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January 17 2013

Yelp partners with NYC and SF on restaurant inspection data

One of the key notions in my “Government as a Platform” advocacy has been that there are other ways to partner with the private sector besides hiring contractors and buying technology. One of the best of these is to provide data that can be used by the private sector to build or enrich their own citizen-facing services. Yes, the government runs a weather website but it’s more important that data from government weather satellites shows up on the Weather Channel, your local TV and radio stations, Google and Bing weather feeds, and so on. They already have more eyeballs and ears combined than the government could or should possibly acquire for its own website.

That’s why I’m so excited to see a joint effort by New York City, San Francisco, and Yelp to incorporate government health inspection data into Yelp reviews. I was involved in some early discussions and made some introductions, and have been delighted to see the project take shape.

My biggest contribution was to point to GTFS as a model. Bibiana McHugh at the city of Portland’s TriMet transit agency reached out to Google, Bing, and others with the question: “If we came up with a standard format for transit schedules, could you use it?” Google Transit was the result — a service that has spread to many other U.S. cities. When you rejoice in the convenience of getting transit timetables on your phone, remember to thank Portland officials as well as Google.

In a similar way, Yelp, New York, and San Francisco came up with a data format for health inspection data. The specification is at http://yelp.com/healthscores. It will reportedly be announced at the US Conference of Mayors with San Francisco Mayor Ed Lee today.

Code for America built a site for other municipalities to pledge support. I’d also love to see support in other local restaurant review services from companies like Foursquare, Google, Microsoft, and Yahoo!  This is, as Chris Anderson of TED likes to say, “an idea worth spreading.”

October 17 2012

Data from health care reviews could power “Yelp for health care” startups

A hospital in MaineA hospital in MaineGiven where my work and health has taken me this year, I’ve been thinking much more about the relationship of the Internet and health data to accountability and patient-driven health care.

When I was looking for a place in Maine to go for care this summer, I went online to look at my options. I consulted hospital data from the government at HospitalCompare.HHS.gov and patient feedback data on Yelp, and then made a decision based upon proximity and those ratings. If I had been closer to where I live in Washington D.C., I would also have consulted friends, peers or neighbors for their recommendations of local medical establishments.

My brush with needing to find health care when I was far from home reminded me of the prism that collective intelligence can now provide for the treatment choices we make, if we have access to the Internet.

Patients today are sharing more of their health data and experiences online voluntarily, which in turn means that the Internet is shaping health care. There’s a growing phenomenon of “e-patients” and caregivers going online to find communities and information about illness and disability.

Aided by search engines and social media, newly empowered patients are discussing health conditions with others suffering from disease and sickness — and they’re taking that peer-to-peer health care knowledge into their doctors’ offices with them, frequently on mobile devices. E-patients are sharing their health data of their own volition because they have a serious health condition, want to get healthy, and are willing.

From the perspective of practicing physicians and hospitals, the trend of patients contributing to and consulting on online forums adds the potential for errors, fraud, or misunderstanding. And yet, I don’t think there’s any going back from a networked future of peer-to-peer health care, anymore than we can turn back the dial on networked politics or disaster response.

What’s needed in all three of these areas is better data that informs better data-driven decisions. Some of that data will come from industry, some from government, and some from citizens.

This fall, the Obama administration proposed a system for patients to report medical mistakes. The system would create a new “consumer reporting system for patient safety” that would enable patients to tell the federal government about unsafe practices or errors. This kind of review data, if validated by government, could be baked into the next generation of consumer “choice engines,” adding another layer for people, like me, searching for care online.

There are precedents for the collection and publishing of consumer data, including the Consumer Product Safety Commission’s public complaint database at SaferProducts.gov and the Consumer Financial Protection Bureau’s complaint database. Each met with initial resistance by industry but have successfully gone online without massive abuse or misuse, at least to date.

It will be interesting to see how medical associations, hospitals and doctors react. Given that such data could amount to government collecting data relevant to thousands of “Yelps for health care,” there’s both potential and reason for caution. Health care is a bit different than product safety or consumer finance, particularly with respect to how a patient experiences or understands his or her treatment or outcomes for a given injury or illness. For those that support or oppose this approach, there is an opportunity for public comment on proposed data collection at the Federal Register.

The power of performance data

Combining patients review data with government-collected performance data could be quite powerful in helping to drive better decisions and adding more transparency to health care.

In the United Kingdom, officials are keen to find the right balance between open data, transparency and prosperity.

“David Cameron, the Prime Minister, has made open data a top priority because of the evidence that this public asset can transform outcomes and effectiveness, as well as accountability,” said Tim Kelsey, in an interview this year. He used to head up the United Kingdom’s transparency and open data efforts and now works at its National Health Service.

“There is a good evidence base to support this,” said Kelsey. “Probably the most famous example is how, in cardiac surgery, surgeons on both sides of the Atlantic have reduced the number of patient deaths through comparative analysis of their outcomes.”

More data collected by patients, advocates, governments and industry could help to shed light on the performance of more physicians and clinics engaged in other expensive and lifesaving surgeries and associated outcomes.

Should that be extrapolated across the medical industry, it’s a safe bet that some medical practices or physicians will use whatever tools or legislative influence they have to fight or discredit websites, services or data that puts them in a poor light. This might parallel the reception that BrightScope’s profiles of financial advisors have received in industry.

When I talked recently with Dr. Atul Gawande about health data and care givers, he said more transparency in these areas is crucial:

“As long as we are not willing to open up data to let people see what the results are, we will never actually learn. The experience of what happens in fields where the data is open is that it’s the practitioners themselves that use it.”

In that context, health data will be the backbone of the disruption in health care ahead. Part of that change will necessarily have to come from health care entrepreneurs and watchdogs connecting code to research. In the future, a move to open science and perhaps establish a health data commons could accelerate that change.

