Prosecution Insights
Last updated: October 02, 2026
Application No. 19/056,352

Systems and Methods for Data Record Routing

Final Rejection §101
Filed
Feb 18, 2025
Examiner
GUNN, JEREMY L
Art Unit
3624
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
Optum Inc.
OA Round
2 (Final)
30%
Grant Probability
At Risk
3-4
OA Rounds
1y 6m
Est. Remaining
76%
With Interview

Examiner Intelligence

Grants only 30% of cases
30%
Career Allowance Rate
49 granted / 164 resolved
-22.1% vs TC avg
Strong +46% interview lift
Without
With
+45.8%
Interview Lift
resolved cases with interview
Typical timeline
3y 1m
Avg Prosecution
27 currently pending
Career history
204
Total Applications
across all art units

Statute-Specific Performance

§101
42.1%
+2.1% vs TC avg
§103
36.3%
-3.7% vs TC avg
§102
13.1%
-26.9% vs TC avg
§112
7.3%
-32.7% vs TC avg
Black line = Tech Center average estimate • Based on career data from 164 resolved cases

Office Action

§101
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 . Claims 1-14 and 16-21 have been reviewed and are under consideration by this office action. Notice to Applicant The following is a Final Office action. Applicant, on 06/29/2026, amended claims, cancelled claim 15, and added claim 21. Claims 1-14 and 16-21 are pending in this application and have been rejected below. Response to Amendment Applicant’s amendments are received and acknowledged. The amended claims overcome the 103 Rejection and is therefore withdrawn. Response to Arguments - 35 USC § 101 Applicant’s arguments with respect to the 35 USC 101 rejections have been fully considered, but they are not persuasive. Applicant contends that the amended claims to incorporate updating/training method which “learn to more accurately account for illustration… Applicant further points to the specification. Examiner respectfully disagrees. The updating via a reinforcement learning model is recited at a high level of generality and as such is merely performing the steps would be no more than mere instructions to apply the exception using a generic computer component. See MPEP 2106.05(f) and/or amounts to no more than generally linking the use of the judicial exception to a particular technological environment or field of use – see MPEP 2106.05(h). Applicant further contends the claims provide a technical improvement over conventional systems as increases the probability that a given data record is routed…. accurately. Examiner respectfully disagrees. The cited improvement merely improves upon the abstract idea itself as opposed to improving the technology or technological field. The 101 rejection is updated and maintained below. 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 1-14 and 16-21 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. Step One - First, pursuant to step 1 in the January 2019 Guidance on 84 Fed. Reg. 53, the claim(s) is/are directed to statutory categories. Step 2A, Prong One – The claims are found to recite limitations that set forth the abstract idea(s), namely in independent claims recite a series of steps for the abstract idea recited below. Regarding independent claim(s), (additional elements bolded) A method comprising:/ A system comprising: one or more processors; and one or more memories storing processor-executable instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising:/ One or more non-transitory, computer-readable media storing processor- executable instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising: segmenting, by one or more processors, a plurality of reviewers into a plurality of clusters based at least in part on first respective feature sets associated with the plurality of reviewers; determining, by the one or more processors, label assignments for the plurality of reviewers based at least in part on the segmenting; generating, by the one or more processors, subject-specific performance indicators for the plurality of reviewers based at least in part on second respective feature sets associated with the plurality of reviewers; storing, by the one or more processors, the subject-specific performance indicators in a database; determining, by the one or more processors and using a natural language processing model, a propensity metric for a first data record, the propensity metric being indicative of a probability that the first data record pertains to a particular subject; generating, by the one or more processors, a first routing decision for the first data record, at least in part by applying as input to a routing model (i) the propensity metric, (ii) the subject-specific performance indicators, and (iii) the label assignments; and routing, by the one or more processors and based at least in part on the first routing decision, the first data record to a first reviewer of the plurality of reviewers; receiving, by one or more processors, feedback data indicating whether an action of the first reviewer associated with the first