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Consumer Data Liquidity – The Road So Far, The Road Ahead – #HITsm Chat Topic

Posted on August 23, 2017 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

We’re excited to share the topic and questions for this week’s #HITsm chat happening Friday, 8/25 at Noon ET (9 AM PT). This week’s chat will be hosted by Greg Meyer (@Greg_Meyer93) on the topic of “Consumer Data Liquidity – The Road So Far, The Road Ahead.”

As my summer tour of interoperability forums, lectures, and webinars winds down, patient engagement/data liquidity is arguably the hottest talk in town.  This leads me to a time of reflection looking back to my own personal experience over the last 10-15 years (yes, I’m still a fairly young guy) starting with early attempts to access my own family’s records, moving on to witnessing the consumer revolution of Dave deBronkart and Regina Holiday, and finally tracking the progression of HealthIT and public health legislation.  We’ve come a long way from the ubiquity of paper and binders and Xerox (oh my) to CDs and PDFs to most recently CDAs, Direct, and FHIR with the latter paving the way for a new breed of apps and tools.

With the lightning speed of change in technology and disruption vis-à-vis consumer devices, one would expect a dramatic shift in the consumer experience over the past 10 years with nirvana in the not too distant future.  Contrary to intuitive thinking, we haven’t come as far as we would like to think.  Even with legislation and a progression of technology such as C-CDA, OpenNotes, Direct, BlueButton, FHIR, and the promise of apps to bring it all together, pragmatically a lot of same the core broken processes and frustrations still exist today.  In July, ONC released a study on the health records request process based on a small sampling of consumers and 50 large health organizations.  Although most of the stories include modern technical capabilities, the processes reek of variance and inefficiencies that have persisted since the long lost days of the house call.

Not to put the whole state of affairs in gloom, there is still a potentially bright future not too far ahead.  With the convergence of forces from contemporary technical standards and recent legislation like the 21st Century Cures Act, consumer data liquidity is staying in the forefront of public health.  And let’s not forget the consumer.  It is partly because of the consumer revolution and patients demanding portability of their records that is forcing providers and vendors to open their systems as platforms of accessibility instead of fostering silos and walled gardens.

This week’s chat will explore the progression of health data access from the consumer’s perspective.

Here are the questions that will serve as the framework for this week’s #HITsm chat:
T1: Describe your perception/experiences of consumer data access 10-15 years ago. #HITsm

T2: Contrast your previous experience to today. Is your experience better, worse, or the same? #HITsm

T3: What gaps exist between what is available today (data, apps, networks, etc.) vs what you would like to have? #HITsm

T4: Would you prefer to manage/move your data yourself or expect HealthIT to do it for you. #HITsm

T5: Beyond FHIR, APIs, and apps, what is the future of consumer access and data liquidity? #HITsm

Bonus: Remember “Gimme My DaM Data?” What would be your slogan for consumer access? #HITsm

Upcoming #HITsm Chat Schedule
9/1 – Digital Strategies for Improving Consumer Experience
Hosted by Kyra Hagan (@HIT_Mktg_Maven from @InfluenceHlth)

9/8 – Digital Health Innovation in Pharma
Hosted by Naomi Fried (@naomifried

We look forward to learning from the #HITsm community! As always, let us know if you’d like to host a future #HITsm chat or if you know someone you think we should invite to host.

If you’re searching for the latest #HITsm chat, you can always find the latest #HITsm chat and schedule of chats here.

Healthcare Data Integration Cutting Room Floor: Cluttered with Valuable Unused and ‘Laundered’ Data – #HITsm Chat Topic

Posted on July 12, 2017 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

We’re excited to share the topic and questions for this week’s #HITsm chat happening Friday, 7/14 at Noon ET (9 AM PT). This week’s chat will be hosted by Bill Fox (@FoxBigData) of @MarkLogic on the topic of “Healthcare Data Integration Cutting Room Floor: Cluttered with valuable unused and ‘laundered’ data.”

Improving healthcare data integration, flexibility, agility and time to market for development and implementation starts with ingesting data and ends with analytics and insights-an operationalize before you analyze best practice approach.

