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
This communication is in response to the amendment filed 02/17/2026. Claims 1, 4-18, 20 have been amended. Claims 2-3 have been canceled. Claim 21 has been added. Claims 1, 4-21 are presented for examination.
Subject Matter Free of Prior Art
Claim(s) 1, 4-21 are allowable over prior art because the prior art of record fail to expressly teach or suggest, either alone or in combination, the features found within the independent claims, in particular: “extracting a first quantity of primary patient indicators, supporting the first diagnosis for the first patient, from a first subset of patient data in the corpus of patient data, captured within target sampling windows defined by the first set of primary target indicators; generating a first notification comprising a first prompt to review each patient indicator, in the first quantity of primary patient indicators, for specifying in a first provider note generated for the first encounter and indicating the first diagnosis for the first patient; transmitting the first notification to the provider via the provider portal; in response to receiving selection of a first subset of patient indicators, in the first quantity of primary patient indicators, from the provider via the provider portal: appending the first provider note with the first subset of patient indicators linked to the first diagnosis; and predicting a first acceptance score for the first provider note based on the first diagnosis and the first subset of patient indicators, the first acceptance score representing a likelihood of acceptance of the first diagnosis for the first patient during the first encounter represented by the first provider note; and in response to the first acceptance score falling below a threshold score extracting a second quantity of secondary patient indicators from a second subset of patient data, in the corpus of patient data, captured within target sampling windows defined by a second set of secondary target indicators supporting the first diagnosis in combination with the first set of primary target indicators; generating a second notification comprising a second prompt to review each patient indicator, in the second quantity of secondary patient indicators, for specifying in the first provider note; and transmitting the second notification to the provider via the provider portal.” Because the prior art does not teach or disclose the above features in the specific manner and combinations recited in independent claims 1, 16, 20-21, claims 1, 16, 20-21 are hereby deemed to be allowable over prior art. Originally numbered dependent claims 4-15, 17-19 incorporate the allowable features of originally numbered independent claims 1, 16, through dependency, respectively.
However, the claims are still rejected under 101.
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.
Claims 1, 4-21 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. Based upon consideration of all of the relevant factors with respect to the claims as a whole, the claims are directed to non-statutory subject matter which do not include additional elements that are sufficient to amount to significantly more than the judicial exception because of the following analysis:
Claim 1 is drawn to a method which is within the four statutory categories (i.e., method). Claim 16 is drawn to a method which is within the four statutory categories (i.e., method). Claim 20 is drawn to a method which is within the four statutory categories (i.e., method). Claim 21 is drawn to a method which is within the four statutory categories (i.e., method).
Independent claim 1 recites… for a first encounter with a first patient, receiving a first diagnosis for the first patient from a provider…; accessing a health record, in a population of health records, corresponding to the first patient and comprising a corpus of patient data associated with the first patient; accessing a diagnostic model comprising a population of modules corresponding to a population of diagnoses, each module in the population of modules defining a set of target indicators supporting a corresponding diagnosis in the population of diagnoses, each target indicator in the set of target indicators defining a target sampling window; accessing a first set of primary target indicators defined for the first diagnosis in a first module, in the population of modules, corresponding to the first diagnosis; extracting a first quantity of primary patient indicators, supporting the first diagnosis for the first patient, from a first subset of patient data, in the corpus of patient data, captured within target sampling windows defined by the first set of primary target indicators; generating a first notification comprising a first prompt to review each patient indicator, in the first quantity of primary patient indicators, for specifying in a first provider note generated for the first encounter and indicating the first diagnosis for the first patient; " [providing] the first notification to the provider…; in response to receiving selection of a first subset of patient indicators, in the first quantity of primary patient indicators…: appending the first provider note with the first subset of patient indicators linked to the first diagnosis; and predicting a first acceptance score for the first provider note based on the first diagnosis and the first subset of patient indicators, the first acceptance score representing a likelihood of acceptance of the first diagnosis for the first patient during the first encounter represented by the first provider note; and " in response to the first acceptance score falling below a threshold score extracting a second quantity of secondary patient indicators from a second subset of patient data, in the corpus of patient data, captured within target sampling windows defined by a second set of secondary target indicators supporting the first diagnosis in combination with the first set of primary target indicators; generating a second notification comprising a second prompt to review each patient indicator, in the second quantity of secondary patient indicators, for specifying in the first provider note; and [providing] the second notification to the provider...
