Privacy could ‘crash’ big data if not done right

April 15, 2014 | By Ashley Gold | FierceHealthIT

Privacy has the potential to crash big data before there’s a chance to get it right, and finding the right balance is key to future success, experts argued at a Princeton University event earlier this month.

The event, titled “Big Data and Health: Implications for New Jersey’s Health Care System” featured four panels exploring health, privacy, cost and transparency in regard to how big data can improve care and patient outcomes, according to an article on the university’s website.

“Privacy will crash big data if we don’t get it right,” Joel Reidenberg, visiting professor of computer science at Princeton and a professor at Fordham University’s School of Law, said at the event.

To view the full article, please visit Privacy could ‘crash’ big data if not done right

 

Petition for OSTP to Conduct Public Comment Process on Big Data and the Future of Privacy

February 10, 2013

Patient Privacy Rights, joined by EPIC, ACLU, Center for Democracy & Technology, EFF and 24 other consumer privacy and public interest organizations asked the White House’s Office of Science and Technology Policy to issue a Request for Information in order to conduct a review that incorporates the concerns and opinions of those whose data may be collected in bulk as a result of their engagement with technology.

“We believe that the public policy considerations arising from big data and privacy are issues of national concerns that ‘require the attention at the highest levels of Government.’”

The Coalition for Patient Privacy believes that the “OSTP should consider a broad range of big data privacy issues, including but not limited to:
(1) What potential harms arise from big data collection and how are these risks currently addressed?
(2) What are the legal frameworks currently governing big data, and are they adequate?
(3) How could companies and government agencies be more transparent in the use of big data, for example, by publishing algorithms?
(4) What technical measures could promote the benefits of big data while minimizing the privacy risks?
(5) What experience have other countries had trying to address the challenges of big data?
(6) What future trends concerning big data could inform the current debate?”

For more information, see EPIC, Coalition Urge White House to Listen to Public on “Big Data and Privacy”

To view a copy of the letter, please visit Petition for OSTP to Conduct Public Comment Process on Big Data and the Future of Privacy

The Biggest Data Myths of 2013

The biggest myth about “Big Data” users of the entire nation’s health information is that personal health data was acquired legally and ethically.

Just ask anyone you know if they ever agreed to the hidden use and sale of sensitive personal information about their minds and bodies by corporations or “research” businesses for analytics, sales, research or any other use. The answer is “no.”

Americans have very strong individual rights to health information privacy, i.e., to control the use of their most sensitive personal information. If US citizens have any “right to privacy,” that right has always applied to sensitive personal health information. This was very clear for our paper medical records and is embodied in the Hippocratic Oath as the requirement to obtain informed consent before disclosing patient information (with rare exceptions).

The IPO filing by IMS Health Holdings at the SEC exposed the vast number of hidden health data sellers and buyers. Buying, aggregating, and selling the nation’s health data is an “unfair and deceptive” trade practice. (Read more of Dr. Peel’s comments on the IMS filing here.)

Does the public know or expect that IMS (and the 100’s of thousands of other hidden health data mining companies) buys and aggregates sensitive “prescription and promotional” records, “electronic medical records,” “claims data,” and “social media” to create “comprehensive,” “longitudinal” health records on “400 million” patients? Or that IMS buys “proprietary data sourced from over 100,000 data suppliers covering over 780,000 data feeds globally”? Again, the answer is “no.”

Given the massive hidden theft, sale, and misuse of the nation’s health information how can any physician, hospital, or health data holder represent that our personal health data is private, secure, or confidential?

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Company That Knows What Drugs Everyone Takes Going Public

Nearly every time you fill out a prescription, your pharmacy sells details of the transaction to outside companies which compile and analyze the information to resell to others. The data includes age and gender of the patient, the name, address and contact details of their doctor, and details about the prescription.

A 60-year-old company little known by the public, IMS Health, is leading the way in gathering this data. They say they have assembled “85% of the world’s prescriptions by sales revenue and approximately 400 million comprehensive, longitudinal, anonymous patient records.”

IMS Health sells data and reports to all the top 100 worldwide global pharmaceutical and biotechnology companies, as well as consulting firms, advertising agencies, government bodies and financial firms. In a January 2nd filing to the Security and Exchange Commission announcing an upcoming IPO, IMS said it processes data from more 45 billion healthcare transactions annually (more than six for each human on earth on average) and collects information from more than 780,000 different streams of data worldwide.

Deborah Peel, a Freudian psychoanalyst who founded Patient Privacy Rights in Austin, Texas, has long been concerned about corporate gathering of medical records.

“I’ve spent 35 years or more listening to how people have been harmed because their records went somewhere they didn’t expect,” she says. “It got to employers who either fired them or demoted them or used the information to destroy their reputation.”

“It’s just not right. I saw massive discrimination in the paper age. Exponential isn’t even a big enough word for how far and how much the data is going to be used in the information age,” she continued. “If personal health data ‘belongs’ to anyone, surely it belongs to the individual, not to any corporation that handles, stores, or transmits that information.”