How healthcare data is captured, represented, secured and made available to the application services intended to support the value-based models of care everyone expects to improve patient outcomes, while addressing escalating costs, is a fundamental necessity for digitally transforming today’s healthcare organizations.

Thankfully, operational data integration technologies have rapidly emerged that address and support the critical functionality healthcare providers, health plans and ancillary organizations need to support the healthcare consumers and patients, and effect true health care outcome improvement and cost containment challenges.

The intention of this chat is to share ideas, facts, thoughts, and opinions on the theme of whether the legacy technology that still dominates most IT shops in healthcare supports reform and innovation initiatives or not. Quite simply, are we leaving too much valuable, unused and ‘laundered’ healthcare data” on the ‘Cutting Room Floor’ of the very healthcare organizations we’re all counting on to best leverage that data? Our hope is that this chat helps to surface how healthcare organizations – providers, payers, 3rd parties and vendors – can get the most from our respective investment in our healthcare data platforms.

Reference & Resources:

This Week’s Topics
T1: What’s your biggest, most expensive health data “hairball” or pain point in combining data across domains or multiple systems? #HITsm

T2: What is the most valuable data that’s not being used today in #healthcare due to cost / complexity of integration? #HITsm

T3: What data impacts #healthcare consumer / member / patient experience and service the most? #HITsm

T4: 80% of all data is unstructured. What types of unstructured data can help improve service, outcomes & lower costs the most? #HITsm

T5: Why should scarce resources be invested in analytics before combining, enriching, harmonizing and operationalizing data first? #HITsm

Bonus: Why do firms continue using legacy ETL & tools vs adopting a “next gen” data integration platform approach? #HITsm

Upcoming #HITsm Chat Schedule
7/21 – Meeting the Patient Where They Are
Hosted by Melody Smith Jones (@MelSmithJones) from HYP3R

7/28 – How Does Age Impact Patient Satisfaction & Provider Switching?
Hosted by Lea Chatham (@leachatham) from @SolutionReach

8/4 – TBD
Hosted by Alan Portela (@AlanWPortela) from Airstrip

8/11 – TBD
Hosted by TBD

8/18 – Diversity in HIT
Hosted by Jeanmarie Loria (@JeanmarieLoria) from @advizehealth

8/25 – TBD
Hosted by TBD

We look forward to learning from the #HITsm community! As always let us know if you’d like to host a future #HITsm chat or if you know someone you think we should invite to host.

If you’re searching for the latest #HITsm chat, you can always find the latest #HITsm chat and schedule of chats here.

Exchange Value: A Review of Our Bodies, Our Data by Adam Tanner (Part 1 of 3)

Posted on January 25, 2017 I Written By

Andy Oram is an editor at O’Reilly Media, a highly respected book publisher and technology information provider. An employee of the company since 1992, Andy currently specializes in open source, software engineering, and health IT, but his editorial output has ranged from a legal guide covering intellectual property to a graphic novel about teenage hackers. His articles have appeared often on EMR & EHR and other blogs in the health IT space.

Andy also writes often for O’Reilly’s Radar site (http://oreilly.com/) and other publications on policy issues related to the Internet and on trends affecting technical innovation and its effects on society. Print publications where his work has appeared include The Economist, Communications of the ACM, Copyright World, the Journal of Information Technology & Politics, Vanguardia Dossier, and Internet Law and Business. Conferences where he has presented talks include O’Reilly’s Open Source Convention, FISL (Brazil), FOSDEM, and DebConf.

A lot of people are feeling that major institutions of our time have been compromised, hijacked, or perverted in some way: journalism, social media, even politics. Readers of Adam Tanner’s new book, Our Bodies, Our Data: How Companies Make Billions Selling Our Medical Records, might well add health care data to that list.

Companies collecting our data–when they are not ruthlessly trying to keep their practices secret–hammer us with claims that this data will improve care and lower costs. Anecdotal evidence suggests it does. But the way this data is used now, it serves the business agendas of drug companies and health care providers who want to sell us treatments we don’t need. When you add up the waste of unnecessary tests and treatments along with the money spent on marketing, as well as the data collection that facilitates that marketing, I’d bet it dwarfs any savings we currently get from data collection.

