Cerner‘s patent involves systems and methods for analyzing patient complexity and matching patient records for efficient healthcare utilization. By creating time series and matching trajectories with clinical event sequences, the technology enables personalized interventions to prevent adverse outcomes. The patent aims to improve clinical decision-making and preventive medicine. GlobalData’s report on Cerner gives a 360-degree view of the company including its patenting strategy. Buy the report here.

According to GlobalData’s company profile on Cerner, was a key innovation area identified from patents. Cerner's grant share as of February 2024 was 66%. Grant share is based on the ratio of number of grants to total number of patents.

Patient care complexity characterization and clinical decision making facilitation

Source: United States Patent and Trademark Office (USPTO). Credit: Cerner Corp

A recently granted patent (Publication Number: US11923056B1) outlines a computer-implemented method for facilitating clinical decision-making. The method involves creating a target patient data frame based on patient information obtained through a clinician interface, generating a timeseries for the patient with complexity indicators, determining patient condition trajectories, matching these trajectories to a reference set of clinical event sequences, and recommending condition interventions based on these matches. The system utilizes a database scan approach, distributed data stores, multi-cluster models, and clinician interfaces to automate the process of identifying and recommending interventions to mitigate clinical conditions based on patient data and historical event sequences.

Furthermore, the patent details the creation of a data frame associated with a patient, determining frequently occurring order-event baskets in reference event sequences, and providing order recommendations for the patient based on these baskets. The method also involves ranking order recommendations, providing them to caregivers, and comparing inter-event patterns in patient timeseries to those in reference event sequences. The system aims to streamline clinical decision-making by leveraging historical data, complex algorithms, and clinician interfaces to automatically generate recommendations for patient care interventions, ultimately enhancing the efficiency and accuracy of clinical decision-making processes.

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GlobalData, the leading provider of industry intelligence, provided the underlying data, research, and analysis used to produce this article.

GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.