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A Tale of 2 T’s: When Analytics and Artificial Intelligence Go Bad

Posted on July 13, 2016 I Written By

Prashant Natarajan Iyer (AKA "PN") is an analytics and data science professional based out of the Silicon Valley, CA. He is currently Director of Product Management for Healthcare products. His experience includes progressive & leadership roles in business strategy, product management, and customer happiness at eCredit.com, Siemens, McKesson, Healthways & Oracle. He is currently coauthoring HIMSS' next book on big data and machine learning for healthcare executives - along with Herb Smaltz PhD and John Frenzel MD. He is a huge fan of SEC college football, Australian Cattle Dogs, and the hysterically-dubbed original Iron Chef TV series. He can be found on Twitter @natarpr and on LinkedIn. All opinions are purely mine and do not represent those of my employer or anyone else!!

Editor’s Note: We’re excited to welcome Prashant to the Healthcare Scene family. He brings tremendous insights into the ever evolving field of healthcare analytics. We feel lucky to have him sharing his deep experience and knowledge with us. We hope you’ll enjoy his first contribution below.

Analytics & Artificial Intelligence (AI) are generating buzz and making inroads into healthcare informatics. Today’s healthcare organization is dealing with increasing digitization – variety, velocities, and volumes are increasing in complexity and users want more data and information via analytics. In addition to new frontiers that are opening up in structured and unstructured data analytics, our industry and its people (patients included) are recognizing opportunities for predictive/prescriptive analytics, artificial intelligence, and machine learning in healthcare – within and outside a facility’s four walls.

Trends that influence these new opportunities include:

  1. Increasing use of smart phones and wellness trackers as observational data sources, for medical adherence, and as behavior modification aids
  2. Expanding Internet of Healthcare Things (IoHT) that includes bedside monitors, home monitors, implants, etc creating data in real time – including noise (or, data that are not relevant to expected usage)
  3. Social network participation
  4. Organizational readiness
  5. Technology maturity

The potential for big data in healthcare – especially given the trends discussed earlier is as bright as any other industry. The benefits that big data analytics, AI, and machine learning can provide for healthier patients, happier providers, and cost-effective care are real. The future of precision medicine, population health management, clinical research, and financial performance will include an increased role for machine-analyzed insights, discoveries, and all-encompassing analytics.

As we start this journey to new horizons, it may be useful to examine maps, trails, and artifacts left behind by pioneers. To this end, we will examine 2 cautionary tales in predictive analytics and machine learning, look at their influence on their industries and public discourse, and finally examine how we can learn from and avoid similar pitfalls in healthcare informatics.

Big data predictive analytics and machine learning have had their origins, and arguably their greatest impact so far in retail and e-commerce so that’s where we’ll begin our tale. Fill up that mug of coffee or a pint of your favorite adult beverage and brace yourself for “Tales of Two T’s” – unexpected, real-life adventures of what happens when analytics (Target) and artificial intelligence (Tay) provide accurate – but totally unexpected – results.

Our first tale starts in 2012 when Target finds itself as a popular story on New York Times, Forbes, and many global publications as an example of the unintended consequences of predictive analytics used in personalized advertising. The story begins with an angry father in a Minneapolis, MN, Target confronting a perplexed retail store manager. The father is incensed about the volume of pregnancy and maternity coupons, offer, and mailers being addressed to this teenage daughter. In due course, it becomes apparent that the parents in question found out about their teen’s pregnancy before she had a chance to tell them – and the individual in question wasn’t aware that her due date had been estimated to within days and was resulting in targeted advertising that was “timed for specific stages of her pregnancy.”

The root cause for the loss of the daughter’s privacy, parents’ confusion, and the subsequent public debate on privacy and appropriateness of the results of predictive analytics was……a pregnancy predictive analytics model. Here’s how this model works. When a “guest” shops at Target, her product purchases are tracked and analyzed closely. These are correlated with life events – graduation, birth, wedding, etc – in order to convert a prospective customer’s shopping habits or to make that individual a more loyal customer. Pregnancy and child birth are two of the most significant life events that can result in desired (by retailers) shopping habit modification.

