DETAILED ACTION
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . This Office action is in response to Applicant’s communication filed on September 8, 2026. Amendments to claims 1-4, 7-11 and 14-18 have been entered. Claims 1-20 are pending and have been examined. The statement of reasons for the indication of allowable subject matter over prior art was already discussed in the Office action mailed on April 4, 2025 and hence not repeated here. The rejections and response to arguments are stated below.
Claim Rejections - 35 USC § 101
2. 35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
3. Claims 1-20 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to an abstract idea without significantly more.
The claim(s) recite(s) a computer-implemented method for adjusting one or more electronic medical bills for a claimant injured in an accident, which is considered a judicial exception because it falls under the category of “Certain Methods of organizing human activity” such as fundamental economic practice as well as commercial or legal interactions including agreements as discussed below. This judicial exception is not integrated into a practical application as discussed below. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception as discussed below.
Analysis
Step 1: In the instant case, exemplary claim 15 is directed to a method.
Step 2A – Prong One: The limitations of “A computer-implemented method for adjusting one or more electronic medical bills for a claimant injured in an accident, the operations comprising:
training, by a processor of a management platform, a machine learning model with historical electronic medical bills and corresponding historical decisions made on the historical electronic medical bills based on a plurality of decisioning factors;
receiving, by the processor of the management platform, from an insurer system of an insurer through a network, an electronic medical bill comprising data representing medical services provided by a provider;
preprocessing, by the processor of the management platform, the received electronic medical bill, wherein preprocessing the received electronic bill comprises performing an input data transformation on the received electronic bill and extracting information from the electronic medical bill using Optical Character Recognition (OCR) and Natural Language Processing (NLP);
providing, by the processor of a management platform, the preprocessed electronic medical bill as an inference input to the trained machine learning model;
selecting, by the processor of the management platform using the trained machine learning model, in response to the inference input, a workflow from a plurality of the workflows defining further processing of the preprocessed electronic medical bill based on data within the preprocessed electronic medical bill and at least one of the plurality of decisioning factors of the trained machine learning model, the workflows including a provider network workflow and a provider negotiations workflow;
routing, by the processor of the management platform, the preprocessed electronic medical bill to a provider network system, wherein the provider network system adjusts the preprocessed electronic medical bill by adjusting one or more payment amounts in the preprocessed electronic medical bill according to agreed-upon network rates;
receiving, by the processor of the management platform, from the provider network system, the adjusted electronic medical bill; and
transmitting, by the processor of the management platform, the adjusted electronic medical bill to the insurer system” under the broadest reasonable interpretation, considered collectively as an ordered combination, covers methods of organizing human activity such as fundamental economic practice as well as commercial or legal interactions including agreements.
Adjusting one or more electronic medical bills for a claimant is fundamental economic practice such as processing insurance claims.
The steps of “providing, by the processor of a management platform, the preprocessed electronic medical bill as an inference input to the trained machine learning model;
selecting, by the processor of the management platform using the trained machine learning model, in response to the inference input, a workflow from a plurality of the workflows defining further processing of the preprocessed electronic medical bill based on data within the preprocessed electronic medical bill and at least one of the plurality of decisioning factors of the trained machine learning model, the workflows including a provider network workflow and a provider negotiations workflow;
routing, by the processor of the management platform, the preprocessed electronic medical bill to a provider network system, wherein the provider network system adjusts the preprocessed electronic medical bill by adjusting one or more payment amounts in the preprocessed electronic medical bill according to agreed-upon network rates;
receiving, by the processor of the management platform, from the provider network system, the adjusted electronic medical bill; and
transmitting, by the processor of the management platform, the adjusted electronic medical bill to the insurer system” under the broadest reasonable interpretation, considered collectively is a form of fulfilling agreements. Hence, the steps of the claim, considered collectively as an ordered combination without the italicized portions, covers the abstract category of “Certain Methods of organizing human activity”.
