There has been a longstanding vision in the digital health industry of what it means to be an analytics platform, and it goes like this: get as much of the data as possible and give it to applications that can transform it to clinical insights. In this single-focus philosophy, anyone who can get to the data claims to have a platform as long as they enable other applications to provide the intelligence.
We have always disagreed. At Etiometry, we believe that an analytics platform should be more than a mechanistic data gatherer—it should be a system that is intelligent by design. In our vision, the application layer does not consist of myriad applications that can do things like predicting cardiac arrest or ICU admission, but of multiple guided workflows that are enabled by an analytics platform that transforms the data into the right actionable information. This blog is my attempt to share our a few reasons why our Risk Analytics Engine technology— which is core to our Risk Analytics Algorithms— is not only a platform but The Right Platform for improving healthcare through analytics.
Reason # 1: It is a Platform that Can Deal with Medical Data
Everybody who has dealt with medical data knows that it is especially noisy. Noise comes from treatment, such as blood draws from the arterial line, or patient motion, such as a dropped pulse oximetry signal or sensor failure, or a blood clot in a catheter. Medical data thus needs to be meaningfully filtered as a basis of any analytics, because otherwise the analytics will produce measures that are plagued by the same false alarm rates as the data from which they are derived. The Etiometry Platform offers a highly scalable approach for detecting data artifacts to create more robust data streams.
Reason # 2: It is a Platform that Understands Physiology
Physiology is central to our Risk Analytics Engine technology, from the way the Risk Analytics Engine employs mechanistic models of human physiology to how algorithms are presented to the clinicians in the context of patient physiology. That means that the data is not treated as a series of numbers but as little bits of evidence for an evolving clinical trajectory that needs to be assembled correctly to reveal the entire picture.
Reason # 3: It is a Platform that Can Inform Treatment
The ultimate goal of any analytics platform is to better inform clinical decision. Given that each clinical decision is meant to mitigate particular patient harms, the primary objective of an analytics platform should be to reveal early signs of these harms in a timely manner. The Etiometry Risk Analytics Engine has been specifically designed to process multiple data streams and synthesize them into meaningful, actionable risks in a scalable way.
This includes elucidating specific harms and relating these harms to specific treatments, and respectively creating apps that utilize the harms into guided treatment protocols. In summary, what makes our Risk Analytics Engine an analytics platform is its ability to transform data into meaningful clinical insights.
In contrast to other players in the market, our application layer is not just one-off, predictive algorithms but tools directly focused on improving clinical workflow that are supported by a scalable analytics architecture. For more information, learn more about the Etiometry Platform.