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 .
DETAILED ACTION
The present office action represents the first action on the merits.
Claims 1-20 are pending.
Priority
This application claims priority to U.S. Provisional Patent Application No. 63/652,469 dated 28 May 2024.
Information Disclosure Statement
The Information Disclosure Statement(s) (lDS) submitted on 28 May 2025 is/are in compliance with the provisions of 37 CFR 1.97 and has/have been fully considered by the Examiner.
Notice to Applicant
The Examiner notes that the subject matter of Claim 15 does not require performance by a processor (“translatable by a processor”). As such, the computer program product comprising stored instructions represents stored data labels that render the claim obvious in view of any CRM that stores data. This is based on the “printed matter” doctrine which finds that printed matter on a substrate are not given patentable weight; without the processor to perform the steps, the only thing claimed is a CRM with written matter on it. The Examiner strongly suggests reciting “a non-transitory computer-readable medium storing instructions that, when executed by a processor cause the processor to perform:….” In the interest of advancing prosecution, the Examiner has cited prior art references that teach the functionality of the claim as if it were required to occur.
The Examiner notes that the claimed or the current applicant and those of related application 19/221,306 currently do not overlap in scope. The Examiner will reevaluate potential double patenting issues as prosecution proceeds.
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, 8, and 15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1
The claim recites a method, system, and non-transitory computer-readable medium (“CRM”) for information retrieval, which are within a statutory category.
Step 2A1
The limitations of (Claim 1 being representative)
performing for each respective patient of a plurality of prediction-eligible patients of a healthcare provider:
determining, by a first model based on observations of the plurality of prediction-eligible patients, an admit status prediction (ASP) for the respective patient;
determining, by a second model utilizing the ASP and major diagnosis category (MDC) prediction features extracted from patient visits eligible for the ASP, a MDC prediction (MDCP) for the respective patient; and
extracting clinical data for the respective patient;
mapping, utilizing the MDCP, individual clinical data points in the clinical data for the respective patient thus extracted into grouped items; and
generating, a visit summary for the respective patient, the visit summary including the ASP, the MDCP, and an explanation of how the ASP and the MDCP were made based at least on the grouped items
, as drafted, is a process that, under the broadest reasonable interpretation, covers certain methods of organizing human activity (i.e., managing personal behavior including following rules or instructions) but for recitation of generic computer components. The claims encompass a series of rules or instructions for a person or persons to follow, with or without the aid of a computer, to analyze patient data to make predictive outputs and create a summary of the outputs (see Spec. Para. 0002) in the manner described in the identified abstract idea, supra. The rules or instructions are the claimed steps of “performing… determining… extracting… mapping… generating” as indicated supra.
Other than reciting generic computer components (discussed infra), i.e., a methos/system implemented by a computer, the claimed invention amounts to managing personal behavior or interaction between people. If a claim limitation, under its broadest reasonable interpretation, covers managing personal behavior or interactions between people but for the recitation of generic computer components, then it falls within the “certain methods of organizing human activity” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
Step 2A2
This judicial exception is not integrated into a practical application. In particular, the claims recite the additional elements of (Claim 1) a computer having a database and a user interface and user interface elements, (Claim 8) a processor, non-transitory CRM, and a user interface having a user interface element, and (Claim 15) a CRM and processor that implement the identified abstract idea. These items are not described by the applicant and are recited at a high-level of generality (i.e., a generic computer or components thereof performing generic computer functions) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim further recites the additional element of using a first and second machine learning model that determines an ASP and a MDCP, respectively. This represents mere instructions to implement the abstract idea on a generic computer. Implementing an abstract idea using a generic computer or components thereof does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. See, e.g., Recentive Analytics, Inc. v. Fox Corp., No. 2023-2437 at 10 (Fed. Cir. April 18, 2025) (finding that claims that do no more than apply established methods of machine learning to a new data environment are ineligible).
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 element of using a computer or components thereof to perform the noted steps amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept (“significantly more”).