How we got to our current data collection practices

Tanner provides a bit of history of data brokering in health care, along with some intriguing personalities who pushed the industry forward. At first, there was no economic incentive to collect data–even though visionary clinicians realized it could help find new diagnoses and treatments. Tanner says that the beginnings of data collection came with the miracle drugs developed after World War II. Now that pharmaceutical companies had a compelling story to tell, ground-breaking companies such as IMS Health (still a major player in the industry) started to help them target physicians who had both the means of using their drugs–that is, patients with the target disease–and an openness to persuasion.

Lots of data collection initiatives started with good intentions, some of which paid off. Tanner mentions, as one example, a computer program in the early 1970s that collected pharmacy data in the pursuit of two laudable goals (Chapter 2, page 13): preventing patients from getting multiple prescriptions for the same drug, and preventing adverse interactions between drugs. But the collection of pharmacy data soon found its way to the current dominant use: a way to help drug companies market high-profit medicines to physicians.

The dual role of data collection–improving care but taking advantage of patients, doctors, and payers–persists over the decades. For instance, Tanner mentions a project by IMS Health (which he treats pretty harshly in Chapter 5) collecting personal data from AIDS patients in 1997 (Chapter 7, page 70). Tanner doesn’t follow through to say what IMS did with the AIDS data, but I am guessing that AIDS patients don’t offer juicy marketing opportunities, and that this initiative was aimed at improving the use and effectiveness of treatments for this very needy population. And Chapter 7 ends with a list of true contributions to patient health and safety created by collecting patient data.

Chapter 6 covers the important legal battles fought by several New England states (including the scrappy little outpost known for its worship of independent thinking, New Hampshire) to prevent pharmacies from selling data on what doctors are prescribing. These attempts were quashed by the well-known 2011 Supreme Court ruling on Vermont’s law. All questions of privacy and fairness were submerged by considering the sale of data to be a matter of free speech. As we have seen during several decisions related to campaign financing, the current Supreme Court has a particularly expansive notion of what the First Amendment covers. I just wonder what they will say when someone who breaks into the records of an insurer or hospital and steals several million patient records pleads free speech to override the Computer Fraud and Abuse Act.

Tanner has become intrigued, and even enamored, by the organization Patient Privacy Rights and its founder, Deborah Peel. I am closely associated with this organization and with Peel as well, working on some of their privacy summits and bringing other people into their circle. Because Tanner airs some criticisms of Peel, I’d like to proffer my own observation that she has made exaggerated and unfair criticisms of health IT in the past, but has moderated her views a great deal. Working with experts in health IT sympathetic to patient privacy, she has established Patient Privacy Rights during the 2010 decade as a responsible and respected factor in the health care field. So I counter Tanner’s repeated quotes regarding Peel as “crazy” (Chapter 8, page 83) by hailing her as a reputable and crucial force in modern health IT.

Coincidentally, Tanner refers (Chapter 8, page 79) to a debate that I moderated between IMS representative Kim Gray and Michelle De Mooy (available in a YouTube video). The discussion started off quite tame but turned up valuable insights during the question-and-answer period (starting at 38:33 in the video) about data sharing and the role of de-identification.

While the Supreme Court ruling stripped doctors of control over data about their practices–a bit of poetic irony, perhaps, if you consider their storage of patient data over the decades as an unjust taking–the question of patient rights was treated as irrelevant. The lawyer for the data miners said, “The patients have nothing to do with this” (Chapter 6, page 57) and apparently went unchallenged. How can patients’ interest in their own data be of no concern? For that question we need to look at data anonymization, also known as de-identification. This will begin the next section of our article.

2 Great Healthcare IT Data Images

Posted on September 10, 2015 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.


We’re doing this in every industry, but no where is it more important than in healthcare. No where is it more challenging either.


Can we move this raw data on “food deserts” into knowledge that can be used by healthcare?

How Do We Balance Improved Outcomes with Protecting Personal Information?

