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 .
Status
This action is in response to applicant’s amendment filed on 2/05/2026. Claims 1-20 are pending. Claim 1 is amended. No claims have been added. No claims have been cancelled. Claims 11-20 have been withdrawn. Claims 1-10 are examined below.
Election/Restrictions
Claims 11-20 are withdrawn from further consideration pursuant to 37 CFR 1.142(b), as being drawn to a nonelected invention, there being no allowable generic or linking claim. Applicant timely traversed the restriction (election) requirement in the reply filed on 9/26/2025.
Response to Arguments
Applicant's arguments filed 2/5/2026 have been fully considered but they are not persuasive. The applicant has argued the previous 101 rejection. The applicant has argued “Here, the rejection under §101 is founded on the grouping of allegedly mental processes which are concluded to be abstract ideas, but the Applicants disagree. The claims at issue are directed to concepts which are not merely mental processes, and which include requirements which cannot practically be performed in the human mind. For instance, engage in dynamic communication between the patient, a referring entity, and the healthcare provider through at least one communication channel, wherein the at least one communication channel is adjustable based on previous communications between the patient, the referring entity, and the healthcare provider. Similarly, the human mind cannot practically obtain feedback from at least one of the healthcare provider and patient, wherein the feedback comprises at least one of a treatment outcome, a diagnosis, a treatment plan, or a follow-up action, dispatch the feedback to an originating entity and to output a report on an outcome of the patient referral, and update the EHR of the patient with the report. Just as in Example 39, the claims encompass at least one requirement that cannot be practically performed in the human mind. Thus, while some individual requirements of the claims may involve an abstract idea, or can allegedly be performed in the human mind, other requirements-and the claim as a whole-is not directed to, nor recites, an abstract idea. Thus, claim 1 as a whole, should be found to not be directed to an abstract idea under Step 2A.” The examiner respectfully disagrees. Applicant’s claimed invention is directed to receiving a referral, analyzing patient information, selecting a provider, scheduling nan appointment, communicating with parties, and generating a feedback report. All of these steps are fundamentally methods of organizing human activity which has historically been done by humans. The additional language of how communication is routed or adjusted does not transform the claim away from the abstract concept of organizing and managing healthcare referral workflows. The use of a computer is as tool used to perform the steps of the invention. USPTO Example 39 involves claims where at least one requirement cannot be performed in the human mind. The non-mental step was not merely used as a tool to carry out an otherwise abstract workflow. Claim 1 does not specify how the communication channel is adjusted, specifically what algorithm or mechanism determines channel selection, or how the technology involved in the EHR is being updated. The limitations are claimed at a high level of generality. The mere recitation of a communication channel does not take the claim outside the realm of abstract ideas. When evaluating the claim as a whole the claim is directed to automating the management of patient referrals. The Courts have consistently held that adding a computer to an abstract concept does not remove the claim from the abstract idea analysis.
The applicant has argued “Further, USPTO Example 42 distinguishes claims involving abstract ideas integrated into a practical application. Example 42's claim limitation of "training the neural network in a first stage using the first training set" recites a method of organizing human activity. Analyzed under Step 2A - Prong 2, however, "the claim recites a combination of additional elements including storing information ... converting updated information that was input by a user in a non- standardized form to a standardized format." Under this analysis, "[t]he claim as a whole integrates the method of organizing human activity into a practical application. Specifically, the additional elements recite a specific improvement over prior art systems by allowing remote users to share information in real time in a standardized format regardless of the format in which the information was input by the user" (emphasis added).” The examiner respectfully disagrees. In Example 42 the claimed improvement was specifically directed to a technical improvement in how data is stored and converted, which improved the functioning of the database system itself. Applicant amendments to claim 1 do not describe a specific technical improvement to a computer system or its underlying architecture. The added limitations describe improvements to the referral management process itself, not to the functioning of the computer technology implementing it. The claim uses generic computing components to perform the abstract idea.
