DETAILED ACTION
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 .
Notice to Applicant
1. Claims 1, 19, and 20 have been amended. Claims 4, 5, 12, 14, and 18 have been canceled. Now, claims 1-3, 6-11, 13, 15-17, and 19-25 are pending.
Information Disclosure Statement
2. The information disclosure statement (IDS) submitted on August 4, 2025 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
3. Claims 1-3, 6-11, 13, 15-17, and 19-25 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Claims 1, 19, and 20 are drawn to a process (method), a machine (device), and an apparatus (non-transitory computer-readable storage medium), each of which is within the four statutory categories. Claims 2, 3, 6-11, 13, 15-17, and 21-25 are further directed to an abstract idea on the grounds set out in detail below.
4. Claim 1 is directed to an abstract idea without significantly more. The claim, as a whole, falls under the grouping of mental processes and a method of organizing human activity of the Subject Matter Groupings of Abstract Ideas enumerated in Section I of the 2019 Revised Patent Eligibility Guidance.
Claim 1 recites the following elements:
Obtaining, from a first user, information about a subject….., the information comprising a diagnosis for the subject;
obtaining medical information about the subject …….., the medical information comprising one or more data types from a group comprising text result data, imaging data, and/or other 'omics data
identifying, based on the information about the subject, a treatment plan corresponding to the diagnosis and based on the medical information about the subject …………., the treatment plan comprising a set of tasks involving the subject, the set of tasks including a first subset of core tasks and a second subset of additional tasks;
generating…………a first set of parameters for the first subset of core tasks required by the treatment plan, wherein the first set of parameters indicates one or more timing windows for the set of tasks;
generating……a second set of parameters for the second subset of additional tasks based on at least a subset of the information about the subject, at least a subset of the first set of parameters for the first subset of core tasks, and additional information obtained……, wherein the second set of parameters comprises one or more timing parameters corresponding to performance times within the one or more timing windows and one or more ownership parameters;
identifying…..one or more additional tasks related to the set of tasks;
generating a resource allocation schedule for the subject using the set of tasks, the one or more additional tasks, first set of parameters, and the second set of parameters, the generating including:
assigning a first set of one or more tasks of the resource allocation schedule to a first entity; and
assigning a second set of one or more tasks of the resource allocation schedule to a second entity;
causing generation of respective scheduling data for the first entity and the second entity wherein the scheduling data corresponds to the performance times;
storing the resource allocation schedule ……. accessible to the first and the second entities …….. associated with the first and second entities;
providing the respective scheduling data to the first and second entities, wherein providing the respective scheduling data comprises causing display of appointment information;
receiving, from a second user or system, a health update about the subject that causes an adjustment of priority of one or more tasks of the set of tasks with respect to other tasks assigned to the first entity or second entity from another resource allocation schedule;
in accordance with receiving the health update, generating an updated resource allocation schedule by updating one or more parameters of the resource allocation schedule according to the adjustment of priority, including generating updated respective scheduling data, wherein the updated respective scheduling data corresponds to different performances times than the respective scheduling data;
providing an indication of the updated resource allocation schedule to the first user;
providing the updated respective scheduling data to the first and second entities via respective notifications, wherein the respective notifications are provided with respective options for the first and second entities to override the updated respective scheduling data; and
replacing, ….., the stored resource allocation schedule with the updated resource allocation schedule, such that the updated resource allocation schedule is accessible via the first and second entities.
As drafted, these elements represent a process that, under its broadest reasonable interpretation, encompasses obtaining patient information, identifying a set of tasks, generating parameters for the task, identifying additional tasks, generating a resource allocation schedule, and providing information about the tasks to the entity, including updated resource and schedule allocation, therefore, the process falls under a concept performed in the human mind (including an observation, evaluation, judgment, and opinion), which falls under a mental process. Accordingly, this Step 2A Prong 1 analysis concludes that claim 1 recites an abstract idea.
Additionally, as drafted, these elements represent a process that, under its broadest reasonable interpretation, encompasses obtaining patient information, obtaining medical information about a patient, identifying a set of tasks, generating parameters for the task, identifying additional tasks, generating a resource allocation schedule, and providing information about the tasks to the entity, including updated resource and schedule allocation and sending a notification of the updated/replaced scheduling data, therefore, the process falls under managing personal behavior or relationships or interactions between people, which falls under organizing human activity. Accordingly, this Step 2A Prong 1 analysis concludes that claim 1 recites an abstract idea.
