Technology fads come and go, but there are a few truths when it comes to healthcare IT:
So now that clinical patient pod technologies have emerged as the newest approach to predictive analytics, it's important to understand them relative to what healthcare requires.
Clinical patient pods allow predictive engines to go beyond patient risk to include other aspects that contribute to improved health outcomes. For example, intervention effectiveness and patient engagement insights are enabled by the clinical patient pod approach. Moreover, this technology expands the number of variables that can be consumed and accounted for within the predictive engine. They enable value out of large disparate data and have the ability to drive tremendous predictive insights even with limited and incomplete patient information.
But implementing solutions that leverage clinical patient pods requires more than just an understanding of the potential within the technology. The predictions and data visualizations driven by the clinical patient pod approach have to meet the expectations of the industry. They have to be accurate; relevant to the pain points faced by providers today, tomorrow, and well into the future; engender meaningful and effective action that improves patient health; and fit directly into the existing workflow. If they don’t meet these criteria, the potential of the clinical patient pod approach can’t be realized. And the investment that providers make in these kinds of solutions won’t deliver the returns that they can and should.
- By Jvion Health