The Paradox of Healthcare Analytics

Keith Bigelow

Balancing the profound and the mundane – a challenge that continues to inspire me six months into a new industry

In a career building analytics platforms and applications, I’ve been fortunate to work with some of the brightest minds in the field, including scientists at Business Objects, Salesforce and, most recently, 3D Robotics.

And then life happened.

Two years ago, I lost a cherished family member (who was also a career analytics leader). As almost everyone does in response to such a passing, I reflected on the uncertainty of our time on earth.

A colleague at 3DR shared with me his brother’s posthumously published memoir about battling lung cancer, When Breath Becomes Air, and I began to wonder if perhaps I might contribute in some way to healthcare. Perhaps it’s in my blood, as my mother’s entire career was as a post-op nurse. Then, out of nowhere, GE called and asked if I might be interested in leading their healthcare analytics solutions.

“The future is already here – it’s just not very evenly distributed.”
– William Gibson

Six months into my new adventure, I can see that healthcare is well on its quest to digitize huge amounts of complex data – from X-ray images to ECG waveforms to the sprawling data structures of the EMR. There’s so much potential and so many brilliant minds here.

And yet, like every customer with whom I have ever worked, the backlog of analytics projects extends far beyond the resources of the teams, resulting in a grueling process of prioritization and funding, of departmental “haves” and “have-nots.”

Thus, even industry thought leaders with massive budgets and infrastructure have uneven analytics coverage. While they might have early traction with a clinical imaging AI project for a specific procedure, that doesn’t mean that they feel they’ve covered the bases of their other clinical, operational and financial analytic objectives. And while there are institutions with surgeries guided by deep learning algorithms, there are many institutions where biomeds and nurses are using USB keys to manually gather and analyze radiation dose in Excel or – worse yet – not tracking it at all.

Uneven distribution indeed.

So how do we bring analytics to every department in healthcare?

How do we improve not just the quality of care but increase access and reduce cost as well? I think the answer is to offer bite-sized analytic applications that providers, payers and ACOs can easily buy and rapidly deploy, to complement the investments they’ve already made.

By offering a software-as-a-service business model, we can radically reduce the upfront cost of new analytic applications and effortlessly evolve them to help create superior outcomes with our customers. So far in my six months, we’ve released two amazing analytic apps in this fashion, with tens more in the backlog. We plan to meet our customers wherever they are, and augment the amazing work they’ve already begun.

While life is no more certain today than it was last year, I have profound conviction that we will make every department at every provider we work with better, and that I can rejoice in new conversations with my mother about the industry she served and encouraged me to enter.


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