This judicial exception is not integrated into a practical application. Beyond the limitations which recite the abstract idea, the claim includes the following additional element:
A user interface, one or more medical databases, a deterministic rules engine, an artificial intelligence (AI) engine, one or more databases, and a calendar application, inter-operable communications between respective devices, (see Specification paragraphs [0018], [0021], [0027], [0029], [0030]).
These elements, individually and in combination, are recited at high-levels of generality as generic computing components, used in ordinary capacities, such that it amounts to merely using a computer as a tool to perform the abstract idea. See MPEP § 2016.05(f). Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea and do not provide improvements to the functioning of computing systems or to another technology or technical field. This Step 2A Prong 2 analysis concludes that claim 1 is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception under Step 2B. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements, when considered individually and in combination, amount to merely using a computer, in its ordinary capacity, as a tool to perform an abstract idea. Merely using a computer, in its ordinary capacity, as a tool to perform an abstract idea cannot provide an inventive concept.
Accordingly, independent claim 1 does not qualify as patent-eligible subject matter.
The dependent claims (claims 2, 3, 6-11, 13, 15-17, and 21-25) have been given the full two-part analysis including analyzing the additional limitations both individually and in combination. The dependent claims, claims 2, 3, 6-11, 13, 15-17, and 21-25, when analyzed individually, and in combination, are also held to be patent ineligible under 35 U.S.C. 101. The additional recited limitations of the dependent claims fail to establish that the claims do not recite an abstract idea because the additional recited limitations of the dependent claims merely further narrow the abstract idea. Beyond the limitations which recite the abstract idea, the dependent claim 2 includes the following additional elements: at least one of the deterministic rules engine and the AI engine; the dependent claim 8 includes the following additional elements: via the AI engine; and dependent claim 10 includes a first machine learning model of the AI engine and a second machine learning model of the AI engine; dependent claim 11 includes via the AI engine; dependent claim 13 includes via the AI engine; dependent claim 15 includes the AI engine, and dependent claim 21 includes one or more databases and the AI engine, claim 24 includes the AI engine, and claim 25 includes a display. These elements, individually and in combination, are recited at high-levels of generality as generic computing components, used in their ordinary capacities, such that they amount to merely using a computer as a tool to perform the abstract idea. See MPEP § 2016.05(f). Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea and do not provide improvements to the functioning of computing systems or to another technology or technical field. This Step 2A Prong 2 analysis concludes that dependent claims 2, 8, 10, 11, 13, 15, and 21 are directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception under Step 2B. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements, when considered individually and in combination, amount to merely using a computer, in its ordinary capacity, as a tool to perform an abstract idea. Merely using a computer, in its ordinary capacity, as a tool to perform an abstract idea cannot provide an inventive concept.
The limitations of the dependent claims fail to integrate an abstract idea into a practical application because the dependent claims do not introduce additional elements; and performing the further narrowed abstract ideas of the dependent claims on the additional elements of the independent claims, individually or in combination, does not impose any meaningful limits on practicing the abstract ideas and does not provide improvements to the functioning of computing systems or to another technology or technical field; therefore, the claims amount to merely using a computer, in its ordinary capacity, as a tool to perform the abstract idea. Similarly, the additional recited limitations of the dependent claims fail to establish that the claims provide an inventive concept because claims that merely use a computer, in its ordinary capacity, as a tool to perform the abstract idea cannot provide an inventive concept.
5. Claim 19 is directed to an abstract idea without significantly more. The claim, as a whole, falls under the grouping of mental processes and a method of organizing human activity of the Subject Matter Groupings of Abstract Ideas enumerated in Section I of the 2019 Revised Patent Eligibility Guidance.
