Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of claims
Claims 1-23 have been examined. Claims 1, 6, 12, 18, 21, 22 have been amended.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-23 are is/are rejected under 35 U.S.C. 103 as being unpatentable over Gnanasambandam et al. (US 20230052573A1 hereinafter Gnanasambandam) in view of Nagaraja et al. (US11240181 hereinafter Nagaraja).
With respect to claim 1, Gnanasambandam teaches a system for generating personalized healthcare schedules within a virtual agent system, comprising:
a device processor (‘573; Para 0131); and
a non-transitory computer readable medium having stored thereon instructions, executable by the processor (‘573; Para 0340), for performing the following steps:
receiving patient data regarding a patient (‘573; Para 0655: by disclosure, Gnanasambandam describes the method 6400 may include receiving patient data that indicates health related information associated with a patient. For example, the computing device 1400 (e.g., using may receive patient data that indicates health related information associated with a patient describes the method may include receiving patient data that indicates health related information associated with a patient. For example, the computing device (e.g., using may receive patient data that indicates health related information associated with a patient); Paras 0668;); and
Nagaraja teaches
improving the system’s effectiveness at engaging the patient by utilizing a schedule builder persona within the virtual agent system to create a care plan that is tailored to the patient's needs, has a predetermined duration, and includes details regarding timing and content of communication to be made with the patient (‘181; page/lines 19/14-33: Steps of a workflow correspond to specific tasks/actions to be performed during the course of delivering the service based on the workflow. For example, diagnosis of a condition can be performed by a step of activating a chatbot equipped with the corresponding diagnostic questionnaire (further including a step of platform 206 providing a link to a HIPAA compliant platform on which the chatbot is to engage the user), and/or a step of facilitating the user making an appointment with a selected medical doctor (further including a step of platform 206 providing a link to a calendar service, and/or a payment service). For another example, treatment can be performed by a step of a chatbot sending the user a care plan (e.g., when simple home remedy seems sufficient based on the diagnosis), a step of platform 206 providing the treating doctor with an online prescription service to prescribe medication for the user, a step of platform 206 allowing the doctor to send the user emails, documents (e.g., educational materials), a step of a chatbot reminding the user to take the medication timely, and the like.) (‘573; Para 0154: the cognitive intelligence platform 102 (e.g., by way of the cognitive agent 110 interacting with the user) holistically manages and executes a health plan for durational care and wellness of the user (e.g., a patient or consumer). The health plan includes various aspects of durational management that is coordinated through a care continuum and proceeds to schedule of a service that aligns with a healthcare plan of the user; Para 0557: the information may be received from a source including an electronic medical records system, an application programming interface, a claims system, an electronic health virtual assistant, an application executing on the user device 104, a data store, or some combination thereof. Para 0532: the care plan 5604 may be tailored for providing action instructions to a user, the natural language representing the care plan 5604 may be tailored for providing action instructions to a medical personnel, and the natural language representing the care plan 5604 may be tailored for providing action instructions to an administrator; Para 0678).
It would have been obvious to one of ordinary skill in the art before the effective filing date of claim invention to modify the system of Gnanasambandam with the technique of Artificial intelligence assisted service as taught by Nagaraja and the motivation is to engage the patient with care plane tailored to the patient needs.
With respect to claim 2, the combined art teaches the system of claim 1, wherein the computer readable medium further includes instructions for consulting an incentive management expert resource to incorporate user-specific goals and rewards into the care plan, ensuring alignment with health plan incentives of the patient (‘573; Para 0682: Fig. 68 show the user interface to may present sections for each care plan that is available for a patient and the goals included in those care plans. For example, a first section for Care Plan includes 3 goals. Goal 1 includes a graphical element indicating the goal is reimbursable, which may provide incentive for a medical personnel to include that goal in the care plan. ).
