Organic Interoperability: Human-Inspired Analytics Influencing a Blueprint for Change

By Jeremy Racine, Healthcare Analytics Principal and Sarah Newton, Government Healthcare Manager, SAS; HIMSS Interoperability Showcase Collaborators

Humans have provided an excellent blueprint that serves as the backbone for many of today’s innovative technologies, including interoperability.

Whether improved communication protocols or automated delivery systems-—when you peel back the onion, you find many of these innovations are mimicking and/or amplifying concepts derived from humans. By observing how the human body operates, we can use our own organic processes as a model for interoperability.

Humans and Hot Pots

Take a simple event, like cooking a meal, and consider the interoperability within us that takes place during this one event. Before touching the pot to remove it from the burner, our nerves are sending data points—such as proximity to the pot and ambient air temperature—while our eyes are sending additional data points about location and other line of sight variables.

But interoperability is not solely reliant on the exchange of data points; without some sort of intelligence these are just data points with little meaning, and whether we grab the pot is a completely random action.

Instead, the human platform executes a well-orchestrated series of events parlaying the data with actionable analytics to avoid a risky and negative outcome. The human body not only uses its central nervous system and brain to securely exchange data, it also algorithmically evaluates these data and intuitively sets off chains of reactions with actionable information (i.e., breathing). In doing so, our eyes and nerve endings quickly foreshadow in our mind the negative impact of picking up the pot and consequently our hand resists the urge to pick it up. By sending data and actionable intelligence, we are able to make a more informed decision and hopefully avoid burning our hand.

Hospitals and Data Noise

Let’s take a real-world healthcare example and apply this concept. Hospitals are inundated with a constant flood of real-time data—EMR, drug delivery, imaging, enterprise resource planning, vitals, personal medical devices, to name a few.

The challenge lies in the fact that each system is independent, designed for individual purposes. Hospitals know these systems must intelligently communicate with one another if they are to shorten the time between diagnosis and treatment. Sadly, the noise of the data often results in providers missing key insights necessary to make critical care decisions. This is not unlike the communication channels that happen within humans and how they operate collaboratively to ensure we don’t pick up that hot pot.

Imagine we have a newborn baby admitted to the neonatal intensive care unit presenting with symptomatic activity of a potential deadly infection, but doctors aren’t able to pinpoint the root cause of the infection. Similarly, our patient may have experienced a recent change in vitals or medications. Any one of these data points could certainly be independently helpful, but when viewed holistically it is clear the patient is at risk of a life-threatening outcome. Without knowing what is causing the illness, the provider doesn’t know yet what treatment options exist. The newborn’s care teams need all of the information presented in an actionable manner to make decisions.

Using Data for Action

Like the human body, data must be securely exchanged amongst systems to ensure that a holistic view of the patient can be created. This scenario requires connectivity, communication, data exchange and analytic exchange to ensure high-risk, acute patients are quickly diagnosed and receive treatment.

The hospital’s interoperability strategy must allow for the merger of various data points from multiple places and for systems to intelligently collaborate and orchestrate a next best action for the patient. Employing such an analytic system could mean machine learning techniques that score and assess the holistic data points not just against this patient but also compared to historically similar patients. This can reveal hidden relationships, assign a criticality level, alert service providers as needed, and ultimately avoid a time lapse of care with the patient and prevent a negative outcome.

The human body teaches us so much and perhaps interoperability is no different. In this ever-changing world where information is plentiful and can saturate our minds to the point of making answers to straightforward problems seem much more complex, perhaps the path to solving our interoperability challenges are found from looking within.

Healthcare organizations looking to enhance their approach to interoperability may find tremendous success by employing a human-inspired solution that can securely exchange data and generate well-orchestrated actionable analytics that can support improved clinical decision-making.

We hope to see you at HIMSS20! Stop by the SAS booth to hear more about our views on interoperability and advanced analytics for healthcare.

Sponsored content. The views and opinions expressed in this blog or by commenters are those of the author and do not necessarily reflect the official policy or position of HIMSS or its affiliates.

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