Why Meaningful Mobile Health Is So HardWhy Meaningful Mobile Health Is So Hard

There are already many information-gathering medical device technologies out there that would be highly useful for big hospital systems. But there is a major hurdle presently standing in the way, says Chad Konchak, director of clinical analytics at the Chicago-area NorthShore University HealthSystem.

Chris Newmarker

As head of clinical analytics at NorthShore University HealthSystem, Chad Konchak has made great strides using smart use of data to streamline workflow at the four-hospital, 10,000-employee health system around Chicago.

Integrating predictive modeling into the electronic health record allows NorthShore to better manage patient care gaps and prevent avoidable admissions--something that U.S. health payers such as Medicare have been rewarding hospital systems for since Obamacare was passed in 2010.

NorthShore has made great strides in areas such as predicting patients at risk of MRSA infections. And yet Konchak acknowledges a major hurdle preventing health providers such as NorthShore from harnessing medtech for analytics: "The integration of devices with the electronic medical record is the big barrier we need to work through."

(Visit MD&M East, June 14-16 in New York City, and see Konchak discuss harnessing data analytics in the design and development of medical devices.)

It comes down to one word: "interoperability."

There are still a host of electronic medical record software providers, but a standard API (application program interface) is still in the works--making it a tough business proposition to design medical devices to feed information into such EMR systems, although exciting progress is being made with FHIR (Fast Healthcare Interoperability Resources) standards, Konchak says.

In the United States, the Office of the National Coordinator for Health Information Technology (ONC) is in charge of working on the problem. Konchak's advice to medical device engineers and designers interested in information-gathering and analytics? "It's about having a seat at the table as far as making those standards for interoperability."

When asked about his wish list of medical devices providing information to EMRs, Konchak quickly listed off a handful:

The irony is that there are already medical devices out there that collect such information.

Insulin pump makers Medtronic and Tandem Diabetes Care, for example, already have information-sharing features with their pumps (MiniMed Connect and the CareLink personal website for Medtronic and t:connect for Tandem). Medtronic's Cardiocom has a Telescalefor heart failure patients. Proteus Digital Health has FDA-cleared technology for tracking whether patients are taking their meds, though it is going through the new drug application processfor a specific pairing with drug Abilify.

Interoperability is standing in the way, along the lack of robust analytics work at many health providers, according to Konchak.

"We need to build this tunnel through this enormous mountain," Konchak  says. "The health provider is on one side of the mountain going one way. And all the device manufacturers are on the other end going the other way. And then there's a tremendous amount dirt and crud in the middle that we need to work out to have an integrated medical device information community driving what providers can do about a population."

Konchak is optimistic, though, because there is such a strong incentive for health providers to get serious about analytics and provide value-based care: "The systems that survive going forward are not the ones necessarily that provide the absolutely best care. It's going to be the ones that do so in the most efficient way, by improving patient outcomes."

(Visit MD&M East, June 14-16 in New York City, and see Konchak discuss harnessing data analytics in the design and development of medical devices.) 

Chris Newmarker is senior editor of Qmed and MPMN. Follow him on Twitter at @newmarker.

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