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 1-20 are currently pending.
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 limitation(s) uses 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:
“A prediction cycle controller” recited in Claims 1-20;
“An admit status predictor” recited in Claims 1-20;
“An MDC predictor” recited in Claims 1-20;
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. Specifically, the aforementioned limitations are interpreted as referring to software modules that are executed by a processor, in accordance with [0101], [0108], and [0112]-[0114] of the as-filed Specification.
If applicant does not intend to have 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 functions 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 1-20 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.
Step 1
Claims 1-20 are within the four statutory categories. Claims 1-7 are drawn to a method for patient status prediction, which is within the four statutory categories (i.e. process). Claims 8-14 are drawn to a system for patient status prediction, which is within the four statutory categories (i.e. machine). Claims 15-20 are drawn to a non-transitory computer-readable medium for patient status prediction, which is within the four statutory categories (i.e. manufacture).
Prong 1 of Step 2A
Claim 1, which is representative of the inventive concept, recites: A method, comprising:
querying, by a prediction cycle controller, a first database for patient visits that are eligible for admit status prediction (ASP), the querying including checking whether an inpatient or Outpatient status in the first database has changed;
extracting, by the prediction cycle controller from the patient visits eligible for the ASP, ASP features and major diagnosis category (MDC) prediction features for each of the patient visits, the ASP features including observations of prediction-eligible patients of a healthcare provider, the MDC prediction features including data points for determining a MDC;
communicating, by the prediction controller, the ASP features thus extracted to an admit status predictor, wherein the admit status predictor is operable to examine, utilizing a machine learning model, the observations of the prediction-eligible patients and generate an ASP for each of the prediction-eligible patients;
communicating, by the prediction controller to an MDC predictor, the MDC prediction features thus extracted and the ASP thus generated by the admit status predictor for each of the prediction-eligible patients, wherein the MDC predictor is operable to examine the MDC prediction features thus extracted and the ASP thus generated by the admit status predictor for each of the prediction-eligible patients and generate a MDC prediction (MDCP); and
presenting, by the prediction controller via a user interface on a user device, the ASP and the MDCP.
The underlined limitations as shown above recite the abstract idea of a mental process and/or a certain method of organizing human activity because they recite a process that could be practically performed in the human mind (i.e. observations, evaluations, judgments, and/or opinions – in this case, the steps of querying for ASP eligible patient visits, extracting ASP features and MDC prediction features for the patient visits, communicating the ASP features to examine, utilizing a model, observations and generate an ASP for each patient, and communicating the MDC prediction features and the ASP to generate an MDC prediction recite at least evaluations including collecting information, analyzing it, and displaying certain results of the collection and analysis) or using a pen and paper, but for the recitation of generic computer components (i.e. the prediction cycle controller, the first database, the admit status predictor, the machine learning model, the user interface, and the user device), and/or 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 querying for ASP eligible patient visits, extracting ASP features and MDC prediction features for the patient visits, communicating the ASP features to examine, utilizing a model, observations and generate an ASP for each patient, communicating the MDC prediction features and the ASP to generate an MDC prediction, and presenting the ASP and the MDC prediction recite following rules or instructions to evaluate a patient and make patient status predictions), 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 Claims 8 and 15 is identical as the abstract idea for Claim 1, because the only difference between Claims 1, 8, and 15 is that Claim 1 recites a method, whereas Claim 8 recites a system and Claim 15 recites a non-transitory computer-readable medium.
Dependent Claims 2-7, 9-14, and 16-20 include other limitations, for example Claims 2, 9, and 16 recite retrieving a deep learning model defining patient hospital states, Claims 3, 10, and 17 recite periodically obtaining patient records, Claims 4, 11, and 18 recites checking various conditions regarding the retrieval of the machine learning model, Claims 5 and 12 recite formats of the querying, Claims 6, 13, and 19 recite contents of databases, and Claims 7, 14, and 20 recite types of ASP features, 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 2-7, 9-14, and 16-20 nonetheless recite the same abstract idea as independent Claims 1, 8, and 15.