The ability of caregivers and patients alike to make better data-driven decisions is limited by access to data. To make a difference, that data will also need to be meaningful to both the patient and the clinician, said Dr. Gawande. He continued:

“[Health data] needs to be able to connect the abstract world of data to the physical world of what really happens, which means it has to be timely data. A six-month turnaround on data is not great. Part of what has made Wal-Mart powerful, for example, is they took retail operations from checking their inventory once a month to checking it once a week and then once a day and then in real-time, knowing exactly what’s on the shelves and what’s not. That equivalent is what we’ll have to arrive at if we’re to make our systems work. Timeliness, I think, is one of the under-recognized but fundamentally powerful aspects because we sometimes over prioritize the comprehensiveness of data and then it’s a year old, which doesn’t make it all that useful. Having data that tells you something that happened this week, that’s transformative.”

Health data, in other words, will need to be open, interoperable, timely, higher quality, baked into the services that people use, and put at the fingertips of caregivers, as US CTO Todd Park explains in the video below:

There is more that needs to be done than simply putting “how to live better” information online or into an app. To borrow a phrase from Robert Kirkpatrick, for data to change health care, we’ll need to apply the wisdom of the crowds, the power of algorithms and the intuition of experts to find meaning in health data and help patients and caregivers alike make better decisions.

That isn’t to say that health data, once published, can’t be removed or filtered. Witness the furor over the removal of a malpractice database from the Internet last year, along with its restoration.
But as more data about doctors, services, drugs, hospitals and insurance companies goes online, the ability of those institutions to control public perception of the institutions will shift, just as it has with government and media. Given flaws in devices or poor outcomes, patients deserve such access, accountability and insight.

Enabling better health-data-driven decisions to happen across the world will be far from easy. It is, however, a future worth building toward.

Reposted byfortmyersrealty fortmyersrealty

September 18 2012

When data disrupts 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.

“Genes aren’t destiny,” Magoulas said. “It’s how they interact with other things. I think people are starting to see that. It’s the same with the EHR [Electronic Health Record]. The EHR doesn’t solve anything. It’s part of a puzzle.” [4:13]

And here’s where the opportunity lies. Extracting meaning from datasets is a process data scientists and Silicon Valley entrepreneurs have already refined. That means the same skills that improve mindless ad-click rates can now be applied to something profound.

“There’s this huge opportunity for those people with those talents, with that experience, to come and start working on stuff that really matters,” O’Reilly said. “They can save lives and they can save money in one of the biggest and most critical industries of the future.” [5:20]

The language O’Reilly and Magoulas used throughout their conversation was telling. “Save lives,” “work on stuff that matters,” “huge opportunity” — these aren’t frivolous phrases. The health care disruption they discussed will touch everyone, which is why it’s imperative the best minds come together to shape these changes.

The full conversation between O’Reilly and Magoulas is available in the following video.

Here are key points with direct links to those segments:

  • Internet companies used data to solve John Wanamaker’s advertising dilemma (“Half the money I spend on advertising is wasted; the trouble is I don’t know which half”). Similar methods can apply to health care. [17 seconds in]
  • The “quasi-market system” of health care makes it harder to disrupt than other industries. [3:15]
  • The U.S. is facing an existential crisis around health care costs. “This is bigger than one company.” [3:43]
  • We can benefit from the multiple data types coming “on stream” at the same time. These include electronic medical records, inexpensive gene sequencing, and personal sensor data. [4:28]
  • The availability of different datasets presents an opportunity for Silicon Valley because data scientists and technologists already have the skills to manage the data. Important results can be found when this data is correlated: “The great thing is we know it can work.” [5:20]
  • Personal data donation is a trend to watch. [6:40]
  • Disruption is often associated with trivial additions to the consumer Internet. With an undisrupted market like health care, technical skills can create real change. [7:04]
  • “There’s no question this is going to be a huge field.” [8:15]

If the disruption of health care and associated opportunities interests you, O’Reilly has more to offer. Check out our interviews, ongoing coverage, our recent report, “Solving the Wanamaker problem for health care,” and the upcoming Strata Rx conference in San Francisco.

This post was originally published on strata.oreilly.com.

August 30 2012

A marriage of data and caregivers gives Dr. Atul Gawande hope for health care

Dr. Atul GawandeDr. Atul GawandeDr. Atul Gawande (@Atul_Gawande) has been a bard in the health care world, straddling medicine, academia and the humanities as a practicing surgeon, medical school professor, best-selling author and staff writer at the New Yorker magazine. His long-form narratives and books have helped illuminate complex systems and wicked problems to a broad audience.

One recent feature that continues to resonate for those who wish to apply data to the public good is Gawande’s New Yorker piece “The Hot Spotters,” where Gawande considered whether health data could help lower medical costs by giving the neediest patients better care. That story brings home the challenges of providing health care in a city, from cultural change to gathering data to applying it.

This summer, after meeting Gawande at the 2012 Health DataPalooza, I interviewed him about hot spotting, predictive analytics, networked transparency, health data, feedback loops and the problems that technology won’t solve. Our interview, lightly edited for content and clarity, follows.

Given what you’ve learned in Camden, N.J. — the backdrop for your piece on hot spotting — do you feel hot spotting is an effective way for cities and people involved in public health to proceed?

Gawande: The short answer, I think, is “yes.”

Here we have this major problem of both cost and quality — and we have signs that some of the best places that seem to do the best jobs can be among the least expensive. How you become one of those places is a kind of mystery.

It really parallels what happened in the police world. Here is something that we thought was an impossible problem: crime. Who could possibly lower crime? One of the ways we got a handle on it was by directing policing to the places where there was the most crime. It sounds kind of obvious, but it was not apparent that crime is concentrated and that medical costs are concentrated.

The second thing I knew but hadn’t put two and two together about is that the sickest people get the worst care in the system. People with complex illness just don’t fit into 20-minute office visits.

The work in Camden was emblematic of work happening in pockets all around the country where you prioritize. As soon as you look at the system, you see hundreds, thousands of things that don’t work properly in medicine. But when you prioritize by saying, “For the sickest people — the 5% who account for half of the spending — let’s look at what their $100,000 moments are,” you then understand it’s strengthening primary care and it’s the ability to manage chronic illness.

It’s looking at a few acute high-cost, high-failure areas of care, such as how heart attacks and congestive heart failure are managed in the system; looking at how renal disease patients are cared for; or looking at a few things in the commercial population, like back pain, being a huge source of expense. And then also end-of-life care.

