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 .
Status of the Claims
Claims 1-15 are currently pending.
Information Disclosure Statement
The information disclosure statements submitted on December 18, 2023 and May 16, 2024 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements have been considered by Examiner.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1-2, 4-5, 9-10, and 12-13 of the present application are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over Claims 1, 4-5, 11, and 14 of copending Application No. 18/544606 (“the ‘606 application”).
Regarding Claim 1 of the present application, Claim 1 of the present application is anticipated by Claim 1 of the ‘606 application, which recites substantially the same limitations as Claim 1 of the present application. For example, Claim 1 of the ‘606 application recites a “likelihood of dropout for the patient” based on a “chronological snapshot of the patient,” wherein the “chronological snapshot” is generated using features extracted from patient records. Hence, the “likelihood of dropout for the patient” recited in Claim 1 of the ‘606 application is equivalent to the “dropout risk score” recited in Claim 1 of the present application. Additionally, the “root dropout cause,” and the “recommended interventions” recited in Claim 1 of the ‘606 application are equivalent to the “potential dropout cause” and “recommended engagement action” recited in Claim 1 of the present application. Hence Claim 1 of the ‘606 application anticipates Claim 1 of the present application.
Regarding Claim 2 of the present application, Claim 2 of the present application is anticipated by Claim 14 of the ‘606 application because Claim 14 of the ‘606 application recites limitations that are equivalent to Claim 2 of the present application, with the exception that Claim 14 of the ‘606 application recites a system, whereas Claim 2 of the present application recites a system. Examiner notes that, as will be explained below, several limitations of Claim 2 require interpretation under 35 U.S.C. 112(f), and hence Claim 2 is interpreted as reciting a method executed by structural components, which is functionally equivalent to a system. Hence, Claim 2 of the present application is anticipated by Claim 14 of the ‘606 application.
Regarding Claims 4-5 of the present application, Claims 4-5 of the present application are anticipated by Claims 4-5 of the ‘606 application because Claims 4-5 of the ‘606 application recite limitations that are equivalent to Claims 4-5 of the present application.
Regarding Claim 9 of the present application, Claim 9 of the present application substantially mirrors the limitations of Claim 1 of the present application with the exception that Claim 1 of the present application recites a method whereas Claim 9 of the present application recites a system. Similarly, Claim 11 of the ‘606 application substantially mirrors Claim 1 of the ‘606 application with the exception that Claim 1 of the ‘606 application recites a method whereas Claim 11 of the ‘606 application recites a system. Therefore, Claim 9 of the present application is similarly rejected under non-statutory, obviousness type double patenting in view of Claim 11 of the ‘606 application for the same reasons as those disclosed above for Claim 1 of the present application
Regarding Claim 10 of the present application, Claim 14 of the ‘606 application recites the claimed limitations of Claim 10 of the present application. Therefore, Claim 10 of the present application is anticipated by Claim 14 of the ‘606 application.
Regarding Claims 12-13 of the present application, Claims 12-13 of the present application are also anticipated by Claims 4-5 of the ‘606 application because Claims 4-5 of the ‘606 application recite limitations that are equivalent to Claims 12-13 of the present application.
Claims 3 and 11 of the present application are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over Claim 1 of the ‘606 application in view of Appelbaum (US 2022/0051773).
Regarding Claim 3 of the present application, Claim 1 of the ‘606 application does not teach but Appelbaum teaches utilizing Tree Shapley Additive Explanation (SHAP) algorithm to generate more interpretable predictions, wherein the SHAP algorithm assigns each explanatory variable an importance value for each prediction, such that it determines which explanatory variables drove a particular prediction, e.g. see Appelbaum [0127]. Furthermore, before the effective filing date, it would have been obvious to one ordinarily skilled in the art of healthcare to modify Claim 1 of the ‘606 application to incorporate the SHAP algorithm as taught by Appelbaum in order to generate more interpretable predictions, e.g. see Appelbaum [0127].
Regarding Claim 11 of the present application, the limitations of Claim 11 of the present application are substantially similar to those claimed in Claim 3 of the present application, with the sole difference being that Claim 3 of the present application recites a method, whereas Claim 11 of the present application recites a system and its associated structural limitations. Hence, the grounds of rejection provided above for Claim 3 of the present application are similarly applied to Claim 11 of the present application.
Claims 6-7 and 15 of the present application are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over Claim 1 of the ‘606 application in view of Baym (US 2015/0112728).