As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a first and second machine learning model that determines an ASP and a MDCP, respectively was found to represent mere instructions to implement the abstract idea on a generic computer and/or confine the use of the abstract idea (i.e., the trained model) to a particular technological environment or field of use. This has been re-evaluated under the “significantly more” analysis and determined to be insufficient to provide significantly more. MPEP 2106.05(I) indicates that mere instructions to implement the abstract idea on a generic computer and/or confining the use of the abstract idea to a particular technological environment or field of use cannot provide significantly more. See also Recentive Analytics, Inc. v. Fox Corp., No. 2023-2437 at 17 (Fed. Cir. April 18, 2025) (finding that applying machine learning to an abstract idea does not transform a claim into something significantly more).
The Examiner takes this opportunity to note that Specification Para. 0134 states that “[i]n general, the functions of the invention can be achieved by any means as is known in the art.” This means that any elements (i.e., addition elements) that perform (“achieve”) the abstraction are admitted by the Applicant to be well-understood, routine, and conventional in the art.
Claims 2-7, 9-14, and 16-20 are similarly rejected because they either further define/narrow the abstract idea and/or do not further limit the claim to a practical application or provide as inventive concept such that the claims are subject matter eligible even when considered individually or as an ordered combination.
Claim(s) 2, 9, 16 merely describe(s) the type of summary, which further defines the abstract idea.
Claim(s) 3, 10, 17 merely describe(s) the content of the explanation, which further defines the abstract idea.
Claim(s) 4, 11 merely describe(s) the content of the summary, which further defines the abstract idea.
Claim(s) 5, 12, 18 merely describe(s) they type of model, which further defines the abstract idea.
The Examiner notes that Spec. Para. 0134 states that the machine learning models are known in the art and are thus well-understood, routine, and conventional in the art.
Claim(s) 6, 13, 19 merely describe(s) the observations, which further defines the abstract idea.
Claim(s) 7, 14, 20 merely describe(s) what is displayed, which further defines the abstract idea.
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 1-20 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 pre-AIA the applicant regards as the invention.
Claim 1 recites “prediction-eligible patients… the plurality of prediction-eligible patients…patient visits eligible for the ASP….” The claim is indefinite because there is no determination as to whether patients are eligible for anything and thus the Examiner is unclear as to how the claim can be met. There appears to be one or more missing steps in the claim rendering it indefinite.
Claim 1 further recites, in the generating step, “a visit summary for the respective patient.” The claim is indefinite because it is unclear what visit the limitation is referring to; no visit is recited. The only other recitation of “visits” is in the second determining step; however, this appears to be past visits prior to the visit discussed in the generating step. Also, these are multiple “visit,” so even assuming the generating step is referring to one of those, it is unclear which visit of the plurality of visits the step is referring to. The Examiner is extremely confused as to what the claim requires.
Claim 1 further recites “generating…a visit summary for the respective patient, the visit summary including the ASP, the MDCP, and an explanation of how the ASP and the MDCP were made based at least on the grouped items.” The claim is indefinite because it is unclear how the “visit summary” can include an “an explanation of how the ASP and the MDCP were made based at least on the grouped items” when the grouped items are not based on the ASP and MDCP. The grouped items are recited to be mapped using the MDCP, not the other way around. Further, the MDCP was determined utilizing the ASP meaning that is existed before the grouping of the items.
The Examiner is very confused as to the scope of the claim and interprets the claim to require: creating a summary/report detailing a prediction as to whether a patient will be admitted / readmitted based on likelihood that patient is deteriorating using data from their EMR detailing past visit information.
Claim(s) 8 and 15 is/are analogous to Claim(s) 1, thus Claim(s) 8 and 15 is/are similarly analyzed and rejected in a manner consistent with the rejection of Claim(s) 1.
By virtue of their dependence from Claim 1, 8, or 15, this basis of rejection also applies to dependent Claims 2-7, 9-14, and 16-20.
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.