The applicant has argued “Additionally, in the present case, the mere fact that the claimed invention is used for managing patient referrals does not mean that the invention is directed to a fundamental economic practice or a practice of organizing human activity, nor does it negate the fact that the present invention provides a technical solution to a technical problem of comprehensive digital record keeping in the medical field. Rather, the present invention identifies technical areas in medical referrals to automate the entire process and update EHR records in real time based on dynamic communication and feedback inputs from the patient, healthcare provider, and referring entity. Moreover, this solution is not merely academic. It provides a specific benefit over the prior art in the field. As discussed in the background of the subject application, "The traditional process of patient referrals is often manual, involving paper forms, phone calls, and fax machines. This can lead to delays, lost information, and inefficiencies. The traditional methods of patient referral are riddled with inefficiencies, such as time-consuming manual procedures, unclear correspondence, and delays in scheduling, which ultimately lead to patient discontent and an excessive administrative load on medical professionals. The process is vital for ensuring continuity of care, particularly when patients need specialized services that their current provider cannot offer." (Para. [0002]).” The examiner respectfully disagrees. Automating a previously manual referral workflow does not constitute a technical solution to a technical problem. The fact that patient referrals were historically managed through paper forms does not mean that digitizing and automating the workflow constitutes a technical improvement to computer technology. It merely means that the abstract concept of managing referrals has been applied using a computer which is generic computing equipment, not a technical advance in computing itself. The applicant has characterized the technical problem as “comprehensive digital record keeping in a medical field.” However, the problem identified in paragraph 2 of applicant’s specification is the delays, lost information, unclear correspondence, scheduling inefficiencies, and administrative burden. All of these identified problems are fundamentally organizational and administrative problems, not problems rooted in the computer technology itself.
“To overcome this problem, as explained in the application, an intake module, processing module, scheduling module, and feedback module can extract, analyze, and process comprehensive patient information, provide tailored communication between the patient, healthcare provider, and referring entity, and obtain feedback from at least one of the patient and healthcare provider to output an outcome report and update an EHR system. Thus, for at least the same reason as claim 1 of example 42 was found to be eligible, claim 1 of the present application should likewise be found to be eligible under §101. Moreover, even if these processing steps were attempted to be performed mentally, it would not be practical for a human mind to perform these steps, especially "engage in dynamic communication between the patient, a referring entity, and the healthcare provider through at least one communication channel, wherein the at least one communication channel is adjustable based on previous communications between the patient, the referring entity, and the healthcare provider," as required by claim 1. The mental process grouping should not be expanded in a manner that encompasses claim limitations that cannot practically be performed in the human mind.” The examiner respectfully disagrees. The claimed technology is not being improved. The claimed technology is merely a tool that is used in its normal capacity to implement the steps of the abstract idea. Example 42 was found eligible because it recited a specific technical improvement was found in the way the claims recited how this conversion was technically accomplished. The claim in Example 42 specified the technical means by which the function was achieved in a way that improved the computers functionality. Example 42 included specific structural and operational details that constituted a technical improvement over prior systems. Applicant’s claim 1 recites only the results of the claimed modules’ operation at a high level of generality. Applicant’s invention is merely using general technology as a tool to perform the steps of the invention. The claim as a whole is directed to the abstract idea of organizing healthcare referral workflows which is directed to certain methods of organizing human activity using general purpose computers as a tool to perform the steps of the invention.
The applicant has argued “In this case, the technology of the healthcare sector deals with challenges in the patient referral process, including delays in scheduling, unclear correspondence, and poor communication through inefficient phone calls and fax machines. The specification of the application as-filed describes, "[m]anual processes are time-consuming, leading to delays in patient care. Handwritten notes and verbal communications are prone to errors and miscommunication. Paper documents can be lost or misplaced, resulting in lost information. Poor communication between referring and receiving providers can lead to fragmented care." (Para. [0002]). Like the training strategy in Desjardins, which trained the model to preserve performance on earlier tasks even as it learns new ones, the present application directly addresses the technical problem in the respective field. This is reflected in claim 1, which requires "... a feedback module configured to obtain feedback from at least one of the healthcare provider and patient, wherein the feedback comprises at least one of a treatment outcome, a diagnosis, a treatment plan, or a follow-up action, dispatch the feedback to an originating entity and to output a report on an outcome of the patient referral, and update the EHR of the patient with the report."” The examiner respectfully disagrees. The eligibility findings in Enfish and Desjardins were because the claimed inventions addressed technical problems that were internal to the function of the computer system, not problems arising from human workflows that they systems were designed to support. In Enfish the technical problem was a specific deficiency in how computer databases structured and accessed data. The self-referential database improved the computer’s own storage and retrieval capabilities. In Desjardins, the technical problem was the deficiency of conventional machine learning models in retaining performance on earlier tasks while learning new owns. In Desjardins the improvement was to the technical functioning of the machine learning system, the AI architecture itself. Applicant’s invention does not improve how computers store, process, retrieve, or communicate data. It describes what information should be collected, where it should be sent, and were it should be stored. The Kim Memo confirms that the relevant inquiry focuses on whether the claims improve computer technology, and not whether they improve a particular application domain using computers. The problems identified by the applicant identified in the specification are organizational and administrative in nature, arising from the inefficiencies of manual referral management processes rather than from any deficiency in computing technology. The claims do not recite a specific technical mechanism by which any technology is improved but instead apply generic modules to carry out an existing human administrative workflow. The previous 101 rejection is maintained and updated in view of applicant’s amendments.