Claim 19 recites the following elements:
obtaining, from a first user, information about a subject…..the information comprising a diagnosis for the subject;
obtaining medical information about the subject …….., the medical information comprising one or more data types from a group comprising text result data, imaging data, and/or other 'omics data;
identifying, based on the information about the subject, a treatment plan corresponding to the diagnosis and based on the medical information about the subject………, the treatment plan comprising a set of tasks involving the subject, the set of tasks including a first subset of core tasks and a second subset of additional tasks;
generating….a first set of parameters for the first subset of core tasks required by the treatment plan, wherein the first set of parameters indicates one or more timing windows for the set of tasks;
generating….a second set of parameters for the second subset of additional tasks based on at least a subset of the information about the subject, at least a subset of the first set of parameters for the first subset of core tasks, and additional information obtained….., wherein the second set of parameters comprises one or more timing parameters corresponding to performance times within the one or more timing windows and one or more ownership parameters;
identifying…..one or more additional tasks related to the set of tasks;
generating a resource allocation schedule for the subject using the set of tasks, the one or more additional tasks, first set of parameters, and the second set of parameters, the generating including:
assigning a first set of one or more tasks of the resource allocation schedule to a first entity; and
assigning a second set of one or more tasks of the resource allocation schedule to a second entity;
causing generation of respective scheduling data for the first entity and the second entity, wherein the scheduling data corresponds to the performance times;
storing the resource allocation schedule …….accessible to the first and second entities ………associated with the first and second entities;
providing the respective scheduling data to the first and second entities, wherein providing the respective scheduling data comprises causing display of appointment information;
receiving, from a second user or system, a health update about the subject that causes an adjustment of priority of one or more tasks of the set of tasks with respect to other tasks assigned to the first entity or second entity from another resource allocation schedule;
in accordance with receiving the health update, generating an updated resource allocation schedule by updating one or more parameters of the resource allocation schedule according to the adjustment of priority, including generating updated respective scheduling data, wherein the updated respective scheduling data corresponds to different performances times than the respective scheduling data;
providing an indication of the updated resource allocation schedule to the first user;
providing the updated respective scheduling data to the first and second entities via respective notifications, wherein the respective notifications are provided with respective options for the first and second entities to override the updated respective scheduling data; and
replacing, ….., the stored resource allocation schedule with the updated resource allocation schedule, such that the updated resource allocation schedule is accessible via the first and second entities..
As drafted, these elements represent a process that, under its broadest reasonable interpretation, encompasses obtaining patient information, identifying a set of tasks, generating parameters for the task, identifying additional tasks, generating a resource allocation schedule, and providing information about the tasks to the entity, including providing updated task and allocation scheduling data, therefore, the process falls under a concept performed in the human mind (including an observation, evaluation, judgment, and opinion), which falls under a mental process. Accordingly, this Step 2A Prong 1 analysis concludes that claim 19 recites an abstract idea.
Additionally, as drafted, these elements represent a process that, under its broadest reasonable interpretation, encompasses obtaining patient information, obtaining medical information about a patient, identifying a set of tasks, generating parameters for the task, identifying additional tasks, generating a resource allocation schedule, and providing information about the tasks to the entity, including updated resource and schedule allocation and sending a notification of the updated/replaced scheduling data, therefore, the process falls under managing personal behavior or relationships or interactions between people, which falls under organizing human activity. Accordingly, this Step 2A Prong 1 analysis concludes that claim 1 recites an abstract idea.
This judicial exception is not integrated into a practical application. Beyond the limitations which recite the abstract idea, the claim includes the following additional element:
one or more processors, memory, one or more programs stored in the memory, a user interface, one or more medical databases, via a deterministic rules engine, via an artificial intelligence (AI) engine, one or more databases.
These elements, individually and in combination, are recited at high-levels of generality as generic computing components, used in ordinary capacities, such that it amounts to merely using a computer as a tool to perform the abstract idea. See MPEP § 2016.05(f). Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea and do not provide improvements to the functioning of computing systems or to another technology or technical field. This Step 2A Prong 2 analysis concludes that claim 19 is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception under Step 2B. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements, when considered individually and in combination, amount to merely using a computer, in its ordinary capacity, as a tool to perform an abstract idea. Merely using a computer, in its ordinary capacity, as a tool to perform an abstract idea cannot provide an inventive concept.
Accordingly, independent claim 19 does not qualify as patent-eligible subject matter.