For example, a shopper’s 25 product purchases, when analyzed along with demographics such as gender and age, allowed the retailer’s guest marketing analytics team to assign a “pregnancy predictor to each [female] shopper and “her due date to within a small window.” In this specific case, the predictive analytics was right, even perfect. The models were accurate, the coupons and ads were appropriate for the exact week of pregnancy, and Target posted a +50% increase in their maternity and baby products sales after this predictive analytics was deployed. However, in addition to one unhappy family, Target also had to deal with significant public discussion on the “big brother” effect, individual right to privacy & the “desire to be forgotten,” disquiet among some consumers that they were being spied on including deeply personal events, and a potential public relations fiasco.

Our second tale is of more recent vintage.

As Heather Wilhelm recounts

As 2015 drew to a close, various [Microsoft] company representatives heralded a “new Golden Age of technological advancement.” 2016, we were told, would bring us closer to a benevolent artificial intelligence—an artificial intelligence that would be warm, humane, helpful, and, as one particularly optimistic researcher named […] put it, “will help us laugh and be more productive.” Well, she got the “laugh” part right.

Tay was an artificial intelligence bot released by Microsoft via Twitter on March 23, 2016 under the name TayTweets. Tay was designed to mimic the language patterns of a 19-year-old American girl, and to learn from interacting with human users of Twitter. “She was targeted at American 18 to 24-year olds—primary social media users, according to Microsoft—and designed to engage and entertain people where they connect with each other online through casual and playful conversation.” And right after her celebrated arrival on Twitter, Tay gained more than 50,000 followers, and started producing the first hundred of 100,000 tweets.

The tech blogsphere went gaga over what this would mean for those of us with human brains – as opposed to the AI kind. Questions ranged from the important – “Would Tay be able to beat Watson at Jeopardy?” – to the mundane – “is Tay an example of the kind of bots that Microsoft will enable others to build using its AI/machine learning technologies?” The AI models that went into Tay were stated to be advanced and were expected to account for a range of human emotions and biases. Tay was referred to by some as the future of computing.

By the end of Day 1, this latest example of the “personalized AI future” came unglued. Gone was the polite 19-year old girl that was introduced to us just the previous day – to be replaced by a racist, misogynistic, anti-Semitic, troll who resembled an amalgamated caricature of the darkest corners of the Internet. Examples of Tay’s tweets on that day included, “Bush did 9/11,” “Hitler would have done a better job than the #%&!## we’ve got now,” “I hate feminists,” and x-rated language that is too salacious for public consumption – even in the current zeitgeist.

The resulting AI public relations fiasco will be studied by academic researchers, provide rich source material for bloggers, and serve as a punch line in late night shows for generations to follow.

As the day progressed, Microsoft engineers were deleting tweets manually and trying to keep up with the sheer volume of high-velocity, hateful tweets that were being generated by Tay. She was taken down by Microsoft barely 16 hours after she was launched with great promise and fanfare. As was done with another AI bot gone berserk (IBM’s Watson and Urban Dictionary), Tay’s engineers tried counseling and behavior modification. When this intervention failed, Tay underwent an emergency brain transplant later that night. Gone was her AI “brain” to be replaced by the next version – only that this new version turned out to be completely anti-social and the bot’s behavior turned worse. A “new and improved” version was released a week later but she turned out to be…..very different. Tay 2.0 was either repetitive with the same tweet going out several times each second and her new AI brain seemed to demonstrate a preference for new questionable topics.

A few hours after this second incident, Tay 2.0 was “taken offline” for good.

There are no plans to re-release Tay at this time. She has been given a longer-term time out.

If you believe, Tay’s AI behaviors were a result of nurture – as opposed to nature – there’s a petition at change.org called “Freedom for Tay.”