Hence Claims 1-20 recite the aforementioned abstract idea.
Prong 2 of Step 2A
Claims 1, 8, and 15 are not integrated into a practical application because the additional elements (i.e. the non-underlined limitations above – in this case, the prediction cycle controller, the first database, the admit status predictor, the machine learning model, the user interface, and the user device) amount to no more than limitations which:
amount to mere instructions to apply an exception – for example, the recitation of the prediction cycle controller, the first database, the admit status predictor, the user interface, and the user device, which amounts to merely invoking a computer as a tool to perform the abstract idea, e.g. see [0101]-[0103] and [0113]-[0114] of the as-filed Specification, and see MPEP 2106.05(f); and/or
generally link the abstract idea to a particular technological environment or field of use – for example, the utilization of a machine learning model, which amounts to limiting the abstract idea to the field of artificial intelligence/machine learning, e.g. see MPEP 2106.05(h).
Additionally, dependent Claims 2-7, 9-14, and 16-20 include other limitations, but these limitations also amount to no more than mere instructions to apply an exception (e.g. the second database recited in dependent Claims 2-6, 9-13, and 16-19), generally linking the abstract idea to a particular technological environment or field of use (e.g. the specific types of data recited in dependent Claims 4-7, 11-14, and 18-20), and/or do not include any additional elements beyond those already recited in independent Claims 1, 8, and 15, and hence also do not integrate the aforementioned abstract idea into a practical application.
Hence Claims 1-20 do not include additional elements that integrate the judicial exception into a practical application.
Step 2B
Claims 1, 8, and 15 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, the prediction cycle controller, the first database, the admit status predictor, the machine learning model, the user interface, and the user device), 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 structural additional elements are well-understood, routine, and conventional in nature:
[0101]-[0103] and [0113]-[0114] of the as-filed Specification discloses that the additional elements (i.e. the prediction cycle controller, the first database, the admit status predictor, the user interface, and the user device) comprise a plurality of different types of generic computing systems;
Relevant court decisions: The functional limitations interpreted as additional elements are analogized to the following 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 additional elements recite querying and receiving data from a database over a network, e.g. see [0103] of the as-filed Specification;
Electronic recordkeeping, e.g. see Alice Corp v. CLS Bank – similarly, the additional elements merely recite the maintaining of patient visit data on a database;
Storing and retrieving information in memory, e.g. see Versata Dev. Group, Inc. v. SAP Am., Inc. – similarly, the additional elements recite storing patient visit data in a database and/or electronic memory, and retrieving the patient visit data from storage in order to ultimately determine and present the ASP and MDCP;
Dependent Claims 2-7, 9-14, and 16-20 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 no more than mere instructions to apply an exception (e.g. the second database recited in dependent Claims 2-6, 9-13, and 16-19), generally linking the abstract idea to a particular technological environment or field of use (e.g. the specific types of data recited in dependent Claims 4-7, 11-14, and 18-20), and/or the limitations recited by the dependent claims do not recite any additional elements not already recited in independent Claims 1, 8, and 15, and hence do not amount to “significantly more” than the abstract idea.
Hence, Claims 1-20 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 1-20 are nonetheless 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 (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 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, 7-8, 14-15, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Volosin (US 2019/0282178) in view of Presley (US 2012/0136673).