To view the full article please visit: Company That Knows What Drugs Everyone Takes Going Public

Data Mining to Recruit Sick People

Companies Use Information From Data Brokers, Pharmacies, Social Networks

Some health-care companies are pulling back the curtain on medical privacy without ever accessing personal medical records, by probing readily available information from data brokers, pharmacies and social networks that offer indirect clues to an individual’s health.

Companies specializing in patient recruitment for clinical trials use hundreds of data points—from age and race to shopping habits—to identify the sick and target them with telemarketing calls and direct-mail pitches to participate in research.

“I think patients would be shocked to find out how little privacy protection they have outside of traditional health care,” says Nicolas P. Terry, professor and co-director at the Center for Law and Health at Indiana University’s law school. He adds, “Big Data essentially can operate in a HIPAA-free zone.”

FTC Commissioner Julie Brill says she is worried that the use of nonprotected consumer data can be used to deny employment or inadvertently reveal illnesses that people want kept secret. “As Big Data algorithms become more accurate and powerful, consumers need to know a lot more about the ways in which their data is used,” Ms. Brill says.

To view the full article, please visit: Data Mining to Recruit Sick People (article published December 17, 2013)

 

 

Can Big Data Make Healthcare Better, Cheaper?

December 12, 2013
Medical records are being digitized on a massive scale to bring down the costs of healthcare and, maybe, to produce better outcomes. It also means a loss of patient privacy. President Obama’s Affordable Care Act promotes the digitization of millions of medical records to measure outcomes and contain costs. Big Data may also help doctors better understand many diseases, who’s most likely to get them and what the best treatments might be. It also makes the most intimate kind of personal information available to the government, insurance and drug companies — even prospective employers. Should patients be able to say “yes” or “no?”

 

Host, Warren Olney of NPR affiliate KCRW, interviews Dr. Deborah Peel, to discuss the risks and the benefits of Big Data in the field of medicine. She is joined by fellow panelists Joel Dudley, Department of Genetics and Genomic Sciences, Mt. Sinai Medical School, Iya Khalil, Executive VP and Co-Founder, GNS Healthcare, and Nortin Hadler, Professor of Medicine and Microbiology/Immunology, University of North Carolina at Chapel Hill.
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Can we at least try not to kill 440,000 patients per year?

Check out the latest from Doc Searls, courtesy of Doc Searls Weblog.

Obamacare matters. But the debate about it also misdirects attention away from massive collateral damage to patients. How massive? Dig To Make Hospitals Less Deadly, a Dose of Data, by Tina Rosenberg in The New York Times. She writes,

Until very recently, health care experts believed that preventable hospital error caused some 98,000 deaths a year in the United States — a figure based on 1984 data. But a new report from the Journal of Patient Safety using updated data holds such error responsible for many more deaths — probably around some 440,000 per year. That’s one-sixth of all deaths nationally, making preventable hospital error the third leading cause of death in the United States. And 10 to 20 times that many people suffer nonlethal but serious harm as a result of hospital mistakes.

The bold-facing is mine. In 2003, one of those statistics was my mother. I too came close in 2008, though the mistake in that case wasn’t a hospital’s, but rather a consequence of incompatibility between different silo’d systems for viewing MRIs, and an ill-informed rush into a diagnostic procedure that proved unnecessary and caused pancreatitis (which happens in 5% of those performed — I happened to be that one in twenty). That event, my doctors told me, increased my long-term risk of pancreatic cancer.

Risk is the game we’re playing here: the weighing of costs and benefits, based on available information. Thus health care is primarily the risk-weighing business we call insurance. For generations, the primary customers of health care — the ones who pay for the services — have been insurance companies. Their business is selling bets on outcomes to us, to our employers, or both. They play that game, to a large extent, by knowing more than we do. Asymmetrical knowledge R them.

Now think about the data involved. Insurance companies live in a world of data. That world is getting bigger and bigger. And yet, McKinsey tells us, it’s not big enough. In The big-data revolution in US health care: Accelerating value and innovation (subtitle: Big data could transform the health-care sector, but the industry must undergo fundamental changes before stakeholders can capture its full value), McKinsey writes,

Fiscal concerns, perhaps more than any other factor, are driving the demand for big-data applications. After more than 20 years of steady increases, health-care expenses now represent 17.6 percent of GDP—nearly $600 billion more than the expected benchmark for a nation of the United States’s size and wealth.1 To discourage overutilization, many payors have shifted from fee-for-service compensation, which rewards physicians for treatment volume, to risk-sharing arrangements that prioritize outcomes. Under the new schemes, when treatments deliver the desired results, provider compensation may be less than before. Payors are also entering similar agreements with pharmaceutical companies and basing reimbursement on a drug’s ability to improve patient health. In this new environment, health-care stakeholders have greater incentives to compile and exchange information.

While health-care costs may be paramount in big data’s rise, clinical trends also play a role. Physicians have traditionally used their judgment when making treatment decisions, but in the last few years there has been a move toward evidence-based medicine, which involves systematically reviewing clinical data and making treatment decisions based on the best available information. Aggregating individual data sets into big-data algorithms often provides the most robust evidence, since nuances in subpopulations (such as the presence of patients with gluten allergies) may be so rare that they are not readily apparent in small samples.