With a few projects, it became more apparent to me that you genuinely could transform the system. You could begin to move people from depending on the most expensive places where they get the least care to places where you actually are helping people achieve goals of care in the most humane and least wasteful ways possible.

The data analytics office in New York City is doing fascinating predictive analytics. That approach could have transformative applications in health care, but it’s notable how careful city officials have been about publishing certain aspects of the data. How do you think about the relative risks and rewards here, including balancing social good with the need to protect people’s personal health data?

Gawande: Privacy concerns can sometimes be a barrier, but I haven’t seen it be the major barrier here. There are privacy concerns in the data about households as well in the police data.

The reason it works well for the police is not just because you have a bunch of data geeks who are poking at the data and finding interesting things. It’s because they’re paired with people who are responsible for responding to crime, and above all, reducing crime. The commanders who have the responsibility have a relationship with the people who have the data. They’re looking at their population saying, “What are we doing to make the system better?”

That’s what’s been missing in health care. We have not married the people who have the data with people who feel responsible for achieving better results at lower costs. When you put those people together, they’re usually within a system, and within a system, there is no privacy barrier to being able to look and say, “Here’s what we can be doing in this health system,” because it’s often that particular.

The beautiful aspect of the work in New York is that it’s not at a terribly abstract level. Yes, they’re abstracting the data, but they’re also helping the police understand: “It’s this block that’s the problem. It’s shifted in the last month into this new sector. The pattern of the crime is that it looks more like we have a problem with domestic violence. Here are a few more patterns that might give you a clue about what you can go in and do.” There’s this give and take about what can be produced and achieved.

That, to me, is the gold in the health care world — the ability to peer in and say: “Here are your most expensive patients and your sickest patients. You didn’t know it, but here, there’s an alcohol and drug addiction issue. These folks are having car accidents and major trauma and turning up in the emergency rooms and then being admitted with $12,000 injuries.”

That’s a system that could be improved and, lo and behold, there’s an intervention here that’s worked before to slot these folks into treatment programs, which by and large, we don’t do at all.

That sense of using the data to help you solve problems requires two things. It requires data geeks and it requires the people in a system who feel responsible, the way that Bill Bratton made commanders feel responsible in the New York police system for the rate of crime. We haven’t had physicians who felt that they were responsible for 10,000 ICU patients and how well they do on everything from the cost to how long they spend in the ICU.

Health data is creating opportunities for more transparency into outcomes, treatments and performance. As a practicing physician, do you welcome the additional scrutiny that such collective intelligence provides, or does it concern you?

Gawande: I think that transparency of our data is crucial. I’m not sure that I’m with the majority of my colleagues on this. The concerns are that the data can be inaccurate, that you can overestimate or underestimate the sickness of the people coming in to see you, and that my patients aren’t like your patients.

That said, I have no idea who gets better results at the kinds of operations I do and who doesn’t. I do know who has high reputations and who has low reputations, but it doesn’t necessarily correspond to the kinds of results they get. As long as we are not willing to open up data to let people see what the results are, we will never actually learn.

The experience of what happens in fields where the data is open is that it’s the practitioners themselves that use it. I’ll give a couple of examples. Mortality for childbirth in hospitals has been available for a century. It’s been public information, and the practitioners in that field have used that data to drive the death rates for infants and mothers down from the biggest killer in people’s lives for women of childbearing age and for newborns into a rarity.

Another field that has been able to do this is cystic fibrosis. They had data for 40 years on the performance of the centers around the country that take care of kids with cystic fibrosis. They shared the data privately. They did not tell centers how the other centers were doing. They just told you where you stood relative to everybody else and they didn’t make that information public. About four or five years ago, they began making that information public. It’s now available on the Internet. You can see the rating of every center in the country for cystic fibrosis.

Several of the centers had said, “We’re going to pull out because this isn’t fair.” Nobody ended up pulling out. They did not lose patients in hoards and go bankrupt unfairly. They were able to see from one another who was doing well and then go visit and learn from one and other.

I can’t tell you how fundamental this is. There needs to be transparency about our costs and transparency about the kinds of results. It’s murky data. It’s full of lots of caveats. And yes, there will be the occasional journalist who will use it incorrectly. People will misinterpret the data. But the broad result, the net result of having it out there, is so much better for everybody involved that it far outweighs the value of closing it up.

U.S. officials are trying to apply health data to improve outcomes, reduce costs and stimulate economic activity. As you look at the successes and failures of these sorts of health data initiatives, what do you think is working and why?

Gawande: I get to watch from the sidelines, and I was lucky to participate in Datapalooza this year. I mostly see that it seems to be following a mode that’s worked in many other fields, which is that there’s a fundamental role for government to be able to make data available.

When you work in complex systems that involve multiple people who have to, in health care, deal with patients at different points in time, no one sees the net result. So, no one has any idea of what the actual experience is for patients. The open data initiative, I think, has innovative people grabbing the data and showing what you can do with it.

Connecting the data to the physical world is where the cool stuff starts to happen. What are the kinds of costs to run the system? How do I get people to the right place at the right time? I think we’re still in primitive days, but we’re only two or three years into starting to make something more than just data on bills available in the system. Even that wasn’t widely available — and it usually was old data and not very relevant to this moment in time.

My concern all along is that data needs to be meaningful to both the patient and the clinician. It needs to be able to connect the abstract world of data to the physical world of what really happens, which means it has to be timely data. A six-month turnaround on data is not great. Part of what has made Wal-Mart powerful, for example, is they took retail operations from checking their inventory once a month to checking it once a week and then once a day and then in real-time, knowing exactly what’s on the shelves and what’s not.

That equivalent is what we’ll have to arrive at if we’re to make our systems work. Timeliness, I think, is one of the under-recognized but fundamentally powerful aspects because we sometimes over prioritize the comprehensiveness of data and then it’s a year old, which doesn’t make it all that useful. Having data that tells you something that happened this week, that’s transformative.

Are you using an iPad at work?

