Community Hospitals And The Big Data Disservice

It’s funny how seemingly incongruous events can converge and bring about an “aha” experience. You know aha experiences. Those funny little brain burps when synapses cascade and create new meaning, solve problems and lead, if we are lucky, to new ideas and solutions. We all have them. Individuals that have a lot of them are often called creative. For most of us, the events go unnoticed or are shrugged off as a strange feeling. But sometimes, just sometimes, they stick.

Well, today I had an “aha” experience. It happened in the shower. They always seem to happen in the shower for me, but as I was enjoying the warmth of the water as it chased away the chill of the air, a quote from a book I was listening to became connected with an issue about big data.

Let me explain. I have a long and tedious commute to work. I drive from central New Jersey into Brooklyn, New York every day. The 32-mile trip takes anywhere from one and a half hours to two hours — longer on holidays and Fridays. As result, I started listening to books on my smartphone. More often than not, these are books I have already read. I find that listening adds a new dimension to the prose. In the past year, I have finished over 46 books and recently started listening to the Dune series by Frank Herbert. I’m currently reading Good Emperor of Dune.

During my more productive hours at work, I have been struggling with the need for analytics at my hospital. The constant battering of vendors talking about big data confuses me. I did not seek to establish the kingdom of big data in my health system. I did not expect or invite this new burden of resources on an already overworked staff.  But it is upon me, and I am muddled. You see, I am under the impression that healthcare does not know big data — at least not yet.

I acknowledge really big data is happening. A Japanese engineering corporation has sensors on the wheels of high-speed trains that monitor vibration. The sensors take thousands measurements per second, which are used to reduce vibration and noise. That’s big data. A genomic company in California analyzed over 100 million gene samples to predictively identify coronary artery disease candidates. That’s big data.

What you and I are being asked to do at our hospitals — that’s not big data.

Yes, the magnitude of data being produced is astounding. Exabytes of new data are created every day. But just because the volume of data is big, does not mean the data is meaningful. Just because operational data is available, does not mean the data is useful. And just because the wealth of transactional data is at our fingertips, does not mean we have the capacity to use it. Healthcare has to differentiate between big data and crucial analytics.

And that is where my “aha” experience clicked.

“Desire brings the participants together. Data sets the limits of their dialogue. Doubt frames their questions.” – Aphorisms from God Emperor of Dune

This quote collided with my confusion around big data and something fell into place. Big data is real. It is more than simply a matter of size, desire, data and doubt. Big data is the desire for new insights and opportunity. Big data bursts the limit of the dialogue and big data drives down doubt.

You see, big data is predictive. Large health systems and academic medical centers like Kaiser Permanente, The Cleveland Clinic, and Geisinger Health System, I am sure, are doing big data. They use big data as an opportunity to find insights in new and emerging types of questions. It is not seeking a specific answer; they use it predictively and are, I suppose, positioned to respond accordingly.

Most of us at the community hospital however are not doing big data; we are doing crucial analytics — desire, data and doubt. Analytics has the desire to bring items together. It sets limits on its data, and drives up doubt. Analytics is generally retroactive. It targets a specific question and seeks a specific answer. When I am looking for HbA1C over 10 in the primary zip codes of my hospital, I am doing analytics. When I compare physician utilization on a DRG, I am doing analytics. When I know there is a specific answer, I am doing analytics.

There is the difference. Big data is predictive and demands no specific result, while analytics is retroactive and seeks a specific answer. I think most of us are doing analytics. Big data demands data scientists and big budgets. How many community hospitals can afford the human and financial resources of big data? Not many, I suspect.

Analytics, however, has its place and is getting lost in all the talk of big data. I want to do analytics. I want to understand the nature of my population. I want to offer appropriate services to my community. I want my patients to trust my health system to treat them well.

But when vendors come to my hospital and try to sell me big data, they do me a disservice. Big data involves big staffing needs and data scientists with skills beyond the reach of most community settings. Trying to sell me a predictive tool by telling me it will open up new opportunities has no value to me. Trying to sell me a tool and not define the massive resources needed to manage predictive data is just wrong.

Don’t get me wrong; I’m glad there are organizations exploring the power of big data in healthcare, and I am sure it will empower providers. I’m just not sure when. I know big data in health care will live in genomics and synaptic pathway studies, and will eventually provide predictive indicators that will allow a caregiver to provide better care. I wish I could contribute to this pursuit in a positive and meaningful way, but today, big data challenges the capacity of the community hospitals and health systems. Our future depends upon our ability to be agile and act on results. Big data is not there yet. It needs to bake a little longer because the hard part, the thing that no one talks about is this — the true meaning of data is that we master its value.