Health Data Outside the Doctor’s Office

Screen Shot 2014-12-02 at 7.01.42 AMHealth primarily happens outside the doctor’s office—playing out in the arenas where we live, learn, work and play. In fact, a minority of our overall health is the result of the health care we receive.  If we’re to have an accurate picture of health, we need more than what is currently captured in the electronic health record.

That’s why the U.S. Department of Health and Human Services (HHS) asked the distinguished JASON group to bring its considerable analytical power to bear on this problem: how to create a health information system that focuses on the health of individuals, not just the care they receive. JASON is an independent group of scientists and academics that has been advising the Federal government on matters of science and technology for over 50 years.

Why is it important to pursue this ambitious goal? There has been an explosion of data that could help with all kinds of decisions about health. Right now, though, we do not have the capability to capture and share that data with those who make decisions that impact health—including individuals, health care providers and communities.

The new report, called Data for Individual Health, builds upon the 2013 JASON report, A Robust Health Data Infrastructure.  It lays out recommendations for an infrastructure that could not only achieve interoperability among electronic health records (EHRs), but could also integrate data from all walks of life—including data from personal health devices, patient collaborative networks, social media, environmental and demographic data and genomic and other “omics” data.

This report, done in partnership with the Agency for Healthcare Research and Quality (AHRQ) and the Office of the National Coordinator for Health Information Technology (ONC) with support from the Robert Wood Johnson Foundation, comes at a pivotal time: ONC is in the process of developing a federal health IT strategic plan and a shared, nationwide interoperability roadmap, which will ensure that information can be securely shared across an emerging health IT infrastructure.

Data sharing is a critical piece of this equation. While we need infrastructure to capture and organize this data, we also need to ensure that individuals, health care professionals and community leaders can access and exchange this data, and use it to make decisions that improve health.

Initiatives like Blue Button and OpenNotes are already empowering patients and allowing them to take a more active role in their care. But giving individuals access to integrated streams of data from inside and outside the doctor’s office can increase the ways in which people engage directly in their own health and wellness.

Broadening data beyond the four walls of the doctors’ office will give health care professionals a more holistic view of their patient’s health. Sharing that data among members of the health care team will also lead to greater care coordination. Ensuring this data is used in meaningful ways will of course require training our health care workforce to a higher level of quantitative literacy.

Efforts now underway like County Health Rankings guide community leaders in setting priorities for improving health. With access to more data, communities can make faster, smarter decisions that support health—creating healthier homes, schools, workplaces and neighborhoods. For example, if a city wants to plan bike infrastructure, they could invest millions in conducting studies into where bike lanes should go, or they instead could quickly access information generated by bikers, such as Map My Ride or Strava, to see where people are actually riding.

While there are an enormous number of uses for the data that we can imagine and many more we cannot yet anticipate, it will be vitally important that we all make every effort to protect the privacy and security of these data. The report highlights numerous ways to protect the data in ways that benefit health and wellness, while also prompting accelerated innovation.

We’re excited by the potential to take this emerging data and turn it into useable information to build a Culture of Health—a nation where everyone has the opportunity to live longer, healthier lives.

We encourage everyone— consumers, providers, employers, purchasers, health IT developers and others—to take a look at the report and share your comments below. We look forward to hearing from you.

66 replies »

  1. It’s about capturing their attention requires accuracy, personalization and trust when it comes to healthcare professionals.
    And if we have the real picture of health, precisely we need more than that we captured.

  2. William-thanks for the comment-you’re essentially making one of the core points the JASONs made. People need to either own or if the law doesn’t support that (yet) manage and control their data. That premise should be the foundation for any data architecture. Not sure where all the comments about giving data to the government came from. These reports highlight the same worries. In fact they’re describing an ecosystem with personal data control and encryption that looks a lot more like the Apple encryption that…wait for it…has the government so concerned. #ironiesabound #readthereport

  3. Bob-thanks for the great comment. Of course the point of these reports is exactly the point you’re making. It’s not about collecting more data. In fact it’s not about collecting any data. It’s about recognizing that we are creating more and more data in our lives in and out of health care (who knew there’s life outside of health care?) the reports describe ways to organize the data…so people can..ask the right questions…make the data useful information to help us all make better decisions. Kind of like we can get to information on the Internet when we need it…

  4. It’s illegal to sell organ donations in the US. It’s illegal to force labor. One has to get permission from the patient to use a blood or other body specimen for research or commercial purposes. And if discoveries or patents or other uses bring revenue to the users of such specimens then the patients get shares of this revenue.