Gawande: I do use the iPad here and there, but it’s not readily part of the way I can manage the clinic. I would have to put in a lot of effort for me to make it actually useful in my clinic.

For example, I need to be able to switch between radiology scans and past records. I predominantly see cancer patients, so they’ll have 40 pages of records that I need to have in front of me, from scans to lab tests to previous notes by other folks.

I haven’t found a better way than paper, honestly. I can flip between screens on my iPad, but it’s too slow and distracting, and it doesn’t let me talk to the patient. It’s fun if I can pull up a screen image of this or that and show it to the patient, but it just isn’t that integrated into practice.

What problems are immune to technological innovation? What will need to be changed by behavior?

Gawande: At some level, we’re trying to define what great care is. Great care means being able to provide optimally knowledgeable care in the right time and the right way for people and not wasting resources.

Some of it’s crucially aided by information technology that connects information to where it needs to be so that good decision-making happens, both by patients and by the clinicians who work with them.

If you’re going to be able to make health care work better, you’ve got to be able to make that system work better for people, more efficiently and less wastefully, less harmfully and with much better teamwork. I think that information technology is a tool in that, but fundamentally you’re talking about making teams that can go from being disconnected cowboys in care to pit crews that actually work together toward solving a problem.

In a football team or a pit crew, technology is really helpful, but it’s only a tiny part of what makes that team great. What makes the team great is that they know what they’re aiming to do, they’re very clear about their goals, and they are able to make sure they execute every basic thing that’s crucial for that success.

What do you worry about in this surge of interest in more data-driven approaches to medicine?

Gawande: I worry the most about a disconnect between the people who have to use the information and technology and tools, and the people who make them. We see this in the consumer world. Fundamentally, there is not a single [health] application that is remotely like my iPod, which is instantly usable. There are a gazillion number of ways in which information would make a huge amount of difference.

That sense of being able to understand the world of the user, the task that’s accomplished and the complexity of what they have to do, and connecting that to the people making the technology — there just aren’t that many lines of marriage. In many of the companies that have some of the dominant systems out there, I don’t see signs that that’s necessarily going to get any better.

If people gain access to better information about the consequences of various choices, will that lead to improved outcomes and quality of life?

Gawande: 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.”

It’s that give and take that ends up being very powerful.

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August 23 2012

Balancing health privacy with innovation will rely on improving informed consent

Society is now faced with how to balance the privacy of the individual patient with the immense social good that could come through great health data sharing. Making health data more open and fluid holds both the potential to be hugely beneficial for patients and enormously harmful. As my colleague Alistair Croll put it this summer, big data may well be a civil rights issue that much of the world doesn’t know about yet.

This will likely be a tension that persists throughout my lifetime as technology spreads around the world. While big data breaches are likely to make headlines, more subtle uses of health data have the potential to enable employers, insurers or governments to discriminate — or worse. Figuring out shopping habits can also allow a company to determine a teenager was pregnant before her father did. People simply don’t realize how much about their lives can be intuited through analysis of their data exhaust.

To unlock the potential of health data for the public good, informed consent must mean something. Patients must be given the information and context for how and why their health data will be used in clear, transparent ways. To do otherwise is to duck the responsibility that comes with the immense power of big data.

In search of an informed opinion on all of these issues, I called up Deven McGraw (@HealthPrivacy), the director of the Health Privacy Project at the Center for Democracy and Technology (CDT). Our interview, lightly edited for content and clarity, follows.

Should people feel better about, say, getting their genome decoded because the Patient Protection and Affordable Care Act (PPACA) was upheld by the Supreme Court? What about other health-data-based discrimination?

Deven McGraw: The reality that someone could get data and use it in a way that harms people, and the inability to get affordable health care insurance or to get insurance at all, has been a significant driver of the concerns people have about health data for a very long time.

It’s not the only driver of people’s privacy concerns. Just removing the capacity for entities to do harm to individuals using their health data is probably not going to fully resolve the problem.

It’s important to pursue from a policy standpoint, but it’s also the case that people feel stigmatized by their health data. They feel health care is something they want to be able to pursue privately, even if the chances are very low that anybody could get the information and actually harm them with it by denying them insurance or denying them employment, which is an area we actually haven’t fully fixed. Your ability to get life insurance or disability insurance was not fixed by the Affordable Care Act.

Even if you fix all of those issues, privacy protections are about building an ecosystem in health care that people will trust. When they need to seek care that might be deemed to be sensitive to them, they feel like they can go get care and have some degree of confidence that that information isn’t going to be shared outside of those who have a need to know it, like health care providers or their insurance company if they are seeking to be reimbursed for care.

Obviously, public health can play a role. The average individual doesn’t realize that, often, their health data is sent to public health authorities if they have certain conditions or diseases, or even just as a matter of routine reporting for surveillance purposes.

Some of this is about keeping a trustworthy environment for individuals so they can seek the care they need. That’s a key goal for privacy. The other aspect of it is making sure we have the data available for important public purposes, but in a way that respects the fact that this data is sensitive.

We need to not be disrupting the trust people have in the health care system. If you can’t give people some reasonable assurance about how their data is used, there are lots of folks who will decline to seek care or will lie about health conditions when truthfulness is important.

Are health care providers and services being honest about health data use?

Deven McGraw: Transparency and openness about how we use health data in this country is seriously lacking. Part of it is the challenge of being up front with people, disclosing things they need to know but not overwhelming them with so much information in a consent form that they just sign on the bottom and don’t read it and don’t fully understand it.

It’s really hard to get notice and transparency right, and it’s a constant struggle. The FTC report on privacy talks a lot about how hard it is to be transparent with people about data sharing on the Internet or data collection on your mobile phone.

Ideally, for people to be truly informed, you’d give them an exhaustive amount of information, right? But if you give them too much information, the chances that they’ll read it and understand it are really low. So then people end up saying “yes” to things they don’t even realize they’re saying “yes” to.

On the other hand, we haven’t put enough effort into trying different ways of educating people. We, for too long, have assumed that, in a regulatory regime that provides permissive data sharing within the health care context, people will just trust their doctors.