6. Claim 20 is directed to an abstract idea without significantly more. The claim, as a whole, falls under the grouping of mental processes and a method of organizing human activity of the Subject Matter Groupings of Abstract Ideas enumerated in Section I of the 2019 Revised Patent Eligibility Guidance.
Claim 20 recites the following elements:
obtaining, from a first user, information about a subject….., the information comprising a diagnosis for the subject;
obtaining medical information about the subject ………, the medical information comprising one or more data types from a group comprising text result data, imaging data, and/or other 'omics data
identifying, based on the information about the subject, a treatment plan corresponding to the diagnosis and based on the medical information about the subject ……, the treatment plan comprising a set of tasks involving the subject, the set of tasks including a first subset of core tasks and a second subset of additional tasks;
generating, via a deterministic rules engine, a first set of parameters for the first subset of core tasks required by the treatment plan, wherein the first set of parameters indicates one or more timing windows for the set of tasks;
generating, via an artificial intelligence (AI) engine, a second set of parameters for the second subset of additional tasks based on at least a subset of the information about the subject, at least a subset of the first set of parameters for the first subset of core tasks, and additional information obtained from one or more databases, wherein second set of parameters comprises one or more timing parameters corresponding to performance times within the one or more timing windows and one or more ownership parameters;
identifying, via the AI engine, one or more additional tasks related to the set of tasks;
generating a resource allocation schedule for the subject using the set of tasks, the one or more additional tasks, first set of parameters, and the second set of parameters, the generating including:
assigning a first set of one or more tasks of the resource allocation schedule to a first entity; and
assigning a second set of one or more tasks of the resource allocation schedule to a second entity;
causing generation of respective scheduling data for the first entity and the second entity wherein the scheduling data corresponds to the performance times;
storing the resource allocation schedule ….. accessible to the first and the second entities ……associated with the first and second entities;
providing the respective scheduling data to the first and second entities, wherein providing the respective scheduling data comprises causing display of appointment information;
receiving, from a second user or system, a health update about the subject that causes an adjustment of priority of one or more tasks of the set of tasks with respect to other tasks assigned to the first entity or second entity from another resource allocation schedule;
in accordance with receiving the health update, generating an updated resource allocation schedule by updating one or more parameters of the resource allocation schedule according to the adjustment of priority, including generating updated respective scheduling data, wherein the updated respective scheduling data corresponds to different performances times than the respective scheduling data;
providing an indication of the updated resource allocation schedule to the first user;
providing the updated respective scheduling data to the first and second entities via respective notifications, wherein the respective notifications are provided with respective options for the first and second entities to override the updated respective scheduling data; and
replacing the stored resource allocation schedule with the updated resource allocation schedule, such that the updated resource allocation schedule is accessible via the first and second entities..
As drafted, these elements represent a process that, under its broadest reasonable interpretation, encompasses obtaining patient information, identifying a set of tasks, generating parameters for the task, identifying additional tasks, generating a resource allocation schedule, and providing information about the tasks to the entity, including providing updated task and allocation scheduling data, therefore, the process falls under a concept performed in the human mind (including an observation, evaluation, judgment, and opinion), which falls under a mental process. Accordingly, this Step 2A Prong 1 analysis concludes that claim 20 recites an abstract idea.
Additionally, as drafted, these elements represent a process that, under its broadest reasonable interpretation, encompasses obtaining patient information, obtaining medical information about a patient, identifying a set of tasks, generating parameters for the task, identifying additional tasks, generating a resource allocation schedule, and providing information about the tasks to the entity, including updated resource and schedule allocation and sending a notification of the updated/replaced scheduling data, therefore, the process falls under managing personal behavior or relationships or interactions between people, which falls under organizing human activity. Accordingly, this Step 2A Prong 1 analysis concludes that claim 1 recites an abstract idea.
This judicial exception is not integrated into a practical application. Beyond the limitations which recite the abstract idea, the claim includes the following additional elements:
A non-transitory computer-readable storage medium storing one or more programs, a computing device having one or more processors and memory, a user interface, one or more medical databases, via a deterministic rules engine, via an artificial intelligence (AI) engine, one or more databases, via inter-operable communications between respective devices.