With respect to claim 3, the combined art teaches the system of claim 1, wherein the computer readable medium further includes instructions for continuously updating the care plan based on real-time feedback received from the patient, as processed by a feedback collection persona. (‘573; Para 0385: FIG. 23 shows a method 2300 for using feedback pertaining to the accuracy of cognified data to update an artificial intelligence engine, in accordance with various embodiments)
With respect to claim 4, the combined art teaches the system of claim 3, wherein the computer readable medium further includes instructions for providing immediate guidance to the patient upon receipt of the real-time feedback (‘573; Para 0094).
With respect to claim 5, the combined art teaches the system of claim 1, wherein the computer readable medium further includes instructions for collecting data regarding a compliance status of the patient, reflecting the patient’s compliance with one or more healthcare directives; and generating one or more updates to the care plan that are customized in view of the compliance status of the patient (‘573; Para 0124: the patient graph for each condition may also include an engagement profile that may be used to determine a compliance of the user with the care plan.)
With respect to claim 6, Gnanasambandam teaches a system for generating personalized healthcare messaging within a virtual agent system, comprising:
a device processor (‘573; Para 0375); and
a non-transitory computer readable medium having stored thereon instructions, executable by the processor (‘573; Paras 0374-0375), for performing the following steps:
receiving patient data regarding a patient (‘573; Para 0655: by disclosure, Gnanasambandam describes the method 6400 may include receiving patient data that indicates health related information associated with a patient. For example, the computing device 1400 (e.g., using may receive patient data that indicates health related information associated with a patient describes the method may include receiving patient data that indicates health related information associated with a patient. For example, the computing device (e.g., using may receive patient data that indicates health related information associated with a patient); Paras 0668); and
Nagaraja teaches
utilizing a message builder persona within the virtual agent system to generate a series of personalized messages based on the created care plan in order to ensure that the content of the messages is compliant with healthcare regulations and effectively motivates the patient (‘181; page/lines 19/34-46: a step of generating a HIPAA compliant communication link for embedment into a SMS message to the user is indexed under, e.g., HIPAA link. For another example, once platform 206 narrows down the user's request from a relatively general one (e.g., #doc) to a relatively specific one (e.g., sore throat, flu) after obtaining more information from the user (e.g., by conducting diagnostic questionnaire guided communication, which is described with more details below), a step of a chatbot sending the user a care plan is mapped to the chatbot sending a care plan specific to the identified narrowed request.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of claim invention to modify the system of Gnanasambandam with the technique of Artificial intelligence assisted service as taught by Nagaraja and the motivation is to engage the patient with care plane tailored to the patient needs.
With respect to claim 7, the combined art teaches the system of claim 6, wherein the computer readable medium further includes instructions for collecting data regarding the patient’s personality type; and generating one or more messages of the series of personalized messages that are customized according to the patient’s personality type (‘573; Figs 8A & B and C).
With respect to claim 8, the combined art teaches the system of claim 6, wherein the computer readable medium further includes instructions for consulting a message validation expert resource to ensure that all communications of the series of personalized messages adhere to predetermined guidelines and/or regulations (‘573; Paras 0094, 0156).
With respect to claim 9, the combined art teaches the system of claim 6, wherein the computer readable medium further includes instructions for consulting an email timing expert resource; and optimizing timing of the communications of the series of personalized messages to maximize engagement by the patient (‘573; Para 0534, Para 0689).
With respect to claim 10, the combined art teaches the system of claim 6, wherein the computer readable medium further includes instructions for consulting an incentive management expert resource to assess user wellbeing; receiving feedback from the incentive management expert resource; and customizing one or more of the communications of the series of personalized messages to provide guidance to the patient on how to achieve improved wellbeing or to meet certain incentives (‘573; Para 0152: he cognitive intelligence platform 102, itself. In order to address the care needs and well-being of the user, the cognitive intelligence platform 102 collects, analyzes, and processes information from the use; Para 0682).
With respect to claim 11, the combined art teaches the system of claim 6, wherein the computer readable medium further includes instructions for consulting a case management expert resource to develop guidelines for crafting patient messages based on presented conditions and risk analysis data; and customizing one or more of the communications of the series of personalized messages based on the guidelines developed by the case management expert resource (‘573; Para 0094).