I’ve been to a seminar on researchers getting access to data. The response of one of the researchers to the issue of “How do you regulate data uses for research?” and “What’s the role of consent?” and “What’s the role of institutional review boards?” was, “Well, people should just trust researchers.”

Maybe some people trust researchers, but that’s not really good enough. You have to earn trust. There’s a lot of room for innovative thinking along those lines. It’s something I have been increasingly itchy to try to dive into in more detail with folks who have expertise in other disciplines, like sociology, anthropology and community-building. What does it take to build trusted infrastructures that are transparent, open and that people are comfortable participating in?

There’s no magic endpoint for privacy, like, “Oh, we have privacy now,” versus, “Oh, we don’t have privacy.” To me, the magic endpoint is whether we have a health care data ecosystem that most people trust. It’s not perfect, but it’s good enough. I don’t think we’re quite there yet.

What specifically needs to happen on the openness and transparency side?

Deven McGraw: When I hear about state-based or community-based health information exchanges (HIE) going out and having town meetings with people in advance of building the HIE, working with the physicians in their communities to make sure they’re having conversations with their patients about what’s happening in the community, the electronic records movement and the HIE they’re building, that’s exactly the kind of work you need to do. When I hear about initiatives where people have actually spent the time and resources to educate patients, it warms my heart.

Yes, it’s fairly time- and resource-intensive, but in my view, it pays huge dividends on the backend, in terms of the level of trust and buy-in the community has to what you’re doing. It’s not that big of a leap. If you live in a community where people tend to go to church on Sundays, reach out to the churches. Ask pastors if you can speak to their congregations. Or bring them along and have them speak to their own congregations. Do tailored outreach to people through vehicles they already trust.

I think a lot of folks are pressed for time and resources, and feeling like digitization of the health care system should have happened yesterday. People are dying from errors in care and not getting their care coordinated. All of that is true. But this is a huge change in health care, and we have to do the hard work of outreach and engagement of patients in the community to do it right. In many ways, it’s a community-by-community effort. We’re not one great ad campaign away from solving the issue.

Is there mistrust for good reason? There have been many years of data breaches, coupled with new fears sparked by hacks enabled by electronic health record (EHR) adoption.

Deven McGraw: Part of it is when one organization has a breach, it’s like they all did. There is a collective sense that the health care industry, overall, doesn’t have its act together. It can’t quite figure out how to do electronic records right when we have breach after breach after breach. If breaches were rare, that would be one thing, but they’re still far too frequent. Institutions aren’t taking the basic steps they could take to reduce breaches. You’re never going to eliminate them, but you certainly can reduce them below where we are today.

In the context of certain secondary data uses, like when parents find out after the fact that blood spots collected from their infants at birth are being used for multiple purposes, you don’t want to surprise people about what you’re doing with their health information, the health information of their children, and that of other family members.

I think most people would be quite comfortable with many uses of health data, including those that do not necessarily directly benefit them but benefit human beings generally, or people who have the same disease, or people like them. In general, we’re actually a fairly generous people, but we don’t want to be surprised by unexpected use.

There’s a tremendous amount of work to do. We have a tendency to think issues like secondary use get resolved by asking for people’s consent ahead of time. Consent certainly plays an important role in protecting people’s privacy and giving them some sense of control over their health care information, but because consent in practice actually doesn’t do such a great job, we can’t over-rely on it to create a trust ecosystem. We have to do more on the openness and transparency side so that people are brought along with where we’re going with these health information technology initiatives.

What do doctors’ offices need to do to mitigate risks from EHR adoption?

Deven McGraw: It’s absolutely true that digitizing data in the absence of the adoption of technical security safeguards puts it much more at risk. You cannot hack into a paper file. If you lose a paper file, you’ve lost one paper file. If you lose a laptop, you’ve lost hundreds of thousands of records, if they’re on there and you didn’t encrypt the data.

Having said that, there are so many tools that you can adopt in technology with data in a digital form that are much stronger from a security standpoint than is true in paper. You can set role-based access controls for who can access a file and track who has accessed a file. You can’t do that with paper. You can use encryption technology. You can use stronger identity and authentication levels in order to make sure the person accessing the data is, in fact, authorized to do so and is the person they say they are on the other end of the transaction.

We do need people to adopt those technologies and to use them. You’re talking about a health care industry that has stewardship over some of the most sensitive data we have out there. It’s not the nuclear codes, but for a lot of people, it’s incredibly sensitive data — and yet, we trust the security of that data to rank amateurs. Honestly, there’s no other way around that. The people who create the data are physicians. Most of them don’t have any experience in digital security.

We have to count on the vendors of those systems to build in security safeguards. Then, we have to count on giving physicians and their staffs as much guidance as we can so they can actually deploy those safeguards and don’t create workarounds to them that create bigger holes in the security of the data and potentially create patient safety issues. It’s an enormously complex problem, but it’s not the reason to say, “Well, we can’t do this.”

Due to the efforts of many advocates, as you well know, health data has become a big part of the discussion around open data. What are the risks and benefits?

Deven McGraw: Honestly, people throw the term “open data” around a lot, and I don’t think we have a clear, agreed-upon definition for what that is. It’s a mistake to think that open data means all health data, fully identifiable, available to anybody, for any purpose, for any reason. That would be a totally “open data” environment. No rules, no restrictions, you get what you need. It certainly would be transformative and disruptive. We’d probably learn an awful lot from the data. But at the same time, we’ve potentially completely blown trust in the system because we can give no guarantees to anybody about what’s going to happen with their data.

Open data means creating rules that provide greater access to data but with certain privacy protections in place, such as protections on minimizing the identifiability of the data. That typically has been the way government health data initiatives, for example, have been put forth: the data that’s open, that’s really widely accessible, is data with a very low risk of being identified with a particular patient. The focus is typically on the patient side, but I think, even in the government health data initiatives that I’m aware of, it’s also not identifiable to a particular provider. It’s aggregate data that says, “How often is that very expensive cardiac surgery done and in what populations of patients? What are the general outcomes?” That’s all valuable information but not data at the granular level, where it’s traceable to an individual and, therefore, puts at risk the notion they can confidentially receive care.

