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How This Rural Health System Is Outdoing Silicon Valley

Erika Fry
By
Erika Fry
Erika Fry
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Erika Fry
By
Erika Fry
Erika Fry
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March 19, 2018, 6:30 AM ET
A couple of years ago, executives at Geisinger Health discovered that, late at night, a number of the Pennsylvania health system’s doctors were still logged into the system’s electronic health records. The reason? Physicians were staying up doing all the administrative work they couldn’t get done during the day. Geisinger CEO David Feinberg knew that burnout had reached epidemic levels within America’s medical community, largely for this reason—and so, after reviewing the data, he made a bold decision: He doubled the length of appointment time given to patients 65 and older.

Geisinger physicians now spend 40 minutes with those patients, and as a result, see many fewer per day—an expensive decision for the system, it would seem. But in time, the data proved it was financially sound. Here’s why: Older patients, having undergone a more thorough exam, were far less likely to show up at the ER or require hospitalization for an issue that didn’t get discussed in the visit.

If data is the oil of modern day, Geisinger— which serves 3 million patients in rural Pennsylvania—may just be health care’s Saudi Arabia. Founded in 1915 as an integrated system—it both cares for patients and insures them (and, more important, gets data from both roles)— Geisinger became, in 1996, one of the first U.S. health systems to adopt a full-featured EHR. And they’ve invested in it ever since. Patients can even carry their records on an iPhone.

Read more on this topic on our feature Tech’s Next Big Wave: Big Data Meets Biology.

With such clinical and claims data merged together in a searchable form, Geisinger physicians can query data—even in unstructured forms like doctor’s notes and medical images— in real time, and as easily as a Google search.

In the past few years, its newfound capabilities have helped it rationalize the use of ORs (previously, every operation was slotted for 45 minutes, even if surgeons were known to run over), pinpoint costly variability in the system (such as surgeons who spend more on supplies), and prioritize the review of medical images. An A.I.-trained computer, for instance, identifies those of potential stroke victims.

For CEO Feinberg, all this big data isn’t a qualitative change for his physicians and nurses, he says. It’s just another tool to help them take better care of their patients.

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Erika Fry
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