With respect to claim 12, Gnanasambandam teaches a system for directing a patient to healthcare programs within a virtual agent system, comprising:
a device processor; and
a non-transitory computer readable medium having stored thereon instructions, executable by the processor, for performing the following steps:
receiving patient data regarding a patient (573; Para 0655: by disclosure, Gnanasambandam describes the method 6400 may include receiving patient data that indicates health related information associated with a patient); and
Nagaraja teaches
utilizing an healthcare program specialist persona to navigate prescription drug programs and identify suitable options for the patient based on the patent’s current medications and medical conditions in order to ensure patients have access to the most beneficial and cos-effective drug coverage available to them (‘181; page/lines 19/14-33: Steps of a workflow correspond to specific tasks/actions to be performed during the course of delivering the service based on the workflow. For example, diagnosis of a condition can be performed by a step of activating a chatbot equipped with the corresponding diagnostic questionnaire (further including a step of platform 206 providing a link to a HIPAA compliant platform on which the chatbot is to engage the user), and/or a step of facilitating the user making an appointment with a selected medical doctor (further including a step of platform 206 providing a link to a calendar service, and/or a payment service). For another example, treatment can be performed by a step of a chatbot sending the user a care plan (e.g., when simple home remedy seems sufficient based on the diagnosis), a step of platform 206 providing the treating doctor with an online prescription service to prescribe medication for the user, a step of platform 206 allowing the doctor to send the user emails, documents (e.g., educational materials), a step of a chatbot reminding the user to take the medication timely, and the like.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of claim invention to modify the system of Gnanasambandam with the technique of Artificial intelligence assisted service as taught by Nagaraja and the motivation is to engage the patient with care plane tailored to the patient needs
With respect to claim 13, the combined art teaches the system of claim 12, wherein the computer readable medium further includes instructions for consulting a prescription drug expert resource to ensure that all drugs prescribed to the patient optimally align with the user’s conditions (‘573; Para 0296).
With respect to claim 14, the combined art teaches the system of claim 12, wherein the computer readable medium further includes instructions for consulting a prescription drug expert resource to monitor a prescription history of the patient across different healthcare programs; and providing the patient with a message reminding the patient of their latest healthcare programs in the event the patient purchases medication through a healthcare program that the patient has replaced with a program in which the patient has more recently enrolled (‘573; Para 0284: scrolled down the menu, such that additional menu items below Health Plans & Assessments (element 812) are shown. The additional menu items include Reports (element 814), Health Team (element 816), and Purchases and Services ).
With respect to claim 15, the combined art teaches the system of claim 12, wherein the computer readable medium further includes instructions for consulting a healthcare program expert resource to analyze and interpret healthcare programs to match them with the patient’s specific medical conditions and needs; and providing a recommendation to the patient for the patient to enroll in one or more new healthcare programs (‘573; Para 0353: enerating a therapeutic paradigm logical framework 1800 for interpreting of the medical question).
With respect to claim 16, the combined art teaches the system of claim 12, wherein the computer readable medium further includes instructions for consulting an enrollment expert resource in order to facilitate enrollment in one or more healthcare programs (‘573; Para 0287: The cognitive agent 110 can align a user's respective health plan based on a health assessment at enrollment. In various embodiments, the cognitive agent 110 aligns the respective health plan with an interest of the user, a goal and priority of the user).
With respect to claim 17, the combined art teaches the system of claim 12, wherein the computer readable medium further includes instructions for receiving prescription drug data and medical conditions data associated with the patient; and redirecting a user of the virtual agent to one or more applications external to the virtual agent such that the user interacts with one or more application programming interfaces (APIs) associated with the one or more external applications to modify at least one aspect of the patient’s healthcare (‘573; Para 0403).