We have a legal regime that opens the doors to data use much wider if you mask identifiers in data, remove them from a dataset, or use statistical techniques to render data to have a very low risk of re-identification.

We don’t have a perfect regulatory regime on that front. We don’t have any strict prohibitions against re-identifying that data. We don’t have any mechanisms to hold people accountable if they do re-identify the data, or if they release a dataset that then is subsequently re-identified because they were sloppy in how they de-identified it. We don’t have the regulatory regime that we need to create an open data ecosystem that loosens some of the regulatory constraints on data but in a way that still protects individual privacy to the maximum extent possible.

Again, it’s a balance. What we’re trying to achieve is a very low risk of re-identification; it’s impossible to achieve no risk of re-identification and still have any utility in the data whatsoever, or so I’m told by researchers.

It is absolutely the path we need to proceed down. Our health care system is so messed up and fails so many people so much of the time. If we don’t start using this data, learning from it and deploying testing initiatives more robustly, getting rid of the ones that don’t work and more aggressively pursuing the interventions that do, we’re never going to move the needle. And consumers suffer from that. They suffer as much — or more, quite frankly — than they do from violations of their privacy. The end goal here is we need to create a health care system that works and that people trust. You need to be pursuing both of those goals.

Congress hasn’t had much appetite for passing new health care legislation in this election year, aside from the House trying to repeal PPACA 33 times. That would seem to leave reform up to the U.S. Department of Health and Human Services (HHS), for now. Where do we stand with rulemaking around creating regulatory regimes like those you’ve described?

Deven McGraw: HHS certainly has made progress in some areas and is much more proactive on the issue of health privacy than I think they have been in the past. On the other hand, I’m not sure I can point to significant milestones that have been met.

Some of that isn’t completely their fault. Within an administration, there are multiple decision-makers. For any sort of policy matter where you want to move the ball forward, there’s a fair amount of process and approval up the food chain that has to happen. In an election year, in particular, that whole mechanism gets jammed up in ways that are often disappointing.

We still don’t have finalized HIPAA rules from the HITECH changes, which is really unfortunate. And I’m now thinking we won’t see them until November. Similarly, there was a study on de-identification that Congress called for in the HITECH legislation. It’s two years late, creeping up on three, and we still haven’t seen it.

You can point to those and you sort of throw up your hands and say, “What’s going on? Who’s minding the store?” If we know and appreciate that we need to build this trust environment to move the needle forward on using health IT to address quality and cost issues, then it starts to look very bad in terms of a report card for the agency on those elements.

On the other hand, you have the Office of the National Coordinator for Health IT doing more work through setting funding conditions on states to get them to adopt privacy frameworks for health information exchanges.

You have progress being made by the Office for Civil Rights on HIPAA enforcement. They’re doing audits. They now have more enforcement actions in the last year than they had in the total number of years the regulations were in effect prior to this year. They’re getting serious.

From a research perspective, the other thing I would mention is the efforts to try to make the common rule — the set of rules that governs federally funded research — more consistent with HIPAA and more workable for researchers. But there’s still a lot of work to be done on that initiative as well.

We started the conversation by saying these are really complex issues. They don’t get fixed overnight. In some respects, fast action is less important than getting it right, but we really should be making faster progress than we are.

What does the trend toward epatients and peer-to-peer health care mean for privacy, prevention and informed consent?

Deven McGraw: I think the epatient movement and increase in people’s use of Internet technologies, like social media, to connect with one another and to share data and experiences in order to improve their care is an enormously positive development. It’s a huge game-changer. And, of course, it will have an impact on privacy.

One of the things we’re going to have to keep an eye on is the fact that one out of six people, when they’re surveyed, say they practice what we call “privacy protective behaviors.” They lie to their physicians. They don’t go to seek the care they need, which is often the case with respect to mental illness. Or they seek care out of their area in order to prevent people they might know who work in their local hospital from seeing their data.

But that’s only one out of six people who say that, so there are an awful lot of people who, from the start, even when they’re healthy, are completely comfortable being open with their data. Certainly when you’re sick, your desire is to get better. And when you’re seriously sick, your desire is to save your life. Anything you can do to do that means whatever qualms you may have had about sharing your data, if they existed at all, go right out the window.

On the other hand, we have to build an ecosystem that the one out of six people can use as well. That’s what I’m focusing on, in particular, in the consumer-facing health space, the “Health 2.0 space” and on social media sites. It really should be the choice of the individual about how much data they share. There needs to be a lot of transparency about how that data is used.

When I look at a site like PatientsLikeMe, I know some privacy advocates think it’s horrifying and that those people are crazy for sharing the level of detail in their data on that site. On the other hand, I have read few privacy policies that are as transparent and open about what they do with data as PatientsLikeMe’s policy. They’re very up front about what happens with that data. I’m confident that people who go on the site absolutely know what they’re doing. It’s not my job to tell them they can’t do it.

But we also need to create environments so people can get the benefits of sharing their experiences with other patients who have their disease — because it’s enormously empowering and groundbreaking from a research standpoint — without telling people they have to throw all of their inhibitions out the door.

You clearly care about these issues deeply. How did you end up in your current position?

Deven McGraw: I was working at the National Partnership for Women and Families, which is another nonprofit advocacy organization here in town [Washington, D.C.], as their chief operating officer. I had been working on health information technology policy issues — specifically, the use of technology to improve health care quality and trying to normalize or reduce costs. I was getting increasingly involved in being a consumer representative at meetings on health information technology adoption and applauding health information technology adoption, and thinking about what the benefits for consumers were and how we can make sure that those happen.

The one issue that kept coming up in those conversations was that we know we need to build in privacy protections for this data and we know we have HIPAA — so where are the gaps? What do we need to do to move the ball forward? I never had enough time to really drill down on that issue because I was the chief operating officer of a nonprofit.

At the time, the Health Privacy Project was an independent nonprofit organization that had been founded and led by one dynamic woman, Janlori Goldman. She was living in New York and was ready to transition the work to somebody else. When the CDT approached me about being the director of the Health Privacy Project, they were moving it into CDT to take advantage of all the technology and Internet expertise at a time when we’re trying to move health care aggressively into the digital space. It was a perfect storm, with me wishing I had more time to think through the privacy issues and then this job aligned with the way I like to do policy work, which is to sit down with stakeholders and try to figure out a solution that ideally works for everybody.