Applicant’s arguments with respect to the 103 rejection of claim(s) 1 have been considered but are moot because the applicant has amended the claims to include additional limitations that required further search and consideration.
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 1-10 are rejected under 35 USC 101 because the claimed invention is directed to a judicial exception (i.e. abstract idea) without anything significantly more.
Step 1: Claims 1-10 are directed to a system. Therefore, claims 1-10 are directed to patent eligible categories of invention.
Step 2A, Prong 1: Claim 1 recites a patient referral management system, constituting an abstract idea based on “Certain Methods of Organizing Human Activity” related to managing personal behavior or interactions between individuals including social activities. Claim 1 recites abstract limitations including “A system for standalone automated patient referral management, the system comprising; …configured to accept and process a patient referral from a referral communication channel and to retrieve patient information of a patient; … configured to analyze patient information to pinpoint a healthcare provider based on at least one of a requirement and a preference of the patient, and a schedule availability of the healthcare provider; … configured to schedule an appointment and to engage in dynamic communication between the patient, a referring entity, and the healthcare provider; obtain feedback from at least one of the healthcare provider and patient, wherein the feedback comprises at least one of a treatment outcome, a diagnosis, a treatment plan, or a follow-up action… and … configured to dispatch feedback to an originating entity and to output a report on an outcome of the patient referral, and update the records of the patient with the report.” These limitations, as drafted, is a process that, under its broadest reasonable interpretation, but for the language of “using at least one processor,” covers an abstract idea but for the recitation of generic computer components. That is, other than reciting “using at least one processor,” nothing in the claim elements preclude the steps from being interpreted as an abstract idea. For example, with the exception of the “using the at least one processor” language, the claim steps in the context of the claim encompass an abstract idea directed to a “mental process” and “Certain Methods of Organizing Human Activity.”
Dependent claims 8 further narrow the abstract idea identified in the independent claims and do not introduce further additional elements for consideration.
Dependent claims 2-7, 9-10, will be evaluated under Step 2A, Prong 2 below.
Step 2A, Prong 2: Independent claim 1 does not integrate the judicial exception into a practical application. Claim 1 is a system comprising “a computerized device having at least one non-transitory memory and at least one processor capable of executing instructions stored in the memory, an intake module, a processing module, a scheduling module…through at least one communication channel, wherein the at least one communication channel is adjustable based on previous communications between the patient, the referring entity, and the healthcare provider, a feedback module, update the EHR.” These additional elements are mere instructions to implement an abstract idea using a computer in its ordinary capacity, or merely uses the computer as a tool to perform the identified abstract idea. Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to accept, process, schedule, and configure data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., certain methods of organizing human activity) does not integrate a judicial exception into a practical application. See MPEP 2106.05(f).
Therefore, the additional elements of the independent claims, when considered both individually and in combination, are not sufficient to prove integration into a practical application.
Dependent claims 8 further narrow the abstract idea identified in the independent claims and do not introduce further additional elements for consideration, which does not integrate the judicial exception into a practical application.
Dependent claim 2 introduces the additional element of “wherein the intake module further comprises a natural language processing (NLP) module.” Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to extract, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., certain methods of organizing human activity) does not integrate a judicial exception into a practical application. See MPEP 2106.05(f).
Dependent claim 3 introduces the additional element of “wherein the intake module further comprises a healthcare provider interaction module.” Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., certain methods of organizing human activity) does not integrate a judicial exception into a practical application. See MPEP 2106.05(f).
Dependent claim 4 introduces the additional element of “wherein the processing module leverages real-time data.” Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., certain methods of organizing human activity) does not integrate a judicial exception into a practical application. See MPEP 2106.05(f).