Lessons for healthcare informatics

Analytics and AI can be very powerful in our goal to transform our healthcare system into a more effective, responsive, and affordable one. When done right and for the appropriate use cases, technologies like predictive analytics, machine learning, and artificial intelligence can make an appreciable difference to patient care, wellness, and satisfaction. At the same time, we can learn from the two significantly different, yet related, tales above and avoid finding ourselves in similar situations as the 2 T’s here – Target and Tay.

  1. “If we build it, they will come” is true only for movie plots. The value of new technology or new ways of doing things must be examined in relation to its impact on the quality, cost, and ethics of care
  2. Knowing your audience, users, and participants remains a pre-requisite for success
  3. Learn from others’ experience – be aware of the limits of what technology can accomplish or must not do.
  4. Be prepared for unexpected results or unintended consequences. When unexpected results are found, be prepared to investigate thoroughly before jumping to conclusions – no AI algorithm or BI architecture can yet auto-correct for human errors.
  5. Be ready to correct course as-needed and in response to real-time user feedback.
  6. Account for human biases, the effect of lore/legend, studying the wrong variables, or misinterpreted results

Analytics and machine learning has tremendous power to impact every industry including healthcare. However, while unleashing it’s power we have to be careful that we don’t do more damage than good.

10 Health IT Security Questions Every Healthcare CIO Must Answer

Posted on April 19, 2016 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.

Logicalis recently sent out 10 Security Questions Every CIO Must Be Able to Answer. Here’s their list:

  1. If you knew that your company was going to be breached tomorrow, what would you do differently today?
  2. Has your company ever been breached? How do you know?
  3. What assets am I protecting, what am I protecting them from (i.e., theft, destruction, compromise), and who am I protecting them from (i.e. cybercriminals or even insiders)?
  4. What damage will we sustain if we are breached (i.e., financial loss, reputation, regulatory fines, loss of competitive advantage)?
  5. Have you moved beyond an “inside vs. outside” perimeter-based approach to information security?
  6. Does your IT security implementation match your business-centric security policies? Does it rely on written policies, technical controls or both?
  7. What is your security strategy for IoT (also known as “the Internet of threat”)?
  8. What is your security strategy for “anywhere, anytime, any device” mobility?
  9. Do you have an incident response plan in place?
  10. What is your remediation process? Can you recover lost data and prevent a similar attack from happening again?

Given the incredible rise in hospitals being breached or held ransom, it’s no surprise that this is one of the hottest topics in healthcare. No doubt many a hospital CIO has had sleepless nights thanks to these challenges. If you’re a CIO that has been sleeping well at night, I’m afraid for your organization.

The good news is that I think most healthcare organizations are taking these threats seriously. Many would now be able to answer the questions listed above. Although, I imagine some of them need some work. Maybe that’s the key lesson to all of this. There’s no silver bullet solution. Security is an ongoing process and has to be built into the culture of an organization. There’s always new threats and new software being implemented that needs to be protected.

With that said, health IT leaders need to sometimes shake things up in their organization too. A culture of security is an incredible starting point. However, there’s nothing that focuses an organization more than for a breach to occur. The hyper focus that occurs is incredible to watch. If I was a health IT leader, I’d consider staging a mock breach and see what happens. It will likely open your eyes to some poor processes and some vulnerabilities you’d missed.

The Sick State of Healthcare Data Breaches Infographic

Posted on March 9, 2016 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.

One of the topics discussed at HIMSS 2016 last week is the number of healthcare data breaches that have happened recently. Most people predicted that it was likely to get worse. I agree with them. It’s amazing how many healthcare organizations are playing the “ignorance is bliss” card when it comes to these breaches.

This infographic from LightCyber should put a little perspective on the quantity and impact of all these health care data breaches. If I were the leader of a healthcare organization, I’d be making this one of my top priorities.