From a timing perspective, it couldn’t have been more perfect. It was right during the consideration of bills on health IT. There were hearings on health information technology that we were invited to testify in. We wrote papers to put ourselves on the map, in terms of our theory about how to do privacy well in health IT and what the role of patient consent should be in privacy, because a lot of the debate was really spinning around that one issue. It’s been a terrific experience. It’s an enormous challenge.

Strata Rx — Strata Rx, being held Oct. 16-17 in San Francisco, is the first conference to bring data science to the urgent issues confronting health care.

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August 03 2012

StrataRx: Data science and health(care)

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.

Data has a long history of being “unreasonably effective.” And at least from the technologist point of view it looks like we are on the cusp of something big. We have the opportunity to move from “Health IT” to an era of data-illuminated technology-enabled health.

For example, it is well known that poverty places a disproportionate burden on the health care system. Poor people don’t have medical insurance and can’t afford to see doctors; so when they’re sick they go to the emergency room at great cost and often after they are much sicker than they need to be. But what happens when you look deeper? One project showed that two apartment buildings in Camden, NJ accounted for a hugely disproportionate number of hospital admissions.

Targeting those buildings, and specific people within them, with integrated preventive care and medical intervention has led to significant savings.

That project was made possible by the analysis of hospital admissions, costs, and intervention outcomes — essentially, insurance claims data — across all the hospitals in Camden. Acting upon that analysis and analyzing the results of the action led to savings.

But claims data isn’t the only game in town anymore. Even more is possible as electronic medical records (EMR), genomic, mobile sensor, and other emerging data streams become available.

With mobile-enabled remote sensors like glucometers, blood pressure monitors, and futuristic tools like digital pills that broadcast their arrival in the stomach, we have the opportunity to completely revolutionize disease management. By moving from discrete and costly data events to a continuous stream of inexpensive remotely monitored data, care will improve for a broad range of chronic and life-threatening diseases. By involving fewer office visits, physician productivity will rise and costs will come down.

We are also beginning to see tantalizing hints of the future of personalized medicine in action. Cheap gene sequencing, better understanding of how drug molecules interact with our biology (and each other), and the tools and horsepower to analyze these complex interactions for a specific patient with specific biology in near real time will change how we do medicine. In the same way that Google’s AdSense took cost out of advertising by using data to target ads with precision, we’ll soon be able to make medical interventions that are much more patient-specific and cost effective.

StrataRx is based on the idea that data will improve health and health care, but we aren’t naive enough to believe that data alone solves all the problems we are facing. Health and health care are incredibly complex and multi-layered and big data analytics is only one piece of the puzzle. Solving our national crisis will also depend on policy and system changes, some of them to systems outside of health care. However, we know that data and its analysis have an important role to play in illuminating the current reality and creating those solutions.

StrataRx is a call for data scientists, technologists, health professionals, and the sector’s business leadership to convene, take part in the discussion, and make a difference!

Strata Rx — Strata Rx, being held Oct. 16-17 in San Francisco, is the first conference to bring data science to the urgent issues confronting healthcare.

Save 20% on registration with the code RADAR20

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July 26 2012

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

If we look ahead to the next decade, it’s worth wondering whether the way we think about health and healthcare will have shifted. Will healthcare 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 foment 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 healthcare 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 Healthcare IT area is up 60 percent 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 healthcare, data and information technology.

"yes, but the sharks must love it!""yes, but the sharks must love it!"

[Photo Credit: Rick Smolan, via Esther Dyson]

Dyson, who started her career as a journalist, is now an angel investor and philanthropist. Dyson is a strong supporter of “preemptive healthcare” – and she’s putting her money where her interest lies, with her investments. She’ll be speaking at the StrataRX conference this October in San Francisco.

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

How do you see healthcare changing?

Dyson: There’s multiple perspectives. The one I’ve got does not invalidate others, nor it is intended to any of trump the others, but it’s the one that I focus on — and that’s really “health” as opposed to “healthcare.”

If you maintain good health, you can avoid healthcare. That’s one of those great and unrealizable goals, but it’s realizable in part. Any healthcare you can avoid because you’re healthy is valuable.

What I’m mostly focused on is trying to change people’s behavior. You’ll get agreement from almost everybody that eating right, not smoking, getting exercise, avoiding too much stress, and sleeping a lot are good for your health.

The challenge is what makes people do those things, and that’s where there’s a real lack of data. So a lot of what I’m doing is investing on space. There’s evidence-based medicine. There’s also evidence-based prevention, and that’s even harder to validate.

Right now, a lot of people are doing a lot of different things. Many of them are collecting data, which over time, with luck, will prove that some of these things I’m going to talk about are valuable.

What does the landscape for healthcare products and services look like to you today?

Dyson: I see three markets.

There’s the traditional healthcare market, which is what people usually talk about. It’s drugs, clinics, hospitals, doctors, therapies, devices, insurance companies, data processors, or electronic health records.

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 new [third] market for health existed already as health clubs. What’s exciting is that there’s now an explicit market for things that are designed to change your behavior. Usually, they’re information and social-based. These are the quantified self – analytical tools, tools for sharing, tools for fostering collaboration or competition with people that behave in a healthy way. Most of those have very little data to back them up. It’s people think they make sense. The business models are still not too clear, because if I’m healthy, who’s going to pay for that? The chances are that if I’ll pay for it, I’m already kind of a health nut and don’t need it as much as someone who isn’t.

Pharma companies will pay for some such things, especially if they think that they can sell people drugs in conjunction with them. I’ll sell you a cholesterol lowering drug through a service that encourages you to exercise, for example. That’s a nice market. You go to the pre-diabetics and you sell them your statin. Various vendors of sports clubs and so forth will fund this. But over time, I expect you’re going to see employers realize the value of this, then finally long-term insurance companies and perhaps government. But it’s a market that operates mostly on faith at this point.