Dependent claim 5 introduces the additional element of “wherein an Al Virtual Healthcare Assistant uses NLP to interpret and process natural language to extract and process.” This limitation does not integrate the judicial exception into a practical application because it is nothing more than generally linking the use of the judicial exception to a particular technological environment. See MPEP 2106.05(h). Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., certain methods of organizing human activity) does not integrate a judicial exception into a practical application. See MPEP 2106.05(f).
Dependent claim 6 introduces the additional element of “wherein the Al Virtual Healthcare Assistant further comprises a data store module, an external source module, and a recognition module having a text-to-speech conversion sub-module configured to deliver medical information.” Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., certain methods of organizing human activity) does not integrate a judicial exception into a practical application. See MPEP 2106.05(f).
Dependent claim 7 introduces the additional element of “further comprising a learning and adaptation module.” Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., certain methods of organizing human activity) does not integrate a judicial exception into a practical application. See MPEP 2106.05(f).
Dependent claim 9 introduces the additional element of “wherein the scheduling module is configured to arrange an appointment through natural language communication.” Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., certain methods of organizing human activity) does not integrate a judicial exception into a practical application. See MPEP 2106.05(f).
Dependent claim 10 introduces the additional element of “wherein the feedback module further comprises an integrated feedback loop configured to communicate with an EHR system.” Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., certain methods of organizing human activity) does not integrate a judicial exception into a practical application. See MPEP 2106.05(f).
Therefore, the additional elements of the dependent claims, when considered both individually and in the context of the independent claims, are not sufficient to prove integration into a practical application.
Step 2B: Independent claim 1 does not comprise anything significantly more than the judicial exception. As can be seen above with respect to Step 2A, Prong 2, Claim 1 is a system comprising “a computerized device having at least one non-transitory memory and at least one processor capable of executing instructions stored in the memory, an intake module, a processing module, a scheduling module…through at least one communication channel, wherein the at least one communication channel is adjustable based on previous communications between the patient, the referring entity, and the healthcare provider, a feedback module, update the EHR.” These additional elements are mere instructions to implement an abstract idea using a computer in its ordinary capacity, or merely uses the computer as a tool to perform the identified abstract idea. Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., certain methods of organizing human activity) is not anything significantly more than the judicial exception. See MPEP 2106.05(f).
The additional elements of the independent claims, when considered both individually and in combination, do not comprise anything significantly more than the judicial exception.
Dependent claim 8 further narrows the abstract idea identified in the independent claims and do not introduce further additional elements for consideration, which is not anything significantly more than the judicial exception.
Dependent claim 2 introduces the additional element of “wherein the intake module further comprises a natural language processing (NLP) module.” Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., certain methods of organizing human activity) is not anything significantly more than the judicial exception. See MPEP 2106.05(f).
Dependent claim 3 introduces the additional element of “wherein the intake module further comprises a healthcare provider interaction module.” Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., certain methods of organizing human activity) is not anything significantly more than the judicial exception. See MPEP 2106.05(f).
Dependent claim 4 introduces the additional element of “wherein the processing module leverages real-time data.” Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., certain methods of organizing human activity) is not anything significantly more than the judicial exception. See MPEP 2106.05(f).
Dependent claim 5 introduces the additional element of “wherein an Al Virtual Healthcare Assistant uses NLP to interpret and process natural language to extract and process.” This limitation is not anything significantly more than the judicial exception because it is nothing more than generally linking the use of the judicial exception to a particular technological environment. See MPEP 2106.05(h). Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., certain methods of organizing human activity) is not anything significantly more than the judicial exception. See MPEP 2106.05(f).
Dependent claim 6 introduces the additional element of “wherein the Al Virtual Healthcare Assistant further comprises a data store module, an external source module, and a recognition module having a text-to-speech conversion sub-module configured to deliver medical information.” Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., certain methods of organizing human activity) is not anything significantly more than the judicial exception. See MPEP 2106.05(f).
Dependent claim 7 introduces the additional element of “further comprising a learning and adaptation module.” Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., certain methods of organizing human activity) is not anything significantly more than the judicial exception. See MPEP 2106.05(f).
Dependent claim 9 introduces the additional element of “wherein the scheduling module is configured to arrange an appointment through natural language communication.” Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., certain methods of organizing human activity) is not anything significantly more than the judicial exception. See MPEP 2106.05(f).
