Optum Patent for Dynamic Health Appointment Scheduling Using Real-Time Health Conditions
Summary
USPTO granted Patent US12603183B2 to Optum, Inc. covering systems and methods for scheduling healthcare appointments dynamically based on real-time health conditions. The patent claims 17 total claims and was filed on October 7, 2022. The technology uses machine learning to identify similar health profiles, generate appointment schedules, evaluate risk scores, and adjust scheduling based on changes in user health data.
What changed
USPTO granted Patent US12603183B2 to Optum, Inc. for a system that dynamically schedules healthcare appointments based on real-time health conditions. The patent covers inputting user health datasets into machine learning models to identify similar health profiles, determining monitoring frequency, appointment types, and durations, and adjusting schedules based on evaluated risk scores. Inventors include Saloni Kakkar, Surajit Das, Gregory J. Boss, and Lo Fu Tan.
Patent grants establish intellectual property rights but do not impose compliance obligations on third parties. Healthcare technology companies developing appointment scheduling systems may wish to review the scope of the granted claims to assess potential licensing needs or to understand competitive landscape developments in health informatics technology.
Archived snapshot
Apr 17, 2026GovPing captured this document from the original source. If the source has since changed or been removed, this is the text as it existed at that time.
Systems and methods for a dynamic scheduling of appointments based on real-time health conditions of users
Grant US12603183B2 Kind: B2 Apr 14, 2026
Assignee
Optum, Inc.
Inventors
Saloni Kakkar, Surajit Das, Gregory J. Boss, Lo Fu Tan
Abstract
Systems and methods are disclosed for scheduling appointments based on changing health conditions of users. The method includes inputting the initial health dataset of a user to a machine learning model configured to identify other users with similar health profiles. A frequency of monitoring, a frequency of appointments, a duration between the appointments, or a type and length of the appointments is determined to generate a schedule of appointments. A subsequent health dataset of the user is received, and health scores, rule scores, or medication scores for the user are determined based on the subsequent health dataset. A plurality of risk scores for the user is evaluated based on the health scores, rule scores, or medication scores. A recent risk score is determined based on a change in the plurality of risk scores. The schedule of appointments is adjusted based on the recent risk score and the user is notified.
CPC Classifications
G16H 50/30 G16H 80/00
Filing Date
2022-10-07
Application No.
18045116
Claims
17
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