Regarding Claim 6 of the present application, Claim 1 of the ‘606 application does not teach but Baym teaches a threshold specified by an insurer regarding patient adherence to particular activities, wherein the threshold is used in determining whether or not to deny coverage, e.g. see Baym [0058], [0097]-[0098], and [0124]. Furthermore, before the effective filing date, it would have been obvious to one ordinarily skilled in the art of healthcare to modify Claim 1 of the ‘606 application to incorporate the insurance coverage limitations as taught by Baym in order to enable a patient to manage their risk, e.g. see Baym [0054].
Regarding Claim 7 of the present application, Claim 1 of the ‘606 application does not teach but Baym teaches insurer requirements to determine whether the insurer will provide coverage, e.g. see Baym [0058], [0097]-[0098], and [0124]. Furthermore, before the effective filing date, it would have been obvious to one ordinarily skilled in the art of healthcare to modify Claim 1 of the ‘606 application to incorporate the insurance coverage limitations as taught by Baym in order to enable a patient to manage their risk, e.g. see Baym [0054].
Regarding Claim 15 of the present application, the limitations of Claim 15 of the present application are substantially similar to those claimed in Claims 6-7 of the present application, with the sole difference being that Claims 6-7 of the present application recite a method whereas Claim 15 of the present application recites a system performing the functions of Claims 6-7 of the present application. Hence, the grounds of rejection provided above for Claims 6-7 of the present application are similarly applied to Claim 15 of the present application.
Claims 8 and 14 of the present application are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over Claim 1 of the ‘606 application in view of Garcia (US 2021/0134431).
Regarding Claim 8 of the present application, Claim 1 of the ‘606 application does not teach but Garcia teaches determining a concern score for a patient based on at least three to five parameters, wherein the concern score may be used to determine that the patient should belong to a group of patients whose concern score exceeds a threshold, and further wherein the system determines recommended actions for the group of patients whose scores exceed the threshold, e.g. see Garcia [0172]-[0174], [0204], [0208]-[0210], and [0214]-[0215]. Furthermore, before the effective filing date, it would have been obvious to one ordinarily skilled in the art of healthcare to modify Claim 1 of the ‘606 application to incorporate the insurance coverage limitations as taught by Baym in order to enable a patient to manage their risk, e.g. see Baym [0054].
Regarding Claim 14 of the present application, the limitations of Claim 14 of the present application are substantially similar to those claimed in Claim 8 of the present application, with the sole difference being that Claim 8 of the present application recite a method whereas Claim 14 of the present application recites a system performing the functions of Claims 8 of the present application. Hence, the grounds of rejection provided above for Claim 8 of the present application are similarly applied to Claim 14 of the present application.
These are provisional nonstatutory double patenting rejections because the patentably indistinct claims have not in fact been patented.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitations use a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitations are as follows:
“Dropout prediction engine” recited in Claims 1-15;
“Engagement recommendation engine” recited in Claims 1-15;
“Care provider interface” recited in Claims 1-15;
Because these claim limitations are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, they are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitations interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitations to avoid them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitations recite sufficient structure to perform the claimed function so as to avoid them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
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 1-15 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 1-15 are within the four statutory categories. Claims 9-15 are drawn to a system for predicting patient dropout risk, which is within the four statutory categories (i.e. machine). Claims 1-8 are drawn to a method for predicting patient dropout risk, which is within the four statutory categories (i.e. process). Claims *** are drawn to a non-transitory medium for *** which is within the four statutory categories (i.e. manufacture). Claims *** are drawn to a “computer readable medium,” which does not distinguish Claims *** from a transitory medium or article of manufacture, and hence Claims *** do not fall within the four statutory categories. However, as will be shown below, even assuming, arguendo, that Claims *** were directed towards a non-transitory medium or article of manufacture, Claims *** are nonetheless unpatentable under 35 U.S.C. 101.
Prong 1 of Step 2A
Claim 1, which is representative of the inventive concept, recites: A method for predicting dropout risk for a patient under remote monitoring using a dropout prediction system, the method comprising:
obtaining, from an electronic patient records database, a plurality of medical records for a patient under remote monitoring by a care provider;
extracting, from the plurality of medical records for the patient under remote monitoring by the care provider, a plurality of dropout prediction features for the patient;
generating, using a dropout prediction engine, a dropout risk score for the patient based on the plurality of dropout prediction features;
determining, using an engagement recommendation engine, a potential dropout cause based on at least the plurality of dropout prediction features;
determining, using the engagement recommendation engine, a recommended engagement action, wherein the recommended engagement action is intended to prevent dropout of the patient from remote monitoring by the care provider; and
presenting, via a care provider interface, the recommended engagement action to a care team member of the care provider.