Independent claim 16 recites… for an encounter with a patient, receiving a first diagnosis for the patient from a provider…; accessing a health record, in a population of health records, corresponding to the patient and comprising a corpus of patient data associated with the patient; accessing a diagnostic model comprising a population of modules, corresponding to a population of diagnoses, each module, in the population of modules, defining a set of target indicators supporting a corresponding diagnosis in the population of diagnoses; accessing a first set of target indicators defined for the first diagnosis in a first module, in the population of modules, and supporting the first diagnosis, the first set of target indicators comprising: a set of primary target indicators supporting the first diagnosis, each primary target indicator in the set of primary target indicators defining a primary target sampling window; and a set of secondary target indicators supporting the first diagnosis in combination with the set of primary target indicators, each secondary target indicator in the set of secondary target indicators defining a secondary target sampling window; extracting a set of primary patient indicators, from a first subset of patient data captured within primary target sampling windows defined by the set of primary target indicators and supporting the first diagnosis for the patient; in response to a first quantity of primary patient indicators in the set of primary patient indicators exceeding a threshold quantity: withholding extraction of secondary patient indicators corresponding to the set of secondary target indicators; populating a first notification with the set of primary patient indicators and a first prompt to select indicators, in the set of primary patient indicators, for specifying in a provider note generated for the encounter and indicating the first diagnosis for the patient; and [providing] the first notification to the provider…; and in response to receiving selection of a first subset of primary patient indicators, in the set of primary patient indicators, appending the provider note with the first subset of primary patient indicators linked to the first diagnosis.
Independent claim 20 recites… for an encounter with a patient, receiving a diagnosis for the patient from a provider…; accessing a health record, in a population of health records, corresponding to the patient and comprising a corpus of patient data associated with the patient; accessing a diagnostic model comprising a population of modules, corresponding to a population of diagnoses, each module, in the population of modules, defining a set of target indicators supporting a corresponding diagnosis in the population of diagnoses; accessing a set of primary target indicators defined for the diagnosis in a first module, in the population of modules, corresponding to the diagnosis; extracting a set of primary patient indicators from a subset of patient data, in the corpus of patient data, corresponding to the set of primary target indicators and supporting the diagnosis for the patient; in response to a first quantity of primary patient indicators, in the set of primary patient indicators, exceeding a threshold quantity, selecting a first subset of patient indicators, in the set of primary patient indicators, for presenting to the provider in support of the diagnosis, the first subset of patient indicators predicted to yield a threshold probability of acceptance of a provider note specifying the diagnosis and the first subset of patient indicators; generating a notification comprising the first subset of patient indicators and a prompt to review each patient indicator, in the first subset of patient indicators, for specifying in the provider note generated for the encounter and indicating the diagnosis for the patient; [providing] the notification to the provider…; and in response to receiving selection of a second subset of patient indicators, in the first subset of patient indicators, from the provider…, appending the provider note with the second subset of patient indicators linked to the diagnosis.
Independent claim 21 recites… for an encounter with a patient, receiving a diagnosis for the patient from a provider…; accessing a health record, in a population of health records, corresponding to the patient and comprising a corpus of patient data associated with the patient; " accessing a diagnostic model comprising a population of modules corresponding to a population of diagnoses, each module in the population of modules defining a set of target indicators supporting a corresponding diagnosis in the population of diagnoses, each target indicator in the set of target indicators defining a target sampling window; " accessing a set of target indicators defined for the diagnosis in a module, in the population of modules, corresponding to the diagnosis, the set of target indicators comprising: a set of primary target indicators supporting the diagnosis; and a set of secondary target indicators supporting the diagnosis in combination with the set of primary target indicators; " filtering the corpus of patient data by timestamp to isolate a first subset of patient data captured within target sampling windows defined by the set of primary target indicators; " extracting a first quantity of primary patient indicators, supporting the diagnosis for the patient, from the first subset of patient data; " in response to the first quantity of primary patient indicators falling below a threshold quantity: filtering the corpus of patient data by timestamp to isolate a second subset of patient data captured within target sampling windows defined by the second set of secondary target indicators; and extracting a second quantity of secondary patient indicators, supporting the diagnosis for the patient, from the second subset of patient data, the second quantity of secondary patient indicators exceeding the threshold quantity in combination with the first quantity of primary patient indicators; " generating a notification comprising a prompt to review patient indicators, in the first quantity of primary patient indicators and the second quantity of secondary patient indicators, for specifying in a provider note generated for the encounter; " [providing] the notification to the provider…; and " in response to receiving selection of a subset of patient indicators, in the first quantity of primary patient indicators and the second quantity of secondary patient indicators, from the provider…: appending the provider note with the subset of patient indicators linked to the diagnosis; predicting an acceptance score for the provider note based on the diagnosis and the subset of patient indicators, the acceptance score representing a likelihood of acceptance of the diagnosis for the patient; and in response to the acceptance score exceeding a threshold score, verifying the provider note.
Under its broadest reasonable interpretation, the limitations noted above, as drafted, covers certain methods of organizing human activity (i.e., managing personal behavior or relationships or interactions between people…following rules or instructions), but for the recitation of generic computer components. That is, other than reciting a “a computing device,” the claim encompasses rules or instructions to collect data (i.e., related to a patient), analyze the collected data, and output relevant information (i.e., related to a diagnosis) for a user (i.e., doctor) accordingly. If a claim limitation, under its broadest reasonable interpretation, covers managing personal behavior or relationships or interactions between people, but for the recitation of generic computer components, then it falls within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas. Accordingly, the claims recite an abstract idea.