That is, other than, one or more hardware processors, a memory comprising instructions stored therein to perform the claimed operations, an insurer system of an insurer, a network, electronic medical bills, a trained machine learning model, the Optical Character Recognition (OCR), the Natural Language Processing (NLP), the provider negotiations system and a provider network system, nothing in the claim precludes the steps from being performed as a method of organizing human activity. If the claim limitations, under the broadest reasonable interpretation, covers methods of organizing human activity 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 claim recites an abstract idea.
Step 2A – Prong Two: The judicial exception is not integrated into a practical application. In particular, the independent claims (1, 8 and 15) only recite the additional elements of one or more hardware processors, a memory comprising instructions stored therein to perform the claimed operations, an insurer system of an insurer, a network, electronic medical bills, a trained machine learning model, the Optical Character Recognition (OCR), the Natural Language Processing (NLP), a provider negotiations system and a provider network system to perform all the steps. A plain reading of Figures 1, 2 and 5 and associated description in at least paragraphs [0072] – [0086] reveals that the one or more hardware processors may be general purpose microprocessors. The memory comprising instructions stored therein is a generic memory suitably programmed to store the associated information/instructions. The insurer system of an insurer, the provider negotiations system and the provider network system are generic systems suitably programmed to perform the associated functions. The network is a generic network suitably programmed to communicate with the associated components. The trained machine learning model, the Optical Character Recognition (OCR), and the Natural Language Processing (NLP) are broadly interpreted to include suitably programmed software to perform the associated functions. The electronic medical bills and one or more non-transitory machine-readable storage media are similarly interpreted to include suitably programmed generic computer components. Hence, the additional elements in the claims are all generic components suitably programmed to perform their respective functions. The additional elements in all the steps are recited at a high-level of generality (i.e., as generic computer components performing generic computer functions) such that it amounts no more than mere instructions to apply the exception using generic computer components. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Hence, claims 1, 8 and 15 are directed to an abstract idea.
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, using the additional elements (identified above) to perform the claimed steps amounts to no more than mere instructions to apply the exception using a generic computer component. The additional elements of the instant underlying process, when taken in combination, together do not offer substantially more than the sum of the functions of the elements when each is taken alone. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Hence, independent claims 1, 8 and 15 are not patent eligible.
Dependent claims 2-7, 9-14 and 16-20, when analyzed as a whole are held to be patent ineligible under 35 U.S.C. 101 because the additional recited limitations only refine the abstract idea further.
For instance, in claims 2, 9 and 16, the steps “wherein the instructions further cause the one or more hardware processors to, responsive to selecting the provider negotiations workflow:
route the preprocessed electronic medical bill to a provider negotiations process, wherein the provider negotiations process adjusts the preprocessed electronic medical bill by adjusting one or more payment amounts in the preprocessed electronic medical bill;
receive, from the provider negotiations system, through the network, the adjusted electronic medical bill; and
transmit the adjusted electronic medical bill to the insurer system through the network” under the broadest reasonable interpretation, are further refinements of methods of organizing human activity because these steps describe the intermediate steps of the underlying process.
In claims 3, 10 and 17, the steps “wherein the instructions further cause the one or more hardware processors to, prior to selecting a workflow:
retrieve, from a rules database, one or more rules established by the insurer; and
adjust the preprocessed electronic medical bill according to the one or more rules” under the broadest reasonable interpretation, are further refinements of methods of organizing human activity because these steps describe the intermediate steps of the underlying process. The additional element of a rules database is broadly interpreted to correspond to generic database suitably programmed to store the associated rules. The additional element of the rules database, performs a traditional function recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using generic computer components.
In claims 4, 11 and 18, the steps “wherein the plurality of decisioning factors comprise at least one of:
a dollar value of charges in the electronic medical bill;
insurance policy coverage of the claimant;
expected turnaround time for processing the preprocessed electronic medical bill; and
historical rates of success in provider negotiations for a type of preprocessed electronic medical bill” under the broadest reasonable interpretation, are further refinements of methods of organizing human activity because these steps describe the data/information used in the intermediate steps of the underlying process.
