Patent Application Titled “Systems And Methods For Generating Customizable Digital Data Structures” Published Online (USPTO 20240127912): Patent Application

2024 MAY 06 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- According to news reporting originating from Washington, D.C., by NewsRx journalists, a patent application by the inventors Brown, Scott (Cottonwood Heights, UT, US); Brown, Tyler (Cottonwood Heights, UT, US); Coutts, Brian (Cottonwood Heights, UT, US); Eliason, Eric (Cottonwood Heights, UT, US); Obray, Nate (Cottonwood Heights, UT, US), filed on October 16, 2023, was made available online on April 18, 2024.

No assignee for this patent application has been made.

Reporters obtained the following quote from the background information supplied by the inventors: “People are injured in accidents of all types every day. Many accident victims suffer physical injuries or damage to their property. Often, parties to an accident have insurance to (at least partially) cover the appurtenant damages including medical costs, lost wages, pain and suffering, and potential repair bills. However, there are times when an insurer does not want to cover a particular expense or may disagree about how much compensation is owed or which costs should be borne by the insurance company. In such cases, the individual(s) may need to seek legal help to obtain a recovery that is rightfully theirs. Seeking legal help, however, may be costly and time-consuming. Moreover, many people do not know whether they have a good case against an insurer and don’t know where to start to find that type of information.”

In addition to obtaining background information on this patent application, NewsRx editors also obtained the inventors’ summary information for this patent application: “The embodiments described herein are directed to systems and apparatuses that generate digital data structures based on aggregated data gleaned from a user’s responses to specific informational prompts. In one scenario, a method is provided that includes accessing various portions of data related to an event in which a user was involved. The method further includes determining, for the event, which informatory elements related to the event meet at least a minimum significance threshold. The method next includes presenting to the user, via a graphical user interface, one or more informational prompts associated with the event to obtain supporting information related to those informatory elements associated with the event that were determined to meet the minimum significance threshold. The method also includes generating a digital data structure that includes at least a portion of dynamically written language related to the event and further includes at least a portion of the supporting information received from the user in response to the informational prompts.

“In some embodiments, the informational prompts are dynamically generated and include at least one free-form answer prompt. In some examples, the user provides a free-form answer to the free-form answer prompt that is analyzed to obtain additional supporting information related to the informatory elements. In some cases, the informational prompts are dynamically generated and include at least one prompt that has multiple selectable options that are selectable via the graphical user interface.

“In some examples, the user selects at least one of the selectable options in the dynamically generated prompt, and the selected options are analyzed to obtain additional supporting information related to the informatory elements. In some cases, the user is a party involved in an accident and/or a witness to the accident. In some embodiments, the user additionally provides, as supporting information, data structures in a local data store owned by the user, data structures that include text, image, audio or video files, personal healthcare records (PHRs), data structures that include financial records, and/or data structures stored in a decentralized Health Information Exchange.

“In some cases, the informational prompts presented to the user are generated dynamically and are unique to the event in which the user was involved. In some embodiments, the dynamically generated informational prompts are generated using artificial intelligence. In some cases, the artificial intelligence is trained to determine which informatory elements related to the event meet the minimum significance threshold. In some examples, the artificial intelligence is trained to consider at least two of the elements meeting the minimum significance threshold in different manners. In some examples, the artificial intelligence is trained to alter the informational prompts presented to the user in the graphical user interface based on which supporting information is provided by the user.

“A corresponding system may be provided that includes: at least one physical processor and physical memory comprising computer-executable instructions that, when executed by the physical processor, cause the physical processor to: access various portions of data related to an event in which a user was involved, determine, for the event, which informatory elements related to the event meet at least a minimum significance threshold, present to the user, via a graphical user interface, one or more informational prompts associated with the event to obtain supporting information related to those informatory elements associated with the event that were determined to meet the minimum significance threshold, and generate a digital data structure that includes at least a portion of dynamically written language related to the event and further includes at least a portion of the supporting information received from the user in response to the informational prompts.

“In some cases, the digital data structure may be a case summary that includes an analysis of the case. In some examples, at least a portion of the supporting information is incorporated into the case summary. In some embodiments, the user interface allows the user to select which supporting information is to be included in the case summary. In some cases, the supporting information includes at least one of pictures, videos, text messages, email messages, or health records. In some cases, the supporting information is accessed from a mobile electronic device associated with the user. In some embodiments, the system may further train a machine learning model to determine, for the event, which informatory elements related to the event meet at least the minimum significance threshold.

“A corresponding non-transitory computer-readable medium may also be provided that includes one or more computer-executable instructions that, when executed by at least one processor of a computing device, cause the computing device to: access various portions of data related to an event in which a user was involved, determine, for the event, which informatory elements related to the event meet at least a minimum significance threshold, present to the user, via a graphical user interface, one or more informational prompts associated with the event to obtain supporting information related to those informatory elements associated with the event that were determined to meet the minimum significance threshold, and generate a digital data structure that includes at least a portion of dynamically written language related to the event and further includes at least a portion of the supporting information received from the user in response to the informational prompts.