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 of this title, 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) 1-5, 7-12, 14-18, and 20 is/are rejected under 35 U.S.C. § 103 as being unpatentable over Mohammad et al. (U.S. Pre-Grant Patent Publication No. 2021/0035693) in view of Nicholas et al. (WIPO Publication No. WO2024/092136).
REGARDING CLAIM 1
As best understood by the Examiner, Mohammad teaches the claimed method, comprising:
performing, by a computer for each respective patient of a plurality of prediction-eligible patients of a healthcare provider: [Para. 0031 teaches that a prediction is made for patients, meaning that the patient is necessarily eligible for the prediction. The Patients are interpreted to be “of a healthcare provider.”]
determining, by a first machine learning model based on observations of the plurality of prediction-eligible patients, an admit status prediction (ASP) for the respective patient; [Para. 0031, 0061 teaches utilizing a random forest classifier (a first machine learning model) to predict hospitalization of a patient (an admit status prediction) using patient data.]
[…];
predict something about the cancer (treatment will be successful?)]
extracting, from a database, clinical data for the respective patient; [0031 patient visit data stored in patient medical database (EHR). 0037 raw data]
mapping, by the computer […], individual clinical data points in the clinical data for the respective patient thus extracted into grouped items; and [Para. 0037, 0040 teaches that raw patient data is divided into subsets and stored.]
generating, by the computer, a visit summary for the respective patient, [Para. 0031, 0054 teaches that a report (visit summary) is generated.] the visit summary including […data…]. [creating a summary/report detailing a prediction as to whether a patient will be admitted / readmitted based on likelihood that current diagnosis will worsen using data from their emr] [Para. 0031, 0054 a report Para. 0033 data collected from EMR Para. 0040 teaches generating data points for each patient in the group of patients.]
Mohammad may not explicitly teach
determining, by a second machine learning model utilizing the ASP and major diagnosis category (MDC) prediction features extracted from patient visits eligible for the ASP, a MDC prediction (MDCP) for the respective patient; and
utilizing the MDCP
As best understood by the Examiner, Nicholas at Para. 0031, 0032, 0048, 0049 teaches that it was known in the art of computerized healthcare, at the time of filing, to predict whether a hospitalized patient’s prognosis by evaluating EMR data using a machine learning model
determining, by a second machine learning model utilizing the ASP and major diagnosis category (MDC) prediction features extracted from patient visits eligible for the ASP, a MDC prediction (MDCP) for the respective patient; and [Para. 0031, 0032, 0048, 0049 teaches that if the patient is hospitalized (the predicted hospitalization of Mohammad), a machine learning model (a second machine learning model) is used to predict the patient’s prognosis (an MDC prediction) based on analysis of the patient’s EMR data (major diagnosis category (MDC) prediction features extracted from patient visits). Para. 0083 teaches that the prediction is applied to cancer.]
utilizing the MDCP [Nickolas at Fig. 2 (line connecting items 270 and 250), Para. 0045, 0049 teaches that the prediction (the MDCP) is used to select patient features (the subset determination of Mohammad). The Examiner notes that there is no claimed indication as to how the MDCP is “utilized” to map data points.]
Therefore, it would have been prima facie obvious to one of ordinary skill in the art of computerized healthcare, at the time of filing, to modify the patient hospitalization predicting and reporting system of Mohammad to predict whether a hospitalized patient’s prognosis will improve or worsen by evaluating EMR data using a machine learning model as taught by Nickolas, with the motivation of improving the calibration of care plans by improving caretaker knowledge (See Nicholas at Para. 0003).
Mohammad/Nicholas may not explicitly teach that the report (of Mohammad) includes
the ASP, the MDCP, and an explanation of how the ASP and the MDCP were made based at least on the grouped items
However, the limitation claims information/labels that do not result in a manipulative difference between the information/labels of the prior art and the functionally of the claimed method. The function taught by the prior art would be performed the same regardless of whether the information/labels was substituted with nothing. Because Mohammad teaches providing a report includes information, substituting the information/labels of the claimed invention for the information/labels of the prior art would be an obvious substitution of one known element for another, producing predictable results. Therefore, would have been prima facie obvious to one of ordinary skill in the art at the time of filing to have substituted the information/labels applied to the stored data of the prior art with any other information/labels because the results would have been predictable.
