Privacy

Long time (well very long time) readers of THCB will remember my extreme frustration with Patients Privacyflying cadeucii Rights founder Deborah Peel who as far as I can tell spent the entire 2000s opposing electronic health data in general and commercial EMR vendors in particular. I even wrote a very critical piece about her and the people from the World Privacy Forum who I felt were fellow travelers back in 2008. And perhaps nothing annoyed me more than her consistently claiming that data exchange was illegal and that vendors were selling personally identified health data for marketing and related purposes to non-covered entities (which is illegal under HIPAA).

However, in recent years Deborah has teamed up with Adrian Gropper, whom I respect and seemed to change her tune from “all electronic data violates privacy and is therefore bad”, to “we can do health data in a way that safeguards privacy but achieves the efficiencies of care improvement via electronic data exchange”. But she never really came clean on all those claims about vendors selling personally identified health data, and in a semi-related thread on THCB last week, it all came back. Including some outrageous statements on the extent of, value of, and implications of selling personally identified health data. So I’ve decided to move all the relevant comments to this blog post and let the disagreement continue.

What started the conversation was a throwaway paragraph at the end of a comment I left in which I basically told Adrian to rewrite what he was saying in such a way that normal people could understand it. Here’s my last paragraph

As it is, this is not a helpful open letter, and it makes a bunch of aggressive claims against mostly teeny vendors who have historically been on the patients’ side in terms of accessing data. So Adrian, Deborah & PPR need to do a lot better. Or else they risk being excluded back to the fringes like they were in the days when Deborah & her allies at the World Privacy Forum were making ridiculous statements about the concept of data exchange.

Here’s Deborah’s first comment Continue reading “Is Deborah Peel up to her old tricks?”

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I’ve been thinking about EMRs, electronic medical records, lately. It’s a subject, despite some professional experience, I don’t feel particularly close to. In fact, if anything, they are a source of consternation.

As an industry insider, I see them as an expensive albatross around our collective neck. As a human centered design advisor, I see them as an encumbrance for both providers and patients.

And, as a patient I see them largely as an opaque blob of data about me with a placating window in the form of a portal.

Which makes me wonder, am I obsessed with EMRs lately?

One of the reasons is certainly my personal interest in technology. And, while I don’t work in health IT, it’s natural to draw some connections. For instance,Wikipedia is consistently in among the top 10 most visited internet sites ( it is currently number 6 ).

And, say what you will about citing Wikipedia, but a 2010 study found it as accurate as Britanica.

Google trusts Wikipedia enough to use it as the primary source for its knowledge graph cards; and we’ve all settled a bar bet by finding some fact where a Wikipedia article is the canonical answer.

The secret sauce for Wikipedia is in it’s roots. Literally, the root of its name, wiki, describes the underlying structure. Wikis were the internet’s a solution to knowledge bases – large repositories of information about a process or thing. Companies had been using knowledge base software for years. Traditionally, a central maintainer, often a sort of corporate librarian, curated information, such as common answers to customer questions, so customer service reps could find it quickly.

Continue reading “What If EMRs Worked Like Wikipedia?”

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This story was co-published with NPR’s “Shots” blog.

In the name of patient privacy, a security guard at a hospital in Springfield, Missouri, threatened a mother with jail for trying to take a photograph of her own son. In the name of patient privacy , a Daytona Beach, Florida, nursing home said it couldn’t cooperate with police investigating allegations of a possible rape against one of its residents.

In the name of patient privacy, the U.S. Department of Veterans Affairs allegedly threatened or retaliated against employees who were trying to blow the whistle on agency wrongdoing.When the federal Health Insurance Portability and Accountability Act passed in 1996, its laudable provisions included preventing patients’ medical information from being shared without their consent and other important privacy assurances.But as the litany of recent examples show, HIPAA, as the law is commonly known, is open to misinterpretation – and sometimes provides cover for health institutions that are protecting their own interests, not patients’.