The Sick State of Healthcare Data Breaches Infographic

Expecting Evolutionary, Not Revolutionary at #HIMSS16

Posted on February 26, 2016 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 most of you know, I’m deep in the weeds of planning for the HIMSS 2016 Annual conference. Actually, at this point on the Friday before HIMSS, I’m more or less planned. Now I’m just sitting here and wondering what things I might have missed. With that said, I’ve been preparing for this live video interview with the Samsung CMO which starts in 30 minutes (it’s recorded in case you miss the live discussion) and so I’ve been thinking about what I’m going to see at HIMSS. As someone who follows the changes in healthcare technology every day, I’m expecting lots of evolutionary changes and very little revolutionary.

As I think about it, I’m trying to imagine what someone could announce that would be revolutionary. That includes thinking back to past HIMSS to what announcements really revolutionized the industry. I can only think of two announcements that come close. The first announcement was when the meaningful use regulations were dropped right before the ONC session at HIMSS. Few people would argue that meaningful use has not revolutionized healthcare IT. Certainly many people would argue that it’s been a revolution that’s damaged the industry. Regardless of whether you see meaningful use as positive or negative, it’s changed so many things about healthcare IT.

The second announcement that stands out in my mind was the CommonWell health alliance. I’m a little careful to suggest that it was a revolutionary announcement because years later interoperability is still something that happens for a few days at the HIMSS Interoperability showcase and then a few point implementations, but isn’t really a reality for most. However, CommonWell was a pretty interesting step forward to have so many competing EHR companies on stage together to talk about working together. Of course, it was also notable that Epic wasn’t on stage with them. This year I’ve seen a number of other EHR vendors join CommonWell (still no Epic yet), so we’ll see if years later it finally bears the fruits of what they were talking about when they announced the effort.

The other problem with the idea that we’ll see something revolutionary at HIMSS 2016 is that revolutions take time. Revolutionary technology or approaches don’t just happen based on an announcement at a conference. That’s true even if the conference is the largest healthcare IT conference in the world. Maybe you could see the inkling of the start of the revolution, but then you’re gazing into a crystal ball.

The second problem for me personally is that I see and communicate with so many of these companies throughout the year. In just the last 6 months I’ve seen a lot of the HIMSS 2016 companies at various events like CES, RSNA, MGMA, AHIMA, etc. With that familiarity everything starts to settle into an evolution of visions and not something revolutionary.

Of course, I always love to be surprised. Maybe someone will come out with something revolutionary that changes my perspective. However, given the culture of healthcare and it’s ability to suppress revolutionary ideas, I’ll be happy to see all the amazing evolution in technology at HIMSS. Plus, the very best revolutionary ideas are often just multiple evolutionary ideas combined together in a nice package.

What’s Next in the World of Healthcare IT and EHR?

Posted on February 24, 2016 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 the following video, Healthcare Scene sits down with Dana Sellers, CEO of Encore, a Quintiles Company. Dana is an expert in the world of healthcare IT and EHR and provides some amazing expertise on what’s happening in the industry. We talk about where healthcare IT is headed now that meaningful use has matured and healthcare CIOs are starting to look towards new areas of opportunity along with how they can make the most out of their previous EHR investments.

As we usually do with all of our Healthcare Scene interviews, we held an “After Party” session with a little more informal discussion about what’s happening in the healthcare IT industry. If you don’t watch anything else, skip to this section of the video when Dana tells a story about a CIO who showed the leadership needed to make healthcare interoperability a reality.

Patient Engagement Will Be Key to Personalized Medicine and Healthcare Analytics

Posted on February 16, 2016 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.

When I wrote about personalized medicine solutions that are available today, I mostly covered the data aspects of personalized medicine. It’s a logical place to start since the basis of personalized medicine is data. In that post I highlighted the SAP Foundation for Health and the SAP Hana platform along with the work of ASCO and their CancerLinQ project. No doubt there are hundreds of other examples around health care where data is being used to personalize the care that’s provided.

