Tech giant Google has filed for a broad patent that practically encompasses the entirety of health analytics and deep learning. Based on the FHIR (Fast Healthcare Interoperability Resources) standard, the Google patent application focuses on “system and method for predicting and summarizing medical events from electronic health records”.
Google’s patent application is yet to be approved. Despite a possibility that it may disrupt development in the healthcare analytics sector, many think that is will be very hard to enforce the patent’s claim to intellectual property.
Jennifer Bresnick summarizes Google’s sweeping patent filing in this post from Health IT Analytics:
In the application, first filed in August of 2017, the company argues that existing methods of aggregating and analyzing health data for predictive purposes are insufficient, and require too much time and effort to be scalable and repeatable.
“Traditionally…predictive models in healthcare are created separately for each task by collecting variables that are measured consistently on a pre-specified cohort, often in a clinical registry or trial to ensure high-quality data collection. By contrast, data generated in routine care may produce datasets that are incomplete, inaccurate, and inconsistent,” the patent states.
“Therefore, to create a predictive model, researchers expend considerable effort to define variables, normalize data, and handle missing measurements which complicates deployment as such steps must be recreated, in real-time, on live data.”
In contrast, the new methodology leverages standardized data and machine learning techniques to analyze large volumes of data and identify adverse events, such as an unplanned readmission, that could be prevented with more proactive interventions.
Google states that its patent is for a three-part system that includes a “computer memory” or database for storing aggregated structured and/or unstructured EHR data, a computer or processing unit to execute machine learning models trained on the data, and an end-user device, such as a tablet or workstation, that shows healthcare providers the results. Basically, that’s healthcare analytics in a nutshell.