Mohammad/Nicholas may not explicitly teach may not explicitly teach that the method is performed for multiple patients; however, the performance for multiple patients would have been prima facie obvious to one of ordinary skill in the art at the time of the invention in view of the teaching of Mohammad/Nicholas based on the duplication of parts rationale (see In re Harza, MPEP 2144.04(VI)(B)). Mohammad/Nicholas teaches performing the notes steps for a patient (see basis oof rejection) and that there are multiple patients within the system (see Mohammad at Para. 0029). The application of the recited method to multiple patients produces no new and unexpected result which would result in patentable significance over the teaching of Mohammad/Nicholas; the application of the system of Mohammad/Nicholas to multiple patients does not change how the claim effects the formulation of report.
REGARDING CLAIM 2
As best understood by the Examiner, Mohammad/Nicholas teaches the claimed method of Claim 1. Mohammad/Nicholas further teaches
generating, utilizing the visit summary, a clinical summary in a distributable document format. [Mohammad at Para. 0028 teaches that the report may be distributed using a mobile based reporting system, thus the report is in a distributable document format (see Spec. Para. 0018). The Examiner notes that the claim appears to merely be relabeling the “visit summary” to “clinical summary” as there is no claimed description as to how/what is generated.]
REGARDING CLAIM 3
As best understood by the Examiner, Mohammad/Nicholas teaches the claimed method of Claim 1. Mohammad/Nicholas may not explicitly teach
wherein the explanation comprises a plurality of explanation factors describing the MDC.
However, the limitation claims information/labels that do not result in a manipulative difference between the information/labels of the prior art and the functionally of the claimed method. The function taught by the prior art would be performed the same regardless of whether the information/labels was substituted with nothing. Because Mohammad teaches providing a report includes information, substituting the information/labels of the claimed invention for the information/labels of the prior art would be an obvious substitution of one known element for another, producing predictable results. Therefore, would have been prima facie obvious to one of ordinary skill in the art at the time of filing to have substituted the information/labels applied to the stored data of the prior art with any other information/labels because the results would have been predictable.
REGARDING CLAIM 4
As best understood by the Examiner, Mohammad/Nicholas teaches the claimed method of Claim 1. Mohammad/Nicholas may not explicitly teach
wherein the visit summary further comprises a singleton item.
However, the limitation claims information/labels that do not result in a manipulative difference between the information/labels of the prior art and the functionally of the claimed method. The function taught by the prior art would be performed the same regardless of whether the information/labels was substituted with nothing. Because Mohammad teaches providing a report includes information, substituting the information/labels of the claimed invention for the information/labels of the prior art would be an obvious substitution of one known element for another, producing predictable results. Therefore, would have been prima facie obvious to one of ordinary skill in the art at the time of filing to have substituted the information/labels applied to the stored data of the prior art with any other information/labels because the results would have been predictable.
REGARDING CLAIM 5
As best understood by the Examiner, Mohammad/Nicholas teaches the claimed method of Claim 1. Mohammad/Nicholas further teaches
wherein the first machine learning model comprises a multi-class classifier and [Mohammad at Para. 0048, 0060 teaches that the classifier ised for ASP is a random forest classifier (a multi-class classifier).]
wherein the second machine learning model comprises a binary classifier. [Nicholas at Para. 0033 teaches that the machine learning model is a decision tree ensemble learning algorithm (a binary classifier).]
REGARDING CLAIM 7
As best understood by the Examiner, Mohammad/Nicholas teaches the claimed method of Claim 1. Mohammad/Nicholas further teaches
providing a user interface with a user interface element for editing the visit summary. [Nicholas at Fig. 1, Para. 0039 teaches a user interface that allows for the receipt of user input, which is interpreted as occurring via an icon (user interface element as is ubiquitous in the art). The Examiner notes that “editing the visit summary” is an intended use of the item, which is not required to occur.]