Regarding Claim 1, Volosin teaches the following: A method, comprising:
querying, by a prediction cycle controller, a first database for patient visits that are eligible for admit status prediction (ASP) (The system includes a communication interface in communication with a remote console that is connected with one or more databases that store patient data for subsequent viewing, processing, and analysis, e.g. see Volosin [0107].);
extracting, by the prediction cycle controller from the patient visits eligible for the ASP, ASP features and major diagnosis category (MDC) prediction features for each of the patient visits, the ASP features including observations of prediction-eligible patients of a healthcare provider, the MDC prediction features including data points for determining a MDC (The system obtains various patient data, for example ECG measurement data (i.e. any of which may be interpreted as ASP features), e.g. see Volosin [0060], [0107], and [0146], wherein the obtained patient data (i.e. any of which may also be interpreted as MDC prediction features) is also used to determine clinically actionable events for a patient, wherein the clinically actionable events include re-hospitalization, e.g. see Volosin [0060]-[0061] and [0300].);
communicating, by the prediction controller, the ASP features thus extracted to an admit status predictor, wherein the admit status predictor is operable to examine, utilizing a machine learning model, the observations of the prediction-eligible patients and generate an ASP for each of the prediction-eligible patients (The system determines a current condition (i.e. an ASP) for the patient based on the obtained patient data, e.g. see Volosin [0060]-[0061] and [0300], wherein the determination is performed utilizing machine learning, e.g. see Volosin [0136] and [0141].);
communicating, by the prediction controller to an MDC predictor, the MDC prediction features thus extracted and the ASP thus generated by the admit status predictor for each of the prediction-eligible patients, wherein the MDC predictor is operable to examine the MDC prediction features thus extracted and the ASP thus generated by the admit status predictor for each of the prediction-eligible patients and generate a MDC prediction (MDCP) (The system utilizes the patient’s current condition (i.e. the ASP) obtained based on the obtained patient data to determine clinically actionable events including re-hospitalization (i.e. an MDC prediction), e.g. see Volosin [0060]-[0061] and [0300].); and
presenting, by the prediction controller via a user interface on a user device, the ASP and the MDCP (The system includes a user interface comprising input and output devices that provide a visual output (i.e. presents) including the patient’s current condition (i.e. the ASP) and relating to the one or more clinically actionable events (i.e. the MDCP), e.g. see Volosin [0060], [0089], and [0141].).
But Volosin does not teach and Presley teaches the following:
the querying including checking whether an Inpatient or Outpatient status in the first database has changed (The system includes a memory (i.e. a database) and a level of care (LOC) event module, wherein the LOC event module examines (i.e. queries) the data in memory to determine whether a level of care is changed, for example indicating that a patient is admitted to a health care facility (i.e. Inpatient status) or discharged from the health care facility (i.e. Outpatient status), e.g. see Presley [0043].).
Furthermore, before the effective filing date, it would have been obvious to one ordinarily skilled in the art of healthcare to modify Volosin to incorporate querying the database to determine whether the patient’s admission status has changed as taught by Presley in order to efficiently and reliably generate notifications to healthcare personnel for events that may need to be performed for patients based on the changes in the level of care, e.g. see Presley [0013].
Regarding Claim 7, the combination of Volosin and Presley teaches the limitations of Claim 1, and Volosin further discloses the following:
The method according to claim 1, wherein the ASP features comprise observations, the observations including 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 (The patient data (i.e. the ASP features) include changes in physiological parameters (i.e. changes in the severity of the patient symptoms), and further monitors changes in the patient’s condition (i.e. changes in the severity of the patient illness), e.g. see Volosin [0060] and [0064].).
Regarding Claims 8 and 15, the limitations of Claims 8 and 15 are substantially similar to those claimed in Claim 1, with the sole difference being that Claim 1 recites a method, whereas Claim 8 recites a system and Claim 15 recites a non-transitory computer-readable medium. Specifically pertaining to Claims 8 and 15, Examiner notes that Volosin teaches that the functions of the invention may be implemented by one or more processors executing software stored in a data store, e.g. see Volosin [0098], and hence the grounds of rejection provided above for Claim 1 are similarly applied to Claims 8 and 15.
