The Internal Combustion of EHRs

I grew up in the Detroit area, where grandmothers and infants were expected to know how to replace a fuel gauge sensor and wire brush battery connections. So I always like to check the latest and greatest at auto shows, which for years have been all about piling on fuel efficiency features and on-board communication systems and trying to make hybrids and EVs viable options for the masses.

But amid all the chatter about ushering in a new age of the automobile you sometimes see industry insiders acknowledging the main impediment to any real breakthrough in efficiency:  The internal combustion engine, for all the brainpower that’s gone into its engineering and design, only uses about 15 percent of the energy generated by fuel to move the car down the road and run accessories.

Some of that loss is from idling and braking, but the majority of the problem is in the actual engine. Studies show that 60 to 65 percent of energy loss is the inability of the engine to convert the fuel’s chemical energy into mechanical energy, due to engine friction, pumping air in and out of the engine, and wasted heat. There’s obviously enormous opportunities there, and engineers across the globe are banging away with innovations like direct fuel injection, cylinder deactivation, new polymers and lubricants and even nanotechnology to improve efficiency. But that 85 percent energy loss has remained stubbornly consistent for decades.

There’s an apt analogy to electronic health records. Hospitals and practices spend heavily implementing EHRs, but the price for caring and feeding those engines continue to pressure budgets and drive strategic IT plans. And for what?

During a recent interview, I ran that analogy past Clive Fields, M.D., the president of Village Family Practice, which is immersed in layering analytics on top of its EHR to support its transition from fee-for-service to value-based care (more than 90 percent of its commercial-based business in under some form of value-based contract.)

Fields took it a step further, noting that patient visits and interactions generate an enormous amount of energy that often dissipates when it’s cycled through an EHR. “If you ask any physician who has been practicing before and after EHRs became commonplace, I’m fairly certain they’d all tell you that they’ve seen very few clinical improvements driven by EHRs. It’s made us better documenters, but not better doctors. But I think we’re at an inflection point with new technologies that can bring us back to being better doctors.” Fields was referring to analytics and other tools that can sift through large volumes of data—much of it extraneous--to provide a clinically relevant picture of a patient.

Many providers are still directing their efforts at providing more fuel for their EHR engine, casting wider data nets and trying to drag ever more information in, as part of the widespread Big Data effort founded on the belief that more data will yield bigger benefits.

But that’s not necessarily the case. Konstantin Kakaes, author of books and commentary about technology trends, noted in a recent piece for CNN that when the 2011 McKinsey Global Institute report which popularized the term “Big Data” was published, its authors noted that “there is no empirical evidence of a link between data intensity ... and productivity in specific sectors." And since then, the evidence remains scant that more is necessarily better.

I’ve written in the past that regulatory requirements and other pressures have created an environment where documentation seems to be fighting clinical care as the primary goal of healthcare, and the focus on more and more data, instead of contextual intelligence, is making all data equal, in the sense that it’s equally meaningless. During Health Data Management’s annual analytics symposium, it’s been jarring to hear HIT leaders talk about how their high-impact clinical initiatives driven by analytics typically hinge on a small number of data points that are extremely difficult to unearth in an EHR, even though clinical leaders understood their significance.

Kakaes has his own take on that, stating that “The central claim of data proponents is that data always has some positive value. This premise is false. Data-gathering that seems innocuous enough to the managerial class often brings with it undue burden on the subjects of the data gathering.”

There’s no argument that the healthcare industry should double down on efforts to improve data quality and establish a stable foundation for interoperability. But what’s critical at this inflection point is that providers establish information governance structures that focus on their EHRs in terms of the knowledge and intelligence they provide for caregivers. For all their resources and data they’re putting in, what’s coming out that can actually drive clinical improvements? Asking that question is the first step in developing an IT plan that provides a better measure of the efficiency of EHR efforts.

Greg Gillespie is a freelance writer and content consultant based in Chicago. He formerly served as editor-in-chief at Health Data Management. He can be reached at gregg_60657@yahoo.com.