The underlined limitations as shown above, given the broadest reasonable interpretation, cover the abstract idea of a certain method of organizing human activity because they recite managing personal behavior or relationships or interactions between people (i.e. social activities, teaching, and following rules or instructions – in this case, the steps of obtaining medical records, extracting dropout prediction features from the medical records, generating a dropout risk score based on the extracted dropout prediction features, determining a potential dropout cause based on the dropout prediction features, determining a recommended engagement action, and presenting the recommended engagement action are reasonably interpreted as following rules or instructions in order to provide a care provider with recommended actions), e.g. see MPEP 2106.04(a)(2). Any limitations not identified above as part of the abstract idea are deemed “additional elements,” and will be discussed in further detail below.
Furthermore, the abstract idea for Claim 9 is identical as the abstract idea for Claim 1, because the only difference between Claims 1 and 9 is that Claim 1 recites a method, whereas Claim 9 recites a system and its associated structural limitations (i.e. processors), which, as will be further explained below, are interpreted as additional elements.
Dependent Claims 2-8 and 10-15 include other limitations, for example Claims 2 and 10 recite utilizing a trained machine learning algorithm to determine the dropout risk score, Claims 3 and 11 recite utilizing a Shapley values algorithm to determine the potential dropout cause, Claims 4-5 and 12-13 recite types of medical records, Claims 6-7 and 15 further define the dropout risk score, and Claims 8 and 14 recite determining a phenotype for the patient based on the dropout prediction features, wherein the recommended engagement action is based on the phenotype, but these only serve to further narrow the abstract idea, and a claim may not preempt abstract ideas, even if the judicial exception is narrow, e.g. see MPEP 2106.04, and/or do not further narrow the abstract idea and instead only recite additional elements, which will be further addressed below. Hence dependent Claims 2-8 and 10-15 are nonetheless directed towards fundamentally the same abstract idea as independent Claims 1 and 9.
Prong 2 of Step 2A
Claims 1 and 9 are not integrated into a practical application because the additional elements (i.e. the non-underlined limitations above – in this case, electronic patient records database, the dropout prediction engine, the engagement recommendation engine, the care provider interface, the one or more processors) amount to no more than limitations which:
amount to mere instructions to apply an exception – for example, the recitation of the electronic patient records database, the dropout prediction engine, the engagement recommendation engine, the care provider interface, the one or more processors, which amounts to merely invoking a computer as a tool to perform the abstract idea, e.g. see pg. 18, line 12 through pg. 19, line 22 of the as-filed Specification, and see MPEP 2106.05(f);
generally link the abstract idea to a particular technological environment or field of use – for example, the claim language reciting that the extracted features from the patient records are dropout prediction features, and the claim language reciting presenting the recommended engagement action to a care provider, which amount to limiting the abstract idea to the field of healthcare, e.g. see MPEP 2106.05(h); and/or
add insignificant extra-solution activity to the abstract idea – for example, the recitation of presenting the recommended engagement action to a care provider, which amounts to an insignificant application, e.g. see MPEP 2106.05(g).
Additionally, dependent Claims 2-8 and 10-15 include other limitations, but these limitations also amount to no more than mere instructions to apply an exception (e.g. the trained machine learning model recited in dependent Claims 2 and 10), generally linking the abstract idea to a particular technological environment or field of use (e.g. the types of patient records recited in dependent Claims 4-5 and 12-13), and/or do not include any additional elements beyond those already recited in independent Claims 1 and 9, and hence also do not integrate the aforementioned abstract idea into a practical application.
Hence Claims 1-15 do not include additional elements that integrate the judicial exception into a practical application.