These elements, individually and in combination, are recited at high-levels of generality as generic computing components, used in their ordinary capacities, such that they amount to merely using a computer as a tool to perform the abstract idea. See MPEP § 2016.05(f). Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea and do not provide improvements to the functioning of computing systems or to another technology or technical field. This Step 2A Prong 2 analysis concludes that claim 20 is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception under Step 2B. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements, when considered individually and in combination, amount to merely using a computer, in its ordinary capacity, as a tool to perform an abstract idea. Merely using a computer, in its ordinary capacity, as a tool to perform an abstract idea cannot provide an inventive concept.
Accordingly, independent claim 20 does not qualify as patent-eligible subject matter.
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.
7. Claims 1-3, 6-11, 13, 15-17, and 19-25 are rejected under 35 U.S.C. 103 as being unpatentable over United States Patent Application Publication Number 2020/0411170, Brown, et al., hereinafter Brown in view of United States Patent Application Publication Number 2017/0124526, Sanderford, et al., hereinafter Sanderford.
8. Regarding claim 1, Brown discloses a method of task management, comprising:
Obtaining, from a first user, information about a subject via a user interface, the information comprising a diagnosis for the subject, (para. 44, the static/semi-static system data can include information stored one or more databases regarding defined system protocols, regulations, operating requirements, employee administrative information, patient electronic health records (EHRs), patient imaging studies, patient laboratory studies, clinical orders/notes, patient preference information and para. 73, the care plan information can be automatically generated and provided by an artificial intelligence (AI) system configured to evaluate a patient's condition, diagnosis, needs and medical history and generate a care plan accordingly);
obtaining medical information about the subject from one or more medical databases, the medical information comprising one or more data types from a group comprising text result data, imaging data, and/or other 'omics data, (para. 44, the static/semi-static system data can include information stored one or more databases regarding defined system protocols, regulations, operating requirements, employee administrative information, patient electronic health records (EHRs), patient imaging studies, patient laboratory studies, clinical orders/notes, patient preference information, employee performance records);
identifying, based on the information about the subject, a treatment plan corresponding to the diagnosis and based on the medical information about the subject from the one or more medical databases, the treatment plan comprising a set of tasks involving the subject, the set of tasks including a first subset of core tasks and a second subset of additional tasks, (para. 44, the static/semi-static system data can include information stored one or more databases regarding defined system protocols, regulations, operating requirements, employee administrative information, patient electronic health records (EHRs), patient imaging studies, patient laboratory studies, clinical orders/notes, patient preference information, employee performance records, para. 73, the care plan information can be automatically generated and provided by an artificial intelligence (AI) system configured to evaluate a patient's condition, diagnosis, needs and medical history and generate a care plan accordingly, and para. 84, depending on the type of operating entity and timeframe evaluated, the healthcare tasks can include tasks scheduled for performance as specific points in time (e.g., patient appointments scheduled for specific dates and times), healthcare tasks scheduled and/or requested for performance over a relatively recent timeframe or window of time (e.g., the next hour, the next 24 hours, between 2:00 pm and 5:00 pm, etc.), healthcare tasks that need to be performed as soon as possible (e.g., urgent/critical tasks));
generating, via a deterministic rules engine, a first set of parameters for the first subset of core tasks required by the treatment plan, wherein the first set of parameters indicates one or more timing windows for the set of tasks, (para. 56, the optimization criteria can include (but is not limited to), facilitating optimal patient flow, minimizing delay between performance of tasks, meeting fixed constraints (e.g., regarding timing and order, location, quality/standard of care, etc.), meeting patient preferences/needs, maximizing utilization of resources, para. 65, The rules/requirements associated with a task can also include information identifying or indicating a relative priority level of a task (e.g., in accordance with a defined priority level coding/ranking scheme), as well as information identifying or indicating any performance dependency constraints with other tasks, and para. 131, the task optimization analysis component 702 can employ various machine learning and/or statistical task optimization models/algorithms to facilitate determinizing how to schedule tasks and assign resources to the tasks based on the various parameters/variables described above (e.g., associated with the tasks, the patients associated with the tasks, the healthcare workers that perform the tasks, the non-human resources needed for the tasks, and in some implementations, the forecasted task demand and resource availability).);;
