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 1-20 are pending. Claims 6-20 have been withdrawn in view of the restriction requirement. Claims 1-5 are under examination.
Election/Restrictions
Applicant's election with traverse of Invention I in the reply filed on 11/25/2025 is acknowledged. The traversal is on the ground(s) that it would not place an undue search burden on the Examiner to search the subject matter of the claims in the different groups. This is not found persuasive because while the inventions involve patient parameters and event data, they have different utility and would require different search strategy as indicated in the restriction requirement.
The requirement is still deemed proper and is therefore made FINAL.
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 1-5 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 1
Claims 1-5 are drawn to a system for facilitating implementation of a mitigation action, which is within the four statutory categories (i.e. machine).
Step 2A | Prong One
Claim 1 recites a system comprising:
a non-transitory computer-readable medium storing instructions (apply it, MPEP § 2106.05(f) and insignificant extra-solution activity, MPEP § 2106.05(g)); and
a processing device communicatively coupled to the non-transitory computer-readable medium, wherein the processing device is configured to execute the instructions and thereby perform operations (apply it, MPEP § 2106.05(f)) comprising:
receiving a set of patient event data, the set of patient event data including at least one respective instance of a respective patient event experienced by each respective patient of a plurality of patients;
receiving a first set of parameters, the first set of parameters including a respective set of one or more parameters for each respective patient of the plurality of patients that were associated with the respective patient immediately before or while the patient experienced the at least one instance of the respective patient event;
receiving, for a particular patient, a set of particular patient parameters;
processing the first set of parameters, the set of patient event data, and the set of particular patient parameters using at least one of a rules-based model or a machine-learning model to generate a prediction of a future patient event for the particular patient;
receiving, for each respective patient event, respective event mitigation data;
receiving, for each respective patient event, respective event outcome data;
processing the prediction of the future patient event, the respective event mitigation data, and the respective event outcome data to generate a future patient event mitigation recommendation; and
facilitating implementation of a mitigating action defined by the future patient event mitigation recommendation.
The bolded limitations, given the broadest reasonable interpretation, cover a certain method of organizing human activity because it recites fundamental economic practices, commercial or legal interactions, and/or managing personal behavior or relationships or interactions between people. Any limitations not identified above as part of the abstract idea are underlined and are deemed “additional elements,” and will be discussed in further detail below.
Dependent Claims 2-5 include other limitations, for example Claim 2 recites wherein the step of processing the first set of parameters, the set of patient event data, and the set of particular patient parameters comprises: identifying, for each respective patient event, based on a plurality of respective instances of the respective patient event, a subset of patient parameters that are commonly associated with the respective patient event, each of the subset of patient parameters being selected from the first set of parameters; and processing the first set of parameters, the set of patient event data, the subset of patient parameters, and the set of particular patient parameters using at least one of a rules-based model or a machine-learning model to generate the prediction of a future patient event for the particular patient, Claim 3 recites wherein the first set of parameters comprise one or more of a set of medication adherence parameters, a set of bowel movement parameters, a set of exercise parameters, a set of dietary parameters, a set of weight trend parameters, a set of psychological parameters, or a set of fitness tracking device parameters, Claim 4 recites wherein the operations further comprise: identifying a set of potentially mitigating actions for each respective patient event; determining, for each respective potentially mitigating action from the set of potentially mitigating actions, a respective consent requirement; generating a graphical user interface (apply it, MPEP § 2106.05(f)) for soliciting consent, from the particular patient, for each respective potentially mitigating action by configuring the user interface by: including a first set of interface elements that each correspond to a first subset of the set of potentially mitigating actions for which the respective consent requirement includes a requirement for affirmative consent, wherein each interface element of the first set of interface elements is configured to elicit, from the particular patient, the affirmative consent defined by the respective consent requirement for the respective potentially mitigating action; and excluding a second set of interface elements that correspond to a second subset of the set of potentially mitigating actions for which the respective consent requirement does not include the requirement for affirmative consent; and receiving, from the particular patient via the first set of interface elements on the graphical user interface (apply it, MPEP § 2106.05(f)), the affirmative consent for the first subset of potentially mitigating actions, and Claim 5 recites wherein the operations further comprise: determining whether the particular patient has previously provided the affirmative consent for the mitigating action; and in response to determining that the particular patient has previously provided the affirmative consent for the mitigating action, automatically facilitating implementation of the mitigating action without further prompting the particular patient for additional consent, but these only serve to further limit the abstract idea, and hence are nonetheless directed towards fundamentally the same abstract idea as independent Claim 1.