Claim 1 recites additional elements (i.e., a provider portal executing on a computing device accessed by the provider). Claim 16 recites additional elements (i.e., a provider portal executing on a computing device accessed by the provider). Claim 20 recites additional elements (i.e., a provider portal executing on a computing device accessed by the provider). Claim 21 recites additional elements (i.e., a provider portal executing on a computing device accessed by the provider). Looking to the specifications, a computing device having a user portal is recited at a high level of generality (¶ 0025-0026; ¶ 00203), such that it amounts to no more than mere instructions to apply the exception using generic computer components. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements individually. The 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. Accordingly, the claims are directed to an abstract idea.
Reevaluated under step 2B, the additional elements noted above do not provide “significantly more” when taken either individually or as an ordered combination. The use of a general purpose computer or computers (i.e., a computing device having a user portal) amounts to no more than mere instructions to apply the exception using generic computer components and does not impose any meaningful limitation on the computer implementation of the abstract idea, so it does not amount to significantly more than the abstract idea. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements individually. The combination of elements does not indicate a significant improvement to the functioning of a computer or any other technology and their collective functions merely provide a conventional computer implementation of the abstract idea. Furthermore, the additional elements or combination of elements in the claims, other than the abstract idea per se, amount to no more than a recitation of generally linking the abstract idea to a particular technological environment or field of use, as the courts have found in Parker v. Flook; similarly, the current invention merely limits the claimed calculations to the healthcare industry which does not impose meaningful limits on the scope of the claim. Therefore, there are no limitations in the claims that transform the judicial exception into a patent eligible application such that the claims amount to significantly more than the judicial exception.
Dependent claims 4-15, 17-19 include all the limitations of the parent claims and further elaborate on the abstract idea discussed above and incorporated herein.
Claims 4-6, 10-15, 17-19 further define the analysis and organization of data for the performance of the abstract idea and do not recite any additional elements. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements individually. Thus, the claims do not integrate the abstract idea into a practical application and do not provide “significantly more.”
Claims 7-9 further recites the additional elements of “a data packet,” which amounts to no more than mere instructions to apply the exception using generic computer components, and only generally links the claimed invention to a particular technological environment or field of use (i.e., computer technology), which does not impose meaningful limits on the scope of the claim. Also, functional limitations further define the analysis and organization of data for the performance of the abstract idea. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements individually. Thus, the additional elements do not integrate the abstract idea into a practical application and do not provide “significantly more.”
Although the dependent claims add additional limitations, they only serve to further limit the abstract idea by reciting limitations on what the information is and how it is received and used. These information characteristics do not change the fundamental analogy to the abstract idea grouping of “Certain Methods of Organizing Human Activity,” and, when viewed individually or as a whole, they do not add anything substantial beyond the abstract idea. Furthermore, the combination of elements does not indicate a significant improvement to the functioning of a computer or any other technology. Therefore, the claims when taken as a whole are ineligible for the same reasons as the independent claims.
Response to Arguments
Applicant's arguments filed 02/17/2026 have been fully considered but they are not persuasive. Applicant’s arguments will be addressed hereinbelow in the order in which they appear in the response filed 02/17/2026.
In the remarks, Applicant argues in substance that:
Regarding the 101 rejections,
“the Examiner has ignored and/or not addressed the claimed execution logic that governs how a computer system accesses, evaluates, and presents patient data from large, heterogeneous electronic health records under real-time constraints. In particular, the Examiner has failed to address how the following technical elements of the Claims and/or fail to integrate the Claims into a practical application: " selectively limiting which portions of a patient's electronic health record are accessed based on relevance to a provider-entered diagnosis; " prioritizing higher-value supporting indicators before initiating additional data access and processing; " conditionally expanding record analysis only when initial evidence is insufficient to support the diagnosis; and " presenting only selectively identified supporting indicators to the provider portal. In particular, the system defines distinct target sampling windows for individual indicators to isolate a specific subset of patient data captured within a defined time period preceding the encounter, thereby reducing the search space of the database (see at least paragraphs [0048] and [0073] of the originally-filed application). Additionally, the system implements a diagnostic model with a set of tiered evidence, such that the computer system identifies a primary target indicator supporting the diagnosis independent of secondary indicators and only evaluates the secondary indicators dependent on the presence (or absence) of the primary tier (see at least paragraphs [0046] and [0047] of the originally-filed