“Sometimes it’s really hard to tell whether people are just genuinely confused or misinformed, or whether they’re intentionally obfuscating,” said Deven McGraw, partner in the healthcare practice of Manatt, Phelps & Phillips and former director of the Health Privacy Project at the Center for Democracy & Technology.For example, McGraw said, a frequent health privacy complaint to the U.S. Department of Health and Human Services Office of Civil Rights is that health providers have denied patients access to their medical records, citing HIPAA. In fact, this is one of the law’s signature guarantees.”Often they’re told [by hospitals that] HIPAA doesn’t allow you to have your records, when the exact opposite is true,” McGraw said.

I’ve seen firsthand how HIPAA can be incorrectly invoked.

In 2005, when I was a reporter at the Los Angeles Times, I was asked to help cover a train derailment in Glendale, California, by trying to talk to injured patients at local hospitals. Some hospitals refused to help arrange any interviews, citing federal patient privacy laws. Other hospitals were far more accommodating, offering to contact patients and ask if they were willing to talk to a reporter. Some did. It seemed to me that the hospitals that cited HIPAA simply didn’t want to ask patients for permission.

Continue reading “Are Patient Privacy Laws Being Abused to Protect Medical Centers?”

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By now, most of you have probably heard—perhaps via your Facebook feed itself—that for one week in January of 2012, Facebook altered the algorithms it uses to determine which status updates appeared in the News Feed of 689,003 randomly-selected users (about 1 of every 2500 Facebook users). The results of this study—conducted by Adam Kramer of Facebook, Jamie Guillory of the University of California, San Francisco, and Jeffrey Hancock of Cornell—were just published in the Proceedings of the National Academy of Sciences (PNAS).

Although some have defended the study, most have criticized it as unethical, primarily because the closest that these 689,003 users came to giving voluntary, informed consent to participate was when they—and the rest of us—created a Facebook account and thereby agreed to Facebook’s Data Use Policy, which in its current iteration warns users that Facebook “may use the information we receive about you . . . for internal operations, including troubleshooting, data analysis, testing, research and service improvement.”

Some of the discussion has reflected quite a bit of misunderstanding about the applicability of federal research regulations and IRB review to various kinds of actors, about when informed consent is and isn’t required under those regulations, and about what the study itself entailed.

Continue reading “Why We May Be Making Too Much of the Facebook Experiment”

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At the first White House public workshop on Big Data, Latanya Sweeney, a leading privacy researcher at Carnegie Mellon and Harvard who is now the chief technologist for the Federal Trade Commission, was quoted as asking about privacy and big data, “computer science got us into this mess; can computer science get us out of it?”

There is a lot computer science and other technology can do to help consumers in this area. Some examples:

•    The same predictive analytics and machine learning used to understand and manage preferences for products or content and improve user experience can be applied to privacy preferences. This would take some of the burden off individuals to manage their privacy preferences actively and enable providers to adjust disclosures and consent for differing contexts that raise different privacy sensitivities.

Computer science has done a lot to improve user interfaces and user experience by making them context-sensitive, and the same can be done to improve users’ privacy experience.

•    Tagging and tracking privacy metadata would strengthen accountability by making it easier to ensure that use, retention, and sharing of data is consistent with expectations when the data was first provided.

•    Developing features and platforms that enable consumers to see what data is collected about them, employ visualizations to increase interpretability of data, and make data about consumers more available to them in ways that will allow consumers to get more of the benefit of data that they themselves generate would provide much more dynamic and meaningful transparency than static privacy policies that few consumers read and only experts can interpret usefully.

In a recent speech to MIT’s industrial partners, I presented examples of research on privacy-protecting technologies.

Continue reading “Using Technology to Better Inform Consumers about Privacy Decisions”

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T was never a star service tech at the auto dealership where he worked for more than a decade. If you lined up all the techs, he wouldn’t stand out: medium height, late-middle age, pudgy, he was as middle-of-the-pack as a guy could get.