    Why not make it illegal to use patient data without the patient’s permission and, if it is used for commercial purposes, patients receive a share of any revenue generated thereby? Allow patients to sell their records. If it is illegal to use the data generated from the taking of and using a patient’s specimen, then it should surely be illegal to use the data generated from the entire body without permission or recompense. The body is merely a large specimen, is it not?

  5. Trust the “government” with my ALL of my personal health data?

    NO PROBLEM!! I’m sure they will take excellent care of it, and never lose it like Lois Lerner’s emails, or let it get out there on the web, or use it against me.

  6. Ugh, these dang message board features are forever mucked up. Anyway, Talos, ignore my snide reply about Vik K, and consider that the subject of this thread has almost nothing to do with wiring up EPIC coast to coast – perish THAT god-awful thought.

    So you can put away your simple math, because it’s really inapplicable in this instance.

  7. Gee Matt, Vik sounds loaded most of the time, as most frothing crypto-libertarians do. Three sheets to the black helicopters wind….

    He DOES make Al Lewis sound positively moderate, which is nice

  8. Gee Matt, Vik sounds loaded most of the time, as most frothing crypto-libertarians do. Three sheets to the black helicopters wind….

    He DOES make Al Lewis sound positively moderate, which is nice

  9. “If contributors to that big data realize that it is a large data project–eg giving census data–will they be less assidious is being accurate”

    Just look at almost any EMR note . . .

  10. Big data is not always true data, (accurate, facts, reality…called the noumena in philosophy–what is actually out there in the objective world, not created by our subjective thoughts.)

    If there is a low percentage of true data/total data could this be dangerous to our policy derived from that data? Or hazardous to our knowledge base?

    If contributors to that big data realize that it is a large data project–eg giving census data–will they be less assidious is being accurate than if it were a small data project–eg becoming part of a clinical trial?

  11. It is the delusional thinking in this piece that has kept HIT from being useful to the patients, their doctors and nurses, and the researchers who are finding that Big Data is actually Flawed Data. Who is checking?

  12. “The problem is that you and I, none of us, can get to our data when we need or want it”

    As someone who is also a patient, I’m unclear as to what of my data I want or need. I don’t care what my serum sodium was six months ago. I don’t need to know how many steps I took last week. I have no interest in getting a print-out of where I bought smokes and condoms over the last ten years.

    There are people who need and want my data to be aggregated and accessible: unfortunately, they all want to sell me something.

  13. “The unilateral rejection of facts may be the ultimate metaphor and irony of the Information Age; the more official the source the less likely it is to be believed.

    Skepticism is as old as king and country. History itself has been aptly described as an argument un-ended. But there is a profound difference between revisionist history based on new evidence and evolving social mores and the rejection of facts.

    We are overwhelmed with data from every quarter, and our capacity to filter fact from fraud is limited. But the web never rests.

    In our digital world, all the accumulated knowledge of human history is available in the palm of our hands. But intermingled with hard-won truths are half-baked theories and outright lunacy—decorated with footnotes, graphs, pie charts, and citations from credentialed “experts”—proving that the Earth is warming, the Earth is cooling, or the Earth is flat.

    If you seek it, you’ll find it. That’s the problem.

    We are overwhelmed with data from every quarter, and our capacity to filter fact from fraud is limited. But the web never rests. Men and women of good intent who simply seek “the truth” upon which to base their opinions find themselves awash in folderol.

    No longer confident in any single source for simple truths, more and more of us today are choosing to believe what we are predisposed to believe, period. Contravening facts are dismissed as lies or propaganda.

    In a more circumspect time Daniel Patrick Moynihan famously said, “You are entitled to your own opinion, but you are not entitled to your own facts.” In the dotcom world we all have our own facts.”


  14. Seems an interesting comment; isn’t this blog spurring us to think about unregulated versus regulated data? Is it spurring us to question supply side health care versus demand side health care? Questions must proceed data; good science only has a chance in experiments, not data sets.