application). Furthermore, the system presents only selectively identified supporting indicators to the provider to reduce data transfer payloads and minimize network-related latency (see at least paragraphs [0026] and [0076] of the originally-filed application) and thus reduce computational resources allocated to surfacing patient data and note generation. A system executing the Claims can therefore apply a specific execution strategy that limits unnecessary data access and processing, including: " limiting record access to candidate portions of a patient's electronic health record (or "EHR") relevant to a provider-entered diagnosis; " suppressing unnecessary data retrieval when evidentiary sufficiency is already established; and " transmitting only selectively extracted subsets of patient indicators to the provider portal. Accordingly, the system provides an improvement to the technical functioning of distributed health record systems by enabling rapid data retrieval with reduced computational overhead and without sacrificing diagnostic accuracy. Exhaustive scanning of a full electronic health record for all possible supporting evidence imposes substantial computational and network burdens and introduces latency that is incompatible with real-time documentation and decision-making by a provider. By prioritizing the extraction of high-value primary patient indicators within strictly defined target sampling windows, the system satisfies evidentiary sufficiency requirements while avoiding processing of redundant or irrelevant historical data. The system thus ensures that the provider portal receives a diagnostically comprehensive but computationally lean notification, thereby reducing bandwidth utilization and minimizing latency during time-critical clinical encounters... the claimed method provides a specific technical solution to processing electronic health records, reducing unnecessary computation and data transmission, and real-time presentation of diagnostically-relevant patient data… The instant Office Action does not specifically address any of the dependent Claims in terms of patent-ineligibility despite the requirement”; and
“The system thus improves computational efficiency by avoiding exhaustive scanning of large electronic health records, such as during a time-constrained patient encounter. More specifically, the system filters the corpus of patient data by timestamp to isolate only data captured within target sampling windows defined by primary target indicators, rather than retrieving all historical patient data. The system then scans only this temporally-filtered patient data for primary patient indicators. This temporal filtering immediately constrains the search space, reducing database query execution time and memory consumption by preventing unnecessary retrieval of irrelevant historical data (e.g., data captured years prior to the current encounter). The system then conditionally expands the patient record search only when primary evidence is insufficient by (e.g., upon predicting an acceptance score below a threshold score): filtering the corpus again by timestamp using different sampling windows defined by secondary target indicators; and scanning this second, distinct subset for secondary patient indicators. By conditionally expanding this patient record search, the system prevents unnecessary secondary queries when primary evidence alone suffices, thereby conserving computational resources (e.g., CPU cycles, memory, disk I/O)… the amended claims improve computer capabilities by reducing the amount of data the system must retrieve, evaluate, and transmit in order to surface diagnostically-relevant evidence in real time. Furthermore, the system reduces network resource consumption across a network of provider portals concurrently accessing patient records stored in remote or cloud-based EHR systems. More specifically, exhaustive scanning of patient records would require repeated retrieval and transmission of large volumes of patient data across multiple instances of the provider portal (i.e., when multiple providers simultaneously query different patient records). Thus, by limiting data retrieval to candidate portions of the EHR that are relevant to the provider-entered diagnosis, the system reduces the volume of patient data requested, transferred, and processed across the network, thereby reducing the amount of patient data transmitted over the network and minimizing network-related latency experienced at the provider portal (e.g., during an ongoing patient encounter). Additionally, the system reduces computational resources allocated to retrieval and transmission of patient data by transmitting selectively extracted subsets of supporting evidence, rather than unfiltered or complete patient records to the provider portal. In particular, the system generates provider-facing notifications populated only with patient indicators determined to support the diagnosis, rather than transmitting all candidate patient data evaluated during record scanning, thereby reducing size and frequency of data payloads transmitted to provider devices, decreasing network congestion, and avoiding unnecessary data transfer that does not contribute to diagnostic support. Accordingly, Applicant respectfully submits that the amended claims recite significantly more than an abstract idea. The claimed method provides specific improvements to computational efficiency by: filtering patient data by timestamp to limit data access and processing, thereby reducing database query time and memory consumption; implementing conditional query logic that suppresses unnecessary secondary data retrieval when primary indicators suffice, thereby conserving computational resources; and minimizing network resource consumption by transmitting only selectively extracted supporting evidence rather than complete patient records, thereby reducing bandwidth utilization across distributed provider portals. These limitations impose meaningful constraints on computer implementation by specifying how the system selectively accesses, filters, evaluates, and transmits patient data based on relevance, temporal constraints, and evidentiary sufficiency.”