Posted on July 29, 2015 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

There’s an interesting article by the Pacific Standard (never heard of them before now) about the “hidden market” of medical data that exists. The final paragraph provides a great summary of the challenges we face when it comes to health data:

There is no perfect way to balance the competing priorities of using big data for improved health outcomes and protecting our personal information. Opinions on which interests should come first will differ—and should. But the debate cannot be open, honest, or effective if major companies like Walgreens or Safeway are secretive about what they do. People are often generous when it comes to volunteering personal data for the purpose of advancing medicine. They are less so when it comes to enriching sellers of information. Either way, the proper course of action is disclosure. Simply put, if our medical data is being bought and sold, we deserve to know it—and have a say. Perhaps making our data available to others is as helpful to medicine as IMS claims. But shouldn’t that be up to us?

That’s the best summary of balancing improved outcomes and personal information that I’ve ever read. We all want better outcomes and I think that most of us believe that the right healthcare data will get us to better outcomes. We also all want our data to be protected from people who will use it inappropriately. The balance between the two competing priorities will never be perfect.

The reality is that there’s going to be more and more healthcare data available about all of us. Much of that data is going to be shared with a large number of organizations. Most people are just fine with that sharing assuming they believe the sharing will help them receive better care. However, there does need to be some mechanism of transparency and disclosure about when and how data is used. That doesn’t happen today, but it should happen.

The challenge is that pandora’s already out of the box. The data is already flowing a lot of places and putting in accountability now will be a real challenge. Not that I’m against challenging things, but we’re kidding ourselves if we think that accountability and transparency around where and when are data is shared is going to be easy to accomplish. First, companies are going to be dragged kicking and screaming to make it happen. Some because they know they’re doing some things that are at least in the grey area and some are totally shady. Others aren’t doing anything inappropriate, but they realize the costs to implement transparency and accountability for the health data they share is going to be very high. A high cost project that doesn’t add any more revenue is a hard business proposition.

While I’m not hopeful that we’ll see a widespread transparency about what health data’s being shared where, I do think that some forward thinking healthcare companies could push this agenda forward. It will likely happen with some of the companies who have avoided the grey and shady areas of health data sharing that want to create a competitive advantage over their competitors and build trust with their users. Then, some others will follow along.

What do you think that could be done to make health data sharing that’s happening today more transparent?

The Importance of Information Governance in Healthcare – Where Should We Start?

Posted on July 14, 2015 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

As more and more health data is being captured be health organizations, health information governance is becoming an extremely important topic. In order to better understand what’s happening with health Information Governance, I sat down with Rita Bowen, Senior Vice President of HIM and Privacy Officer at HealthPort, to talk about the topic. We shot these videos as one long video, but then chopped them up into shorter versions so you could more easily watch the ones that interest you most. You can find 3 of the videos below and 2 more over on Hospital EMR and EHR.

The State of Information Governance

What’s HIM’s Role in Health Information Governance?

Where Should We Start with Information Governance?

Downsides of Incorporating Behavioral and Social Data Into an EHR

Posted on June 19, 2015 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

In response to my post about incorporating behavioral and social data into EHR, I got the following email from one of our readers:

My worry on the collection of such behavioral and social data is that it will get used to further prescribe people with the psychiatric drugs that have such horrendous side effects to the benefit of big pharma rather than move towards diet, health education, nutrition and other non-medical remedies that can have long lasting benefits for a lifetime.

It’s a very fine point. In my previous article I didn’t spend enough time talking about the potential downsides of incorporating all that data into an EHR. The reader pointed out the potential abuse by big pharma to sell more drugs. No doubt, pharma is trying to sell more drugs. I’m sure the creative minds at pharma will try and find ways to leverage this data and sell more drugs. That’s the nature of healthcare.

However, I think pharma would try to do this whether the data was in the EHR or not. In fact, having this data in the EHR for the doctor might mean the doctor makes better choices and doesn’t always default to pharma to treat a patient. For example, if you know they’re living in a poor area, then you can ask them if they have enough food or heat in the winter in order to avoid them returning to you a few weeks later with another cold. This would actually lead to less drugs because you’re actually treating the cause of the problem as opposed to just the presenting problem.

While this example paints a pretty picture, you could also paint an awful picture where this data is used for discrimination. This could be in the office itself or by insurance companies. Some of the new ACA laws help when it comes to insurance discrimination, but many fear that the move to ACOs will cause these organization to discriminate against the unhealthy and poor. I have this fear as well. When you pay to keep people healthy, who do you want to have in your patient population? The healthy.

