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 .
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 11/05/2025 and 06/10/2026 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner.
Claim Objections
Claim 11 is objected to because of the following informalities:
Claim 11 recites “the medical coding record; [OBJ]” in line 8 when it should most likely recite “the medical coding record;”.
Appropriate correction is required.
Claim Rejections - 35 USC § 112(b)
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 15-16 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 15 recites “wherein generating the contextual information…” Neither claims from which this claim depends from, claims 11 and 13, recite a generating step involving the contextual information. Accordingly, the elaboration upon this generating in claim 15 is unclear as there is no generating occurring up until this point. This claim has been deemed indefinite in view of this lack of clarity.
Claim 16 is rejected based on it’s dependency on claim 15.
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Claims 1-10 are drawn to a system, claims 11-19 are drawn to a method, and claim 20 is drawn to a medium, each of which is within the four statutory categories. Claims 1-20 are further directed to an abstract idea on the grounds set out in detail below. As discussed below, the claims do not include additional elements that are sufficient to amount to significantly more than the abstract idea because the additional computer elements, which are recited at a high level of generality, provide conventional computer functions that do not add meaningful limits to practicing the abstract idea (Step 1: YES).
Step 2A:
Prong One:
Claim 1 recites a system comprising:
a) at least one processor;
b) a computer-readable medium comprising instructions that, when executed by the at least one processor, causes the system to:
1) identify a plurality of edits corresponding to a medical coding record, the plurality of edits being indicative of resolutions to at least one error associated with the medical coding record;
2) analyse the plurality of edits using a code editing model to rank the plurality of edits, c) the code editing model being trained based on the statistical information indicative of relevance of the plurality of edits for resolution of errors associated with the medical coding record; and
3) provide the ranked plurality of edits along with a set of recommended actions for resolution of the error associated with the medical coding record.
Claim 1 recites, in part, performing the steps of 1) identify a plurality of edits corresponding to a medical coding record, the plurality of edits being indicative of resolutions to at least one error associated with the medical coding record, 2) analyse the plurality of edits using a code editing model to rank the plurality of edits, and 3) provide the ranked plurality of edits along with a set of recommended actions for resolution of the error associated with the medical coding record. These steps correspond to Certain Methods of Organizing Human Activity, more particularly, managing personal behavior or relationships or interactions between people (including following rules or instructions). For example, the claim describes providing recommendations to be made based on detecting medical codes with errors which is something a person can do. Independent claim 11 recites similar limitations and is also directed to an abstract idea under the same analysis.
Claim 20 recites a non-transitory computer readable medium comprising computer-readable instructions that when executed cause a processing resource of a computing device to:
1) identify a plurality of edits corresponding to a medical coding record, the plurality of edits being indicative of resolutions to at least one error associated with the medical coding record;
2) analyse the plurality of edits using a code editing model to evaluate the plurality of edits, c) the code editing model being trained based on the statistical information indicative of relevance of the plurality of edits for resolution of errors associated with the medical coding record, wherein to evaluate the plurality of edits, the instructions cause the processing resource to:
2a) compute a confidence score for each of the plurality of edits; and
2b) rank each of the plurality of edits based on the confidence score; and
3) provide the ranked plurality of edits along with a set of recommended actions for resolution of the error associated with the medical coding record.
Claim 20 recites, in part, performing the steps of 1) identify a plurality of edits corresponding to a medical coding record, the plurality of edits being indicative of resolutions to at least one error associated with the medical coding record, 2) analyse the plurality of edits using a code editing model to evaluate the plurality of edits, wherein to evaluate the plurality of edits, the instructions cause the processing resource to: 2a) compute a confidence score for each of the plurality of edits and 2b) rank each of the plurality of edits based on the confidence score, and 3) provide the ranked plurality of edits along with a set of recommended actions for resolution of the error associated with the medical coding record. These steps correspond to Certain Methods of Organizing Human Activity, more particularly, managing personal behavior or relationships or interactions between people (including following rules or instructions). For example, the claim describes providing recommendations to be made based on detecting medical codes with errors which is something a person can do.