Step 2B
Claims 1 and 9 do not include additional elements that are sufficient to amount to “significantly more” than the judicial exception because the additional elements (i.e. the non-underlined limitations above – in this case, electronic patient records database, the dropout prediction engine, the engagement recommendation engine, the care provider interface, the one or more processors), as stated above, are directed towards no more than limitations that amount to mere instructions to apply the exception, generally link the abstract idea to a particular technological environment or field of use, and/or add insignificant extra-solution activity to the abstract idea, wherein the additional elements comprise limitations which:
amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields, as demonstrated by:
The present Specification expressly disclosing that the additional elements are well-understood, routine, and conventional in nature:
Pg. 18, line 12 through pg. 19, line 22 of the as-filed Specification discloses that the additional elements (i.e. the electronic patient records database, the dropout prediction engine, the engagement recommendation engine, the care provider interface, the one or more processors) comprise a plurality of different types of generic computing systems that are configured to perform generic computer functions (i.e. storing data, obtaining data, analyzing the data, and displaying the results of the analysis) that are well-understood, routine, and conventional activities previously known to the pertinent industry (i.e. healthcare);
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):
Receiving or transmitting data over a network, e.g. see Intellectual Ventures v. Symantec – similarly, the current invention receives patient data from an electronic records database over a network, e.g. see pg. 12, line 30 through pg. 13, line 4 of the as-filed Specification;
Electronic recordkeeping, e.g. see Alice Corp v. CLS Bank – similarly, the current invention merely recites the storing of patient records on a database;
Storing and retrieving information in memory, e.g. see Versata Dev. Group, Inc. v. SAP Am., Inc. – similarly, the current invention recites storing patient records in a database, and retrieving the data from the patient records in order to ultimately produce and present the recommended engagement action;
Dependent Claims 2-8 and 10-15 include other limitations, but none of these limitations are deemed significantly more than the abstract idea because the additional elements recited in the aforementioned dependent claims similarly amount to mere instructions to apply the exception (e.g. the trained machine learning model recited in dependent Claims 2 and 10), generally link the abstract idea to a particular technological environment or field of use (e.g. the types of patient records recited in dependent Claims 4-5 and 12-13), and/or the limitations recited by the dependent claims do not recite any additional elements not already recited in independent Claims 1 and 9, and hence do not amount to “significantly more” than the abstract idea.
Hence, Claims 1-15 do not include any additional elements that amount to “significantly more” than the judicial exception.
Thus, taken alone, the additional elements do not amount to significantly more than the abstract idea identified above. 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 1-15 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.
Claims 1-2, 4, 8-10, 12, and 14 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Garcia (US 2021/0134431).
Regarding Claim 1, Garcia discloses the following: A method for predicting dropout risk for a patient under remote monitoring using a dropout prediction system (The patient treatment is monitored at the patient’s home, e.g. see [0011] and [0067].), the method comprising:
obtaining, from an electronic patient records database, a plurality of medical records for a patient under remote monitoring by a care provider (The system includes a plurality of clinics and hospitals that each maintain electronic medical databases (i.e. any of which may be interpreted as a “electronic patient records database”), e.g. see Garcia [0086], wherein the databases contain patient specific treatment and prescription data obtained as log files from therapy machines, e.g. see Garcia [0087] and [0090], and wherein the patient data may be transmitted to a system hub and subsequently to a clinician device upon request, e.g. see Garcia [0089] and [0124].);
extracting, from the plurality of medical records for the patient under remote monitoring by the care provider, a plurality of dropout prediction features for the patient (The system utilizes a segment of the patient and treatment data to compare to a training dataset, e.g. see Garcia [0174]-[0175] and [0180], wherein the patient and treatment data includes parameters, at least three to five or more of which are compared to training data in order to determine a predicted probability that the patient will stop treatment, e.g. see Garcia [0174]-[0175]..);
generating, using a dropout prediction engine, a dropout risk score for the patient based on the plurality of dropout prediction features (The system determines a likelihood that the patient may stop or reduce treatments as a concern score (i.e. a dropout risk score), wherein the determination utilizes an AI model trained using training data set including at least three to five (or more) parameters (i.e. the dropout prediction features), e.g. see Garcia [0172]-[0174].);
determining, using an engagement recommendation engine, a potential dropout cause based on at least the plurality of dropout prediction features (The system identifies crucial parameters or contributing factors that cause a high concern score, e.g. see Garcia [0177], Fig. 17.);
determining, using the engagement recommendation engine, a recommended engagement action (The system includes a guidance processor that determines guidance that corresponds to the concern score and the crucial parameters or contributing factors, e.g. see Garcia [0209]-[0210], Fig. 19.), wherein the recommended engagement action is intended to prevent dropout of the patient from remote monitoring by the care provider (The guidance is intended to help improve the patient’s adherence (i.e. prevent dropout) to a prescribed therapy, e.g. see Garcia [0210].); and
presenting, via a care provider interface, the recommended engagement action to a care team member of the care provider (The guidance is displayed to a user, for example a clinician, e.g. see Garcia [0210].).