When you start talking about including all this new data in an EHR, there are a lot of privacy and security questions that come up as well. We’ve always known that the patient record was a treasure trove of personal information that needed to be safeguarded and protected from abuse. Social and behavioral data makes the health record even that much more desirable to nefarious groups who want to abuse the data. HIPAA along with privacy and security will become that much more important.

I’m sure I’m just touching the surface on the challenges and problems associated with all this new data. Although, the thing that scares me most is the way people could abuse the data. I don’t think these are reasons to not use this data. We need to use this data to move healthcare forward. However, it is a call to be very thoughtful about how we collect, secure, and use the data we’re collecting.

A Few Quick HIMSS15 Thoughts

Posted on April 13, 2015 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

Today’s been a long day packed with meetings at HIMSS 2015. I need to reach out to HIMSS to get the final numbers, but word is that there are over 40,000 people at the show. In the hallways, the exhibit hall and the taxi lines it definitely seems to be the case. I’m not sure the jump in attendees, but I saw one tweet that IBM had 400 people there. Don’t quote me on it since I can’t find the tweet, but that’s just extraordinary to even consider that many people from one company.

Of course, the reason I can’t find the tweet is that the Twitter stream has been setting new records each day. The HIMSS 2015 Twitter Tips and Tricks is valuable if you want to get value out of the #HIMSS15 Twitter stream. I also have to admit that I might be going a bit overboard on the selfies. I think I’ve got the @mandibpro selfie disease. Not sure the treatment for it since my doctor doesn’t do a telemedicine visit while I’m in Chicago.

I’ve had some amazing meetings that will inform my blog posts for weeks to come. However, my biggest takeaway from the first official day of HIMSS is that change is in the air. The forces are at work to make interoperability a reality. It’s going to be a massive civil war as the various competing parties battle it out as they set the pathway forward.

You might think that this is a bit of an exaggeration, but I think it’s pretty close to what’s happening. What’s not clear to me is whose going to win and what the final outcome will look like. There are so many competing interests that are trying to get at the data and make it valuable for the doctor and health system.

Along those lines, I’m absolutely fascinated by the real time analytics capabilities that I saw being built. A number of companies I talked to are moving beyond the standard batch loaded enterprise data warehouse approach to a real time (or as one vendor said…we all have to call it near real time) stream of data. I think this is going to drive a massive change in innovation.

I’ll be talking more about the various vendors I saw and their approaches to this in future posts after HIMSS. While I’m excited by some of the many things these companies are doing, I still feel like many of them are constrained by their inability to get to the data. A number of them were working on such small data sets. This was largely because they can’t get the other data. One vendor told me that their biggest challenge is getting an organization to turn over their data for them for analysis.

While it’s important that organizations are extremely careful with how they handle and share their data. More organizations should be working with trusted partners in order to extract more value out of the data and to more importantly make new discoveries. The discoveries we’re making today are really great, but I can only imagine how much more we could accomplish with more data to inform those discoveries.

The Future Of…Healthcare Innovation

Posted on March 17, 2015 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

This post is part of the #HIMSS15 Blog Carnival which explores “The Future of…” across 5 different healthcare IT topics.

Innovation is a fascinating concept. Historians and philosophers have been thinking and investigating the key to innovation forever. I’m not sure anyone has ever found the true secret sauce to innovation. Every innovation I’ve ever seen has been a mix of timing, luck, and hard work.

Some times the timing is not right for a product and therefore it fails. The product might have been great, but the timing wasn’t right for it to be rolled out. Innovation always requires a little luck. Maybe it was the chance meeting with an investor that helps take and idea to the next level. Maybe it’s the luck of getting the right exposure that catapults your idea into a business. Maybe it’s the luck of the right initial end users which shape the direction of the product. Every innovation has also required hard work. In fact, the key to ensuring you’re ready for luck to be heaped upon you or to test if your timing is right is to put in the work.

The great thing is that it’s a brilliant time to be working on innovations in healthcare. We’re currently at the beginning of a confluence of healthcare innovations. Each one on its own might seem like a rather small innovation, but taken together they’re going to provide amazing healthcare innovations that shape the future of healthcare as we know it.