In claims 5, 12 and 19 the steps “wherein the instructions further cause the one or more hardware processors to:
obtain a training data set comprising the historical electronic medical bills and corresponding historical decisions; and
train the machine learning model using the training data set” under the broadest reasonable interpretation, are further refinements of methods of organizing human activity because these steps describe the data/information used in the intermediate steps of the underlying process.
In claims 6, 13, and 20 the step “wherein the instructions further cause the one or more hardware processors to: generate the training data set” under the broadest reasonable interpretation, is a further refinement of methods of organizing human activity because this step describes an intermediate steps of the underlying process.
In claims 7 and 14, the steps “wherein the instructions further cause the one or more hardware processors to:
determine whether the preprocessed electronic medical bill is eligible for further processing; and
select a workflow only responsive to determining the preprocessed electronic medical bill is eligible for further processing” under the broadest reasonable interpretation, are further refinements of methods of organizing human activity because these steps further describe the intermediate steps of the underlying process.
In all the dependent claims, the judicial exception is not integrated into a practical application because the limitations are recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using generic computer components. Also, the claims do not affect an improvement to another technology or technical field; the claims do not amount to an improvement to the functioning of a computer system itself; the claims do not affect a transformation or reduction of a particular article to a different state or thing; and the claims do not move beyond a general link of the use of an abstract idea to a particular technological environment. In addition, the dependent claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The additional elements of the instant underlying process, when taken in combination, together do not offer substantially more than the sum of the functions of the elements when each is taken alone. The claims as a whole, do not amount to significantly more than the abstract idea itself. For these reasons, the dependent claims also are not patent eligible.
Response to Arguments
4. In response to Applicants arguments on pages 10-17 of the Applicant’s remarks that the claims are patent-eligible under 35 USC 101 when considered under MPEP 2106, the Examiner respectfully disagrees.
The fact that the claims are Patent-Ineligible when considered under the MPEP 2106 has already been addressed in the rejection and the Applicant’s arguments have already been addressed in the rejection and hence not repeated here.
Response to Applicants’ arguments regarding Step 2A – Prong one:
The claims recite a computer-implemented method for adjusting one or more electronic medical bills for a claimant injured in an accident, which is considered a judicial exception because it falls under the category of “Certain Methods of organizing human activity” such as fundamental economic practice as well as commercial or legal interactions including agreements as discussed in the rejection.
Adjusting one or more electronic medical bills for a claimant is fundamental economic practice such as processing insurance claims.
The steps of “providing, by the processor of a management platform, the preprocessed electronic medical bill as an inference input to the trained machine learning model; selecting, by the processor of the management platform using the trained machine learning model, in response to the inference input, a workflow from a plurality of the workflows defining further processing of the preprocessed electronic medical bill based on data within the preprocessed electronic medical bill and at least one of the plurality of decisioning factors of the trained machine learning model, the workflows including a provider network workflow and a provider negotiations workflow; routing, by the processor of the management platform, the preprocessed electronic medical bill to a provider network system, wherein the provider network system adjusts the preprocessed electronic medical bill by adjusting one or more payment amounts in the preprocessed electronic medical bill according to agreed-upon network rates; receiving, by the processor of the management platform, from the provider network system, the adjusted electronic medical bill; and transmitting, by the processor of the management platform, the adjusted electronic medical bill to the insurer system” under the broadest reasonable interpretation, considered collectively is a form of fulfilling agreements such as insurance. Hence, the steps of the claim, considered collectively as an ordered combination without the italicized portions, covers the abstract category of “Certain Methods of organizing human activity”.