Depending claims 2-10 and 12-19 include all of the limitations of claims 1 and 11, and therefore likewise incorporate the above described abstract idea. Depending claims 2 and 12 add abstract limitations from claim 20 to the independent claims from which these depend on; claims 3 and 13 add additional, non-functional details to the claims; and claims 4-10 and 14-19 add additional functional limitations to the claims which are part of the abstract idea. These additional limitations only further serve to limit the abstract idea. Claim 15 adds an additional limitation of using d) natural language processing (NLP) and claims 10 and 19 add the additional element of e) “training the code editing model based on the updated statistical information” and are further assessed below in Step 2A, Prong Two. Thus, depending claims 2-10 and 12-19 are nonetheless directed towards fundamentally the same abstract idea as independent claims 1 and 11 (Step 2A (Prong One): YES).
Prong Two:
This judicial exception is not integrated into a practical application. In particular, the claims recite the additional elements of – using a) at least one processor, b) a computer-readable medium comprising instructions that, when executed by the at least one processor, c) the code editing model being trained based on the statistical information indicative of relevance of the plurality of edits for resolution of errors associated with the medical coding record, and d) natural language processing (NLP) to perform the claimed steps.
The claims also include the additional element step of e) “training the code editing model based on the updated statistical information”.
The a) at least one processor and b) computer-readable medium comprising instructions that, when executed by the at least one processor in these steps are recited at a high-level of generality (i.e., as generic components performing generic computer functions such as determining data from a set of data) such that they amount to no more than mere instructions to apply the exception using generic computer components (see: Applicant’s specification, paragraphs [0021] and [0022] where there is a lack of discussion of anything but what may be considered as generic computing components, see MPEP 2106.05(f)).
Additionally, c) “the code editing model being trained based on the statistical information indicative of relevance of the plurality of edits for resolution of errors associated with the medical coding record” in these steps and the additional element step of e) “training the code editing model based on the updated statistical information” generally link the abstract idea to a particular technological environment or field of use (such as machine learning, see MPEP 2106.05(h)).
Finally, the d) natural language processing (NLP) in these steps generally links the abstract idea to a particular technological environment or field of use (such as NLP, see MPEP 2106.05(h)).
Dependent claims recite additional subject matter which amount to limitations consistent with the additional elements in the independent claims. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation and do not impose a meaningful limit to integrate the abstract idea into a practical application.
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. The claims are directed to an abstract idea (Step 2A (Prong Two): NO).
Step 2B:
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, the additional elements of using a) at least one processor, b) a computer-readable medium comprising instructions that, when executed by the at least one processor, c) “the code editing model being trained based on the statistical information indicative of relevance of the plurality of edits for resolution of errors associated with the medical coding record”, and d) natural language processing (NLP) to perform the claimed steps and using the additional element step of e) “training the code editing model based on the updated statistical information” amounts to no more than a general linking to a particular technological field or mere instructions to apply the exception using generic computer components that do not offer “significantly more” than the abstract idea itself because the claims do not recite an improvement to another technology or technical field, an improvement to the functioning of any computer itself, or provide meaningful limitations beyond generally linking an abstract idea to a particular technological environment. It should be noted that the claims do not include additional elements that amount to significantly more than the judicial exception because the Specification recites mere generic computer components, as discussed above that are being used to apply certain method steps of organizing human activity. Specifically, MPEP 2106.05(f) and MPEP 2106.05(h) recite that the following limitations are not significantly more:
Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, e.g., a limitation indicating that a particular function such as creating and maintaining electronic records is performed by a computer, as discussed in Alice Corp., 134 S. Ct. at 2360, 110 USPQ2d at 1984 (see MPEP § 2106.05(f)); and
Generally linking the use of the judicial exception to a particular technological environment or field of use, e.g., a claim describing how the abstract idea of hedging could be used in the commodities and energy markets, as discussed in Bilski v. Kappos, 561 U.S. 593, 595, 95 USPQ2d 1001, 1010 (2010) or a claim limiting the use of a mathematical formula to the petrochemical and oil-refining fields, as discussed in Parker v. Flook, 437 U.S. 584, 588-90, 198 USPQ 193, 197-98 (1978) (MPEP § 2106.05(h)).