Let me give a few examples of the wave of innovations that are happening. Health sensors are exploding. Are ability to know in real time how well our body is performing is off the charts. There are sensors out there for just about every measurable aspect of the human body. The next innovation will be to take all this sensor data and collapse it down into appropriate communication and actions.

Another example, is the innovations in genomic medicine. The cost and speed required to map your genome is collapsing faster than Moore’s law. All of that genomic data is going to be available to innovators who want to build something on top of it.

3D printing is progressing at light speed. Don’t think this applies to healthcare? Check out this 3D printed prosthetic hand or this 3D printed heart. If you really want your mind blown, check out people’s work to provide blood to 3D printed organs.

If you think we’ve gotten value out of healthcare data, you’re kidding yourself. There are so many innovations in healthcare data that are sitting there waiting in healthcare data hoards. We just need to tap into that data and start sharing those findings with a connected healthcare system.

The mobile device is an incredible innovation just waiting for healthcare. We are all essentially walking around with a computer in our pocket now. We’ve already started to see the innovations this will provide healthcare, but it’s only just the beginning. This computer in our pocket will become the brain and communication hub for our healthcare needs.

I’m sure you can think of other innovations that I haven’t mentioned including robotics, health literacy, healthcare gaming, etc. What’s most exciting to me about the future of healthcare innovation is that each of these innovations will combine into a unforeseen innovation. The most powerful innovations in healthcare will not be a single innovative idea. Instead, it will come from someone who combines multiple innovations into one beautiful package.

The most exciting part of innovation is that it’s usually unexpected and surprising. I love surprises. What do you see as the future building blocks of innovation in healthcare?

De-Identification of Data in Healthcare

Posted on January 14, 2015 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

Today I had a chance to sit down with Khaled El Emam, PhD, CEO and Founder of Privacy Analytics, to talk about healthcare data and the de-identification of that healthcare data. Data is at the center of the future of healthcare IT and so I was interested to hear Khaled’s perspectives on how to manage the privacy and security of that data when you’re working with massive healthcare data sets.

Khaled and I started off the conversation talking about whether healthcare data could indeed be de-identified or not. My favorite Patient Privacy Rights advocate, Deborah C. Peel, MD, has often made the case for why supposedly de-identified healthcare data is not really private or secure since it can be re-identified. So, I posed that question to Khaled and he suggested that Dr. Peel is only telling part of the story when she references stories where healthcare data has been re-identified.

Khaled makes the argument that in all of the cases where healthcare data has been reidentified, it was because those organizations did a poor job of de-identifying the data. He acknowledges that many healthcare organizations don’t do a good job de-identifying healthcare data and so it is a major problem that Dr. Peel should be highlighting. However, just because one organization does a poor job de-identifying data, that doesn’t mean that proper de-identification of healthcare data should be thrown out.

This kind of reminds me of when people ask me if EHR software is secure. My answer is always that EHR software can be more secure than paper charts. However, it depends on how well the EHR vendor and the healthcare organization’s staff have done at implementing security procedures. When it’s done right, an EHR is very secure. When it’s done wrong, and EHR could be very insecure. Khaled is making a similar argument when it comes to de-identified health data.

Khaled did acknowledge that the risks are never going to be 0. However, if you de-identify healthcare data using proper techniques, the risks are small enough that they are similar to the risks we take every day with our healthcare data. I think this is an important point since the reality is that organizations are going to access and use healthcare data. That is not going to stop. I really don’t think there’s any debate on this. Therefore, our focus should be on minimizing the risks associated with this healthcare data sharing. Plus, we should hold organizations accountable for the healthcare data sharing their doing.

Khaled also suggested that one of the challenges the healthcare industry faces with de-identifying healthcare data is that there’s a shortage of skilled professionals who know how to do it properly. I’d suggest that many who are faced with de-identifying data have the right intent, but likely lack the skills needed to ensure that the healthcare data de-identification is done properly. This isn’t a problem that will be solved easily, but should be helped as data security and privacy become more important.

What do you think of de-identification in healthcare? Is the way it’s being done a problem today? I see no end to the use of data in healthcare, and so we really need to make sure we’re de-identifying healthcare data properly.