Step 2A | Prong Two
Furthermore, Claims 1-5 are not integrated into a practical application because the additional elements (i.e. the limitations not identified as part of the abstract idea) amount to no more than limitations which:
amount to mere instructions to apply an exception – for example, the recitation of a non-transitory computer-readable medium, a processing device communicatively coupled to the non-transitory computer-readable medium, and a graphical user interface, which amounts to merely invoking a computer as a tool to perform the abstract idea, e.g. see paragraphs [0036], [0085-0086] and [0094] of the present Specification, see MPEP 2106.05(f); and
add insignificant extra-solution activity to the abstract idea – for example, the recitation of storing data, which amounts to an insignificant application, see MPEP 2106.05(g).
Step 2B
Furthermore, the Claims do not include additional elements that are sufficient to amount to “significantly more” than the judicial exception because, the additional elements (i.e. the elements other than the abstract idea) amount to no more than limitations which:
amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields, as demonstrated by:
The Specification expressly disclosing that the additional elements are well-understood, routine, and conventional in nature:
paragraphs [0036], [0085-0086] ad [0094] of the Specification discloses that the additional elements (i.e. non-transitory computer readable medium, processing device, user interface) comprise a plurality of different types of generic computing systems that are configured to perform generic computer functions (i.e. storing data) that are well-understood, routine, and conventional activities previously known to the pertinent industry (i.e. healthcare management);
Relevant court decisions: The following are examples of court decisions demonstrating well-understood, routine and conventional activities, e.g. see MPEP 2106.05(d)(II):
Electronic recordkeeping, e.g. see Alice Corp v. CLS Bank – similarly, the current invention merely recites the storing of program data on a database and/or electronic memory;
Dependent Claims 2-5 include other limitations, but none of these functions are deemed significantly more than the abstract idea because the additional elements recited in the aforementioned dependent claims (the graphical user interface of claim 4) similarly represent no using generic computer components to implement the recited abstract idea.
Thus, taken alone, the additional elements do not amount to “significantly more” than the above-identified abstract idea. Furthermore, looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually, and there is no indication that the combination of elements improves the functioning of a computer or improves any other technology, and their collective functions merely provide conventional computer implementation.
Therefore, whether taken individually or as an ordered combination, Claims 1-5 are nonetheless rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-3 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Cho (U.S. Pub. No. 2022/0369937 A1).