Regarding Claim 2, Garcia discloses the limitations of Claim 1, and Garcia further discloses the following:
The method of claim 1, wherein the dropout prediction engine comprises a trained dropout prediction model (The concern score is calculated using a trained AI model, e.g. see Garcia [0172]-[0178].), the trained dropout prediction model being trained by a machine learning algorithm on a training dataset that comprises a plurality of medical records for a plurality of historical patients (The AI model is trained using a training data set, e.g. see Garcia [0173].).
Regarding Claim 4, Garcia discloses the limitations of Claim 1, and Garcia further discloses the following:
The method of claim 1, wherein the plurality of medical records for the patient under remote monitoring include at least one of: identification information for the patient; socioeconomic information for the patient; medical history for the patient; treatment history for the patient; medical directives for the patient; and one or more physiological measurements taken from the patient (The patient data includes patient-specific treatment and prescription data (i.e. medical directives for the patient), e.g. see Garcia [0087], and patient data may be determined from treatment data, wherein the patient data includes prescription history (i.e. treatment history), and a patient identifier (i.e. identification information), e.g. see Garcia [0065].).
Regarding Claim 8, Garcia discloses the limitations of Claim 1, and Garcia further discloses the following: The method of claim 1, further comprising:
determining a phenotype for the patient under remote monitoring based on one or more of the dropout prediction features, the dropout risk score generated for the patient, and the potential dropout cause determined for the patient (Given the broadest reasonable interpretation in light of the as-filed Specification, a “phenotype” may be interpreted as “a classification or subgroup that the patient may be sorted into based on one or more similar characteristics,” e.g. see pg. 8, lines 18-19 of the as-filed Specification. The system determines a likelihood that the patient may stop or reduce treatments as a concern score (i.e. a dropout risk score), wherein the determination utilizes an AI model trained using training data set including at least three to five (or more) parameters (i.e. the dropout prediction features), e.g. see Garcia [0172]-[0174], wherein the system may further determine that the patient belongs to a group of patients whose concern score exceeds a threshold (i.e. a phenotype), and in response creates an alert and/or a document for the patient including the concern score and a top number of contributing critical parameters, e.g. see Garcia [0204] and [0214].), wherein the phenotype for the patient indicates a subgroup of similar historical patients (The patient concern score is based on a comparison of similar historical patients, e.g. see Garcia [0174], and hence the concern score exceeding a threshold (i.e. the phenotype) is indicative of the similarity of the patient to at least some of the historical patients.);
wherein the recommended engagement action is determined at least in part based on the phenotype for the patient (The system provides recommendations for addressing critical parameters based on the score exceeding the threshold, e.g. see Garcia [0208]-[0210] and [0214]-[0215].).
Regarding Claim 9, the limitations of Claim 9 are substantially similar to those claimed in Claim 1, with the sole difference being that Claim 1 recites a method whereas Claim 9 recites a system. Specifically pertaining to Claim 9, Examiner notes that Garcia teaches both a method and a system including a processor that performs the aforementioned functions, e.g. see Garcia [0088], and hence the grounds of rejection provided above for Claim 1 are similarly applied to Claim 9.
Regarding Claims 10, 12, and 14, the limitations of Claims 10, 12, and 14 are substantially similar to those claimed in Claims 2, 4, and 8 respectively, with the sole difference being that Claims 2, 4, and 8 recite a method whereas Claims 10, 12, and 14 recite a system. Specifically pertaining to Claims 10, 12, and 14, Examiner notes that Garcia teaches both a method and a system including a processor that performs the aforementioned functions, e.g. see Garcia [0088], and hence the grounds of rejection provided above for Claims 2, 4, and 8 are similarly applied to Claims 10, 12, and 14.
Claim Rejections - 35 USC § 103
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 3 and 11 are rejected under 35 U.S.C. 103 as being unpatentable over Garcia in view of Appelbaum (US 2022/0051773).
Regarding Claim 3, Garcia discloses the limitations of Claim 1, but does not teach and Appelbaum teaches the following:
The method of claim 1, wherein the potential dropout cause is determined by evaluating a feature value contribution for one or more dropout prediction features, the feature value contributions being determined using a Shapley values algorithm (The system utilizes a Tree Shapley Additive Explanation (SHAP) algorithm to generate more interpretable predictions, wherein the SHAP algorithm assigns each explanatory variable an importance value for each prediction, such that it determines which explanatory variables drove a particular prediction, e.g. see Appelbaum [0127].).
Furthermore, before the effective filing date, it would have been obvious to one ordinarily skilled in the art of healthcare to modify Garcia to incorporate the SHAP algorithm as taught by Appelbaum in order to generate more interpretable predictions, e.g. see Appelbaum [0127].
