MedCity News published an article that covers “4 questions every healthcare provider should ask about fitness wearables.” When asking “What’s the cost of data integration?”, the article states that “Wearables and EHRs don’t share the same operating systems, thus requiring the building of expensive interfaces.”
It’s true; fitness wearables, such as FitBits, Apple Watch, and other such activity trackers, do a poor job of sharing data in ways that would be useful to healthcare providers. While there are integrations with other tracker applications, today’s wearables lack the ability to get their data into EHRs, or into clinical management systems.
In other words, current wearables lack the out-of-the-box ability for my doctor to easily see what activities I’ve racked up, and relate that activity to my overall health, including blood work, blood pressure, heart rate, etc. The idea is to find a correlation between healthy activity and overall health.
While most would cite privacy and HIPAA issues for wearables’ lack of compatible data interfaces, the points of integration are very proprietary, and thus it’s expensive to develop interfaces to link them up to traditional systems. Indeed, most health care organizations that have attempted to link up fitness wearables and clinical systems have had to go through some painful programming for each wearable that they were attempting to integrate.
“Health Level Seven International and various other groups currently working to develop standards for mobile device interoperability, but it could be years before these standards are finalized.”
A much better approach to wearables data integration is to leverage a data integration tool. These tools will place the volatility that is normally found in the different structures and formats of data into a single domain. Thus, you can adapt the different ways that data is persisted, and structured, from device to system, and system to device.
A data integration tool circumvents the need to wait for standards to emerge, or build custom interfaces between source and target devices or systems. It’s really just a matter of leveraging best practices in data integration that have evolved over the years, with newer IoT technology and traditional systems. These are problems that have already been solved.
While many in health care may not be aware of data integration best practices and technology, there have been some huge advances in the last several years. We’re now able to connect any data source to any target. This includes connecting wearables to traditional systems.
Today’s call to action today for those who maintain clinical systems is to leverage the data their patients are now spinning off wearable devices. Wearables are becoming commonplace, and the data that they produce provides key data points that clinicians can leverage to determine the overall health of a patient, and take corrective action when needed. If it’s just a matter of data integration, and that’s an easy problem to solve.