# US 2021/0343385 A1 · Method and system for managing a participant health regimen > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2021/0343385 A1 - Document ID: US20210343385A1 - Status: Published application - Kind: A1 - Application number: 17/307,544 - Filed: 2021-05-04 - Published: 2021-11-04 - Earliest claimed: 2020-05-04 - Assignees: Omada Health, Inc. - Applicants: Omada Health, Inc. - Inventors: Carolyn Jasik; Mike Tadlock; Michael Turken; Ken Huang; Jimmy Xu - Web page: https://patentgrep.com/patent/US20210343385A1 ## CPC - G16H 20/10: relating to drugs or medications, e.g. for ensuring correct administration to patients - G16H 50/20: for computer-aided diagnosis, e.g. based on medical expert systems - G16H 20/70: relating to mental therapies, e.g. psychological therapy or autogenous training - G16H 40/20: for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms - G16H 40/67: for remote operation - G16H 80/00: ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring - G16H 10/20: for electronic clinical trials or questionnaires - G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA ## Abstract A system managing a participant health regimen can include any or all of: a computing system; a set of dashboards; a set of models; a user device; a sensor system; one or more supplementary devices; a client application; and/or any other components. A method for managing a participant health regimen includes collecting a set of inputs; determining a participant condition; determining a barrier associated with the participant; and determining and/or triggering an action. Additionally or alternatively, the method can include training and/or retraining any or all of a set of models and/or any other processes. ## Claims ### Claim 1 A method for the computer-aided management of a health regimen of a user, the method comprising: collecting a set of inputs, wherein the set of inputs comprises: a set of user inputs, wherein the set of user inputs is collected with a client application executing on a user device of the user; a first set of sensor inputs, wherein the first set of sensor inputs is collected with a first set of sensors arranged onboard the user device, and wherein the first set of sensor inputs comprises a set of location inputs associated with the user; a second set of sensor inputs, wherein the second set of sensor inputs is collected with a second set of sensors arranged onboard a supplementary device, wherein the second set of sensor inputs comprises a set of parameters associated with a health condition of the user; transmitting the set of inputs to a remote computing system; at the remote computing system: based on the set of inputs, with a first model, determining a set of barriers associated with the user; based on the set of inputs and the set of barriers, with a second model, wherein the second model is a trained model, determining an action associated with the user; automatically triggering the action; receiving a second set of inputs in response to the action; and automatically updating the second model based on the second set of inputs. ### Claim 2 (depends on 1) The method of claim 1, wherein the set of user inputs comprises a set of survey inputs collected from a set of multiple surveys administered at a client application executing on the user device. ### Claim 3 (depends on 2) The method of claim 2, wherein the set of multiple surveys is administered with at least a minimum temporal spacing between surveys of the set of multiple surveys. ### Claim 4 (depends on 2) The method of claim 2, further comprising determining a social determinant score of the user based on the location. ### Claim 5 (depends on 4) The method of claim 4, wherein the set of barriers is determined based on the social determinant score. ### Claim 6 (depends on 1) The method of claim 1, wherein the set of inputs further comprises clickstream data collected from a set of client applications executing on the user device, wherein the set of client applications comprises the client application. ### Claim 7 (depends on 1) The method of claim 1, wherein the action comprises prompting the user to engage with a ride share application executing on the user device. ### Claim 8 (depends on 7) The method of claim 7, wherein the action further comprises providing a destination for the ride share application, wherein the destination is a destination of a pharmacy proximal to the user. ### Claim 9 (depends on 1) The method of claim 1, wherein the supplementary device comprises a medical device, wherein the set of barriers is associated with a particular health condition of the user. ### Claim 10 (depends on 9) The method of claim 9, wherein the medical device comprises at least one of: a glucose sensor, a blood pressure monitor, a scale, and a pill box. ### Claim 11 (depends on 9) The method of claim 9, wherein the set of barriers is further determined based on a set of communication parameters determined based on a set of messages exchanged between the user and a coach assigned to the user. ### Claim 12 (depends on 11) The method of claim 11, wherein the set of communication parameters comprises at least one of: a content associated with the set of messages, a length of the messages, and a frequency of the messages. ### Claim 13 (depends on 1) The method of claim 1, wherein the second trained model is configured to determine the action associated with a highest predicted impact for the user based on the set of barriers. ### Claim 14 (depends on 13) The method of claim 13, wherein the second trained model implements uplift modeling. ### Claim 15 (depends on 1) The method of claim 1, wherein the set of barriers comprises a logistics barrier, wherein the logistics barrier is determined at least in part based on detecting that location inputs of the set of location inputs are associated with a low variability. ### Claim 16 (depends on 15) The method of claim 15, wherein the action comprises a prompt for the user to engage with a second client application at the user device. ### Claim 17 (depends on 16) The method of claim 16, wherein the second client application comprises a ride sharing application. ### Claim 18 (depends on 1) The method of claim 1, wherein the action is triggered in absence of a reminder being transmitted from the coach to the user. ### Claim 19 The method, wherein the first model comprises a first trained model. ### Claim 20 A method for the computer-aided management of a health regimen of a user, the method comprising: collecting a set of inputs, wherein the set of inputs comprises: a set of user inputs, wherein the set of user inputs is collected with a client application executing on a user device of the user; a set of sensor inputs, wherein the set of sensor inputs is collected with at least one of: a first set of sensors arranged onboard the user device; and a second set of sensors arranged onboard a supplementary medical device; transmitting the set of inputs to a remote computing system; at the remote computing system: based on the set of inputs, determining a set of barriers associated with the user; based on the set of inputs and the set of barriers, determining an action associated with the user; and automatically triggering the action at the user device.