Regarding Claim 11, the limitations of Claim 11 are substantially similar to those claimed in Claim 3, with the sole difference being that Claim 3 recites a method whereas Claim 11 recites a system. Specifically pertaining to Claim 11, Examiner notes that Garcia teaches both a method and a system including a processor that performs the aforementioned functions, e.g. see Garcia [0088], and hence the grounds of rejection provided above for Claim 3 are similarly applied to Claim 11.
Claims 5 and 13 are rejected under 35 U.S.C. 103 as being unpatentable over Garcia in view of Sadler (US 2009/0240525).
Regarding Claim 5, Garcia discloses the limitations of Claim 4, but does not teach and Sadler teaches the following:
The method of claim 4, wherein the plurality of medical records for the patient under remote monitoring further includes at least one of: virtual care solution usage information; a technology affinity measured for the patient; and feedback information from one or more historical or concurrent patients (The system includes patient medical records which include recorded telemedicine virtual visit sessions (i.e. virtual care solution usage information), e.g. see Sadler [0022]-[0023].).
Furthermore, before the effective filing date, it would have been obvious to one ordinarily skilled in the art of healthcare to modify Garcia to incorporate storing a record of patient telemedicine virtual visit sessions as taught by Sadler in order to reduce the number of patient errors, fraud, and improve overall efficiency, e.g. see Sadler [0026].
Regarding Claim 13, the limitations of Claim 13 are substantially similar to those claimed in Claim 5, with the sole difference being that Claim 5 recites a method whereas Claim 13 recites a system. Specifically pertaining to Claim 13, Examiner notes that Garcia teaches both a method and a system including a processor that performs the aforementioned functions, e.g. see Garcia [0088], and hence the grounds of rejection provided above for Claim 5 are similarly applied to Claim 13.
Claims 6-7 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Garcia in view of Baym (US 2015/0112728).
Regarding Claim 6, Garcia discloses the limitations of Claim 1, but does not teach and Baym teaches the following:
The method of claim 1, wherein the dropout risk score generated for the patient is a likelihood that the patient will fail to meet a participation threshold set by a third party (The system includes required conditions (i.e. a threshold) specified by an insurer (i.e. a third party) in order for an insurer to provide coverage, wherein the conditions include that a patient must engage in one or more specified activities such as making all treatment appointments, e.g. see Baym [0097]-[0098], wherein the system further calculates a probability than an insurer will deny some or all coverage (i.e. by virtue of failing to meet the requirements), e.g. see Baym [0058] and [0124].).
Furthermore, before the effective filing date, it would have been obvious to one ordinarily skilled in the art of healthcare to modify Garcia to incorporate the insurance coverage limitations as taught by Baym in order to enable a patient to manage their risk, e.g. see Baym [0054].
Regarding Claim 7, the combination of Garcia and Baym teaches the limitations of Claim 6, and Baym further teaches the following:
The method of claim 6, wherein the third party is an insurance company and the participation threshold determines whether the remote monitoring of the patient is covered under an insurance plan associated with the patient (The insurer requirements (i.e. the participation threshold) determine whether the insurer will provide coverage, e.g. see Baym [0058], [0097]-[0098], and [0124].).
Furthermore, before the effective filing date, it would have been obvious to one ordinarily skilled in the art of healthcare to modify Garcia to incorporate the insurance coverage limitations as taught by Baym in order to enable a patient to manage their risk, e.g. see Baym [0054].
Regarding Claim 15, the limitations of Claim 15 are substantially similar to those claimed in Claims 6-7, with the sole difference being that Claims 6-7 recite a method whereas Claim 15 recites a system performing the functions of Claims 6-7. Specifically pertaining to Claim 15, Examiner notes that Garcia teaches both a method and a system including a processor that performs the aforementioned functions, e.g. see Garcia [0088], and hence the grounds of rejection provided above for Claims 6-7 are similarly applied to Claim 15.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure is as follows:
Fiedler (US 2018/0137932) – teaches a system for patient monitoring that records patient feedback;
Abu El Ata (US US2022/0230759) – teaches a system for predicting unexpected behaviors in patients and determining the root causes of the unexpected behavior.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOHN P GO whose telephone number is (703)756-1965. The examiner can normally be reached Monday-Friday 9am-6pm PST.
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, PETER H CHOI can be reached at (469)295-9171. 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.
/JOHN P GO/Examiner, Art Unit 3681