The Examiner does not see the parallel between Applicant's claims and those in McRO (McRo, Inc. v. Bandai Namco Games Am., 2015-1080 (Fed. Cir. Sept. 13, 2016)). In McRO the patents relate to “automating part of existing 3D animations of a character’s facial expressions and synchronize those expressions to the actual speech”, which were to be done manually before the issuance of the patent. The claims were directed to a patentable technological improvement over the existing, manual 3D animation techniques by using “limited complex set of rules specifically designed to achieve an improved technological result” thus providing "unconventional" practices than used in a conventional industry practice. Hence the claims in McRo were patent eligible because they recited significantly more than an abstract idea. Such features are not present in the Applicant’s claims.
Whereas the Applicants’ invention is a business solution, using computers, to a problem rooted in an abstract idea. Functions such as “training a machine learning model with historical data and corresponding historical decisions made on the historical data based on a plurality of decisioning factors; receiving additional data; preprocessing the received data, by extracting information from the data using Optical Character Recognition (OCR) and Natural Language Processing (NLP); providing the preprocessed data as an inference input to the trained machine learning model; selecting using the trained machine learning model, in response to the inference input, a workflow further processing of the preprocessed data based on a criteria; routing the preprocessed data to network system, by adjusting the preprocessed data based on a different criteria; receiving, the adjusted data; and transmitting the adjusted data to the another system" are conventional functions of a computer system. In McRo the application of the limited complex set of rules resulted in an improvement of the 3D animation technology. On the other hand, the application of the specific set of rules, in the Applicant’s invention, may at best be considered an improvement in the business solution, using computers, to the problem of adjusting one or more electronic medical bills for a claimant injured in an accident. An improvement in abstract idea is still abstract (SAP America v. Investpic *2-3 (“We may assume that the techniques claimed are “groundbreaking, innovative, or even brilliant,” but that is not enough for eligibility. Association for Molecular Pathology v. Myriad Genetics, Inc., 569 U.S. 576, 591 (2013); accord buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1352 (Fed. Cir. 2014). Nor is it enough for subject-matter eligibility that claimed techniques be novel and nonobvious in light of prior art, passing muster under 35 U.S.C. §§ 102 and 103. See Mayo Collaborative Servs. v. Prometheus Labs., Inc., 566 U.S. 66, 89–90 (2012); Synopsys, Inc. v. Mentor Graphics Corp., 839 F.3d 1138, 1151 (Fed. Cir. 2016) (“A claim for a new abstract idea is still an abstract idea). The additional elements (identified in the claim) are generic computer components used to apply the abstract idea. It does not involve any improvements to another technology, technical field, or improvements to the functioning of the computer itself. Hence, Applicants’ arguments are not persuasive.
Response to Applicants’ arguments regarding Step 2A – Prong two:
According to MPEP 2106, limitations that are indicative of integration into a practical application include:
Improvements to the functioning of a computer, or to any other technology or technical field - see MPEP 2106.05(a)
Applying or using a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition
Applying the judicial exception with, or by use of, a particular machine - see MPEP 2106.05(b)
Effecting a transformation or reduction of a particular article to a different state or thing - see MPEP 2106.05(c)
Applying or using the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception - see MPEP 2106.05(e).
In the instant case, the judicial exception is not integrated into a practical application, because none of the above criteria is met. The independent claims (1, 8 and 15) only recite the additional elements of one or more hardware processors, a memory comprising instructions stored therein to perform the claimed operations, an insurer system of an insurer, a network, electronic medical bills, a trained machine learning model, the Optical Character Recognition (OCR), the Natural Language Processing (NLP), a provider negotiations system and a provider network system to perform all the steps. A plain reading of Figures 1, 2 and 5 and associated description in at least paragraphs [0072] – [0086] reveals that the one or more hardware processors may be general purpose microprocessors. The memory comprising instructions stored therein is a generic memory suitably programmed to store the associated information/ instructions. The insurer system of an insurer, the provider negotiations system and the provider network system are generic systems suitably programmed to perform the associated functions. The network is a generic network suitably programmed to communicate with the associated components. The trained machine learning model, the Optical Character Recognition (OCR), and the Natural Language Processing (NLP) are broadly interpreted to include suitably programmed software to perform the associated functions. The electronic medical bills and one or more non-transitory machine-readable storage media are similarly interpreted to include suitably programmed generic computer components. Hence, the additional elements in the claims are all generic components suitably programmed to perform their respective functions. The additional elements in all the steps are recited at a high-level of generality (i.e., as generic computer components performing generic computer functions) such that it amounts no more than mere instructions to apply the exception using generic computer components. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Hence, the claims are directed to an abstract idea.