identifying, via the AI engine, one or more additional tasks related to the set of tasks, (para. 7, the availability analysis component can employ machine learning and artificial intelligence to facilitate determining the availability information (e.g., using one or more models developed/trained based on historical activity information for the healthcare workers and historical performance of the healthcare tasks under various operating conditions/contexts of the healthcare system), and para. 105, the task assessment module 106 can include task assessment machine learning component 318 to facilitate determining one or more of these task parameters in real-time using various suitable machine learning and/or artificial intelligence (AI)-based schemes, and para. 75, the task reporting systems can include an AI system that determines new tasks to be performed based on information regarding results/outputs of previously completed tasks, monitored changes in patient conditions/status, monitored changes in healthcare worker task performance);
generating a resource allocation schedule for the subject using the set of tasks, the one or more additional tasks, first set of parameters, and the second set of parameters, the generating including: (para. 33, a system is provided that can facilitate optimizing scheduling of different healthcare tasks and assigning resources to the different healthcare tasks in real-time in a manner that synchronizes and harmonizes patient needs and provider capabilities under the dynamic operating conditions associated with the healthcare environment, and para. 37, (e.g., the task assessment module 110, the resources assessment module 114, and the task scheduling and resource assignment optimization module 118) that when executed by the at least one processor 122, facilitate performance of operations defined by the executable instructions. In some embodiments, the memory 124 can also store one or more of the various data sources and/or data structures of system 100 (e.g., the healthcare information systems/sources 102, the dynamic operating data 104, the static/semi-static system data 106, the indexed task data 112, the resource availability data 116, and the task scheduling and resource assignment information 126) and para. 146, The task optimization analysis component 702 can also determine a second task scheduling and resource assignment information 126 using a second optimization model configured to determine an optimal task scheduling and resource assignment scheme using a second optimization model configured to determine an alternative scheme that focuses more heavily on meeting patient preferences and para. 153, the system can determine a first subset of available healthcare workers of to perform the currently pending healthcare tasks based on monitoring activity data for the healthcare workers (e.g., using worker activity monitoring component 504). At 1006, the system can determine a second subset of qualified healthcare workers included in the first subset of available healthcare workers based on defined worker capability information and defined capability requirements of the currently pending healthcare tasks.)
assigning a first set of one or more tasks of the resource allocation schedule to a first entity, (para. 33, a system is provided that can facilitate optimizing scheduling of different healthcare tasks and assigning resources to the different healthcare tasks in real-time in a manner that synchronizes and harmonizes patient needs and provider capabilities under the dynamic operating conditions associated with the healthcare environment, and para. 37, (e.g., the task assessment module 110, the resources assessment module 114, and the task scheduling and resource assignment optimization module 118) that when executed by the at least one processor 122, facilitate performance of operations defined by the executable instructions. In some embodiments, the memory 124 can also store one or more of the various data sources and/or data structures of system 100 (e.g., the healthcare information systems/sources 102, the dynamic operating data 104, the static/semi-static system data 106, the indexed task data 112, the resource availability data 116, and the task scheduling and resource assignment information 126) and para. 146, The task optimization analysis component 702 can also determine a second task scheduling and resource assignment information 126 using a second optimization model configured to determine an optimal task scheduling and resource assignment scheme using a second optimization model configured to determine an alternative scheme that focuses more heavily on meeting patient preferences and para. 153, the system can determine a first subset of available healthcare workers of to perform the currently pending healthcare tasks based on monitoring activity data for the healthcare workers (e.g., using worker activity monitoring component 504). At 1006, the system can determine a second subset of qualified healthcare workers included in the first subset of available healthcare workers based on defined worker capability information and defined capability requirements of the currently pending healthcare tasks.); and
assigning a second set of one or more tasks of the resource allocation schedule to a second entity, (para. 33, a system is provided that can facilitate optimizing scheduling of different healthcare tasks and assigning resources to the different healthcare tasks in real-time in a manner that synchronizes and harmonizes patient needs and provider capabilities under the dynamic operating conditions associated with the healthcare environment, and para. 37, (e.g., the task assessment module 110, the resources assessment module 114, and the task scheduling and resource assignment optimization module 118) that when executed by the at least one processor 122, facilitate performance of operations defined by the executable instructions. In some embodiments, the memory 124 can also store one or more of the various data sources and/or data structures of system 100 (e.g., the healthcare information systems/sources 102, the dynamic operating data 104, the static/semi-static system data 106, the indexed task data 112, the resource availability data 116, and the task scheduling and resource assignment information 126) and para. 146, The task optimization analysis component 702 can also determine a second task scheduling and resource assignment information 126 using a second optimization model configured to determine an optimal task scheduling and resource assignment scheme using a second optimization model configured to determine an alternative scheme that focuses more heavily on meeting patient preferences and para. 153, the system can determine a first subset of available healthcare workers of to perform the currently pending healthcare tasks based on monitoring activity data for the healthcare workers (e.g., using worker activity monitoring component 504). At 1006, the system can determine a second subset of qualified healthcare workers included in the first subset of available healthcare workers based on defined worker capability information and defined capability requirements of the currently pending healthcare tasks.);