“This Summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This Summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter.

“Additional features and advantages will be set forth in the description which follows, and in part will be apparent to one of ordinary skill in the art from the description or may be learned by the practice of the teachings herein. Features and advantages of embodiments described herein may be realized and obtained by means of the instruments and combinations particularly pointed out in the appended claims. Features of the embodiments described herein will become more fully apparent from the following description and appended claims.”

The claims supplied by the inventors are:

“1. A computer-implemented method comprising: accessing one or more portions of data related to an event in which a user was involved; determining, for the event, which informatory elements related to the event meet at least a minimum significance threshold; presenting to the user, via a graphical user interface, one or more informational prompts associated with the event to obtain supporting information related to those informatory elements associated with the event that were determined to meet the minimum significance threshold; and generating a digital data structure that includes at least a portion of dynamically written language related to the event and further includes at least a portion of the supporting information received from the user in response to the informational prompts.

“2. The computer-implemented method of claim 1, wherein the informational prompts are dynamically generated and include at least one free-form answer prompt.

“3. The computer-implemented method of claim 2, wherein the user provides a free-form answer to the free-form answer prompt that is analyzed to obtain additional supporting information related to the informatory elements.

“4. The computer-implemented method of claim 1, wherein the informational prompts are dynamically generated and include at least one prompt that has multiple selectable options that are selectable via the graphical user interface.

“5. The computer-implemented method of claim 4, wherein the user selects at least one of the selectable options in the dynamically generated prompt, and wherein the selected options are analyzed to obtain additional supporting information related to the informatory elements.

“6. The computer-implemented method of claim 1, wherein the user comprises at least one of a party involved in an accident or a parent or guardian of a party involved in an accident.

“7. The computer-implemented method of claim 1, wherein the user additionally provides, as supporting information, at least one of: data structures in a local data store owned by the user, data structures that include personal healthcare records (PHRs), data structures that include financial records, or data structures stored in a decentralized Health Information Exchange.

“8. The computer-implemented method of claim 1, wherein the informational prompts presented to the user are generated dynamically and are unique to the event in which the user was involved.

“9. The computer-implemented method of claim 8, wherein the dynamically generated informational prompts are generated using artificial intelligence.

“10. The computer-implemented method of claim 9, wherein the artificial intelligence is trained to determine which informatory elements related to the event meet the minimum significance threshold.

“11. The computer-implemented method of claim 9, wherein the artificial intelligence is trained to alter the informational prompts presented to the user in the graphical user interface based on which supporting information is provided by the user.

“12. The computer-implemented method of claim 1, further comprising training a machine learning model to determine, for the event, which informatory elements related to the event meet at least the minimum significance threshold.

“13. A system comprising: at least one physical processor; and physical memory comprising computer-executable instructions that, when executed by the physical processor, cause the physical processor to: access one or more portions of data related to an event in which a user was involved; determine, for the event, which informatory elements related to the event meet at least a minimum significance threshold; present to the user, via a graphical user interface, one or more informational prompts associated with the event to obtain supporting information related to those informatory elements associated with the event that were determined to meet the minimum significance threshold; and generate a digital data structure that includes at least a portion of dynamically written language related to the event and further includes at least a portion of the supporting information received from the user in response to the informational prompts.

“14. The system of claim 13, wherein the digital data structure comprises a case summary that includes an analysis of the case.

“15. The system of claim 14, wherein at least a portion of the supporting information is incorporated into the case summary.

“16. The system of claim 15, wherein the user interface allows the user to select which supporting information is to be included in the case summary.

“17. The system of claim 13, wherein the supporting information includes at least one of pictures, videos, text messages, email messages, or health records.

“18. The system of claim 17, wherein the supporting information is accessed from a mobile electronic device associated with the user.

“19. The system of claim 17, further comprising training a machine learning model to determine, for the event, which informatory elements related to the event meet at least the minimum significance threshold.

“20. A non-transitory computer-readable medium comprising one or more computer-executable instructions that, when executed by at least one processor of a computing device, cause the computing device to: access one or more portions of data related to an event in which a user was involved; determine, for the event, which informatory elements related to the event meet at least a minimum significance threshold; present to the user, via a graphical user interface, one or more informational prompts associated with the event to obtain supporting information related to those informatory elements associated with the event that were determined to meet the minimum significance threshold; and generate a digital data structure that includes at least a portion of dynamically written language related to the event and further includes at least a portion of the supporting information received from the user in response to the informational prompts.”

For more information, see this patent application: Brown, Scott; Brown, Tyler; Coutts, Brian; Eliason, Eric; Obray, Nate. Systems And Methods For Generating Customizable Digital Data Structures. U.S. Patent Application Number 20240127912, filed October 16, 2023 and posted April 18, 2024. Patent URL (for desktop use only): https://ppubs.uspto.gov/pubwebapp/external.html?q=(20240127912)&db=US-PGPUB&type=ids

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