  15. Brilliant! Dr Hardin said it best. It is not the tragedy of the commons, per se. It is the tragedy of the unregulated commons. The unregulated commons has bred the pasture of data. My comments were meant to remind, as yours, that we must regulate our ideas. My regulation would go something like this; data be damned; balance sheets at EHR companies be damned; government health plans be damned. But, instead, patients, be honored, be informed, be cared for behind close doors in a relationship. Patients will ultimately regulate the commons; physicians and health systems will not.

  16. From my blog post “Big Data” and “surveillant anxiety”:

    “Already, the lived reality of big data is suffused with a kind of surveillant anxiety — the fear that all the data we are shedding every day is too revealing of our intimate selves but may also misrepresent us.”

    From The Anxieties of Big Data, by Kate Crawford, author of the aforementioned Atlantic Monthly piece. Kate continues.

    “The current mythology of big data is that with more data comes greater accuracy and truth. This epistemological position is so seductive that many industries, from advertising to automobile manufacturing, are repositioning themselves for massive data gathering. The myth and the tools, as Donna Haraway once observed, mutually constitute each other, and the instruments of data gathering and analysis, too, act as agents that shape the social world. Bruno Latour put it this way: “Change the instruments, and you will change the entire social theory that goes with them.” The turn to big data is a political and cultural turn, and we are just beginning to see its scope.”

    “With more data comes greater accuracy and truth?” Myth, indeed. The utility of any set of data is a function of its intended use. “Big data” shot through with inacurracies can still be handsomely profitable for the analytical user (or buyer), irrespective of any harms they might visit on the individuals swept up (usually without their knowledge or assent) in the data hauls and subsequent proprietary modeling.

    A personal illustration. I worked for a number of years (2000 – 2005) in subprime credit risk modeling at a VISA/MC issuer. We routinely bought “pre-screened” prospect mailing lists for our direct mail marketing campaigns. Direct mail campaigns can be in the aggregate quite profitable at a one percent response rate or lower. Ours, being targeted to credit-hungry subprime prospects with blemished credit histories, typically had response rates of about 4%. Of those who responded, about half did not pass the initial in-house analytical cut for one reason or another (many owing to impossible, bad data in the individuals’ dossiers). Of the remaining 2% that we actually booked, perhaps half of those would eventually “charge off” (default). These were our “false positives.”

    The surviving 1% were lucrative enough to pay for everything, including a nice net margin (we set new annual profit levels every year I was there). It’s called “CPA” — cost per acquisition. Ours were about $100 per new account. Fairly standard in the industry at the time.

    Potentially creditworthy (and profitable) prospects that we passed on after they replied were our “false negatives.” And, ~96% of our marketing targets didn’t even respond, so were were “wrong” about them (the “unknown unknowns”) at the outset.

    To sum up; we were in, a material sense, routinely 99% “wrong,” but, notwithstanding, incredibly profitable.

    Now, “big data shot through with inaccuracies” is entirely another matter when it comes to, say, “terrorism surveillance” and getting it wrong…

  17. Beyond matters of empirical epistemology:

    “…The tribes of the new pastures are engaged in bitter, often bloody conflict, even though they are all, in their different ways , moral peoples. They fight not because they are fundamentally selfish but because they have incompatible visions of what a moral society should be. These are not merely scholarly disagreements, although their scholars have those, too. Rather, each tribe’s philosophy is woven into its daily life. Each tribe has its own version of moral common sense. The tribes of the new pastures fight not because they are immoral but because they view life on the new pastures from very different moral perspectives. I call this the Tragedy of Commonsense Morality.

    The Parable of the New Pastures is fictional, but the Tragedy of Commonsense Morality is real. It’s the central tragedy of modern life, the deeper tragedy behind the moral problems that divide us.”

    Greene, Joshua (2013-10-31). Moral Tribes: Emotion, Reason, and the Gap Between Us and Them (pp. 4-5). Penguin Group US. Kindle Edition.

  18. Great post Bob. The purpose of data collection just seems to data collection. The king has no clothes.

  19. This is an amazing post. Filled with ideas, ideology, beliefs and facts. This AM I was listening to a Mike and Mike discuss the college football ratings. A tweet came in from a sports journalist that went something like this: we have become slaves to metrics and data but not common sense. His problem was that teams that had been beaten by other teams were ahead of the victorious on the list.

    This struck me as related to this post. Dr Marcia Angell wrote a nice piece about the Harvard study that followed graduates to predict long life. The study has been going on for decades and some of the original cohort are over 90. The data amassed on this group, which included many variables proposed to be garnered by big data infrastructure, failed to predict who would and would not live. In fact, little of anything could be predicted from the big organized data set.