Speaking of faith, Rock Health shared data that around 80 percent of mobile health apps are being abandoned by consumers after two weeks. Thoughts?

Dyson: To me, that’s infant mortality. The challenge is to take the 20 percent and then make those persist. But yeah, you’re right, people try a lot of stuff and it turns out to be confusing and not well-designed, et cetera.

If you look ahead a decade, what are the big barriers for health data and mobile technology playing a beneficial role, as opposed to a more dystopian one?

Dyson: Well, the benign version is we’ve done a lot of experimentation. We’ve discovered that most apps have an 80 percent abandon rate, but the 20 percent that are persisting get better and better and better. So the 80 percent that are abandoned vanish and the marketplace and the vendors focus on the 20 percent. And we get broad adoption. You get onto the subway in New York and everybody’s thin and healthy.

Yeah, that’s not going to happen. But there’s some impact. Employers understand the value of this is. There’s a lot more to do than just these [mobile] apps. The employers start serving only healthy food in the cafeteria. Actually, one big sign is going to be what they serve for breakfast at Strata RX. I was at the Kauffman Life Sciences Entrepreneur Conference and they had muffins, bagels and cream cheese.

Carbohydrates and fat, in other words.

Dyson: And sugar-filled yogurts. That was the first day. They responded to somebody’s tweet [the second day] and it was better. But it’s not just the advertising. It’s the selection of stuff that you get when you go to these events or when you go to a hotel or you go to school or you go to your cafeteria at your office.

Defaults are tremendously important. That’s why I’m a big fan of what Bloomberg’s trying to do in New York. If you really want to buy two servings of soda, that’s fine, but the default serving should be one. I mean personally, I’d get rid of them entirely, but anyway. You know, make the defaults smaller dinner plates. All of this stuff really does have an impact.

Anyway, ten years from now, evidence has shown what works. What works is, in fact, working because people are doing it. A lot of this is social norms have changed. The early adopters have adopted, the late adopters are being carried along in the wake — just like there are still people who smoke, but it’s no longer the norm.

Do you have concerns or hopes for the risks and rewards of open health data releases?

Dyson: If we have a sensible healthcare system, the data will be helpful. Hospitals will say, “Oh my God, this guy’s at-risk, let’s prevent him getting sick.” Hospitals and the payers will know, “Gee, if we let this guy get sick, it’s going to cost us a lot more in the long run. And we actually have a business model that operates long-term rather than simply tries to minimize cost in the short-term.”

And insurance companies will say, “Gee, I’m paying for this guy. I better keep him healthy.” So the most important thing is for us to have a system that works long-term like that.

What role will personal data ownership play in the healthcare system of the future?

Dyson: Well, first we have to define what it is. I mean, from my point-of-view, you own your own data. On the other hand, if you want care, you’ve got to share it.

I think people are way too paranoid about their data. There will, inevitably, be data spills. We should try to avoid them, but we should also not encourage paranoia. If you have a rational economic system, privacy will be an issue, but financial security will not. Those two have gotten kind of mingled in people’s minds.

Yes, I may just want to keep it quiet that I have a sexually transmitted disease, but it’s not going to affect my ability to get treatment or to get insurance if I’ve got it. On the other hand, if I have to pay a little more for my diet soda or my hamburger because it’s being taxed, I don’t think that’s such a bad idea. Not that I want somebody recording how many hamburgers I eat, just tax them — but you don’t need to tax me personally: tax the hamburger.

What about the potential for the quantified self-movement to someday potentially reveal that hamburger consumption to insurers?

Dyson: You know, people are paranoid about insurers. They’re too busy. They’re not tracking the hamburgers you eat. They’re insuring populations. I mean seriously, you know? I went to get insurance and I told Aetna, “You can have my genetic profile.” And they said, “We wouldn’t know what to do with it.” I mean seriously, I’m not saying that’s entirely impossible ever in some kind of dystopia, but I really think people obsess too much about this kind of stuff.

How should — or could — startups in healthcare be differentiating themselves? What are the big problems that they could be working on solving?

Dyson: The whole social aspect. How do you design a game, a social interaction, that encourages people to react the way you want them to react? I mean, it’s just like what’s the difference between Facebook and Friendster. They both had the same potential user base. One was successful; one wasn’t. It’s the quality of the analytics, you show individuals about their behavior. It’s the narratives, the tools and the affordances that you give them for interacting with their friends. It’s like what makes one app different from another. They all use the same data in the end, but some of them are very, very different.

For what it’s worth, of the hundreds of companies that Rock Health or anybody else will tell you about, probably a third of them will disappear. One tenth will be highly successful and will acquire the remaining 57 percent.

What are the models that exist right now of the current landscape of healthcare startups that are really interesting to you? Why?

Dyson: I don’t think there’s a single one. There’s bunches of them occupying different places.

One area I really like is user-generated research and experiments. Obviously, 23andMe*. Deep analysis of your own data and the option to share it with other people and with researchers. User-generated data science research is really fascinating.

And then social affordance, like Kia’s Health Rally, where people interact with one and other. Omada Health (which I’m an investor in) is a Rock Health company which says we can’t do it all ourselves — there’s a designated counselor for a group. It’s right now focused on pre-diabetics.

I love that, partly because I think it’s going to be effective, and partly because I really like it as an employment model. I think our country is too focused on manufacturing and there’s a way to turn more people into health counselors. I mean, I’d take all of the laid off auto workers and turn them into gym teachers, and all the laid off engineers and turn them into data scientists or people developing health apps. Or something like that.

[*Dyson is an investor in 23andMe.]

What’s the biggest myth in the health data world? What’s the thing that drives you up the wall, so to speak?

Dyson: 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.

Employers, to some extent, have that already. Your employer wants you to be healthy. They want you to show up for work, be cheerful, motivated and well rested. They get a benefit from you being healthy, far beyond simply avoiding the cost of your care.

Whereas the insurance companies, at this point, simply pass it through. If the insurance company is too effective, they actually have to lower their premiums, which is crazy. It’s really not insurance: it’s a cost-sharing and administration role that the insurance companies play. That’s something a lot of people don’t get. That needs to be fixed, one way or another.

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