data record is valid; updating, by the one or more processors and via a reinforcement learning technique, one or more of the subject-specific performance indicators stored in the database by applying a reward or a penalty to a subject-specific performance indicator of the first reviewer based at least in part on the feedback data; and generating, by the one or more processors, a second routing decision for a second data record based at least in part on the updated one or more of the subject-specific performance indicators. As drafted, this is, under its broadest reasonable interpretation, within the Abstract idea groupings of “Mental processes—concepts performed in the human mind” (observation, evaluation, judgment, opinion) as the claims are directed towards segmenting reviewers, determining label assignments, generating indicators for reviewers, determining a propensity metric, and generating a routing decision all of which are concepts capable of being performed in the human mind (i.e. via pen and paper). Further the claims are directed towards the abstract idea grouping of “Certain methods of organizing human activity” — commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations) and/or managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions) as the claims are directed towards routing data records to particular reviewers (See Specification, [09]). Step 2A, Prong Two - This judicial exception is not integrated into a practical application. The independent claims utilize at least an additional elements bolded above. The additional elements are performing the steps would be no more than mere instructions to apply the exception using a generic computer component. See MPEP 2106.05(f) and/or amounts to no more than generally linking the use of the judicial exception to a particular technological environment or field of use – see MPEP 2106.05(h). 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, the additional elements are just “apply it” on a computer. (See MPEP 2106.05(f) – Mere Instructions to Apply an Exception – “Thus, for example, claims that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not render an abstract idea eligible.” Alice Corp., 134 S. Ct. at 235) and/or amounts to no more than generally linking the use of the judicial exception to a particular technological environment or field of use – see MPEP 2106.05(h). Regarding Claim(s) 2-14, 16-18, and 21, the claim further narrows the abstract idea or recite additional elements previously addressed in the independent claims (i.e. processor, etc.). Accordingly, the claim fails to recite any improvements to another technology or technical field, improvements to the functioning of the computer itself, use of a particular machine, effecting a transformation or reduction of a particular article to a different state or thing, adding unconventional steps that confine the claim to a particular useful application, and/or meaningful limitations beyond generally linking the use of an abstract idea to a particular environment. See 84 Fed. Reg. 55. Viewed individually or as a whole, these additional claim element(s) do not provide meaningful limitation(s) to transform the abstract idea into a patent eligible application of the abstract idea such that the claim(s) amounts to significantly more than the abstract idea itself. Examining Claims with Respect to Prior Art Claims 1-14 and 16-21, though directed to non-statutory subject matter, are deemed to define over the currently known prior art under 35 USC 102 and 103. Examiner interprets based upon the claim limitations that there is no currently known prior art that discloses the features relating to: “segmenting, by one or more processors, a plurality of reviewers into a plurality of clusters based at least in part on first respective feature sets associated with the plurality of reviewers; determining, by the one or more processors, label assignments for the plurality of reviewers based at least in part on the segmenting; generating, by the one or more processors, subject-specific performance indicators for the plurality of reviewers based at least in part on second respective feature sets associated with the plurality of reviewers; storing, by the one or more processors, the subject-specific performance indicators in a database; determining, by the one or more processors and using a natural language processing model, a propensity metric for a first data record, the propensity metric being indicative of a probability that the first data record pertains to a particular subject; generating, by the one or more processors, a first routing decision for the first data record, at least in part by applying as input to a routing model (i) the propensity metric, (ii) the subject-specific performance indicators, and (iii) the label assignments; [[and]] routing, by the one or more processors and based at least in part on the first routing decision, the first data record