Regarding claim 1, Cho discloses a system comprising:
a non-transitory computer-readable medium storing instructions (Paragraph [0009] discusses a non-transitory computer readable storage medium that comprises instructions.); and
a processing device communicatively coupled to the non-transitory computer-readable medium, wherein the processing device is configured to execute the instructions (Paragraph [0009] discusses a non-transitory computer readable storage medium that comprises instructions and is executed by processing circuitry to implement the invention.) and thereby perform operations comprising:
receiving a set of patient event data, the set of patient event data including at least one respective instance of a respective patient event experienced by each respective patient of a plurality of patients (Paragraphs [0064] and [0068] discuss receiving sensed data, including patient input and EHR data, that indicates the patient may be experiencing an acute health event, such as irregular heart rate event. The rules used for assessing the data could be based on the cohort that the patient belongs.);
receiving a first set of parameters, the first set of parameters including a respective set of one or more parameters for each respective patient of the plurality of patients that were associated with the respective patient immediately before or while the patient experienced the at least one instance of the respective patient event (Paragraph [0108-0109] discusses detection of sudden cardiac arrest or other acute health event can be achieved by looking at a number of possible markers, construed as patient parameters, that occur prior to and during the event.);
receiving, for a particular patient, a set of particular patient parameters (Paragraphs [0027] and [0064] discuss obtaining baseline physiological parameter values, previous health events and treatments, disease states, comorbidities, demographics, height, weight, body mass index, and fitness data, including activity level and exercise minutes, of the patient.);
processing the first set of parameters, the set of patient event data, and the set of particular patient parameters using at least one of a rules-based model or a machine-learning model to generate a prediction of a future patient event for the particular patient (Paragraph [0064] and [0084] discusses determining whether there is a sufficient likelihood that the patient is suffering from an acute health event based on the received data using a rules engine.);
receiving, for each respective patient event, respective event mitigation data (Paragraph [0111] discusses providing patient-specific care recommendations for the acute health event prediction.);
receiving, for each respective patient event, respective event outcome data (Paragraph [0103] discusses receiving feedback for the event, construed as including outcome.);
processing the prediction of the future patient event, the respective event mitigation data, and the respective event outcome data to generate a future patient event mitigation recommendation (Paragraphs [0105] and [0111] discuss using the data to update the rules and making additional recommendations, such as purchasing an AED or Chest Compression System.); and
facilitating implementation of a mitigating action defined by the future patient event mitigation recommendation (Paragraph [0111] discusses providing the recommendations to the caregivers, construed as facilitating implementation.).
Regarding claim 2, Cho discloses wherein the step of processing the first set of parameters, the set of patient event data, and the set of particular patient parameters comprises:
identifying, for each respective patient event, based on a plurality of respective instances of the respective patient event, a subset of patient parameters that are commonly associated with the respective patient event, each of the subset of patient parameters being selected from the first set of parameters (Paragraphs [0064], [0078-0079] [0097], and [0107] discuss different rules for different cohorts for the patient parameters.); and
processing the first set of parameters, the set of patient event data, the subset of patient parameters, and the set of particular patient parameters using at least one of a rules-based model or a machine-learning model to generate the prediction of a future patient event for the particular patient (Paragraphs [0031], [0064] and [0084] discuss determining whether there is a sufficient likelihood that the patient is suffering from an acute health event based on the received data using a rules engine, prior to to event happening.).
Regarding claim 3, Cho discloses wherein the first set of parameters comprise one or more of a set of medication adherence parameters, a set of bowel movement parameters, a set of exercise parameters, a set of dietary parameters, a set of weight trend parameters, a set of psychological parameters, or a set of fitness tracking device parameters (Examiners that only one of the above parameters is required. Paragraphs [0064-0065] discuss the parameters include exercise data of the patient.).
Subject Matter Free from Prior Art
Claims 4 and 5 are free from prior art as the prior art fails to disclose or render obvious the limitations of “excluding a second set of interface elements that correspond to a second subset of the set of potentially mitigating actions for which the respective consent requirement does not include the requirement for affirmative consent” in combination with the other limitations of claim 4. Claim 5 is free from prior art as it depends from claim 4.
The closest reference regarding consent includes Shelton (U.S. Pub. No. 2024/0112770 A1), which discusses obtaining explicit patient consent for access to medical records based on regional requirements (Paragraphs [0156] and [0174]), however, it fails to disclose or render obvious “excluding a second set of interface elements that correspond to a second subset of the set of potentially mitigating actions for which the respective consent requirement does not include the requirement for affirmative consent” as described in claim 4.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Rachelle Reichert whose telephone number is (303)297-4782. The examiner can normally be reached M-F 9-5 MT.
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/RACHELLE L REICHERT/Primary Examiner, Art Unit 3686