    As an editor at 3 journals lasting over 25 years I have seen big, country-wide data sets predict little. Data gathered for unsure reasons for unsure questions yields unsure insights. Large data sets are overpowered to detect dribble and mini-odds ratios lead to mini-insights (and, unfortunately, guidelines). Researchers used extensive EHR data to predict hospital outcomes and could only explain a small part of the variations in care until they looked at delta data on present on admission codes and found an insight. We found that a single variable, diagnosis discrepancy, on admission outperformed the best big data prediction models.

    Could it be that what we lack is not data, but appropriate questions? Could it be that what we lack are unified goals or philosophies about how care should proceed rather than how data will tell us it proceeds? Would it be better to develop a cottage-industry relationship with a patient than an intimate relationship with a spread sheet? Is the next tragedy of the commons data? Do we lack data or common sense? Just wondering.

  20. I am as disdainful and distrustful of big philanthropy as I am of big government. In my view, big philanthropy is one of the government’s private sector enforcement tools because of the facade of benevolence that it projects. In reality, there is a revolving door between big government and big philanthropy leaders, and, even more important a long history of the two groups playing footsie with each other while they all accrue more power, more money, and more authority over the lives of individuals.

    I would tell people to openly and vigorously reject cooperating with your initiative.

  21. Agree.
    Kaiser Permanente spent $4+ billion to install EPIC to cover 900,000 (approximately) in 2005. SImple math says that EMR installation to cover a current US population of 319 million (approx.) will cost more than $1.4 trillion. I know that one large EMR company is likely salivating about that number.

    The cost curve of the $2 trillion spent annually on healthcare would have to bend over 7% year-to-year to just cover the expense of installation of systems over 10 years ($140 billion). If anyone has data that shows that EMR installation has the possiblity of bending the cost curve 7%, I would be interested in it. I would also like to thank Vik & Al for reminding me of all the simple math I learned in 5th grade.

  22. No, I think you covered most of them. Just pointing out a recommendation by policy makers,and part of the ACA. Think it will help in the long run?

  23. Another Jason report? When will it be released? How will this fit with the ONC 10 year Roadmap? Seems to be a bit misaligned on timing.

  24. “… health information system that focuses on the health of individuals, not just the care they receive …” – ambitious goal indeed. The problem with any of this is that it can easily lead to a big brother-like situation and make people avoid rather than embrace the sharing of their information. All it takes is some password and user account breaches (be it end users or medical staff accounts) that allow identifiable information to be read by unauthorized eyes to derail such efforts for a long, long time.

  25. Hoping this will work better than the US efforts vs Ebola. Many suits who were inept at managing the threat to public health. They simply did not know what to do.

  26. The US is spending excessively on HIT that has done little to nothing in improving outcomes. Besides, the garbage in data will create erroneous conclusions, no matter how BIG your data is.

    I attended a conversation in which the stated cost of an EHR system was $250 million. That would buy many nurses and medications and food.

    I suggest you cut out the illusions of pie in the sky revelations and cut the mustard as to what it will cost to wire the US medical care system…how many $ trillions? Get real, puleeeease.

  27. Congratulations on a terrific post and report that captures much of what we need to do to fully exploit information technology and advanced analytics to create a smart and learning healthcare system – one that can deliver on the promise to use all that we (collectively) know to improve the health of all Americans.

    I believe it is worth emphasizing a few considerations:

    1. As we include those sources of important and relevant information “..Outside the Doctors Office” we must work to include those fragmented and siloed systems that live inside the hospital, or in, on, or near the patient – the intelligent subset of the 50,000 medical devices that participate in clinical diagnosis, management and treatment. That every patient’s infusion pump doesn’t automatically integrate information from the medical record, the pharmacy, the weight scale, the pulse oximeter, the blood pressure cuff, etc, is an ongoing hazard and a missed opportunity. Seamless sharing of the information in these smart and powerful devices via medical device interoperability will save time, money and lives.

    2. Busy practitioners rarely yearn for more data, as today’s data deluge is tomorrow’s cognitive flood. Rather, they seek greater insight and specific, unassailable cues for actions. We must match the growing complexity of data integration with sufficiently sophisticated expert systems and clinical decision support to make care more automatic, connected and coordinated. It is imperative that we strike the right balance between our privacy and security concerns and the requisite collection and sharing of information required for designing and informing these systems of care; excessive focus on the former will foreclose the enormous opportunity of the latter.