Dependent claim 10 introduces the additional element of “wherein the feedback module further comprises an integrated feedback loop configured to communicate with an EHR system.” Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., certain methods of organizing human activity) is not anything significantly more than the judicial exception. See MPEP 2106.05(f).
The additional elements of the dependent claims, when considered both individually and in the context of the independent claims, are not anything significantly more than the judicial exception.
Accordingly, claims 1-10 are rejected under 35 USC 101.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-10 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1 recites the limitation “update the EHR.” There is insufficient antecedent basis for this limitation in the claim.
The dependent claims inherit the rejections of the claims from which they depend.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Linares et al. (US 12451237 B2) in view of McGarvey et al. (US 20200020454 A1).
Regarding claim 1, Linares teaches an automated patient referral management (col. 7, lines 15-30, disclose that the system provides a referral to a provider.);
a computerized device having at least one non-transitory memory and at least one processor capable of executing instructions stored in the memory (Fig. 5, discloses the technical structure of the system. Col. 10, line 47- col. 11, line 45);
an intake module configured to accept and process a patient referral from a referral communication channel and to retrieve patient information of a patient (col. 3, lines 35-47, discloses the referral communication channel. The chatbot receives all the information. Col. 5, lines 1-41, discloses the chatbot back-end selects one or more health practitioners. It also discloses patient information. col. 7, lines 15-30, disclose that the system provides a referral to a provider. Col. 9, line 45 – col. 10, line 21 discloses the process of referral and retrieving patient information.);
a processing module configured to analyze patient information to pinpoint a healthcare provider based on at least one of a requirement and a preference of the patient, and a schedule availability of the healthcare provider (Col. 9, line 37 – col. 10, line 21 discloses the process of referral and retrieving patient information, checking preferences, and scheduling an appointment based on availability. col. 8, lines 1-11 discloses schedule availability details. Col. 7, lines 15-30, col. 5, line 25-41, col. 6, lines 1-40, Fig. 2A-2B);
a scheduling module configured to schedule an appointment and to engage in dynamic communication between the patient, a referring entity, and the healthcare provider through at least one communication module (col. 2, lines 62-65, disclose communications between a patient, a chatbot, and the provider. Col. 3, lines 37-47, col. 5, line 55- col. 6, line 7, col. 8, lines 1-64, all disclose various methods of communicating and scheduling appointments. Fig. 4).
Linares does not specifically teach wherein the at least one communication channel is adjustable based on previous communications between the patient, the referring entity, and the healthcare provider.
However, McGarvey teaches wherein the at least one communication channel is adjustable based on previous communications between the patient, the referring entity, and the healthcare provider (Fig. 4, 8, ¶ 63, discloses that the messaging tool is integrated into the users profile page. ¶ 55, 59, 67-69, discloses that the network communications platform is multi-modal and various provider relationships. ¶ 33, 78, 87).
It would have been obvious to one of ordinary skill in the art at the time of filing to modify Linares to include/perform wherein the at least one communication channel is adjustable based on previous communications between the patient, the referring entity, and the healthcare provider, as taught/suggested by McGarvey. This known technique is applicable to the system of Linares as they both share characteristics and capabilities, namely, they are directed to the matching of providers to those in need of services. One of ordinary skill in the art would have recognized that applying the known technique of McGarvey would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of McGarvey to the teachings of Linares would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such communication features into similar systems. Further, applying wherein the at least one communication channel is adjustable based on previous communications between the patient, the referring entity, and the healthcare provider would have been recognized by those of ordinary skill in the art as resulting in an improved system that would allow the system the ability to provide the best mode of communication to the user.
Linares does not specifically teach feedback.
However, McGarvey teaches
a feedback module configured to obtain feedback from at least one of the healthcare provider and patient, wherein the feedback comprises at least one of a treatment outcome, a diagnosis, a treatment plan, or a follow-up action (¶ 87-88, discloses obtaining feedback from patient provider interactions comprising clinical outcome data including treatment outcome, a diagnosis, a treatment plan, or a follow-up action. ¶ 33, 53, 55, 78);
dispatch feedback to an originating entity and to output a report on an outcome of the patient referral (¶ 45, discloses a provider patient match process. ¶ 78-79, 87-90, disclose the use of feedback for the match learning process).