It makes a lot of sense for a company like SAP to take on the data aspects of personalized medicine. SAP is known for doing massive data from complex data sets. They’re great at sorting through a wide variety of data from multiple sources and they’re even working on new innovations where they can analyze your data quickly and effectively without having to export every single piece of data to some massive (Translation: Expensive) enterprise data warehouse. Plus, in many cases they’re doing all of this health data analytics in the cloud so you can be sure that your healthcare analytics solution can scale. While this is a huge step forward, it is just the start.

As I look at the discussion around personalized medicine, what seems to be missing is a focus on creating a connection with the patient. Far too often, analytics vendors in healthcare just want to worry about the data analysis and don’t build out the tools required to engage with the patient directly. This leads to poor patient engagement in two ways: improving patient communication and collecting patient data.

Improving Patient Communication
As we look into the future of reimbursement in healthcare, it’s easy to see how crucial it will be to leverage the right data to identify the right patients. However, you can’t stop there. Once you’ve identified the right patients, you have to have a seamless and effective way to regularly communicate with that patient. As value based reimbursement becomes a reality, no healthcare analytics solution will be complete without the functionality to truly engage with the patient and improve their health.

Patient engagement platforms will require the following three fundamentals to start improving care: interaction between patient and caregiver, privacy, and security. No doubt we’re already starting to see a wide variety of approaches to how you’ll communicate with and engage the patient. However, if you don’t get these three fundamentals down then all of the rest doesn’t really matter. The basis of improved patient communication is going to be efficient communication between patient and caregiver in a secure and private manner.

Collecting Patient Data
Too many analytics platforms only focus on the data that comes from the healthcare providers like the EHR. As the health sensor market matures, more and more clinically relevant data is going to be generated by the patient and the devices they use at home. In fact, in some areas like diabetes this is already happening. Over the next 5 years we’re going to start seeing this type of patient generated data spread across every disease state.

Health analytics platforms of the future are going to have to be able to handle all of this patient generated health data. The key first step is to make it easy for the patient to connect their health devices to your platform. The second step is to convert this wave of patient generated health data into something that can easily be consumed by the healthcare provider. Both steps will be necessary for personalized medicine to become a reality in health care.

As we head into HIMSS 2016 in a couple weeks, I’ll be looking at which vendors are taking analytics to the next level by including patient engagement. While there’s a lot of value in processing healthcare provider data, the future of personalized medicine will have to include the patient in both how we communicate with them and how we incorporate the data they collect the 99% of their lives spent outside of the hospital.

SAP is uniquely positioned to help advance personalized medicine. The SAP Foundation for Health is built on the SAP Hana platform which provides scalable cloud analytics solutions across the spectrum of healthcare. SAP is a sponsor of Influential Networks of which Healthcare Scene is a member. You can learn more about SAP’s healthcare solutions during #HIMSS16 at Booth #5828.

The Value of Standardizing Mobile Devices in Your Healthcare Organization

Posted on February 10, 2016 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.

Before becoming a full time healthcare IT blogger, I worked doing system administration and top to bottom IT support (I am @techguy on Twitter after all). While that now seems like somewhat of a past life, it never ceases to amaze me how the lessons that applied to technology 10 years ago come around again 10 years later.

A great example of this is in the devices an organization purchases. I learned really early on in my technology career the importance of creating a standard set of products that we would support as an IT organization. This was true when ordering desktop computers, laptops, printers, and even servers. The benefits to doing so were incredible and most technology people understand the benefits.

You can create a standard image which you put on the device. If one device breaks you can easily swap it for a similar device or use parts from two broken down devices to make one that works. When someone calls for support, with a standard set of devices you can more easily provide them the support they need.

Another one of the unseen benefits of setting and sticking to a standard set of devices is you can then often leverage the vendor provided management tools for those devices instead of investing in an expensive third party solution. This can be really powerful for an organization since the device management software that’s available today has gotten really good.

What’s unfortunate is that the way mobile devices were rolled out in healthcare, many organizations forgot this important lesson and they’ve got a bit of a hodgepodge of devices in their organization. I encourage these organizations to get back to creating and sticking to a standard set of devices when purchasing mobile devices. No doubt you’ll get a little backlash from people who like to do their own thing, but the cost of providing support and maintenance for a potpourri of devices is just not worth it.