causing generation of respective scheduling data for the first and second entity wherein the scheduling data corresponds to the performance times, (Fig. 3, para. 18, example task assessment module that facilitates determining information regarding currently pending and forecasted healthcare tasks for performance by one or more operating entities of an integrated healthcare system),
storing the resource allocation schedule in a database accessible to the first and the second entities via inter-operable communications between respective devices associated with the first and second entities, (para. 38, the healthcare delivery optimization server device 108 can be or correspond to a distributed computing system including a network of interconnected devices (e.g., back-end servers, front-end servers, dedicated machines, virtual machines, client devices, etc.), machine, databases, datastores and the like and para. 51, the resource assessment module 114 can be configured to extract and evaluate the dynamic operating data 104 regarding the activity of the various healthcare workers in real-time in view of any scheduling constraints for the healthcare workers to determine resource availability data 116 regarding availability of the respective healthcare workers to perform currently pending tasks and/or upcoming tasks (e.g., known, scheduled, and/or forecasted));
providing the respective scheduling data to the first and second entities, wherein providing the respective scheduling data comprises causing display of appointment information, (para. 47, the task assessment module 110 can evaluate information for a patient identifying or indicating scheduled procedures, appointments and checkups, identifying clinical orders, defining a prescribed care plan, defining a medication regimen, defining a feeding regimen, tracking patient status, identifying patient transfer needs (including current and destination location of the patient), providing real-time feedback requesting or indicating immediate or future medical care (e.g., provided by the patient, gathered indirectly via a patient monitoring system)).
in accordance with receiving the health update, generating an updated resource allocation schedule by updating one or more parameters of the resource allocation schedule according to the adjustment of priority, including generating updated respective scheduling data, wherein the updated respective scheduling data corresponds to different performances times than the respective scheduling data, (para. 43, the dynamic operating data 104 can include information provided by patient scheduling systems, patient monitoring systems, patient tracking systems, operational data logging systems, workflow tracking systems, resource tracking/monitoring systems, and the like. In one or more implementations, the dynamic operating data 104 can include various types of information for each individual operating entity that identifies or indicates the various healthcare tasks that are needed for performance by/at the operating entity at a current point in time/or over a defined, upcoming timeframe (e.g., the current workday, the next 24 hours, the next week, the next month, etc.) to account for known and optionally forecasted patient needs at the current point in time and over. The dynamic operating data 104 can also include information regarding the state, status/condition, availability, movement, location, and other dynamic parameters associated with the healthcare resources that are needed to perform the healthcare tasks and/or the patient associated with the healthcare task and para. 75, the AI system can evaluate newly received laboratory data for a patient to determine a new task that needs to be performed in response to the specific values reflected in the laboratory data.);
providing an indication of the updated resource allocation schedule to the first user, (para. 149, the task assignment component 714 can generate and send a task assignment message to a device associated with the healthcare worker comprising information that recommends the healthcare worker perform the supplemental healthcare task during the timeslot).
Brown does not explicitly disclose the following:
generating, via an artificial intelligence (AI) engine, a second set of parameters for the second subset of additional tasks based on at least a subset of the information about the subject, at least a subset of the first set of parameters for the first subset of core tasks, and additional information obtained from one or more databases, wherein the second set of parameters comprises one or more timing parameters corresponding to performance times within the one or more timing windows and one or more ownership parameters;
receiving, from a second user or system, a health update about the subject that causes an adjustment of priority of one or more tasks of the set of tasks with respect to other tasks assigned to the first entity or second entity from another resource allocation schedule,;
providing the updated respective scheduling data to the first and second entities via respective notifications, wherein the respective notifications are provided with respective options for the first and second entities to override the updated respective scheduling data; and
replacing, in the database, the stored resource allocation schedule with the updated resource allocation schedule, such that the updated resource allocation schedule is accessible via the first and second entities.
