big data

HIMSS 2019

After taking a break for a few years, I was able to attend this year’s annual HIMSS conference. If you were unable to attend, I can sum up the industry trends in two words: interoperability and analytics. I was there for several days, and I never saw a presentation or exhibit that didn’t discuss analytics. It’s quite a contrast from even a few years ago.

The highlight of the event for me this year was being able to accept UNC Health Care’s award for reaching AMAM Stage 7. As one of the first and only organizations to ever reach the top, I could not be more proud of our teams at UNC Health Care. In addition, I was asked to give a talk on “How Practical Big Data Management Can Drive Value in Healthcare” (session BG5 held Monday Feb 11 at 2:30PM). I’ve posted my slides here if you would like to review the talk.

Sharing Models of Health Analytics Success

I’m honored to have been asked by HIMSS to share some of the models for success in developing health analytics capabilities at next week’s HIMSS Big Data & Healthcare Analytics Forum in Boston, MA. As I shared in my last post, UNC Health Care is one of the first and only organizations to achieve Stage 7, the highest level of analytical capability development, as assessed by the HIMSS Analytics International Adoption Model for Analytics Maturity (AMAM). Along with Philip Bradley, regional director of North America for HIMSS Analytics, we will be talking about some of the competencies that are associated with these advanced stages of maturity. I hope you can join us!

Enterprise Capability Development for Health Analytics


I was asked by the folks at Corinium Global Intelligence to give a keynote address and participate in a discussion panel at their Chief Data and Analytics Officer Winter Event. It was a great opportunity to provide a little more context behind our strategy of shifting from a project to capability-based approach to analytics application. I tried to weave in a few case studies just so people could see how some of this is actually applied as well.

It was interesting to note the commonalities that are emerging between health care and other industries as it attempts to develop these new business capabilities. Though healthcare’s understanding of how to develop and operate advanced analytics “at scale” is immature compared to, for example, it’s competencies around descriptive statistics in areas like quality measures, the market is evolving rapidly.

Corinium was kind enough to post a copy of the slides to LinkedIn, so I thought I would share the presentation with you as well.

CXO Insights Article: The Coming Era of High Performance Medicine

CIO Review recently published an article I wrote regarding how the health care industry can increase the value from their information technology assets. The article, called The Coming Era of High Performance Medicine, focusing on the intersection of enterprise architecture and data sciences.

I'm Hiring at UNC Health Care


For those that may be unaware, I’ve taken on a new role with the UNC Health Care System, and I am building a new team.  We are creating an innovative, industry-leading example of a system-wide health analytics organization – one that is truly focused on bringing advanced analytics, data sciences, agile engineering, and user enablement together to empower health care.  If you love data and want an opportunity to really see how it can improve patients’ lives in one of the nation’s leading academic medical systems, we just might have the perfect opportunity for you.

Go to UNC Health Care’s Career page and search on keywords “Enterprise Analytics” to see the current openings.  The site is constantly be updated with new roles, so check back often.

UNC / Duke Seminar: Making Medicine Smarter Through Analytics and Data Science


UNC, Duke, and other universities in our state have a joint Health Informatics Research Seminar series, and they were kind enough to ask me to come share some thoughts on the state of the health analytics industry. You can see a recording of the talk titled Making Medicine Smarter Through Analytics and Data Sciences by clicking the seminar broadcast link.

The Road to High Performance Medicine

Medical Informatics World asked me to deliver a keynote address on how analytics are evolving within the health and life sciences markets. They were nice enough to record the talk and post it to YouTube, so I’ve provided the link here. If you’d like to see the slides and hear the accompanying talk track in more detail, I’ve posted a slide recording to YouTube as well. The basic question I’m intending to address is whether medicine truly become a performance-driven industry.? The complexity residing at the intersection between the science of medicine, the delivery of health care services, and natural patient variation has made it difficult to scale organizational performance beyond the effectiveness of individual contributors. Yet other fields such as space exploration, battlefield operations, meteorology, financial services, and automotive racing have demonstrated that comparably complex systems can be characterized and even managed to very high levels of performance. By adopting similar capabilities in the context of population health, accountable care, and personalized medicine, my premise is that health and life sciences organizations can unlock a new era of clinical, financial, and operational high performance.

