Data-driven mental health programming patent application

ChangeBridge: Patent Apps - Health Informatics (G16H)

Published September 23rd, 2024

Detected March 26th, 2026

Summary

The USPTO has published a new patent application, US20260088152A1, filed by Charlie Health, Inc. The application details methods and systems for data-driven mental health programming, including ingesting patient data into a knowledge graph, deriving patient archetypes, and assigning patients to therapists and treatment modalities based on this data.

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What changed

This document is a publication of a patent application (US20260088152A1) filed by Charlie Health, Inc. The application describes a system for data-driven mental health programming. Key features include ingesting patient data into an enterprise knowledge graph, deriving patient archetypes, and using these archetypes along with patient attributes to assign patients to therapists and specific treatment modalities.

As this is a patent application, it does not impose direct regulatory obligations on healthcare providers or other entities. However, the technology described could influence future healthcare service delivery models and data management practices within the mental health sector. Compliance officers in health informatics and mental health services should be aware of this technological development as it may shape future industry standards and patient care approaches.

Source document (simplified)

← USPTO Patent Applications

DATA-DRIVEN MENTAL HEALTH PROGRAMMING

Application US20260088152A1 Kind: A1 Mar 26, 2026

Assignee

Charlie Health, Inc

Inventors

CAROLINE FENKEL, JONATHAN KOHLMEIER, MARK MEGERIAN

Abstract

Methods and systems of data-driven mental health programming is provided. Embodiments ingesting (314) patient data (124) into an enterprise knowledge graph (128), wherein the patient data (124) comprises triples of nodes and relationships representing the data of the patients of the program; deriving (316) a set of patient archetypes (350) from the enterprise knowledge graph (128); assigning (318) a patient (102) to a patient archetype (350) in dependence upon patient attributes (306); assigning (320) the patient (102) to a therapist (386) in dependence upon the patient archetype (350), patient attributes (306), and therapist attributes; and assigning (322) the patient to a treatment modality in dependence upon patient archetypes and patient attributes.