Health 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.
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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.
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
Again…interesting…please read the report…
Agree.Nrf2 Activator..
Bobby-thanks. It was obvious from your comments that you had read them.
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…
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?
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.
Safe to say that I have. http://tinyurl.com/mp9n63e
No more than words I can say, “This is really great.”
ahem…have folks in this string actually read the report yet? Just sayin…
applause!
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.
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
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
“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 . . .
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?
Don’t worry Vik, when they come for your data at least you’ll be loaded for bear!
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?
“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.
“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.”
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http://www.thedailybeast.com/articles/2014/12/03/the-facts-about-ferguson-matter-dammit.html
“good science only has a chance in experiments, not data sets.”
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That is fundamentally untrue. e.g.,
http://www.usc.edu/org/cosee-west/Jul_Aug2012/For%20the%20Web/General%20informaion%20on%20OOS/Obs_sci.pdf
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.
“But, instead, patients, be honored, be informed”
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By what?
“Data”?
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.
From my blog post “Big Data” and “surveillant anxiety”:
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“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…
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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.
Well said. I think the key is common sense.
Great post Bob. The purpose of data collection just seems to data collection. The king has no clothes.
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.
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.
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.
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?
Dean-yes, this report is the second. We released it yesterday morning. Follow the links in the post to get it. Regards.
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.
“… 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.
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.
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.
Overcome anxiety attacks http://freefromanxiety.co.nr
Great comment.
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?
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!
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.
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.
Peter1-No argument from me-public health nurses are awesome.
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.
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.
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.
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.
Just Sayin-please do read these reports–they’re pretty interesting.
Great inights, Bobby–as usual. (thanks for catching those typos).
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. The