He was exactly the type of employee that his employer’s wellness vendor said was their ideal customer. They could fix him.

A genial sort, T thought nothing of sitting with a “health coach” to have his blood pressure and blood taken, get weighed, and then use the coach’s notebook computer to answer, for the first time in his life, a health risk appraisal.

He found many of the questions oddly personal: how much did he drink, how often did he have (unprotected) sex, did he use sleeping pills or pain relievers, was he depressed, did he have many friends, did he drive faster than the speed limit? But, not wanting to rock the boat, and anxious to the $100/month bonus that came with being in the wellness program, he coughed up this personal information.

The feedback T got, in the form of a letter sent to both his home and his company mailbox, was that he should lose weight, lower his cholesterol and blood pressure, and keep an eye on his blood sugar. Then, came the perfect storm that T never saw developing.

His dealership started cutting employees a month later. In the blink of an eye, a decade of service ended with a “thanks, it’s been nice to know you” letter and a few months of severance.

T found the timing of dismissal to be strangely coincidental with the incentivized disclosure of his health information.

Continue reading “What If Your Employer Gets Access to Your Medical Records?”

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The field of analytics has fallen into a few big holes lately that represent both its promise and its peril.  These holes pertain to privacy, policy, and predictions.

Policy.  2.2/7. The biggest analytics project in recent history is the $6 billion federal investment in the health exchanges.  The goals of the health exchanges are to enroll people in the health insurance plans of their choice, determine insurance subsidies for individuals, and inform insurance companies so that they could issue policies and bills.

The project touches on all the requisites of analytics including big data collection, multiple sources, integration, embedded algorithms, real time reporting, and state of the art software and hardware.  As everyone knows, the implementation was a terrible failure.

The CBO’s conservative estimate was that 7 million individuals would enroll in the exchanges.  Only 2.2 million did so by the end of 2013.  (This does not include Medicaid enrollment which had its own projections.)  The big federal vendor, CGI, is being blamed for the mess.

Note that CGI was also the vendor for the Commonwealth of Massachusetts which had the worst performance of all states in meeting enrollment numbers despite its long head start as the Romney reform state and its groundbreaking exchange called the Connector. New analytics vendors, including Accenture and Optum, have been brought in for the rescue.

Was it really a result of bad software, hardware, and coding?   Was it  that the design to enroll and determine subsidies had “complexity built-in” because of the legislation that cobbled together existing cumbersome systems, e.g. private health insurance systems?  Was it because of the incessant politics of repeal that distracted policy implementation?  Yes, all of the above.

The big “hole”, in my view, was the lack of communications between the policy makers (the business) and the technology people.  The technologists complained that the business could not make decisions and provide clear guidance.  The business expected the technology companies to know all about the complicated analytics and get the job done, on time.

This ensuing rift where each group did not know how to talk with the other is recognized as a critical failure point.  In fact, those who are stepping into the rescue role have emphasized that there will be management status checks daily “at 9 AM and 5 PM” to bring people together, know the plan, manage the project, stay focused, and solve problems.

Walking around the hole will require a better understanding as to why the business and the technology folks do not communicate well and to recognize that soft people skills can avert hard technical catastrophes.

Continue reading “Very Big Data”

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It’s 8.30 am, just before clinic opens. It is 2010. Dr Byte* checks an online forum, and something catches his eye.

A female patient is complaining about a doctor. Her posting has led to strident reactions from other doctors. Patients are taking her side. It looks ugly.

It turns out that the patient had asked her family doctor whether she could use her smartphone to record the encounter. Her doctor was apparently taken aback and had paused to gather his thoughts. He asked the patient to put her smartphone away, saying that it was not the policy of the clinic to allow patients to take recordings.

The patient described how the mood of the meeting shifted. Initially jovial, the doctor had become defensive. She complied and turned off her smartphone.