REGARDING CLAIM(S) 8
Claim(s) 8 is/are analogous to Claim(s) 1, thus Claim(s) 8 is/are similarly analyzed and rejected in a manner consistent with the rejection of Claim(s) 1.
Mohammad at Para. 0025 teaches that its functions are performed via a computer having a processor, memory, and programming.
REGARDING CLAIM(S) 9-12 AND 14
Claim(s) 9-12 and 14 is/are analogous to Claim(s) 2-5 and 7, respectively, thus Claim(s) 9-12 and 14 is/are similarly analyzed and rejected in a manner consistent with the rejection of Claim(s) 2-5 and 7.
REGARDING CLAIM(S) 15
Claim(s) 15 is/are analogous to Claim(s) 1 and/or 8, thus Claim(s) 15 is/are similarly analyzed and rejected in a manner consistent with the rejection of Claim(s) 1 and/or 8.
REGARDING CLAIM(S) 16, 17, 18, AND 20
Claim(s) 16-18 and 20 is/are analogous to Claim(s) 2, 3, 5 and 7, respectively, thus Claim(s) 16-18 and 20 is/are similarly analyzed and rejected in a manner consistent with the rejection of Claim(s) 2, 3, 5 and 7.
Claim(s) 6, 13, and 19 is/are rejected under 35 U.S.C. § 103 as being unpatentable over Mohammad et al. (U.S. Pre-Grant Patent Publication No. 2021/0035693) in view of Nicholas et al. (WIPO Publication No. WO2024/092136) in view of Tsang et al. (U.S. Pre-Grant Patent Publication No. 2023/0307136).
REGARDING CLAIM 6
As best understood by the Examiner, Mohammad/Nicholas teaches the claimed method of Claim 1. Mohammad/Nicholas may not explicitly teach
wherein the observations comprise at least one of:
a date when a current status was established,
a date when the current status was changed,
any change in severity of a patient's illness, or
any change in the severity of the patient's symptoms.
Tsang at Para. 0038 teaches that it was known in the art of computerized healthcare, at the time of filing, to utilize evaluate a patient to determine discharge date when predicting readmission
wherein the observations comprise at least one of:
a date when a current status was established, [Tsang at Abstract, Para. 0038 teaches that patient data taken into account when predicting readmission includes discharge date (date when a current status was established; i.e., the patient is currently discharged).]
a date when the current status was changed,
any change in severity of a patient's illness, or
any change in the severity of the patient's symptoms.
It would have been prima facie obvious to one of ordinary skill in the art at the time of filing to combine the discharge date of Tsang with patient data analysis of Mohammad/Nicholas since the combination of the references is merely simple substitution of one known element for another producing a predictable result (KSR B). Since each individual element and its function are shown in the prior art, albeit shown in separate references, the difference between the claimed subject matter and the prior art rests not on any individual element or function but in the very combination itself—that is, in the substitution of the discharge date of Tsang for patient data of Mohammad. Thus, the simple substitution of one known element for another producing a predictable result renders the claim obvious.
REGARDING CLAIM(S) 13 AND 19
Claim(s) 13 and 19 is/are analogous to Claim(s) 6, thus Claim(s) 13 and 19 is/are similarly analyzed and rejected in a manner consistent with the rejection of Claim(s) 6.
Conclusion
Prior art made of record though not relied upon in the present basis of rejection are noted in the attached PTO 892 and include:
Volosin et al. (U.S. Pre-Grant Patent Publication No. 2006/0079752) which discloses performing predictive analysis on ECG signals to determine the current physiological condition of the patient.
Spurlock, III et al. (U.S. Pre-Grant Patent Publication No. 2019/0108912) which discloses using machines learning to discover clinical data patterns predictive of a disease.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JASON S TIEDEMAN whose telephone number is (571)272-4594. The examiner can normally be reached 7:00am-4:00pm, off alternate Fridays.
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/JASON S TIEDEMAN/Primary Examiner, Art Unit 3683
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