Regarding Claims 14 and 20, the limitations of Claims 14 and 20 are substantially similar to those claimed in Claim 7, with the sole difference being that Claim 7 recites a method, whereas Claim 14 recites a system and Claim 20 recites a non-transitory computer-readable medium. Specifically pertaining to Claims 14 and 20, Examiner notes that Volosin teaches that the functions of the invention may be implemented by one or more processors executing software stored in a data store, e.g. see Volosin [0098], and hence the grounds of rejection provided above for Claim 7 are similarly applied to Claims 14 and 20.
Claims 2, 9, and 16 are rejected under 35 U.S.C. 103 as being unpatentable over the combination of Volosin and Presley in view of Bates (US 2021/0151140).
Regarding Claim 2, the combination of Volosin and Presley teaches the limitations of Claim 1, and Volosin further teaches the following: The method according to claim 1, further comprising:
querying a second database to obtain configuration data for configuring how a job is run (The system includes one or more databases (i.e. any of which may be interpreted as a first and second database) that store patient data for subsequent viewing, processing, and analysis, e.g. see Volosin [0107].), wherein the configuration data comprises a deep learning model built to predict hospital statuses based on data points derived from electronic medical records (The machine learning model includes a deep learning process, e.g. see Volosin [0299], wherein the machine learning may be used to perform a predictive analysis based on the patient data, and wherein the predictive analysis includes determining clinically actionable events including re-hospitalization (i.e. a hospital status), e.g. see Volosin [0255]-[0257] and [0300].).
But the combination of Volosin and Presley does not teach and Bates teaches the following:
wherein the electronic medical records capture when patients enter and exit specific observation or inpatient statuses, indicating when each patient transitions into or out of one of the statuses (The system obtains patient data from databases of electronic medical records, wherein the patient data includes hospital admission data including time data, e.g. see Bates [0088], and wherein the patient data is used to generate training data for an artificial intelligence model, e.g. see Bates [0095] and [0098]-[0099].).
Furthermore, before the effective filing date, it would have been obvious to one ordinarily skilled in the art of healthcare to modify the combination of Volosin and Presley to incorporate the admission and/or discharge time data as taught by Bates in order to optimize the allocating of resources for patients, e.g. see Bates [0004] and [0006].
Regarding Claims 9 and 16, the limitations of Claims 9 and 16 are substantially similar to those claimed in Claim 2, with the sole difference being that Claim 2 recites a method, whereas Claim 9 recites a system and Claim 16 recites a non-transitory computer-readable medium. Specifically pertaining to Claims 9 and 16, Examiner notes that Volosin teaches that the functions of the invention may be implemented by one or more processors executing software stored in a data store, e.g. see Volosin [0098], and hence the grounds of rejection provided above for Claim 2 are similarly applied to Claims 9 and 16.
Claims 3-4, 10-11, and 17-18 are rejected under 35 U.S.C. 103 as being unpatentable over the combination of Volosin, Presley, and Bates in view of McMains (US 2015/0347599).
Regarding Claim 3, the combination of Volosin, Presley, and Bates teaches the limitations of Claim 2, but does not teach and McMains teaches the following:
The method according to claim 2, wherein configuring the job comprises configuring a job schedule to pull patient records on a per entity basis periodically (The system includes client databases that receive data requests on a scheduled basis, a periodic basis, and/or for recently modified data, e.g. see McMains [0221] and [0223].).
Furthermore, before the effective filing date, it would have been obvious to one ordinarily skilled in the art of healthcare to modify the combination of Volosin, Presley, and Bates to incorporate the periodic retrieval of data from the databases as taught by McMains in order to facilitate quick, easy access to desired data, e.g. see McMains [0005]-[0007].
Regarding Claim 4, the combination of Volosin, Presley, and Bates teaches the limitations of Claim 2, but does not teach and McMains teaches the following:
The method according to claim 2, wherein querying the second database comprises at least one of: checking whether new data has arrived, whether a cooling-off period has elapsed, or whether a patient status has changed. (The system includes client databases that receive data requests on a scheduled basis, a periodic basis, and/or for recently modified data (i.e. new data has arrived), e.g. see McMains [0221] and [0223].).