With respect to claim 18, Gnanasambandam teaches a system for automated healthcare management of a patient, comprising:
a virtual agent system that includes multiple specialized personas (‘573; Para 0143), each configured to perform specific tasks within a healthcare management process, including:
a schedule builder persona configured to generate a personalized care plan based on patient data, integrating input from one or more expert resources to tailor the care plan to the patient’s needs in order to improve the system’s effectiveness at
engaging the patient (‘573; Para 0154: the cognitive intelligence platform 102 (e.g., by way of the cognitive agent 110 interacting with the user) holistically manages and executes a health plan for durational care and wellness of the user (e.g., a patient or consumer). The health plan includes various aspects of durational management that is coordinated through a care continuum and proceeds to schedule of a service that aligns with a healthcare plan of the user; Para 0557: the information may be received from a source including an electronic medical records system, an application programming interface, a claims system, an electronic health virtual assistant, an application executing on the user device 104, a data store, or some combination thereof. Para 0532: the care plan 5604 may be tailored for providing action instructions to a user, the natural language representing the care plan 5604 may be tailored for providing action instructions to a medical personnel, and the natural language representing the care plan 5604 may be tailored for providing action instructions to an administrator; Para 0678:); and
Nagaraja teaches
a message builder persona configured to generate and schedule patient communications based on the generated personalized care plan, ensuring that each message is compliant with healthcare regulations in order to ensure that the content of the messages is compliant with healthcare regulations and effectively motivates the patient (‘181; page/lines 19/34-46: a step of generating a HIPAA compliant communication link for embedment into a SMS message to the user is indexed under, e.g., HIPAA link. For another example, once platform 206 narrows down the user's request from a relatively general one (e.g., #doc) to a relatively specific one (e.g., sore throat, flu) after obtaining more information from the user (e.g., by conducting diagnostic questionnaire guided communication, which is described with more details below), a step of a chatbot sending the user a care plan is mapped to the chatbot sending a care plan specific to the identified narrowed request.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of claim invention to modify the system of Gnanasambandam with the technique of Artificial intelligence assisted service as taught by Nagaraja and the motivation is to engage the patient with care plane tailored to the patient needs;
Gnanasambandam in view of Nagaraja teaches
the system being configured to consult multiple specialized expert resources for analysis of patient data and available healthcare programming (‘573; Para 0030: FIG. 23 shows a method for using feedback pertaining to the accuracy of cognified data to update an artificial intelligence engine), including:
a feedback expert resource configured to receive and analyze real-time feedback from the patient and provide insights that allow the schedule builder persona and message builder persona to adjust the generated care plan and the generated patient communications (‘573; Para 0099: the physician may submit feedback pertaining to whether or not the diagnosis is accurate for the patient. The feedback may be used to update the artificial intelligence engine that uses the knowledge graph and logical structure to generate the diagnosis using the cognified data); and
an incentive management expert resource configured to monitor patient compliance with health plan activities set forth in the generated care plan and incorporating user-specific goals and rewards into the care plan (‘ (‘573; Para 0686): FIG. 68 shows an example of providing a user interface 6800 that presents active care plans, in accordance with various embodiments. …the user interface 6800 may present sections for each care plan that is available for a patient and the goals included in those care plans.).
With respect to claim 19, the combined art teaches the system of claim 18, wherein the system is further configured to collect data regarding the patient’s personality type; and generate one or more of the patient communications that are customized according to the patient’s personality type (‘573; Para 0686).
With respect to claim 20, the combined art teaches the system of claim 18, wherein the system is configured to consult a message validation expert resource to ensure that all of the patient communications adhere to predetermined guidelines and/or regulations (573; Para 0156).
With respect to claim 21, Gnanasambandam teaches a method of self-learning generative artificial intelligence (AI) prompt optimization, comprising:
utilizing a device processor to execute instructions stored on a non-transitory computer readable medium for performing the following steps:
establishing an input prompt; (‘573; Para 0275: prompting the user to build his profile includes displaying a GUI asking the user to enter in additional information, such as age, weight, height, and health concerns.) ;
using a prompt engineering insights expert resource to determine a prompt output score (‘573; Para 0138: the machine learning models may use a combination of knowledge graphs, logical structures, structural similarity comparison mechanisms, and/or pattern recognition to generate the cognified data. The cognified data may be output by the one or more trained machine learning models.);
determining whether the prompt output score meets a predetermined scoring threshold (‘573; Para 0395: The knowledge graphs that include a threshold number of matches between the indicia and the known health related matches in the knowledge graphs may be selected for further processing.); and
recording the input prompt as an optimized prompt if the prompt output score meets the predetermined scoring threshold and generating a new input prompt if the prompt output score does not meet the predetermined scoring threshold (‘573; Para 0396: f there are a threshold number of identified structural similarities between the known logical structures and the possible health related information and/or if there are a threshold number of matches between indicia and known health related information for a particular medical condition, a diagnosis may be generated for that particular medical condition.).
