Desire, Data and Doubt

Desire, Data and Doubt

Daniel Morreale, VP and CIO, Hunterdon Healthcare

Daniel Morreale, VP and CIO, Hunterdon Healthcare

It is funny how seemingly incongruous events can converge and bring about aha experience. You know aha experiences. Those funny little brain burps when synapse cascade and create new meaning, solve problems and lead, if we are lucky, to new ideas and solutions. We all have them. Individual 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 sometime, just sometime they recompense.

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 commute back and forth to work. I drive from southern New Jersey to Central Western New Jersey about 100 miles every day. The trip takes anywhere from two hours to two and a half hours, longer on holiday Fridays. As a result, I started to listen to books, a lot of books.

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 nor provoke the realm 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 big data is really happening. A Japanese engineering corporation has sensors on the wheels of high speed trains that monitor vibration. The sensors take thousands measurements a 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 predicatively 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 - Frank Herbert

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 burst the limit, the dialogue and drives down doubt. You see big data is predictive. Large health systems and academic medical centers like Kaiser Permanente, The Cleveland Clinics, 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 predicatively and, I suppose, are positioned to respond accordingly. Artificial Intelligence (AI) systems add to this confusion. AI will have an impact on health care and will make my organization better at what it does but the growth into AI has to be evolutionary. We have to build the early skill to benefit from information.

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. And, 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 scientist 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 involved big staffing needs and data scientist 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 am 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 healthcare 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 hospital and health system. 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.

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