However, Sanderford teaches the following:
generating, via an artificial intelligence (AI) engine, a second set of parameters for the second subset of additional tasks based on at least a subset of the information about the subject, at least a subset of the first set of parameters for the first subset of core tasks, and additional information obtained from one or more databases, wherein the second set of parameters comprises one or more timing parameters corresponding to performance times within the one or more timing windows and one or more ownership parameters, (para. 149, the step of assigning based on the computed comparison S4300 can be based on a threshold 1470 according to an example. In one scenario the threshold 1470 can be one of a timing criteria or timing threshold 1472, a spatial distance 1474, or the prediction value 1140. The timing threshold 1472 can be a set time, a time duration, or a relative time based on any timer. The spatial distance 1474 threshold can be a set distance or a relative distance based on one of the sensing system 1300, the appointment location 1135, and the patient location 2220. The prediction value 1140 threshold can be a fixed value based on any prediction value associated with any appointment entry component, para. 281, Updating the initial duration estimate by replacing the estimate with the time duration measure on the timer; (ii) Summing the durations yielding improved forecast or subsequently scheduled appointments; (iii) notifying at least one of the remaining patients scheduled on that same day of the improved forecast of scheduler. This process results in a more accurate estimation of the highly variable duration appointment time by resolving timing variability on the day of the scheduled appointment, and para. 283, use of machine learning or artificial intelligence to improve the PAD estimate and restacking method, creating virtual tours of the doctor's office that are visible through the patient device, incorporating a messaging platform that can expand to allow for remote diagnosis via photo/video HIPAA compliant communication between patients and practitioners, as well as a rating/score for providers (whether publicly visible or not) so that certain providers can be ranked higher or receive specific endorsements from the scheduling system based on their performance);
receiving, from a second user or system, a health update about the subject that causes an adjustment of priority of one or more tasks of the set of tasks with respect to other tasks assigned to the first entity or second entity from another resource allocation schedule, (para. 165, An unscheduled patient can be added into the ordered list 1110 for emergency reasons or other reasons, causing the following appointments to restack accordingly);
providing the updated respective scheduling data to the first and second entities via respective notifications, wherein the respective notifications are provided with respective options for the first and second entities to override the updated respective scheduling data, (para. 78, patient device updates the scheduling system 1000 with a patient location 2220 using the one or more sensor systems 1300. The patient device 1414 receives communication from the processing circuitry 1400. In one example the communication is a reminder of the appointment timing or a notification that the appointment timing is revised with options to accept or to reject the revised appointment timing. When the revised appointment timing is rejected the next closest appointment timing can be offered or the patient can be offered to request a new appointment timing); and
replacing, in the database, the stored resource allocation schedule with the updated resource allocation schedule, such that the updated resource allocation schedule is accessible via the first and second entities, (para. 78, para. 78, patient device updates the scheduling system 1000 with a patient location 2220 using the one or more sensor systems 1300. The patient device 1414 receives communication from the processing circuitry 1400. In one example the communication is a reminder of the appointment timing or a notification that the appointment timing is revised with options to accept or to reject the revised appointment timing. When the revised appointment timing is rejected the next closest appointment timing can be offered or the patient can be offered to request a new appointment timing, and para. 165, An unscheduled patient can be added into the ordered list 1110 for emergency reasons or other reasons, causing the following appointments to restack accordingly).
At the time of Applicant's filed invention, it would have been obvious to one of ordinary skill in the art to modify the system of Brown with the teaching of Sanderford. As suggested by Sanderford, one would have been motivated to include these features to communicate any revised timing to the patient, thereby minimizing a total waiting time, (Sanderford - Abstract), to modify the system of Brown with the teaching of Sanderford.
9. Regarding claim 2, Brown discloses the method of claim 1 as described above. Brown further discloses wherein the set of tasks are identifie