From Health Analytics:
Google has applied for a sweeping patent including the fundamentals of deep learning and EHR analytics in the healthcare industry.
- Google has applied for a patent for a deep learning system that aggregates EHR data into a “timeline” in order to predict potential adverse events.*On the Amazon effort, the cutesy patient-facing part is "NHS teams up with Amazon to bring Alexa to patients" (Guardian, July 10) while back end data is collected by companies like Bezos-investee Capita.
The “system and method for predicting and summarizing medical events from electronic health records” is based on the popular data standard known as FHIR, allowing Google to ingest data from a wide variety of sources.
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....MORE
HT: Capita links, Huw Davies.