    3. We must move with a sense of urgency. Our nation’s excessive healthcare spending is squeezing out advances in education, critical infrastructure and even national security while creating a burden of indebtedness for our children. Is 10 years as fast as we can responsibly move?

  28. Like Mike, I also appreciate the dialogue and spectrum of opinions here. There are exciting opportunities and challenging issues that arise from a data rich health environment, and we value a robust discussion about how to approach both. Also as Mike said, I encourage you to dig into the report – almost 100 pages – and talk about what you like and where you don’t agree, and why. Thanks!

  29. I guess I should have more accurately noted that “omics” data are considered “upstream” only to the extent that they largely remain pretty much “outside the doctor’s office.” The other principal “upstream” factors include, in addition to socioeconomic and environmental metrics, issues of “lifestyle.” All of these are correlated to a significant degree.

    I’ll be at the Thursday SF event, btw.

  30. platon20-thanks for these concerns and this comment. I think the vision the JASONs describe is really about how we might organize all the data we all are creating mostly from our many devices that are bristling with sensors. Certainly data from health care that is in the EHRs is important-but those data are going to be dwarfed (if they aren’t already) by the data that we all create as we go about our daily lives. How could or should we try to protect and organize that data so we can get to it when we want or need it–and keep it secure when we don’t. That’s the point of these reports.

  31. Talos-thanks for this comment–and please see the reply to Vik’s comment above–same here. Thank you. Please come to either the San Francisco Data for Health meeting on Thursday or next week to the Charleston event.

  32. Vik Khanna-hello and thanks for this great comment. RWJF right now among other things is holding a series of meetings across the country. The next one is in San Francisco on Thursday–if you live near there please come. At these meetings we’re hoping people will voice both their hopes and aspirations for the sort of data infrastructure these reports describe–but also their concerns, worries and fears. You really capture here exactly the sort of direct concern that we want to hear. Thank you.

  33. William Palmer MD-thanks so much for the read and comment. These two reports are really about a vision for a learning health system. The premise is that we and our devices are creating increasingly huge amounts of data with no end in sight. We need ways to ensure that individuals either own or manage their own data–and can decide when they want to get to it, with whom they want to share it and how. We need a data infrastructure to enable people (not the government) to do that. These reports try to lay out the technical vision for such an infrastructure.

  34. Al Lewis–thanks for the comment-great Newton example of the power of data–if we could only get to it, turn it into useful information that people can use to improve their health or the health of their communities.

  35. Granpappy Yokum-appreciate the read and comment. Take a close look at the report though. I had to read it a few times. I think there are some potentially helpful insights for us. I honestly don’t think that this vision about the government getting these data. Our devices are already collecting all kinds of data about us. The problem is that you and I, none of us, can get to our data when we need or want it. These reports lay out a vision where we own–or at least manage our own data–decide who should get it and when. Please take a look and see what you think.

  36. As a doctor, theoretically this is a good idea but in practical real-world implementation, it is terrible.

    Here’s why:

    When the rubber hits the road, you need a team of data entry clerks to put all this stuff in the EHR. Is Robert Wood Johnson going to fund a grant for every primary care doctor to hire another data entry clerk to do this? Nope. Instead they are going to lobby Congress to make it mandatory for doctors to do it on their own dime.

    It must be nice for the folks at ONC, RWJF, and every other “health care policy” group out there. They get free data at no cost provided to them for analysis. And they get the federal government to mandate other “providers” to give it to them!

    It changes the ER check-in process (which is already way too long) into a 5 hour ordeal as all hospitals are ORDERED to collect information on fresh fruit and vegetable intake form every single patient who comes into the ER.

    All of this so ivory tower researchers who have never treated a patient get access to reams of free data to theorize on and publish studies regarding.

  37. Well, they can still eat fast food now that they are putting up calorie counts as required by the government. I’m sure they’ll all be eating less caloric foods from McDonald’s and Burger King.

  38. “Right now, though, we do not have the capability to capture and share that data with those who make decisions that impact health—including individuals, health care providers and communities.”

    I’m think’in public health nurses have a pretty good handle on it.

