In the past, the healthcare industry has been known to struggle with the disconnect between theory and practice. There is broad agreement that the key to successful accountable care and pay for performance implementation is keeping individuals out of hospitals and focusing on high-risk individuals. This is where the majority of our healthcare dollars are allocated.
Traditionally, our health system has been reactive. Frequently, it is only after a problem has gone beyond the point of no return, that it is addressed, often in emergency rooms and via expensive procedures. In many instances, treatable problems are allowed to progress to chronic and acute levels. This means that there is a tremendous amount of avoidable costs in our health system and, more importantly, avoidable negative outcomes for individuals.
Traditional healthcare focuses on a limited (what may be termed a “90 degree”) view of the patient that is predicated on the subset of rote clinical data stored in an electronic medical record (EMR) system. Unfortunately, this is part of the reactive nature of the current system. As EMR vendors have discovered, it is not sufficient to simply add a patient portal or expensive telehealth device to capture the other 270 degrees.
While telehealth and patient portals are important, patients are not medical professionals and beyond mere tools, they require engagement. This means that it is far more effective to utilize embedded approaches, such as gathering behavioral and vitals data through wearable devices and home sensors. These devices do not interfere with a patient’s daily routine and provide more consistent and comprehensive data streams. In turn, these streams must have a place to go where they can be processed, analyzed and collated with other aspects of the patient’s health record.
Consequently, true pay-for-performance models will be driven through comprehensive population health management platforms. Successful implementation will involve capturing data throughout the care continuum, providing the tools to collaborate and work on that data and then overlaying that data with both real time and predictive analytics. Traditional health care has been disjointed across multiple silos where slices of patient data reside without extracting to a greater whole. To close such data gaps,
many organizations try to force together legacy systems and slice-of-pie solutions, but the end result of this approach is high costs and unusable kluges.