Facebook employee

“Work on stuff that matters.” — Tim O’Reilly

Doctors in operating room with data

In the early days of the 20th century, department store magnate John Wanamaker famously said, “I know that half of my advertising doesn’t work. The problem is that I don’t know which half.”

The consumer Internet revolution was fueled by a search for the answer to Wanamaker’s question. Google AdWords and the pay-per-click model began the transformation of a business in which advertisers paid for ad impressions into one in which they pay for results. “Cost per thousand impressions” (CPM) was outperformed by “cost per click” (CPC), and a new industry was born. It’s important to understand why CPC outperformed CPM, though. Superficially, it’s because Google was able to track when a user clicked on a link, and was therefore able to bill based on success. But billing based on success doesn’t fundamentally change anything unless you can also change the success rate, and that’s what Google was able to do. By using data to understand each user’s behavior, Google was able to place advertisements that an individual was likely to click. They knew “which half” of their advertising was more likely to be effective, and didn’t bother with the rest.

Since then, data and predictive analytics have driven ever deeper insight into user behavior such that companies like Google, Facebook, Twitter,  and LinkedIn are fundamentally data companies. And data isn’t just transforming the consumer Internet. It is transforming finance, design, and manufacturing — and perhaps most importantly, health care.

How is data science transforming health care? There are many ways in which health care is changing, and needs to change. We’re focusing on one particular issue: the problem Wanamaker described when talking about his advertising. How do you make sure you’re spending money effectively? Is it possible to know what will work in advance?

Read more…

The risks and rewards of a health data commons

John Wilbanks on health data donation, contextual privacy, and open networks.

As I wrote earlier this year in an ebook on data for the public good, while the idea of data as a currency is still in its infancy, it’s important to think about where the future is taking us and our personal data.

If the Obama administration’s smart disclosure initiatives gather steam, more citizens will be able to do more than think about personal data: they’ll be able to access their financial, health, education, or energy data. In the U.S. federal government, the Blue Button initiative, which initially enabled veterans to download personal health data, is now spreading to all federal employees, and it also earned adoption at private institutions like Aetna and Kaiser Permanente. Putting health data to work stands to benefit hundreds of millions of people. The Locker Project, which provides people with the ability to move and store personal data, is another approach to watch.

The promise of more access to personal data, however, is balanced by accompanying risks. Smartphones, tablets, and flash drives, after all, are lost or stolen every day. Given the potential of mhealth, and big data and health care information technology, researchers and policy makers alike are moving forward with their applications. As they do so, conversations and rulemaking about health care privacy will need to take into account not just data collection or retention but context and use.

Put simply, businesses must confront the ethical issues tied to massive aggregation and data analysis. Given that context, Fred Trotter’s post on who owns health data is a crucial read. As Fred highlights, the real issue is not ownership, per se, but “What rights do patients have regarding health care data that refers to them?”

Would, for instance, those rights include the ability to donate personal data to a data commons, much in the same way organs are donated now for research? That question isn’t exactly hypothetical, as the following interview with John Wilbanks highlights.

Wilbanks, a senior fellow at the Kauffman Foundation and director of the Consent to Research Project, has been an advocate for open data and open access for years, including a stint at Creative Commons; a fellowship at the World Wide Web Consortium; and experience in the academic, business, and legislative worlds. Wilbanks will be speaking at the Strata Rx Conference in October.

Our interview, lightly edited for content and clarity, follows.

Read more…

StrataRx: Data science and health(care)

A call for data scientists, technologists, health professionals, and business leaders to convene.

By Mike Loukides and Jim Stogdill

StrataRxWe are launching a conference at the intersection of health, health care, and data. Why?

Our health care system is in crisis. We are experiencing epidemic levels of obesity, diabetes, and other preventable conditions while at the same time our health care system costs are spiraling higher. Most of us have experienced increasing health care costs in our businesses or have seen our personal share of insurance premiums rise rapidly. Worse, we may be living with a chronic or life-threatening disease while struggling to obtain effective therapies and interventions — finding ourselves lumped in with “average patients” instead of receiving effective care designed to work for our specific situation.

In short, particularly in the United States, we are paying too much for too much care of the wrong kind and getting poor results. All the while our diet and lifestyle failures are demanding even more from the system. In the past few decades we’ve dropped from the world’s best health care system to the 37th, and we seem likely to drop further if things don’t change.

The very public fight over the Affordable Care Act (ACA) has brought this to the fore of our attention, but this is a situation that has been brewing for a long time. With the ACA’s arrival, increasing costs and poor outcomes, at least in part, are going to be the responsibility of the federal government. The fiscal outlook for that responsibility doesn’t look good and solving this crisis is no longer optional; it’s urgent.

There are many reasons for the crisis, and there’s no silver bullet. Health and health care live at the confluence of diet and exercise norms, destructive business incentives, antiquated care models, and a system that has severe learning disabilities. We aren’t preventing the preventable, and once we’re sick we’re paying for procedures and tests instead of results; and those interventions were designed for some non-existent average patient so much of it is wasted. Later we mostly ignore the data that could help the system learn and adapt.

It’s all too easy to be gloomy about the outlook for health and health care, but this is also a moment of great opportunity. We face this crisis armed with vast new data sources, the emerging tools and techniques to analyze them, an ACA policy framework that emphasizes outcomes over procedures, and a growing recognition that these are problems worth solving.

Read more…

Esther Dyson on health data, “preemptive healthcare” and the next big thing

Dyson says it's time to focus on maintaining good health, as opposed to healthcare.

If we look ahead to the next decade, it’s worth wondering whether the way we think about health and health care will have shifted. Will health care technology be a panacea? Will it drive even higher costs, creating a broader divide between digital haves and have-nots? Will opening health data empower patients or empower companies?

As ever, there will be good outcomes and bad outcomes, and not just in the medical sense. There’s a great deal of thought around the potential for mobile applications right now, from the FDA’s potential decision to regulate them to a reported high abandonment rate. There are also significant questions about privacy, patient empowerment and meaningful use of electronic health care records.

When I’ve talked to US CTO Todd Park or Dr. Farzad Mostashari they’ve been excited about the prospect for health data to fuel better dashboards and algorithms to give frontline caregivers access to critical information about people they’re looking after, providing critical insight at the point of contact.

Kathleen Sebelius, the U.S. Secretary for Health and Human Services, said at this year’s Health Datapalooza that venture capital investment in the health care IT area is up 60% since 2009.

Given that context, I was more than a little curious to hear what Esther Dyson (@edyson) is thinking about when she looks at the intersection of health care, data and information technology.

Read more…