The current invention provides edits utilizing a) at least one processor and b) a computer-readable medium comprising instructions that, when executed by the at least one processor, thus these computing components are adding the words “apply it” with mere instructions to implement the abstract idea on a computer.
Additionally, c) “the code editing model being trained based on the statistical information indicative of relevance of the plurality of edits for resolution of errors associated with the medical coding record” and the additional element step of e) “training the code editing model based on the updated statistical information” generally link the abstract idea to a particular technological environment or field of use. The following represent an example that courts have identified as generally linking the abstract idea to a particular technological environment (e.g. see MPEP 2106.05(h)): Limiting the abstract idea data to a trained model, because limiting application of the abstract idea to machine learning is simply an attempt to limit the use of the abstract idea to a particular technological environment, e.g. see Electric Power Group, LLC v. Alstom S.A.
Lastly, the d) natural language processing (NLP) generally links the abstract idea to a particular technological environment or field of use. The following represent an example that courts have identified as generally linking the abstract idea to a particular technological environment (e.g. see MPEP 2106.05(h)): Limiting the abstract idea data to NLP, because limiting application of the abstract idea to NLP is simply an attempt to limit the use of the abstract idea to a particular technological environment, e.g. see Electric Power Group, LLC v. Alstom S.A.
Mere instructions to apply an exception using generic computer components or, a general linking to a particular technological field cannot provide an inventive concept. The claims are not patent eligible (Step 2B: NO).
Claims 1-20 are therefore rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis 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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
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.
Claims 1-2, 10-12, and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. 2020/0097389 to Smith et al. in view of W.O. 2021/195578 to Chaballout.
As per claim 1, Smith et al. teaches a system comprising:
--at least one processor; (see: paragraph [0028] where there is a processor)
--a computer-readable medium comprising instructions that, when executed by the at least one processor, (see: paragraph [0028] where there is a memory with instructions) causes the system to:
--identify a plurality of edits corresponding to a coding record, (see: paragraph [0068] where a list of sequences (edits) are being identified for errors in code) the plurality of edits being indicative of resolutions to at least one error associated with the coding record; (see: paragraph [0068] where the plurality of edits/sequences are indicative of resolutions to errors in the code/code record)
--analyse the plurality of edits using a code editing model to rank the plurality of edits, (see: paragraph [0068] where there is analysis of suggested change sequences (edits) using a code editing model (a trained machine learning model) to rank the sequences) the code editing model being trained based on the statistical information indicative of relevance of the plurality of edits for resolution of errors associated with the coding record; (see: paragraph [0068] where there is a trained machine learning model (code editing model) based on statistical information (likelihood of selection) indicative of the relevance of the plurality of sequences/edits for resolution of past errors associated with the code) and
--provide the ranked plurality of edits along with a set of recommended actions for resolution of the error associated with the coding record (see: paragraph [0068] where there is display of a ranked list of sequences. A ranked list of edits/sequences is being provided here for resolution of error associated with the code/coding record. Also see: paragraph [0069] where a set of recommended actions including options to share changes, test changes, apply changes, etc.).
Smith et al. may not further, specifically teach:
--coding record as medical coding record.
Chaballout teaches:
--coding record as medical coding record (see: paragraphs [0022] and [0087] where there is display of suggested medical codes).
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to substitute medical coding record as taught by Chaballout for the coding record as disclosed by Smith et al. since each individual element and its function are shown in the prior art, with the difference being the substitution of the elements. In the present case, Smith et al. already teaches of resolving errors in code thus one could replace what errors in what code are being resolved with other types of errors and code and achieve predictable results of resolving code. Thus, one of ordinary skill in the art could have substituted the one known element for the other to produce a predictable result (MPEP 2143).