It is respectfully submitted that Examiner has considered Applicant’s arguments and does not find them persuasive. Examiner has attempted to address all of the arguments presented by Applicant; however, any arguments inadvertently not addressed are not persuasive for at least the following reasons:
In response to Applicant’s argument that (a) regarding the 101 rejections,
“the Examiner has ignored and/or not addressed the claimed execution logic that governs how a computer system accesses, evaluates, and presents patient data from large, heterogeneous electronic health records under real-time constraints. In particular, the Examiner has failed to address how the following technical elements of the Claims and/or fail to integrate the Claims into a practical application: " selectively limiting which portions of a patient's electronic health record are accessed based on relevance to a provider-entered diagnosis; " prioritizing higher-value supporting indicators before initiating additional data access and processing; " conditionally expanding record analysis only when initial evidence is insufficient to support the diagnosis; and " presenting only selectively identified supporting indicators to the provider portal. In particular, the system defines distinct target sampling windows for individual indicators to isolate a specific subset of patient data captured within a defined time period preceding the encounter, thereby reducing the search space of the database (see at least paragraphs [0048] and [0073] of the originally-filed application). Additionally, the system implements a diagnostic model with a set of tiered evidence, such that the computer system identifies a primary target indicator supporting the diagnosis independent of secondary indicators and only evaluates the secondary indicators dependent on the presence (or absence) of the primary tier (see at least paragraphs [0046] and [0047] of the originally-filed application). Furthermore, the system presents only selectively identified supporting indicators to the provider to reduce data transfer payloads and minimize network-related latency (see at least paragraphs [0026] and [0076] of the originally-filed application) and thus reduce computational resources allocated to surfacing patient data and note generation. A system executing the Claims can therefore apply a specific execution strategy that limits unnecessary data access and processing, including: " limiting record access to candidate portions of a patient's electronic health record (or "EHR") relevant to a provider-entered diagnosis; " suppressing unnecessary data retrieval when evidentiary sufficiency is already established; and " transmitting only selectively extracted subsets of patient indicators to the provider portal. Accordingly, the system provides an improvement to the technical functioning of distributed health record systems by enabling rapid data retrieval with reduced computational overhead and without sacrificing diagnostic accuracy. Exhaustive scanning of a full electronic health record for all possible supporting evidence imposes substantial computational and network burdens and introduces latency that is incompatible with real-time documentation and decision-making by a provider. By prioritizing the extraction of high-value primary patient indicators within strictly defined target sampling windows, the system satisfies evidentiary sufficiency requirements while avoiding processing of redundant or irrelevant historical data. The system thus ensures that the provider portal receives a diagnostically comprehensive but computationally lean notification, thereby reducing bandwidth utilization and minimizing latency during time-critical clinical encounters... the claimed method provides a specific technical solution to processing electronic health records, reducing unnecessary computation and data transmission, and real-time presentation of diagnostically-relevant patient data… The instant Office Action does not specifically address any of the dependent Claims in terms of patent-ineligibility despite the requirement”:
It is respectfully submitted that Applicant argues “the Examiner has ignored and/or not addressed the claimed execution logic that governs how a computer system accesses, evaluates, and presents patient data from large, heterogeneous electronic health records under real-time constraints. In particular, the Examiner has failed to address how the following technical elements of the Claims and/or fail to integrate the Claims into a practical application: " selectively limiting which portions of a patient's electronic health record are accessed based on relevance to a provider-entered diagnosis; " prioritizing higher-value supporting indicators before initiating additional data access and processing; " conditionally expanding record analysis only when initial evidence is insufficient to support the diagnosis; and " presenting only selectively identified supporting indicators to the provider portal.” However, as stated previously in Office Action dated 10/16/2025 and updated above, the claim limitations to which Applicant seem to refer as “the claimed execution logic that governs how a computer system accesses, evaluates, and presents patient data from large, heterogeneous electronic health records under real-time constraints” and “" selectively limiting which portions of a patient's electronic health record are accessed based on relevance to a provider-entered diagnosis; " prioritizing higher-value supporting indicators before initiating additional data access and processing; " conditionally expanding record analysis only when initial evidence is insufficient to support the diagnosis; and " presenting only selectively identified supporting indicators to the provider portal” are interpreted as rules or instructions to collect data (i.e., related to a patient), analyze the collected data, and output relevant information (i.e., related to a diagnosis) for a user (i.e., doctor) accordingly, which is the abstract idea, and not additional elements to be interpreted in Step 2A, Prong Two.