to a first reviewer of the plurality of reviewers; receiving, by one or more processors, feedback data indicating whether an action of the first reviewer associated with the first data record is valid; updating, by the one or more processors and via a reinforcement learning technique, one or more of the subject-specific performance indicators stored in the database by applying a reward or a penalty to a subject-specific performance indicator of the first reviewer based at least in part on the feedback data; and generating, by the one or more processors, a second routing decision for a second data record based at least in part on the updated one or more of the subject-specific performance indicators.” The reason to withdraw the 35 USC 103 rejection of claims 1-14 and 16-21 in the instant application is because the prior art of record fails to teach the overall combination as claimed. Therefore, it would not have been obvious to one of ordinary skill in the art to modify the prior art to meet the combination above without unequivocal hindsight and one of ordinary skill would have no reason to do so. Upon further searching the examiner could not identify any prior art to teach these limitations. The prior art on record, alone or in combination, neither anticipates, reasonably teaches, not renders obvious the Applicant’s claimed invention. The closest prior art of record is King et al. et al. (US 20210406805 A1), which teaches: segmenting, by one or more processors, a plurality of reviewers into a plurality of clusters based at least in part on first respective feature sets associated with the plurality of reviewers; determining, by the one or more processors, label assignments for the plurality of reviewers based at least in part on the segmenting; generating, by the one or more processors, subject-specific performance indicators for the plurality of reviewers based at least in part on second respective feature sets associated with the plurality of reviewers; determining, by the one or more processors and using a natural language processing model, a propensity… for a data record, the propensity… being indicative… that the data record pertains to a particular subject; generating, by the one or more processors, a routing decision for the data record, at least in part by applying as input to a routing model (i) the propensity…, (ii) the subject-specific performance indicators, and (iii) the label assignments; but does not teach the limitations as amended. Known Prior Art (patent) US 20210406805 A1 CLAIM ASSIGNMENT SYSTEM US 20230059934 A1 SYSTEM AND METHOD FOR COMPLETION OF AN AUTOMATED TASK SEQUENCE US 20240202620 A1 METHODS AND SYSTEMS FOR GENERATING A LIST OF DIGITAL TASKS US 20110307301 A1 DECISION AID TOOL FOR COMPETENCY ANALYSIS US 20090228309 A1 Method and system for optimizing business process management using mathematical programming techniques US 20200372016 A1 SYSTEMS AND METHODS FOR DETERMINING A COMMUNICATION CHANNEL BASED ON A STATUS OF A NODE PROFILE DETERMINED USING ELECTRONIC ACTIVITIES US 20230119402 A1 MACHINE LEARNING TECHNIQUES FOR CROSS-DOMAIN TEXT CLASSIFICATION US 20200097865 A1 SYSTEM AND METHOD OF WORK ASSIGNMENT MANAGEMENT US 20240193509 A1 SYSTEMS AND METHODS FOR GENERATING WORK SHIFT SCHEDULES Known Prior Art (NPL) P. Aloun, A. Ondrejka and I. Zelinka, "Similarity of Authors' Profiles and Its Usage for Reviewers' Recommendation," 2014 9th International Workshop on Semantic and Social Media Adaptation and Personalization, Corfu, Greece, 2014, pp. 3-8, doi: 10.1109/SMAP.2014.31 Known Prior Art (foreign) KR 102809129 B1 Method and device for providing job information related to an event 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. Any inquiry concerning this communication or earlier communications from the examiner should be directed to JEREMY L GUNN whose telephone number is (571)270-1728. The examiner can normally be reached Monday - Friday 6:30-4:30. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jerry O'Connor can be reached on (571) 272-6787. The fax phone number for the organization where this application or proceeding is assigned 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. /JEREMY L GUNN/ Primary Examiner, Art Unit 3624
Read full office action

Prosecution Timeline

Feb 18, 2025
Application Filed
Apr 03, 2026
Non-Final Rejection mailed — §101
May 14, 2026
Applicant Interview (Telephonic)
May 14, 2026
Examiner Interview Summary
Jun 29, 2026
Response Filed
Aug 19, 2026
Final Rejection mailed — §101
Sep 25, 2026
Examiner Interview Summary
Sep 25, 2026
Applicant Interview (Telephonic)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

3-4
Expected OA Rounds
30%
Grant Probability
76%
With Interview (+45.8%)
3y 1m (~1y 6m remaining)
Median Time to Grant
Moderate
PTA Risk
Based on 164 resolved cases by this examiner. Grant probability derived from career allowance rate.

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