It would have been obvious to one of ordinary skill in the art at the time of filing to modify Linares to include/perform dispatching feedback, as taught/suggested by McGarvey. This known technique is applicable to the system of Linares as they both share characteristics and capabilities, namely, they are directed to the matching of providers to those in need of services. One of ordinary skill in the art would have recognized that applying the known technique of McGarvey would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of McGarvey to the teachings of Linares would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such feedback features into similar systems. Further, applying dispatching feedback would have been recognized by those of ordinary skill in the art as resulting in an improved system that would allow the system the ability to check how accurate or pertinent the referrals are.
Linares teaches records of the patient (col. 6, lines 41-50, Fig. 2A, col. 5, lines 31-50)
Linares does not specifically teach updating the electronic records. However, McGarvey teaches update the EHR of the patient with the report (¶ 67, 94, 95, 103, disclose updating the electronic medical records.)
It would have been obvious to one of ordinary skill in the art at the time of filing to modify Linares to include/perform update the EHR of the patient with the report, as taught/suggested by McGarvey. This known technique is applicable to the system of Linares as they both share characteristics and capabilities, namely, they are directed to the matching of providers to those in need of services. One of ordinary skill in the art would have recognized that applying the known technique of McGarvey would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of McGarvey to the teachings of Linares would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such EHR features into similar systems. Further, applying update the EHR of the patient with the report would have been recognized by those of ordinary skill in the art as resulting in an improved system that would allow the system the ability to keep and report the most up to date information.
Regarding claim 2, Linares teaches wherein the intake module further comprises a natural language processing (NLP) module configured to extract, from conversational speech, at least one of a patient demographic, a clinical procedure, and an insurance detail (col. 3, lines 17-26, disclose the use of NPL with the chatbot. Col. 4, lines 4-15, disclose using natural language to derive meaning from interaction with a user. Col. 6, lines 15-31, disclose using a natural language description of systems. Col. 8,lines 45-52, disclose that the input is a natural language communication.).
Regarding claim 3, Linares teaches wherein the intake module further comprises a healthcare provider interaction module configured to accept the patient referral from the referring entity and to communicate with the patient to arrange an appointment based on both the preference of the patient and a scheduling constraint of the healthcare provider (col. 3, lines 35-47, discloses the referral communication channel. The chatbot receives all the information. Col. 5, lines 25-41, discloses the chatbot back-end selects one or more health practitioners. It also discloses patient information. col. 7, lines 15-30, disclose that the system provides a referral to a provider. Col. 9, line 45 – col. 10, line 21 discloses the process of referral and retrieving patient information. col. 2, lines 62-65, col. 5, line 55- col. 6, line 7, col. 8, lines 1-42, all disclose various methods of communicating and scheduling appointments. Fig. 4).
Regarding claim 4, Linares teaches wherein the processing module leverages real-time data from at least one of an electronic health record (EHR) and a directory to facilitate a match between the patient and the healthcare provider (col. 7, lines 30-63, discloses a virtual health system that matches a patient condition, insurance, and preferences with a provider directory. A virtual triage system checks the eligibility of a patient to be cared for by the provider in real-time.)
Regarding claim 5, Linares teaches wherein an Al Virtual Healthcare Assistant uses NLP to interpret and process natural language to extract and process patient information from communication between the patient and at least one of the referring entity and the healthcare provider (col. 3, lines 17-26, disclose the use of NPL with the chatbot. Col. 4, lines 4-15, disclose using natural language to derive meaning from interaction with a user. Col. 6, lines 15-31, disclose using a natural language description of systems. Col. 8,lines 45-52, disclose that the input is a natural language communication. col. 3, lines 35-47, discloses the referral communication channel. The chatbot receives all the information. Col. 5, lines 25-41, discloses the chatbot back-end selects one or more health practitioners. It also discloses patient information.).
Regarding claim 6, Linares teaches wherein the Al Virtual Healthcare Assistant further comprises a data store module, an external source module, to provide an output in a language based on the preference of the patient (col. 6, lines 30-50, col. 9, lines 18-29, disclose data stores as well as external and internal system records. Col. 8, lines 45-65, col. 7, line 15-55, col. 6, lines 16-30, disclose the use of communications).
Linares does not specifically teach a text to speech conversion sub-module.