Applicant argues “In particular, the system defines distinct target sampling windows for individual indicators to isolate a specific subset of patient data captured within a defined time period preceding the encounter, thereby reducing the search space of the database (see at least paragraphs [0048] and [0073] of the originally-filed application). Additionally, the system implements a diagnostic model with a set of tiered evidence, such that the computer system identifies a primary target indicator supporting the diagnosis independent of secondary indicators and only evaluates the secondary indicators dependent on the presence (or absence) of the primary tier (see at least paragraphs [0046] and [0047] of the originally-filed application). Furthermore, the system presents only selectively identified supporting indicators to the provider to reduce data transfer payloads and minimize network-related latency (see at least paragraphs [0026] and [0076] of the originally-filed application) and thus reduce computational resources allocated to surfacing patient data and note generation. A system executing the Claims can therefore apply a specific execution strategy that limits unnecessary data access and processing, including: " limiting record access to candidate portions of a patient's electronic health record (or "EHR") relevant to a provider-entered diagnosis; " suppressing unnecessary data retrieval when evidentiary sufficiency is already established; and " transmitting only selectively extracted subsets of patient indicators to the provider portal.” However, the claim limitations to which Applicant seem to refer as “distinct target sampling windows for individual indicators to isolate a specific subset of patient data captured within a defined time period preceding the encounter,” “a diagnostic model with a set of tiered evidence, such that the computer system identifies a primary target indicator supporting the diagnosis independent of secondary indicators and only evaluates the secondary indicators dependent on the presence (or absence) of the primary tier,” “presents only selectively identified supporting indicators to the provider,” “" limiting record access to candidate portions of a patient's electronic health record (or "EHR") relevant to a provider-entered diagnosis; " suppressing unnecessary data retrieval when evidentiary sufficiency is already established; and " transmitting only selectively extracted subsets of patient indicators to the provider portal” are interpreted as rules or instructions to collect data (i.e., related to a patient), analyze the collected data, and output relevant information (i.e., related to a diagnosis) for a user (i.e., doctor) accordingly, which is the abstract idea, and not additional elements to be interpreted in Step 2A, Prong Two. Even if the claims provide the alleged improvements of “reducing the search space of the database,” “reduce data transfer payloads and minimize network-related latency…and thus reduce computational resources allocated to surfacing patient data and note generation,” “limits unnecessary data access and processing,” any alleged benefits of the invention are at best, an improvement to the abstract idea (i.e., rules or instructions to collect data (i.e., related to a patient), analyze the collected data, and output relevant information (i.e., related to a diagnosis) for a user (i.e., doctor) accordingly). However, an improved abstract idea is still an abstract idea.
Furthermore, the computing system, which per broadest reasonable interpretation of the claim in light of the specification, is a well-known, general purpose computer, did not cause the argued problem and thus it is not a technical problem caused by the technological environment to which the claims are confined. While the specification need not explicitly set forth the improvement, the disclosure does not provide sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing any technical improvement or any physical improvement to the computer. See MPEP § 2106.04(d)(1) and 2106.05(a). The specification only mentions “reduce resources (e.g., time) dedicated by the provider generating the provider note and therefore increase resources available for the provider to dedicate to patient care” (¶ 0026); “reducing costs to the patient due to an unaccepted provider note; and reducing resources dedicated in generating the provider note and/or implementing post-hoc corrections due to an unaccepted provider note” (¶ 0097; ¶ 00120)), which addresses an administrative problem, and not a technical problem to any specific devices, technology, or computers for that matter, and thus, the claims do not provide a technical solution.
Applicant argues “the system provides an improvement to the technical functioning of distributed health record systems by enabling rapid data retrieval with reduced computational overhead and without sacrificing diagnostic accuracy. Exhaustive scanning of a full electronic health record for all possible supporting evidence imposes substantial computational and network burdens and introduces latency that is incompatible with real-time documentation and decision-making by a provider. By prioritizing the extraction of high-value primary patient indicators within strictly defined target sampling windows, the system satisfies evidentiary sufficiency requirements while avoiding processing of redundant or irrelevant historical data. The system thus ensures that the provider portal receives a diagnostically comprehensive but computationally lean notification, thereby reducing bandwidth utilization and minimizing latency during time-critical clinical encounters... the claimed method provides a specific technical solution to processing electronic health records, reducing unnecessary computation and data transmission, and real-time presentation of diagnostically-relevant patient data.” However, as stated previously above, the computing system, which per broadest reasonable interpretation of the claim in light of the specification, is a well-known, general purpose computer, did not cause the argued problem and thus it is not a technical problem caused by the technological environment to which the claims are confined. While the specification need not explicitly set forth the improvement, the disclosure does not provide sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing any technical improvement or any physical improvement to the computer. See MPEP § 2106.04(d)(1) and 2106.05(a). The specification only mentions “reduce resources (e.g., time) dedicated by the provider generating the provider note and therefore increase resources available for the provider to dedicate to patient care” (¶ 0026); “reducing costs to the patient due to an unaccepted provider note; and reducing resources dedicated in generating the provider note and/or implementing post-hoc corrections due to an unaccepted provider note” (¶ 0097; ¶ 00120)), which addresses an administrative problem, and not a technical problem to any specific devices, technology, or computers for that matter, and thus, the claims do not provide a technical solution.
Furthermore, as stated previously above, the claim limitations to which Applicant seem to refer as providing the alleged improvements are interpreted as rules or instructions to collect data (i.e., related to a patient), analyze the collected data, and output relevant information (i.e., related to a diagnosis) for a user (i.e., doctor) accordingly, which is the abstract idea, and not additional elements to be interpreted in Step 2A, Prong Two. Even if the claims provide the alleged improvements, any alleged benefits of the invention are at best, an improvement to the abstract idea (i.e., rules or instructions to collect data (i.e., related to a patient), analyze the collected data, and output relevant information (i.e., related to a diagnosis) for a user (i.e., doctor) accordingly). However, an improved abstract idea is still an abstract idea.