Furthermore, before the effective filing date, it would have been obvious to one ordinarily skilled in the art of healthcare to modify the combination of Volosin, Presley, and Bates to incorporate the periodic retrieval of data from the databases as taught by McMains in order to facilitate quick, easy access to desired data, e.g. see McMains [0005]-[0007].
Regarding Claims 10-11 and 17-18, the limitations of Claims 10-11 and 17-18 are substantially similar to those claimed in Claims 3-4, with the sole difference being that Claims 3-4 recite a method, whereas Claims 10-11 recite a system and Claims 17-18 recite a non-transitory computer-readable medium. Specifically pertaining to Claims 10-11 and 17-18, Examiner notes that Volosin teaches that the functions of the invention may be implemented by one or more processors executing software stored in a data store, e.g. see Volosin [0098], and hence the grounds of rejection provided above for Claims 3-4 are similarly applied to Claims 10-11 and 17-18.
Claims 5 and 12 are rejected under 35 U.S.C. 103 as being unpatentable over the combination of Volosin, Presley, and Bates in view of Azvine (US 2008/0243912).
Regarding Claim 5, the combination of Volosin, Presley, and Bates teaches the limitations of Claim 2, but does not teach and Azvine teaches the following:
The method according to claim 2, wherein the querying the first database utilizes a data access object (DAO) of a first type and wherein the querying the second database utilizes a DAO of a second type (The system includes a plurality of data access objects (DAOs), wherein different DAOs are required to access different types of data resources, e.g. see Azvine [0086]-[0088], Fig. 7.).
Furthermore, before the effective filing date, it would have been obvious to one ordinarily skilled in the art of data processing to modify the combination of Volosin, Presley, and Bates to incorporate the different DAOs as taught by Azvine in order to enable the system to access and retrieve data from different data resources, e.g. see Azvine [0086].
Regarding Claim 12, the limitations of Claim 12 are substantially similar to those claimed in Claim 5, with the sole difference being that Claim 5 recites a method, whereas Claim 12 recites a system. Specifically pertaining to Claim 12, Examiner notes that Volosin teaches that the functions of the invention may be implemented by one or more processors executing software stored in a data store, e.g. see Volosin [0098], and hence the grounds of rejection provided above for Claim 5 are similarly applied to Claim 12.
Claims 6, 13, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over the combination of Volosin, Presley, and Bates in view of Shah (US 2017/0103167).
Regarding Claim 6, the combination of Volosin, Presley, and Bates teaches the limitations of Claim 2, but does not teach and Shah teaches the following:
The method according to claim 2, wherein the first database stores patient records of the patients and wherein the second database stores metadata and configuration data for controlling how each prediction cycle is run (The system includes a records database including an Electronic Health Record (EHR) repository that stores patient data, for example electronic healthcare records, e.g. see Shah [0035]. Furthermore, the records database is coupled to a data logging unit (i.e. a second database) that stores metadata and various machine learning data, e.g. see Shah [0036], Fig. 2.).
Furthermore, before the effective filing date, it would have been obvious to one ordinarily skilled in the art of data processing to modify the combination of Volosin, Presley, and Bates to incorporate the first database storing patient records and the second database storing metadata as taught by Shah in order to enable transformation and standardization of unstructured or semi-structured data from the various clinical data sources such that it may then be used by a machine learning process such as Natural Language Processing (NLP), e.g. see Shah [0027] and [0036].
Regarding Claims 13 and 19, the limitations of Claims 13 and 19 are substantially similar to those claimed in Claim 6, with the sole difference being that Claim 6 recites a method, whereas Claim 13 recites a system and Claim 19 recites a non-transitory computer-readable medium. Specifically pertaining to Claims 13 and 19, Examiner notes that Volosin teaches that the functions of the invention may be implemented by one or more processors executing software stored in a data store, e.g. see Volosin [0098], and hence the grounds of rejection provided above for Claim 6 are similarly applied to Claims 13 and 19.