However, McGarvey teaches a recognition module having a text-to-speech conversion sub-module configured to deliver medical information, to adjust at least one of a speech rate and a pitch, and to provide an output in a language based on the preference of the patient (¶ 8, 84, disclose the use of pitch, ¶ 83, disclose speech features. ¶ 75, 86, discloses output in any appropriate format).
It would have been obvious to one of ordinary skill in the art at the time of filing to modify Linares to include/perform a text to speech conversion sub-module, as taught/suggested by McGarvey. This known technique is applicable to the system of Linares as they both share characteristics and capabilities, namely, they are directed to the matching of providers to those in need of services. One of ordinary skill in the art would have recognized that applying the known technique of McGarvey would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of McGarvey to the teachings of Linares would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such speech features into similar systems. Further, applying a text to speech conversion sub-module would have been recognized by those of ordinary skill in the art as resulting in an improved system that would allow the system the ability to acknowledge and modify the data related to the text and speech.
Regarding claim 7, Linares teaches a learning and adaptation module configured to provide secure access to historical clinical data of the patient to inform and guide a care management protocol (col. 4, line 58 – col. 5, line 3, discloses health related information. Col. 6, lines 41-50, discloses using records to inform and guide. Col. 9, lines 11-18, discloses accessing health data. Col. 6, lines 16-30, disclose secure access to data).
Regarding claim 8, Linares teaches a matching algorithm configured to match the patient with the healthcare provider based on a criterion including at least one of a specialty, the schedule availability of the healthcare provider, and the preference of the patient (col. 2, lines 54-62, discloses matching algorithms to match a patient to a care provider. Col. 5, lines 40-50, discloses using a provider matching service. Col. 7, lines 31-71, discloses matching a patient with a provider based on schedule and specialty. Col. 9, lines 45-56).
Regarding claim 9, Linares teaches wherein the scheduling module is configured to arrange an appointment through natural language communication, and to confirm the appointment with the patient and the healthcare provider (col. 3, lines 17-26, disclose the use of NPL with the chatbot. Col. 4, lines 4-15, disclose using natural language to derive meaning from interaction with a user. Col. 6, lines 15-31, disclose using a natural language description of systems. Col. 8,lines 45-52, disclose that the input is a natural language communication. col. 3, lines 35-47, discloses the referral communication channel. The chatbot receives all the information. Col. 5, lines 25-41, discloses the chatbot back-end selects one or more health practitioners. It also discloses patient information. Col. 8, line 1-43, discloses the confirming of appointments).
Claim(s) 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Linares et al. (US 12451237 B2) in view of McGarvey et al. (US 20200020454 A1) in further view of Perez et al. (US 11875883 B1).
Regarding claim 10, Linares teaches an integrated feedback loop configured to communicate with a system and to provide an update on the patient referral (col. 7, lines 15-30, discloses providing additional data for an updated patient referral).
Linares does not specifically teach the claimed EHR system.
However, Perez teaches wherein the feedback module further comprises an integrated feedback loop configured to communicate with an EHR system and to provide an update on the patient referral (col. 19, lines 4-27, col. 22, lines 3-30, col. 23, lines 15-53, disclose updating a patient’s EHR. Col. 15, lines 25-37, disclose tailoring a need to update a referral).
It would have been obvious to one of ordinary skill in the art at the time of filing to modify Linares to include/perform an EHR system, as taught/suggested by Perez. This known technique is applicable to the system of Linares as they both share characteristics and capabilities, namely, they are directed to manipulation and storage of patient data records. One of ordinary skill in the art would have recognized that applying the known technique of Perez would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Perez to the teachings of Linares would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such an EHR system features into similar systems. Further, applying an EHR system would have been recognized by those of ordinary skill in the art as resulting in an improved system that would allow an improved quality of care through reduced medical errors and better data accuracy.
Other pertinent prior art includes Lin (US 20230080929 A1) which discloses connecting clients and service providers while continuously improving the matching of clients with service providers. Mancine et al. (US 20160147972 A1) which discloses coordinate healthcare referrals, placements, bed assignment, and tracking, particularly between healthcare systems or departments/care units that are disparate and often utilize unrelated, uncoordinated information systems. Chatfield et al. (US 8612261 B1) which discloses determining the medical record interpretation rules that are modified in accordance with a portion of the feedback data.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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JAMIE H. AUSTIN
Examiner
Art Unit 3625
/JAMIE H AUSTIN/Primary Examiner, Art Unit 3625
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