    After all this data is mined who’s going to get the dementia patient to take their meds or prepare their meals, who’s going to get those patients without transportation to the drug store or their doctor, who’s going to do the home care for so many elderly, who’s going to buy fresh fruits and vegetables to replace fast food in poverty neighborhoods?

  39. Given the recent examples of government officials “leaking” confidential information about governmental critics (most recent examples are http://www.thesmokinggun.com/buster/Elizabeth-Lauten-arrest-786543 and anything to do with the IRS and Lois Lerner), I will never believe that any healthcare data is secured from government access and misuse once this type of project goes fully online.

    When we installed EPIC, I realized I went from being a doctor to being a health information data entry clerk. When I realized that EPIC added 2 unpaid hours per day of extra work to my life, I realized I was working for the insurance companies and not my patients. When I wanted to change how I charted, I realized that I was at the whims of Coding and IT. When I read this article, I realized that I would be aiding in the government-supported violation of the physician-patient confidentiality compact.

    At this point I realized why so many of my colleagues were leaving the profession.

  40. “While there are an enormous number of uses for the data that we can imagine and many more we cannot yet anticipate…”

    This is a fancy way of saying we have not decided how we will use these data to manipulate people, scare them, control them, and make them come to believe that, contrary to the opening of this post, the government and its private sector enforcers, really are your health salvation, because, to paraphrase Deep Throat, that’s where the money is. There is no profit in leaving people alone.

    You need no data about me and how I live my life. You are entitled to nothing that I do not want to share with you voluntarily. The federal government used to gather data the very old-fashioned way, by doing surveys. Is there any evidence that we did not get useful information that way? And, even if it was less than ideal, was it so deficient that sacrificing privacy, consent, and voluntary participation are worth the price of admission to this brave new world of “we need all the data we can get?” Al Lewis and Granpappy Yokum above have it nailed exactly right.

    Now, the data geeks have all taken over and want to bamboozle the rest of us into believing that their technology-and-data-are-magic-fairy-dust mythology. The shroud of benevolence obscures a more subversive agenda. Bureaucrats and technocrats never do things that do not serve their own interests first: bigger budgets, longer titles, tenure (in the case of academics), etc.

    How I eat, exercise, work, enjoy myself, is none of your g.d. business. And neither is how a create a culture of health in the unit that matters the most…my family.

    It is long past time for Americans to tell government bureuacrats to take a hike.

  41. I am the program officer for this project at RWJF.

    We at RWJF are so grateful for opportunity to collaborate with ONC and AHRQ on these two JASON reports. The prior JASON report focused on a potential health data infrastructure from the health care vantage point. This year’s report focuses on such a data infrastructure when our true goal is health not health care. How does that change in vantage point change the recommendations?

    We found the prior report to be a compelling vision to help spark discussion about that health data infrastructure. I also personally think that the JASONs really nailed it with this second report. To me, this vision about using a data infrastructure to help us create a closed loop learning health system is very compelling. In some ways, it is the blueprint for the OS for a Culture of Health.

    Hopefully both reports together will add to the discussion–as we all work to help people turn data into information and from there into action that builds a Culture of Health.

  42. Jon White – as acting Deputy National Coordinator can you provide any insight as to whether or not Dr. DeSalvo will be returning full time as head of the ONC, and if so, when that might be?

  43. It sounds as if you are interested in studying community influence upon the health of individuals and possibly the reverse: the effects upon the community by the aggregate of health vectors from its individuals.

    This is a tall order and almost open ended. You could go so far as to study sales of trans fats in community grocery stores or studying ages on death certificates at the local mortuary.

    You have to remember that there are going to be many individuals and communities that do not want this data to be taken. Desperately.

    The WHO estimates that about 30% of persons have at some time in their lives a DSM classified mental illness. Even if all the processes you describe above are perfect and there is absolute security, these folks are probably not going to want their health data generated or recorded. A little imagination extends these desires to be excluded to: job seekers, bank borrowers, STD patients, HIV patients, patients who have had abortions or pelvic inflammatory disease, politicians running for office, and people who have gone through rehab and drug withdrawal.

    The same holds true for some communities that might have high obesity or suicide rates or a high incidence of coronary occlusion. Does Manchester, UK, want to be known as the coronary capital of Europe?

    Of course, then we can get to crime statistics and income levels and the percentage of cloudy and rainy days and, pretty soon, we can say that everything effects the health of the community and its individuals.

    The push back could be a problem too: people and communities who don’t want this data to be generated may avoid the health care system altogether.