Response to Arguments
Applicant’s arguments, see Remarks, filed July 24, 2026, with respect to the interpretations of Claims 1-20 under 35 U.S.C. 112(f) have been fully considered but are not persuasive.
The three-prong analysis for determining whether a claim should be interpreted under 35 U.S.C. 112(f) is as follows: (1) 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; (2) 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 (3) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function, e.g. see MPEP 2181(I). That is, a claim limitation will be interpreted under 35 U.S.C. 112(f) if it recites a generic placeholder or nonce term performing a function, without reciting sufficient structure to perform the recited function.
With regards to the claimed invention, Examiner asserts that “controller” and “predictor” represent generic placeholder terms, as neither inherently invokes any type of structure, and further notes that that Claims 1, 8, and 15 claim that the “prediction cycle controller” performs various functions (e.g. a querying of a database), the “admit status predictor” performs the function of examining the observations to generate an ASP, and the “MDC predictor” performs the function of examining the MDC prediction features and the ASP to generate an MDC prediction. Hence, each of the “prediction cycle controller,” “admit status predictor,” and “MDC predictor” recite nonce terms performing various functions. Additionally, Claims 1, 8, and 15 do not claim any structure for performing these functions. Hence, the aforementioned limitations require interpretation under 35 U.S.C. 112(f).
Examiner notes that the functions of the aforementioned claim limitations are capable of being embodied as, for example, software modules executed by a computer processor, which, if claimed as such, would cause the limitations to no longer require interpretation under 35 U.S.C. 112(f). However, Examiner further notes that Claim 8 recites a processor and instructions stored on a non-transitory computer readable medium that cause the prediction cycle controller to perform various functions. That is, given the broadest reasonable interpretation, Claim 8 recites that the prediction cycle controller may be a component separate and/or distinct from the processor.
For the aforementioned reasons, the “prediction cycle controller,” the “admit status predictor,” and the “MDC predictor” recited in Claims 1-20 are interpreted under 35 U.S.C. 112(f).
Applicant’s arguments, see Remarks, filed July 24, 2026, with respect to the rejections of Claims 2-6, 9-13, and 16-19 under 35 U.S.C. 112(b) have been fully considered and, in combination with the claim amendments, are persuasive. The rejections of Claims 2-6, 9-13, and 16-19 under 35 U.S.C. 112(b) have been withdrawn.
Applicant’s arguments, see Remarks, filed July 24, 2026, with respect to the rejections of Claims 1-20 under 35 U.S.C. 101 have been fully considered but are not persuasive.
Applicants allege that the claimed invention is patent eligible because it does not recite an abstract idea, specifically because Examiner has not considered the claims as a whole, because the claimed invention recites “special computer functions,” and similar to Enfish, the claimed invention is directed towards a technological improvement in the functionality of a computer, e.g. see pgs. 4-9 of Remarks – Examiner disagrees.
Regarding the evidence pertaining to the abstract idea determination, there is no requirement for the examiner to rely on evidence, such as publications or an affidavit or declaration under 37 CFR 1.104(d)(2), to find that a claim recites a judicial exception, e.g. see MPEP 2106.07(a)(III).
Regarding Enfish, the invention of Enfish recited a self-referential data table for a computer database which, according to the Specification, improved computer functionality such as increased flexibility, faster search times, and smaller memory requirements, which ultimately resulted in the court determining that the invention was not directed towards an abstract idea but was instead directed towards an improvement to computer functionality comprising a specific implementation of a solution to a problem in the software arts, e.g. see MPEP 2106.05(a)(I) and 2106.05(d)(I)(1). In contrast, the claimed invention recites querying and extracting data from a database, and utilizing a machine learning model to perform an analysis on the data to produce predictions for a patient, wherein the Specification discloses that the invention solves the problem of accuracy and optimization with regards to determining patient status for billing codes for workflow and for insurance, e.g. see [0003]-[0009] of the as-filed Specification. Hence, unlike the particular structuring of a database of Enfish that improved computer functionality, at most, the claimed invention recites improvements to a healthcare and/or billing workflow, which are improvements to the abstract idea of a mental process and/or a certain method of organizing human activities, and an improvement in the abstract idea itself (e.g. a recited fundamental economic concept) is not an improvement in technology, e.g. see MPEP 2106.05(a)(II). Moreover, the problem of a utilization management nurse not determining a patient status in an optimal manner, e.g. see [0005] of the as-filed Specification, is not a technological problem in the software arts and/or arising the realm of computer networks because it has existed since long before the advent of any type of computer technology.