Nagaraja teaches
generating care plan messages for a patient using the input prompt in order to ensure that the content of the messages is compliant with healthcare regulations effectively motivates the patient (‘181; page/lines 19/34-46: a step of generating a HIPAA compliant communication link for embedment into a SMS message to the user is indexed under, e.g., HIPAA link. For another example, once platform 206 narrows down the user's request from a relatively general one (e.g., #doc) to a relatively specific one (e.g., sore throat, flu) after obtaining more information from the user (e.g., by conducting diagnostic questionnaire guided communication, which is described with more details below), a step of a chatbot sending the user a care plan is mapped to the chatbot sending a care plan specific to the identified narrowed request.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of claim invention to modify the system of Gnanasambandam with the technique of Artificial intelligence assisted service as taught by Nagaraja and the motivation is to engage the patient with care plane tailored to the patient needs
With respect to claim 22, Gnanasambandam teaches a method of omnichannel communication (‘573; Para 0452: omni-channel messaging may be implemented by the cognitive intelligence platform ), comprising:
a utilizing a device processor to execute instructions stored on a non-transitory computer readable medium for performing the following steps:
receiving patient data regarding a patient (‘573; Para 0655: by disclosure, Gnanasambandam describes the method 6400 may include receiving patient data that indicates health related information associated with a patient);
receiving user input from the patient via a virtual agent (‘573; Para 0557: the information may be received from a source including an electronic medical records system, an application programming interface, a claims system, an electronic health virtual assistant, an application executing on the user device ); and
based on the received patient data and user input, automatically implementing an output manager expert resource to generate a plurality of omnichannel communications to be sent to the patient in order to deliver a more comprehensive and responsive care management solution (‘181; Abstract: the workflow including a set of one or more steps, a step of the set of one or more steps corresponding to a set of attributes including at least one of: a communication mode, a communication type, or a communication priority, the workflow being performed by at least one of: a chatbot, an AI assistant, or a service professional; modifying the workflow based on a new input sequent from the user using a workflow engine comprising at least one of: an AI model, a machine learning model, and a ruleset; and interacting with the user based at least in part on the workflow to deliver the service.; page/lines 26/30-34: artificial intelligence systems create new knowledge, insights, best practices by finding previously unknown patterns in data, and delivering new solutions by learning patterns in data.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of claim invention to modify the system of Gnanasambandam with the technique of Artificial intelligence assisted service as taught by Nagaraja and the motivation is to engage the patient with care plane tailored to the patient needs.
With respect to claim 23, , the combined art teaches teaches the method of claim 22, wherein the omnichannel communications include one or more of the following: email messages, URL’s to interactive web pages, PDF export files, mobile device notifications, and application programming interface (API) calls into external web services (‘573; Para 0114: he autonomous multipurpose application may transmit a message (e.g., email, text message, phone call, onscreen notification, etc.) to the user; Para 0376: n application programming interface (API) may be used to interface with an electronic medical record system used by the physician. The API may retrieve one or more EMRs of the patient and extract the patient notes; Para 0637: PDF format).
Response to Arguments
Applicant’s arguments with respect to claim 02/06/2026 have been considered but are moot because the arguments do not apply to the references of Ngaraja being used in the current rejection.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Lucie Kruse et al.; Would You Go to a Virtual Doctor? A Systematic Literature Review on User Preferences for Embodied Virtual Agents in Healthcare; 2023 IEEE International Symposium on Mixed and Augmented Reality (ISMAR).
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/HIEP V NGUYEN/Primary Examiner, Art Unit 3686