I also delivered a separate talk on enterprise architecture, which I will post separately later.  And I got the opportunity to share the stage with some of my favorite industry speakers during two panel discussions.

Medical Informatics World 2015 Final Panel. From left: Eric Glazer, Gowtham Rao, John Halamka, Stephen Warren, Jason Burke, and J.D. Whitlock. Image courtesy of Cambridge Healthtech Institute.

Medical Informatics World 2015 Final Panel. From left: Eric Glazer, Gowtham Rao, John Halamka, Stephen Warren, Jason Burke, and J.D. Whitlock. Image courtesy of Cambridge Healthtech Institute.

Does health care need “big data” or “big insights?”

I’m thinking of starting my own medical condition:

Big Data Fatigue Syndrome (BDFS): a cognitive disorder characterized by feelings of frustration, disbelief, and growing apathy caused by repeated exposure to over-hyped technology concepts.  Occasionally accompanied by recurring fantasies of slapping publishers.

In the midst of our mad rush to amass yottabytes of “big data” as the cure-all for health care (see my Twitter feed for example articles), I wonder if it might be possible to pause briefly and ask one question:

What exactly are you going to do with the data?

Don’t get me wrong: I am a huge advocate of the opportunity in big data (I actually believe it could be revolutionary).  But it strikes me that health and life sciences has not really mastered “small data,” yet everyone seems excited to discuss big data.  I suppose it is no different in other industries — the hype is rolling along, with Gartner estimating 2013 spending of $34B.  That’s more than ice cream money.

Yet there are a few things we’ve learned in other industries and data experiences that might be applicable to health care:

1.  If you don’t know what you are going to do with data, there is no way you will collect it properly.  Hint: EMR implementers, you might want to look into this.

2.  “More” and “Better” are two different and often unrelated concepts.

3.  “More” increases costs regardless of how it is used (i.e., storage, cleaning, administration, integration architectures, software licenses, etc.).

4.  “Better”, when used properly, increases return on investment (i.e., increased efficacy, productivity, cost containment and avoidance, revenue maximization)

5.  If the “more” is not already inherently “better”, it can only become “better” by incurring additional costs.

“More” is a quantitative assessment – one petabyte is more than 500 terabytes.  “Better” is a qualitative assessment – it requires context in order to assess.  In the world of analytics, that context is directly related to the question you are trying to answer. Without that context, “more” can only ever be “more.”

In a conference I spoke at in July, I posed this question to the audience: do we really want “big data,” or should we be focused on “big insights?” Based on the reaction in the room, I think the question resonated with a lot of health executives.  If we raised the caliber of questions we are asking, we would undoubtedly find big data has a dramatic role to play.  For example, I’ve written before that big data presents a new opportunity in the science we practice.  What sorts of clinical questions could we answer using this analytics-oriented approach…investigations that could potentially offer immediate benefits to patients and physicians?  Could we, for example, model a 3-factor relationship between disease prevalence, socio-economic status, and geography in order to better optimize the design of clinical trials?  Could we mine behavioral propensities to look for non-genomic indicators of treatment efficacy?  Could we predict (not just detect) epidemiological progressions based on real-time consumer data feeds?

For each of these, the question itself opens up a more meaningful dialogue.  How exactly could we analyze that?  What data could we potentially use?  How much data would we likely need?  What would be the limitations of the data, and how might we address those limitations?  What other questions would we need to answer in order to feel confident in our findings?  These questions put us on the road to delivering real value from our data assets, regardless of their size or source.

The discussions we need to be having should be around the insights that could provide the biggest impacts across health and life sciences.  Let’s define “better” before we decide how much “bigger.”