The patient wrote that as soon as the smartphone was turned off the doctor raised his voice and berated her for making the request, saying that the use of a recording device would betray the fundamental trust that is the basis of a good patient-doctor relationship.

The patient wrote that she tried to reason, explaining that the recording would be useful to her and her family. But the doctor shouted at her, asking her to leave immediately and find another doctor.

Some participants on the online forum expressed disbelief. But the patient then went on to state that she could prove that this had actually happened, because she actually had a recording of the encounter. Although she had turned off her smartphone, she had a second recording device in her pocket, turned on, that had captured every word.

Continue reading “Patientgate: Why Patient Recordings Will Change Everything”

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Today, ONC released a report on patient matching practices and to the casual reader it will look like a byzantine subject. It’s not.

You should care about patient matching, and you will.

It impacts your ability to coordinate care, purchase life and disability insurance, and maybe even your job. Through ID theft, it also impacts your safety and security. Patient matching’s most significant impact, however, could be to your pocketbook as it’s being used to fix prices and reduce competition in a high deductible insurance system that makes families subject up to $12,700 of out-of-pocket expenses every year.

Patient matching is the healthcare cousin of NSA surveillance.

Health IT’s watershed is when people finally realize that hospital privacy and security practices are unfair and we begin to demand consent, data minimization and transparency for our most intimate information. The practices suggested by Patient Privacy Rights are relatively simple and obvious and will be discussed toward the end of this article.

Health IT tries to be different from other IT sectors. There are many reasons for this, few of them are good reasons. Health IT practices are dictated by HIPAA, where the rest of IT is either FTC or the Fair Credit Reporting Act. Healthcare is mostly paid by third-party insurance and so the risks of fraud are different than in traditional markets.

Healthcare is delivered by strictly licensed professionals regulated differently than the institutions that purchase the Health IT. These are the major reasons for healthcare IT exceptionalism but they are not a good excuse for bad privacy and security practices, so this is about to change.

Health IT privacy and security are in tatters, and nowhere is it more evident than the “patient matching” discussion. Although HIPAA has some significant security features, it also eliminated a patient’s right to consent and Fair Information Practice.

Continue reading “What You Need to Know About Patient Matching and Your Privacy and What You Can Do About It”

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I’ve recently returned from the 7th ID Ecosystem Steering Group Plenary in Atlanta. This is an international public-private project focused on the anything-but-trivial issue of issuing people authoritative cyber-credentials: digital passports you can use to access government services, healthcare, banks and everything else online.

Cyber ID is more than a single-sign-on convenience, or a money-saver when businesses can stop asking you for the names of your pets, it’s rapidly becoming a critical foundation for cyber-security because it impacts the resiliency of our critical infrastructure.

Healthcare, it turns out, is becoming a design center for IDESG because healthcare represents the most diverse collection of human interactions of any large market sector. If we can solve cyber-identity for healthcare, we will have solved most of the other application domains.

The cyber-identity landscape includes:

  • proving who you are without showing a physical driver’s license
  • opening a new account without having to release private information
  • eliminating the risk of identity theft
  • civil or criminal accountability for your actions based on a digital ID
  • reducing your privacy risks through anonymous or pseudonymous ID
  • enabling delegation to family members or professional colleagues without impersonation
  • reducing hidden surveillance by state or private institutions
  • when appropriate, shifting control of our digital tools to us and away from corporations

The IDESG process is deliberate and comprehensive. It impacts many hot issues in health care including patient matching, information sharing for accountable care and population healthhealth information exchangesprescription drug monitoring programsaccounting for disclosurespatient engagement and meaningful usethe physician’s ability to communicate and refer without institutional censorshipthe patient’s ability to control information from our increasingly connected devices and implants, and more.

Hospitals and health industry incumbents that seek to solve the hot issues raised by health reform are not eager to wait for a deliberate and comprehensive process. For them, privacy and cyber-security is a nice-to-have. Who will pay for this digital enlightenment?

Continue reading “IDESG Is a Glimpse of Our Digital Future”

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