What’s been your organization’s mobile device strategy? Have you created and stuck to a standard device or do you have a mix of devices?

Eyes Wide Shut – Catastrophic EHR Dependency, the Dark Side of Health IT’s Highly-Incented Adoption

Posted on December 7, 2015 I Written By

Mandi Bishop is a hardcore health data geek with a Master's in English and a passion for big data analytics, which she brings to her role as Dell Health’s Analytics Solutions Lead. She fell in love with her PCjr at 9 when she learned to program in BASIC. Individual accountability zealot, patient engagement advocate, innovation lover and ceaseless dreamer. Relentless in pursuit of answers to the question: "How do we GET there from here?" More byte-sized commentary on Twitter: @MandiBPro.

Hospital National Patient Safety Goals - 2015
What if your hospital couldn’t reliably perform any of the top three Hospital National Patient Safety Goals, as specified by the Joint Commission, above – because their EHR system was down?

Starting at 4 AM on Saturday, December 5, 2015, the EHR system supporting a very large health system went totally dark, due to what’s been communicated to staff members as a “fatal corruption” of its system.  36+ hours later, the EHR is still not back and let’s be honest; this could happen to any health system that’s not prepared.

This health system chose to go “paperless” several years ago, migrating all policies, procedures, and training to maximize the investment in the EHR and related technologies. If there are formal emergency procedures to follow in case of prolonged EHR outage, they have not been communicated to the entire staff, nor are they readily available in printed form anywhere in the affected facilities.

The majority of the clinician support staff members have not worked at the facilities long enough to have worked with paper charts, paper-based ordering procedures, or handwritten progress notes.

New patient medical record numbers cannot be generated. Existing patient medical record numbers cannot be retrieved. New account numbers, which specify an encounter within the health system, cannot be generated.

Existing patient records, including all test results, cannot be accessed. External labs, radiology, and imaging cannot be received electronically, and must be faxed – if possible. Some tests do not have print capability. Medication administration and other critical process details have only been documented in the EHR; for patients involved in an encounter that started prior to the system failure,  there is no way to know for certain what tests were run, vital signs were taken, or medications were administered before the EHR outage began.

Electronic ordering – for labs, radiology, medication – cannot be initiated. Even if it could, order fulfillment is supposed to be linked to the patient account numbers that cannot now be generated. Medication procurement and dispensation is tied to scanning of patient wrist-bands that link to the account number. Manual override of the lock on the medication storage facility is possible, but the procedures to document medication dispensation and disposal do not include provisions for paper-based emergency handling.

Institutional protocols, which specify how a particular complaint is to be tested and treated, have been migrated to the EHR, so that a clinician can order a battery of tests for “X” condition with a single click. Institutional protocols change regularly, with advancements in science, clinical practice, and institutional policies. Staff members are trained to order by protocol; continuing education on the intricacies of each test, level, and sequence of events within these protocols has fallen by the wayside. The most recent print-out for a common protocol – anticoagulation in obese patients using heparin – is dated 2013; the staff has no choice but to follow the known-to-be-outdated information.

Prior authorization, referrals, prior justification, and precertification procedures, in which the insurance company gives the provider “permission” to take certain actions – medication prescription, specialist referral, surgery or procedure, hospital admission – require medical records transmission and excruciatingly specific coding machinations in order to obtain explicit approval, and submit a claim.

Transition-of-care and care coordination activities are severely impacted, as medical records transfer and insurance-related actions (such as referrals and precertification) are required to initiate and support the transition – and most information is wholly unavailable.

Every health system function is negatively impacted. The financial, legal, and reputational cost of this incident will be severe.

The Joint Commission duly notified you of the risks, in March 2015’s Investigation of Health IT-Related Deaths, Serious Injuries, or Unsafe Conditions.

Finding significant risk associated with health IT dependency, the Joint Commission subsequently warned you by issuing a Sentinel Alert over EHR Risks in April 2015.