As per claim 2, Smith et al. and Chaballout in combination teaches the system of claim 1, see discussion of claim 1. Chaballout further teaches wherein to rank the plurality of edits, the at least one processor causes the system to:
--compute a confidence score for each of the plurality of edits; (see: paragraph [0087] where there is computation of confidence scores for each prediction/code/edit) and
--rank each of the plurality of edits based on the confidence score (see: paragraph [0087] where there is ranking of edits (prediction/code) based on the confidence scores).
One of ordinary skill before the effective filing date of the claimed invention would have found it obvious to have wherein to evaluate the plurality of edits, the instructions cause the processing resource to: compute a confidence score for each of the plurality of edits and rank each of the plurality of edits based on the confidence score as taught by Chaballout in the system as taught by Smith et al. with the motivation(s) of improving an outcome for the user (see: paragraph [0032] of Chaballout).
As per claim 10, Smith et al. and Chaballout in combination teaches the system of claim 1, see discussion of claim 1. Smith et al. further teaches wherein the at least one processor further causes the system to:
--receive a user selection of at least one recommended action from the set of recommended actions; (see: paragraph [0069] where there is displaying of an option to apply changes. The selection by the user is received here for at least one recommended action (apply changes))
--update the statistical information to include the user selection of the at least one recommended action for resolution of the error associated with the coding record; (see: paragraph [0076] where there is updating of statistical information (likelihood of selection) based on feedback of selection of an accept or reject button. Also see: paragraph [0037] where there is updating of information) and
--train the code editing model based on the updated statistical information (see: paragraph [0076] where there is training of the machine learning model here based on the updated statistical information (updated likelihood of selection)).
Chaballout teaches:
--coding record as medical coding record (see: paragraphs [0022] and [0087] where there is display of suggested medical codes).
The motivations to combine the above-mentioned references are discussed in the rejection of claim 1, and incorporated herein.
As per claim 11, claim 11 is similar to claim 1 and is therefore rejected in a similar manner.
As per claim 12, claim 12 is similar to claim 2 and is therefore rejected in a similar manner.
As per claim 19, claim 19 is similar to claim 10 and is therefore rejected in a similar manner.
As per claim 20, Smith et al. teaches a non-transitory computer readable medium comprising computer-readable instructions (see: paragraph [0028] where there are instructions on a non-transitory medium) that when executed cause a processing resource of a computing device to:
--identify a plurality of edits corresponding to a coding record, (see: paragraph [0068] where a list of sequences (edits) are being identified for errors in code) the plurality of edits being indicative of resolutions to at least one error associated with the coding record; (see: paragraph [0068] where the plurality of edits/sequences are indicative of resolutions to errors in the code/code record)
--analyse the plurality of edits using a code editing model to evaluate the plurality of edits, (see: paragraph [0068] where there is analysis of suggested change sequences (edits) using a code editing model (a trained machine learning model) to rank the sequences) the code editing model being trained based on the statistical information indicative of relevance of the plurality of edits for resolution of errors associated with the coding record, (see: paragraph [0068] where there is a trained machine learning model (code editing model) based on statistical information (likelihood of selection) indicative of the relevance of the plurality of sequences/edits for resolution of past errors associated with the code)
--provide the ranked plurality of edits along with a set of recommended actions for resolution of the error associated with the coding record (see: paragraph [0068] where there is display of a ranked list of sequences. A ranked list of edits/sequences is being provided here for resolution of error associated with the code/coding record. Also see: paragraph [0069] where a set of recommended actions including options to share changes, test changes, apply changes, etc.).
Smith et al. may not further, specifically teach:
1) --coding record as medical coding record; and
2) --wherein to evaluate the plurality of edits, the instructions cause the processing resource to:
2a) --compute a confidence score for each of the plurality of edits; and
2b) --rank each of the plurality of edits based on the confidence score.