Response to Applicants’ arguments regarding Step 2B:
As discussed in the rejection, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, using the additional elements (identified in the rejection) to perform the claimed steps, amount to no more than mere instructions to apply the exception using a generic computer component. The additional elements of the instant underlying process, when taken in combination, together do not offer substantially more than the sum of the functions of the elements when each is taken alone. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Hence, the claims do not recite significantly more than an abstract idea. Therefore, the claims are not patent eligible.
There is a fundamental difference between computer functionality improvements, on the one hand, and uses of existing computers as tools to perform a particular task, on the other. There is nothing, for example, in the pending claims to suggest that the claimed “hardware processors, memory storing instructions, the network, electronic medical bills, the trained machine learning model, the Optical Character Recognition (OCR), the Natural Language Processing (NLP), the provider negotiations system and the provider network system" are somehow made more efficient or that the manner in which these additional elements carry out their basic functions is otherwise improved in any way. The alleged advantages that Applicants tout do not concern an improvement in computer capabilities but instead relate to an alleged improvement in the decisions relating to “training a machine learning model with historical data and corresponding historical decisions made on the historical data based on a plurality of decisioning factors; receiving additional data; preprocessing the received data, by extracting information from the data using Optical Character Recognition (OCR) and Natural Language Processing (NLP); providing the preprocessed data as an inference input to the trained machine learning model; selecting using the trained machine learning model, in response to the inference input, a workflow further processing of the preprocessed data based on a criteria; routing the preprocessed data to network system, by adjusting the preprocessed data based on a different criteria; receiving, the adjusted data; and transmitting the adjusted data to the another system” in the context of adjusting one or more electronic medical bills for a claimant injured in an accident, for which a computer system is used as a tool in its ordinary capacity. The computer system is merely a platform on which the abstract idea is implemented. Therefore, the Applicant's arguments are not persuasive.
For these reasons and those discussed in the rejection, the rejections under 35 USC § 101 are maintained.
Conclusion
5. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
(a) Ketzef; Alon (US Pub. 20230012594 A1) discloses a computerized immediate settlement insurance claim payment system comprising insurance policy issuing functionality for issuing an insurance policy to an insured, and associating the policy with an insurance card to be presented by the insured in association with a card reader to cover the cost of an insurance event, the policy including a chargeback provision allowing the insurer to charge back payments made to the insured via an identified credit card of the insured; automatic insurance claim verification functionality operative to verify the right of the insured to receive payment from the insurer by verifying at least one of the value of the payment, the type and location of the recipient; insurance claim documentation requesting functionality operative to request from the insured documentation of the insured event; and chargeback functionality operative to charge back, in the absence of documentation, at least part of the payment via the identified credit card.
6. 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 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.
Any inquiry concerning this communication or earlier communications from the Examiner should be directed to Narayanswamy Subramanian whose telephone number is (571) 272-6751. The examiner can normally be reached Monday-Friday from 9:00 AM to 5:00 PM. If attempts to reach the examiner by telephone are unsuccessful, the examiner's supervisor, Abhishek Vyas can be reached at (571) 270-1836. The fax number for Formal or Official faxes and Draft to the Patent Office is (571) 273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/Narayanswamy Subramanian/
Primary Examiner
Art Unit 3691
October 13, 2026