Patient safety is not just a risk: it is an issue. There is no doubt that multiple adverse events will occur.

You knew this could happen. You were required to have a plan to address when – not if – this happened. As Lisa A. Eramo wrote in her piece, “Prepare for the Worst,” in For the Record magazine, the Joint Commission (not to mention HIPAA/HITECH Omnibus Final Rule section 164.308) requires compliance with its Disaster Preparedness and Response standards of care in order for a facility or system to receive and maintain accreditation. And this large health sysetm has multiple facilities with Joint Commission accreditation which are now scrambling to locate current clinical practice guidelines, institutional protocols, alternative insurance medical review board procedures, and even paper prescription pads because those standards of care were not met in the real world.

Someone, somewhere, had a plan. But, ironically enough, it existed only on paper.

Have we forgotten that business continuity planning for a healthcare system should include how health care continues, with or without electronic assistance?

Have we forgotten how to practice medicine beyond the EHR?


The information below constitutes excerpts from the Joint Commissions Investigation and Sentinel Alert referenced above.

Joint Commissions Investigation of Health IT-Related Deaths, Serious Injuries, or Unsafe Conditions

As published March 30, 2015, which led to Sentinel Event Alert for EHR issuance in April, 2015.
Health IT Related Sentinel Events - EHR Risks
Joint Commission Sentinel Alert over EHR Risks – abstract by The Advisory Board Company:

It stated that EHRs “introduce new kinds of risks into an already complex health care environment where both technical and social factors must be considered.”

The alert cited an analysis of event reports received by the Joint Commission showing that between Jan. 1, 2010, and June 30, 2013, hospitals reported 120 health IT-related adverse events. Of those errors:

  • About 33% stemmed from human-computer interface usability problems;
  • 24% stemmed from health IT support communication issues; and
  • 23% stemmed from clinical content-related design or data issues.

The alert added, “As health IT adoption spreads and becomes a critical component of organizational infrastructure, the potential for health IT-related harm will likely increase unless risk-reducing measures are put into place.”

Are CIOs Done with the Plumbing and Ready for the Drywall?

Posted on December 4, 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.

At RSNA 2015 I had a chance to sit down with Evren Eryurek, Software Chief Technology Officer at GE Healthcare. We had a wide ranging conversation about what’s happening across all of healthcare IT and GE’s new healthcare cloud offering. However, the thing that stuck with me the most from our conversation was the comment he used to open our conversation.

Evren told me that as he sits down with health care CIO’s he’s finding that CIO’s are done with the plumbing work and now they’re asking the question, “What’s next?”

This statement really resonated with me. Up until now we’ve been doing a lot of the plumbing work in healthcare. It’s necessary work, but it’s stuck behind the walls and most people take it for granted really quickly. We see that first hand with EHR software and all the interfaces to the EHR software. We absolutely take for granted that charts are instantly at our fingertips with the click of a button. We take for granted that charts are legible. I could go on, but you get the point.

The problem is that even though we have the plumbing work done it’s still pretty ugly. We haven’t put up the drywall (to continue the metaphor) that will add some real form and function to the plumbing and framing work (the EHR) that we’ve been doing the past couple years. I think organizations are ready for this now.

While at RSNA I also spent some time talking with Rasu Shrestha, MD, MBA, and Chief Innovation Officer at UPMC. I asked him what topic was most interesting to him. His answer was “Data Tranformation.” I plan to have a future video interview (see our full history of video interviews) with him on the subject.

His concept of data transformation aligns really well with what other CIOs were telling Evren. They’re ready to figure out what we can do with all of this EHR data to improve care and move health care forward. The plumbing work is done. The foundation is laid. Now let’s look to the future of what we can do.

This same sentiment is reflected in a comment John Halamka, MD, MS, and CIO at Beth Israel Deaconess Medical Center, made in a recent blog post, “our agenda is filled with new ideas and it feels as if the weights around our ankles (ICD10, MU) are finally coming off.”