    I’m not arguing against all of this. Some of this data may be very useful. I am essentially only questioning. But be slow and careful and let it grow from the soil.

    And recall that security is not only keeping the message secret. It is authenticating the sender and the receiver. And protecting the “insulation” on the cable so that the message can not be added to or subtracted from. Very difficult. See Ivan Ristic “Bulletproof SSL and TLS”

  44. I am not an expert in this category but have two observations. First, as to the bicycling, it happened right here in Newton MA. An “official” group put out a “bike map” that took two years to produce and consisted of a city map with lines drawn on the main streets, including one without a shoulder and one with that old concrete slab type of pavement that creates a groove between the slab and the asphalt shoulder. Independently, in about 2 weeks, people put a shared file on google that had far more appropriate bike routes, that I myself now use all the time (plus, I contributed one).

    As for health, while not disputing what you have suggested, I would also track “wellness-sensitive medical events” by county. Indeed those are already collected. it is just a question of reporting and age-adjusting them correctly. That is like a “defect rate” in manufacturing. They are rare, but if the number is higher than it should be, it’s an indicator that something is amiss in the health of the community.

  45. Hi folks. I’m the AHRQ project officer for the JASON report, but am also presently on detail to ONC as the acting Deputy National Coordinator. As with last year’s report, we hope that Data for Individual Health is a springboard to deeper discussion on topics that are important to all of us. Thanks in advance for your thoughtful comments, and I look forward to tracking the discussion.


  46. I find it interesting that the ONC felt compelled to write and have published this post on behalf of DeSalvo, I suppose to create the appearance that she is on top of ONC happenings and planning.

    I haven’t looked at the report yet but doesn’t this post say pretty much what most of us already know: that capturing data is not the end game – and that we can not effect change unless we put usable data is in the hands of the right people at the right time?

  47. “In fact, a minority of our overall health is the result of the health care we receive. If we’re to have an accurate picture of health, we need more than what is currently captured in the electronic health record.”

    Minority indeed. Only ~10% by some estimates. Most of the causal and contributory factors are “upstream.” But, beyond the often politically radioactive socioeconomic factors, included in that upstream estimate are the huge sets of “omics,” which many HIT people want to see included in next generation EHRs. Current CHPL certified ambulatory EHRs today house perhaps 3,500 – 4,000 variables or more “under the hood” in the RDBMS tables and schema. Adding “omics” data to those arrays will be problematic absent [1] a transformative shift the the current payment paradigm, and [2] widespread clinician competence with respect to accurately including “omics” data in the dx and tx. A typical 99213 visit today requires a fleeting time-constrained “access/view/update/append/transmit” drive-by of the several hundred (or more) variables that go into the SOAP and progress note (many of which are pro-forma in order to get paid, which goes to point 1). I will soon be 69. I’m a 99213, so this is no abstraction for me.

    The cost of “omics” assays is coming down dramatically. Their irreducible analytical and predictive complexity will remain. For Old Coots in Training like me, the “omics” horse is likely largely already out of the barn. Mandating their inclusion, given the age-related pt encounter UTIL may well be a net loser, writ large.

    “Data sharing is a critical piece of this equation. While we need infrastructure to capture and organize this [sic] data, we also need to ensure that individuals, health care professionals and community leaders can access and exchange this [sic] data, and use it to make decisions that improve health.”

    No small undertaking. We need to figure out how move beyond the fundamental “Opacity = Margin” market imperative. I’m midway through the new Schmidt-Rosenberg book “How Google Works” (which I will soon cite and review on my blog re its import for Health IT). While they laud the Google ethos of “Default of Open,” they’re not about to publish their search and ad placement algorithms. They note that such a stance opens them to charges of hypocrisy, but, so be it.

    “With a few exceptions, Google defaults to open, and for these exceptions we are often criticized as being hypocritical, since we preach open in some areas but then sometimes ignore our own advice. This isn’t hypocritical, merely pragmatic. While we generally believe that open is the best strategy, there are certain circumstances where staying closed works as well.”

    Schmidt, Eric; Rosenberg, Jonathan (2014-09-23). How Google Works (Kindle Locations 1163-1166). Grand Central Publishing. Kindle Edition.

  48. What you eat, how much you exercise, where, when, how and with whom you have sex: yep, the government wants it all.

    And that data will be for sale.