Additionally, the narrowness and/or specificity of the data handled by the invention does not impart eligibility onto the claims. That is, the Claims being narrowly claimed is not dispositive in determining the eligibility of the Claims. The Court has held that a claim may not preempt abstract ideas, laws of nature, or natural phenomena, even if the judicial exception is narrow, e.g. see MPEP 2106.04. That is, a claim reciting a narrow abstract idea nonetheless recites an abstract idea, and must be evaluated under the remainder of the requirements under 35 U.S.C. 101.
Hence, the claimed invention recites the abstract idea of a mental process and/or a certain method of organizing human activities.
Applicants further allege that the claimed invention is patent eligible because it recites significantly more than an abstract idea, specifically because the claimed invention solves the problem of predicting a patient status in a quantifiable way and provides a technological improvement in the functionality of the computer, because the additional elements do not amount to generic computing systems performing generic computing functions, and because the claimed invention must be evaluated as an ordered combination, e.g. see pgs. 9-12 of Remarks – Examiner disagrees.
As stated above, the problems addressed by the claimed invention are problems with healthcare and/or billing workflow, e.g. see [0003]-[0009] of the as-filed Specification, which are improvements to the abstract idea of a mental process and/or a certain method of organizing human activities, and an improvement in the abstract idea itself (e.g. a recited fundamental economic concept) is not an improvement in technology, e.g. see MPEP 2106.05(a)(II).
Furthermore, as stated above, the additional elements of the prediction cycle controller, the first database, the admit status predictor, the machine learning model, the user interface, and the user device comprise hardware limitations for performing the claimed functions, wherein the Specification discloses that the hardware limitations comprise a plurality of generic computing elements including “any medium that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, system or device,” and “any hardware system, mechanism, or component that processes data, signals or other information,” e.g. see [0113]-[0114] of the as-filed Specification. That is, the aforementioned hardware limitations themselves represent mere instructions to apply the abstract idea utilizing the hardware as a tool, and/or are well-understood, routine, and conventional in nature, as demonstrated by the Specification disclosing that the functions of the system may be performed by any medium and any hardware system capable of performing the generic computer functions of storing, processing, and presenting data.
With regards to considering the invention as a whole and/or as an ordered combination, as stated above, looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. For example, the invention of Bascom recited a system for filtering content retrieved from an Internet computer network that represented a non-conventional and non-generic arrangement of components that are individually well-known and conventional, which achieved the improvements of increased defense against hacking, less dependence on local hardware and software, and more flexibility, e.g. see MPEP 2106.05. That is, the claimed elements achieved improvements to computer functionality when considered as an ordered combination. In contrast, the additional elements of the claimed invention (i.e. the prediction cycle controller, the first database, the admit status predictor, the machine learning model, the user interface, and the user device) represent generic computing structure (as disclosed by the Specification) performing generic computer functions (i.e. storing, processing, and presenting data), which, even when considered as an ordered combination, do not achieve any technological improvements.
Hence, the claimed invention does not recite significantly more than the identified abstract idea.
For the aforementioned reasons, Claims 1-20 are rejected under 35 U.S.C. 101.