Applicant argues “The instant Office Action does not specifically address any of the dependent Claims in terms of patent-ineligibility despite the requirement.” However, as stated previously in Office Action dated 10/16/2025 and updated above:
Dependent claims 4-15, 17-19 include all the limitations of the parent claims and further elaborate on the abstract idea discussed above and incorporated herein.
Claims 4-6, 10-15, 17-19 further define the analysis and organization of data for the performance of the abstract idea and do not recite any additional elements. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements individually. Thus, the claims do not integrate the abstract idea into a practical application and do not provide “significantly more.”
Claims 7-9 further recites the additional elements of “a data packet,” which amounts to no more than mere instructions to apply the exception using generic computer components, and only generally links the claimed invention to a particular technological environment or field of use (i.e., computer technology), which does not impose meaningful limits on the scope of the claim. Also, functional limitations further define the analysis and organization of data for the performance of the abstract idea. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements individually. Thus, the additional elements do not integrate the abstract idea into a practical application and do not provide “significantly more.”
Although the dependent claims add additional limitations, they only serve to further limit the abstract idea by reciting limitations on what the information is and how it is received and used. These information characteristics do not change the fundamental analogy to the abstract idea grouping of “Certain Methods of Organizing Human Activity,” and, when viewed individually or as a whole, they do not add anything substantial beyond the abstract idea. Furthermore, the combination of elements does not indicate a significant improvement to the functioning of a computer or any other technology. Therefore, the claims when taken as a whole are ineligible for the same reasons as the independent claims.
Thus, the claims are directed to an abstract idea and the claim as a whole does not integrate the recited judicial exception into a practical application.
“The system thus improves computational efficiency by avoiding exhaustive scanning of large electronic health records, such as during a time-constrained patient encounter. More specifically, the system filters the corpus of patient data by timestamp to isolate only data captured within target sampling windows defined by primary target indicators, rather than retrieving all historical patient data. The system then scans only this temporally-filtered patient data for primary patient indicators. This temporal filtering immediately constrains the search space, reducing database query execution time and memory consumption by preventing unnecessary retrieval of irrelevant historical data (e.g., data captured years prior to the current encounter). The system then conditionally expands the patient record search only when primary evidence is insufficient by (e.g., upon predicting an acceptance score below a threshold score): filtering the corpus again by timestamp using different sampling windows defined by secondary target indicators; and scanning this second, distinct subset for secondary patient indicators. By conditionally expanding this patient record search, the system prevents unnecessary secondary queries when primary evidence alone suffices, thereby conserving computational resources (e.g., CPU cycles, memory, disk I/O)… the amended claims improve computer capabilities by reducing the amount of data the system must retrieve, evaluate, and transmit in order to surface diagnostically-relevant evidence in real time. Furthermore, the system reduces network resource consumption across a network of provider portals concurrently accessing patient records stored in remote or cloud-based EHR systems. More specifically, exhaustive scanning of patient records would require repeated retrieval and transmission of large volumes of patient data across multiple instances of the provider portal (i.e., when multiple providers simultaneously query different patient records). Thus, by limiting data retrieval to candidate portions of the EHR that are relevant to the provider-entered diagnosis, the system reduces the volume of patient data requested, transferred, and processed across the network, thereby reducing the amount of patient data transmitted over the network and minimizing network-related latency experienced at the provider portal (e.g., during an ongoing patient encounter). Additionally, the system reduces computational resources allocated to retrieval and transmission of patient data by transmitting selectively extracted subsets of supporting evidence, rather than unfiltered or complete patient records to the provider portal. In particular, the system generates provider-facing notifications populated only with patient indicators determined to support the diagnosis, rather than transmitting all candidate patient data evaluated during record scanning, thereby reducing size and frequency of data payloads transmitted to provider devices, decreasing network congestion, and avoiding unnecessary data transfer that does not contribute to diagnostic support. Accordingly, Applicant respectfully submits that the amended claims recite significantly more than an abstract idea. The claimed method provides specific improvements to computational efficiency by: filtering patient data by timestamp to limit data access and processing, thereby reducing database query time and memory consumption; implementing conditional query logic that suppresses unnecessary secondary data retrieval when primary indicators suffice, thereby conserving computational resources; and minimizing network resource consumption by transmitting only selectively extracted supporting evidence rather than complete patient records, thereby reducing bandwidth utilization across distributed provider portals. These limitations impose meaningful constraints on computer implementation by specifying how the system selectively accesses, filters, evaluates, and transmits patient data based on relevance, temporal constraints, and evidentiary sufficiency”:
Applicant argues “The system thus improves computational efficiency by avoiding exhaustive scanning of large electronic health records, such as during a time-constrained patient encounter. More specifically, the system filters the corpus of patient data by timestamp to isolate only data captured within target sampling windows defined by primary target indicators, rather than retrieving all historical patient data. The system then scans only this temporally-filtered patient data for primary patient indicators. This temporal filtering immediately constrains the search space, reducing database query execution time and memory consumption by preventing unnecessary retrieval of irrelevant historical data (e.g., data captured years prior to the current encounter). The system then conditionally expands the patient record search only when primary evidence is insufficient by (e.g., upon predicting an acceptance score below a threshold score): filtering the corpus again by timestamp using different sampling windows defined by secondary target indicators; and scanning this second, distinct subset for secondary patient indicators. By conditionally expanding this patient record search, the system prevents unnecessary secondary queries when primary evidence alone suffices, thereby conserving computational resources (e.g., CPU cycles, memory, disk I/O)… the amended claims improve computer capabilities by reducing the amount of data the system must retrieve, evaluate, and transmit in order to surface diagnostically-relevant evidence in real time. Furthermore, the system reduces network resource consumption across a network of provider portals concurrently accessing patient records stored in remote or cloud-based EHR systems. More specifically, exhaustive scanning of patient records would require repeated retrieval and transmission of large volumes of patient data across multiple instances of the provider portal (i.e., when multiple providers simultaneously query different patient records). Thus, by limiting data retrieval to candidate portions of the EHR that are relevant to the provider-entered diagnosis, the system reduces the volume of patient data requested, transferred, and processed across the network, thereby reducing the amount of patient data transmitted over the network and minimizing network-related latency experienced at the provider portal (e.g., during an ongoing patient encounter). Additionally, the system reduces computational resources allocated to retrieval and transmission of patient data by transmitting selectively extracted subsets of supporting evidence, rather than unfiltered or complete patient records to the provider portal. In particular, the system generates provider-facing notifications populated only with patient indicators determined to support the diagnosis, rather than transmitting all candidate patient data evaluated during record scanning, thereby reducing size and frequency of data payloads transmitted to provider devices, decreasing network congestion, and avoiding unnecessary data transfer that does not contribute to diagnostic support. Accordingly, Applicant respectfully submits that the amended claims recite significantly more than an abstract idea. The claimed method provides specific improvements to computational efficiency by: filtering patient data by timestamp to limit data access and processing, thereby reducing database query time and memory consumption; implementing conditional query logic that suppresses unnecessary secondary data retrieval when primary indicators suffice, thereby conserving computational resources; and minimizing network resource consumption by transmitting only selectively extracted supporting evidence rather than complete patient records, thereby reducing bandwidth utilization across distributed provider portals. These limitations impose meaningful constraints on computer implementation by specifying how the system selectively accesses, filters, evaluates, and transmits patient data based on relevance, temporal constraints, and evidentiary sufficiency.” However, the claim limitations to which Applicant seem to refer as providing the alleged improvements are interpreted as rules or instructions to collect data (i.e., related to a patient), analyze the collected data, and output relevant information (i.e., related to a diagnosis) for a user (i.e., doctor) accordingly, which is the abstract idea, and not additional elements to be interpreted in Step 2B. Even if the claims provide the alleged improvements, any alleged benefits of the invention are at best, an improvement to the abstract idea (i.e., rules or instructions to collect data (i.e., related to a patient), analyze the collected data, and output relevant information (i.e., related to a diagnosis) for a user (i.e., doctor) accordingly). However, an improved abstract idea is still an abstract idea.
Furthermore, as stated previously above, the computing system, which per broadest reasonable interpretation of the claim in light of the specification, is a well-known, general purpose computer, did not cause the argued problem and thus it is not a technical problem caused by the technological environment to which the claims are confined. While the specification need not explicitly set forth the improvement, the disclosure does not provide sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing any technical improvement or any physical improvement to the computer. See MPEP § 2106.04(d)(1) and 2106.05(a). The specification only mentions “reduce resources (e.g., time) dedicated by the provider generating the provider note and therefore increase resources available for the provider to dedicate to patient care” (¶ 0026); “reducing costs to the patient due to an unaccepted provider note; and reducing resources dedicated in generating the provider note and/or implementing post-hoc corrections due to an unaccepted provider note” (¶ 0097; ¶ 00120)), which addresses an administrative problem, and not a technical problem to any specific devices, technology, or computers for that matter, and thus, the claims do not provide a technical solution.
Thus, the claim as a whole does not amount to significantly more than the judicial exception.
Thus, Examiner maintains the 101 rejections of claims 1, 4-21, which have been updated to address Applicant’s remarks and to comply with the 2019 Revised Patent Subject Matter Eligibility Guidance and the 2024 Guidance Update on Patent Subject Matter Eligibility, Including on Artificial Intelligence in the above Office Action.
Conclusion
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 extension fee 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 date of this final action.
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/EMILY HUYNH/Primary Examiner, Art Unit 3683
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