Although the health-care industry has lagged behind sectors like retail and banking in the use of big data—partly because of concerns about patient confidentiality—it could soon catch up. First movers in the data sphere are already achieving positive results, which is prompting other stakeholders to take action, lest they be left behind. These developments are encouraging, but they also raise an important question: is the health-care industry prepared to capture big data’s full potential, or are there roadblocks that will hamper its use

The word “patient” appears nowhere in that long passage. The word “stakeholder” appears twice, plus eight more times in the whole piece. Still, McKinsey brooks some respect for the patient, though more as a metric zone than as a holder of a stake in outcomes:

Health-care stakeholders are well versed in capturing value and have developed many levers to assist with this goal. But traditional tools do not always take complete advantage of the insights that big data can provide. Unit-price discounts, for instance, are based primarily on contracting and negotiating leverage. And like most other well-established health-care value levers, they focus solely on reducing costs rather than improving patient outcomes. Although these tools will continue to play an important role, stakeholders will only benefit from big data if they take a more holistic, patient-centered approach to value, one that focuses equally on health-care spending and treatment outcomes.

McKinsey’s customers are not you and me. They are business executives, many of which work in health care. As players in their game, we have zero influence. As voters in the democracy game, however, we have a bit more. That’s one reason we elected Barack Obama.

So, viewed from the level at which it plays out, the debate over health care, at least in the U.S., is between those who believe in addressing problems with business (especially the big kind) and those who believe in addressing problems with policy (especially the big kind, such as Obamacare).

Big business has been winning, mostly. This is why Obamacare turned out to be a set of policy tweaks on a business that was already highly regulated, mostly by captive lawmakers and regulators.

Meanwhile we have this irony to contemplate: while dying of bad data at a rate rivaling war and plague, our physical bodies are being doubled into digital ones. It is now possible to know one’s entire genome, including clear markers of risks such as cancer and dementia. That’s in addition to being able to know one’s quantified self (QS), plus one’s health care history.

Yet all of that data is scattered and silo’d. This is why it is hard to integrate all our available QS data, and nearly impossible to integrate all our health care history. After I left the Harvard University Health Services (HUHS) system in 2010, my doctor at the time (Richard Donohue, MD, whom I recommend highly) obtained and handed over to me the entirety of my records from HUHS. It’s not data, however. It’s a pile of paper, as thick as the Manhattan phone book. Its utility to other doctors verges on nil. Such is the nature of the bizarre information asymmetry (and burial) in the current system.

On top of that, our health care system incentivizes us to conceal our history, especially if any of that history puts us in a higher risk category, sure to pay more in health insurance premiums.

But what happens when we solve these problems, and our digital selves become fully knowable — by both our selves and our health care providers? What happens to the risk calculation business we have today, which rationalizes more than 400,000 snuffed souls per annum as collateral damage? Do we go to single-payer then, for the simple reason that the best risk calculations are based on the nation’s entire population?

I don’t know.

I do know the current system doesn’t want to go there, on either the business or the policy side. But it will. Inevitably.

At the end of whatever day this is, our physical selves will know our data selves better than any system built to hoard and manage our personal data for their interests more than for ours. When that happens the current system will break, and another one will take its place.

How many more of us will die needlessly in the meantime? And does knowing (or guessing at) that number make any difference? It hasn’t so far.

But that shouldn’t stop us. Hats off to leadership in the direction of actually solving these problems, starting with Adrian Gropper, ePatient Dave, Patient Privacy RightsBrian Behlendorf, Esther Dyson, John Wilbanks, Tom Munnecke and countless other good people and organizations who have been pushing this rock up a hill for a long time, and aren’t about to stop. (Send Doc more names or add comments directly to this blog here.)

Courtesy of Doc Searls Weblog

Pairing patient privacy with health big data analytics

“Health privacy and security are often mentioned in tandem, but Deborah Peel, Founder and Chair of Patient Privacy Rights and Adrian Gropper, Chief Technology Officer of Patient Privacy Rights, took a different view in a recent Institute for Health Technology Transformation (iHT2) webcast.”

“The presentation, titled “Competing for Patient Trust and Data Privacy in the Age of Big Data” detailed a few of the nuances between patient data privacy and security and why privacy is so significant as healthcare organizations pull together huge data sets for health information exchange (HIE) and accountable care.”

To view the full article, please visit: Pairing patient privacy with health big data analytics

The webcast can be viewed at: Competing for Patient Trust and Data Privacy in the Age of Big Data Webinar

Re: Pres. Obama appoints Todd Park nation’s CTO

The new US Chief Technical Officer (CTO) was chosen for using “innovative technologies to modernize government, reduce waste and make government information more accessible to the public.”

What role does the CTO have in protecting individuals from technology harms? Whose role is it to protect the public from damaging technologies and “big data”?

Technology could enable break-through health research and improve the quality of healthcare. But we won’t have complete and accurate health data needed for transformative research when millions don’t trust electronic health systems. The 35-40% of the public who are “health privacy intense” realize US law doesn’t adequately protect their rights to health privacy.

The full article by Bernie Monegain in Healthcare IT News: President Obama appoints Todd Park Nation’s CTO