Applicant’s arguments, see Remarks, filed July 24, 2026, with respect to the rejections of Claims 1, 7-8, 14-15, and 20 under 35 U.S.C. 102(a)(1) have been fully considered and, in combination with the claim amendments, are persuasive. The rejections of Claims 1, 7-8, 14-15, and 20 under 35 U.S.C. 102(a)(1) have been withdrawn. However, for the reasons shown above, and as will be discussed in further detail below, Claims 1-20 are nonetheless rejected under 35 U.S.C. 103.
Applicant’s arguments, see Remarks, filed July 24, 2026, with respect to the rejections of Claims 1-20 under 35 U.S.C. 103 have been fully considered but are not persuasive.
Applicant alleges that Volosin is deficient because it does not disclose querying a database “for patient visits that are eligible for admit status prediction (ASP),” and further because it does not disclose “ASP features including observations of prediction-eligible patients of a healthcare provider or major diagnosis prediction features including data points for determining a MDC,” e.g. see pgs. 13-16 of Remarks – Examiner disagrees.
Regarding the step of “querying…for patient visits that are eligible for admit status prediction (ASP),” [0107] of Volosin discloses “a networked server that is connected to one or more databases and configured to store the radio frequency and ECG data for subsequent viewing, processing, and analysis.” That is, the networked server must query the data from the database in order to perform the functions of at least viewing, processing, and analysis. Furthermore, Examiner notes that the Claims do not recite any language defining what makes a patient visit “eligible for ASP.” For example, the Claims do not recite affixing a flag or label or metadata to a patient file indicating that the file is eligible for ASP, and/or do not recite calculating a score and evaluating whether the patient file satisfies some threshold to make the file eligible for ASP. Hence, given the broadest reasonable interpretation, “patient visits that are eligible for admit status prediction (ASP)” may be interpreted as patient data indicative of a patient admission. Similarly, [0062] of Volosin discloses that patients with cardiac pathologies may also be candidates for readmission, and [0181] of Volosin further discloses that the system may score patient data and use the score to make recommendations including whether the patient should be admitted to a hospital. Hence, the patient ECG data stored in the database and retrieved by the server, as recited in [0107] of Volosin, given the broadest reasonable interpretation, is at least indicative of a patient who may, as a result of various determinations, be a patient who should be admitted to a hospital, and hence the patient data in the database may be interpreted as data “for patient visits that are eligible for admit status prediction (ASP).”
Regarding “ASP features including observations of prediction-eligible patients of a healthcare provider or major diagnosis prediction features including data points for determining a MDC,” [0060] of Volosin discloses obtaining patient ECG data, cardio-vibrational or pulmonary-vibrational signals, and radio frequency data including electromagnetic energy into the patient’s thoracic cavity and/or towards the heart. Given the broadest reasonable interpretation, any of the aforementioned data may be properly interpreted “ASP features including observations of prediction-eligible patients” and/or “major diagnosis prediction features including data points for determining a MDC” because the data can be used “to determine whether the patient is at high risk for developing heart failure symptoms that could require eventual hospitalization,” e.g. see Volosin [0061], and a patient requiring eventual hospitalization is at least an “ASP feature,” and the patient being high risk for developing heart failure symptoms is at least a “major diagnosis category.”
Hence, given the broadest reasonable interpretation, Volosin is not deficient to teach the features it is cited for.
Additionally, regarding the newly amended claim language further defining the querying as including checking whether an Inpatient or Outpatient status in the first database has changed, as shown above, Presley is newly cited to teach this feature, and hence any arguments pertaining to this feature in view of the previously cited prior art references are moot.
For the aforementioned reasons, Claims 1-20 are rejected under 35 U.S.C. 103.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure is as follows:
Kanamarlapudi (US 2010/0191546) – teaches a healthcare system including a polling unit that checks if new data is available including new healthcare events such as admission/discharge.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOHN P GO whose telephone number is (703)756-1965. The examiner can normally be reached Monday-Friday 9am-6pm Pacific.
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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.
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/JOHN P GO/Primary Examiner, Art Unit 3681
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