Chaballout teaches:
1) --coding record as medical coding record; (see: paragraphs [0022] and [0087] where there is display of suggested medical codes)
2) --wherein to evaluate the plurality of edits, the instructions cause the processing resource to:
2a) --compute a confidence score for each of the plurality of edits; (see: paragraph [0087] where there is computation of confidence scores for each prediction/code/edit) and
2b) --rank each of the plurality of edits based on the confidence score (see: paragraph [0087] where there is ranking of edits (prediction/code) based on the confidence scores).
One of ordinary skill before the effective filing date of the claimed invention would have found it obvious to have 2) wherein to evaluate the plurality of edits, the instructions cause the processing resource to: 2a) compute a confidence score for each of the plurality of edits and 2b) rank each of the plurality of edits based on the confidence score as taught by Chaballout in the medium as taught by Smith et al. with the motivation(s) of improving an outcome for the user (see: paragraph [0032] of Chaballout).
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to substitute medical coding record as taught by Chaballout for the coding record as disclosed by Smith et al. since each individual element and its function are shown in the prior art, with the difference being the substitution of the elements. In the present case, Smith et al. already teaches of resolving errors in code thus one could replace what errors in what code are being resolved with other types of errors and code and achieve predictable results of resolving code. Thus, one of ordinary skill in the art could have substituted the one known element for the other to produce a predictable result (MPEP 2143).
Claims 3 and 13 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. 2020/0097389 to Smith et al. in view of W.O. 2021/195578 to Chaballout as applied to claims 2 and 11, and further in view of U.S. 2017/0032250 to Chang.
As per claim 3, Smith et al. and Chaballout in combination teaches the system of claim 2, see discussion of claim 2. The combination may not further, specifically teach wherein the statistical information comprises contextual information associated with the plurality of edits, the contextual information including at least one of: a category of the plurality of edits, a severity level of the plurality of edits, an experience level of a coder who created the plurality of edits, a state of resolution indicating whether the plurality of edits led to resolution of the at least one error associated with medical coding record, and a count of utilization of the plurality of edits for resolution of the at least one error associated with medical coding record.
D’Andrea et al. teaches:
--wherein the statistical information comprises contextual information associated with the plurality of edits, the contextual information including at least one of: a category of the plurality of edits, a severity level of the plurality of edits, an experience level of a coder who created the plurality of edits, a state of resolution indicating whether the plurality of edits led to resolution of the at least one error associated with medical coding record, and a count of utilization of the plurality of edits for resolution of the at least one error associated with medical coding record (see: paragraph [0031] where the experience level of a coder (context information) is factored in to the metadata (statistical information)).
One of ordinary skill before the effective filing date of the claimed invention would have found it obvious to have wherein the statistical information comprises contextual information associated with the plurality of edits, the contextual information including at least one of: a category of the plurality of edits, a severity level of the plurality of edits, an experience level of a coder who created the plurality of edits, a state of resolution indicating whether the plurality of edits led to resolution of the at least one error associated with medical coding record, and a count of utilization of the plurality of edits for resolution of the at least one error associated with medical coding record as taught by D’Andrea et al. in the system as taught by Smith et al. and Chaballout in combination with the motivation(s) of achieving reasonable confidence in code quality (see: paragraph [0002] of D’Andrea et al.).
As per claim 13, claim 13 is similar to claim 3 and is therefore rejected in a similar manner.
No Art Rejections
Claims 4-9 and 14-18 do not have art rejections in view of the potential combination of references which could be used to reject these claims being unreasonable combinations.
Additional Relevant References
Examiner would also like to cite U.S. 2020/0226321 to Burns et al., U.S. 2018/0341751 to Lyman et al., U.S. 2004/0003335 to Gertz et al., and U.S. 2017/0032250 to Chang as additional, relevant references.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Steven G.S. Sanghera whose telephone number is (571)272-6873. The examiner can normally be reached M-F 7:30-5:00 (alternating Fri).
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, Shahid Merchant can be reached at 571-270-1360. 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.
/STEVEN G.S. SANGHERA/Primary Examiner, Art Unit 3684
Prosecution Insights