DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
Claims 1-20 are pending.
This communication is in response to the communication filed February 12, 2024.
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 an abstract idea without significantly more. The claims recite inventions for assessing performance of models, which are statutory categories of inventions.
Specifically, the independent claims, taking claim 1 as exemplary, recite computing…a plurality of monitoring values, the plurality of monitoring values including at least a first monitoring value and a second monitoring value for each individual within the population, wherein each of the plurality of monitoring values indicates a risk level of a plurality of risk levels; determining…a plurality of actions taken, each action taken within the plurality of actions taken being in response to the first monitoring value and being performed before computation of the second monitoring value for each individual, each action taken corresponding to a recommended action generated by the predictive model in response to the first monitoring value, wherein the recommended action is generated prior to a first discharge of the individual from a healthcare facility; associating each action taken for each individual with a trend in monitoring values and an amount of time between when the recommended action is provided and when the action is taken, the trend being based on at least the first monitoring value and the second monitoring value for each individual; stratifying the population of individuals corresponding to their first monitoring values or the risk levels; estimating…a frequency with which the recommended action when taken generates a positive trend, wherein each group of individuals corresponds to a different first monitoring value or the risk level; generating an assessment of the predictive model based on the frequency, the trend associated with the action taken for each individual, and the amount of time; generating an assessment of the predictive model based on the trend associated with the action taken for each individual and the amount of time; …determining, using the adjusted predictive model, a typical trajectory of the medical condition for the population of individuals to reach from a first risk level of the plurality of risk levels to a second risk level of the plurality of risk levels, in response to the plurality of actions taken for the common medical condition; and generating an alert when a trajectory as generated using the adjusted predictive model for an individual deviates from the typical trajectory.
The limitations directed towards determining a plurality of monitoring values, determining a plurality of actions taken, determining a plurality of time periods, associating each action taken for each individual, and generating assessments which are grouped within the mental processes grouping of abstract ideas. The totality of the limitations is directed as being grouped within the “certain methods of organizing human activity” grouping of abstract ideas because the claims involve collecting data, analyzing it, and generating an alert for an individual deviating from typical trajectory. See MPEP 2106.04. The claims are interpreted to recite concepts relating to tracking or organizing information. Accordingly, the claims recite an abstract idea.
The dependent claims recite the limitations of the independent claims. The dependent claims also recite limitations directed to predicting an effective time period, predicting an expiry time period, explaining the actions taken may be prescribing a drug, defining risk levels, explaining trends, and determining the recommended action based on a deviation from the typical trajectory. The totality of the limitations is directed as being grouped within the “certain methods of organizing human activity” grouping of abstract ideas because the claims involve collecting data, analyzing it, and generating an alert for an individual deviating from typical trajectory. The claims recite additional elements that are not interpreted as part of the abstract idea, and are addressed below.
The additional elements include extracting information from electronic medical records, using a predictive model, adjusting a predictive model, processors, and non-transitory computer readable storage medium. This judicial exception is not integrated into a practical application. Integration into a practical application requires an additional element or a combination of additional elements in the claim to apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the exception.
The claims merely use the additional elements as tools to perform abstract ideas and generally link the use of a judicial exception to a particular technological environment. The use of the additional elements as tools to implement the abstract idea and generally to link the use of the abstract idea to a particular technological environment does not render the claim patent eligible, because it requires no more than a computer performing functions that correspond to acts required to carry out the abstract idea. Specifically, the non-transitory computer readable storage medium can be any volatile, nonvolatile, removable, non- removable media implemented in any method or technology for storage of information and data (par. 19). Electronic medical records perform the steps or functions of storing data (par. 25). Adjusting the model is not specifically described as to what may be deemed an adjustment, since any piece of information provided by the generated assessment may be used to make a simple adjustment such as delaying the input time. Making the adjustment does necessarily lead to any improvement to the model. Moreover, the invention can leverage well-known computing system environments and many components and their interconnections arc well known (par. 16, 24). The processor may be part of well-known computing system functioning to extract information from electronic medical records, use a predictive model, adjust a predictive model, determine a plurality of monitoring values, determine a plurality of actions taken, determine a plurality of time periods, associate each action taken for each individual, and generate assessments and alerts (par. 17).
The additional elements do not show an improvement to the functioning of a computer or to any other technology, rather the additional elements perform general computing functions and do not indicate how the particular combination improves any technology or provides a technical solution to a technical problem. See Apple v. Ameranth, 842 F.3d 1229, 1240 (Fed. Cir. 2016). The additional elements do not use the exception to affect a particular treatment or prophylaxis for a disease, do not apply the exception using particular machines, and do not effect a transformation or reduction of a particular article to a different state or thing, rather the computer elements are generally stated as to their structure and function and are only used to alert users and provide recommendations instead of directly providing specific treatment or prophylaxis. Therefore, the additional elements do not impose any meaningful limits on practicing the abstract idea and the additional limitations are not indicative of materializing into a practical application. Accordingly, the claim is directed to an abstract idea.
Generic computer elements recited as performing generic computer functions that are well-understood, routine, or conventional activities amount to no more than implementing the abstract idea with a computerized system (Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network and performing repetitive calculations); Bancorp Services v. Sun Life, 687 F.3d 1266, 1278, 103 USPQ2d 1425, 1433 (Fed. Cir. 2012) ("The computer required by some of Bancorp’s claims is employed only for its most basic function, the performance of repetitive calculations, and as such does not impose meaningful limits on the scope of those claims."); See MPEP 2106.05(d) and July 2015 Update: Section IV). Here, the claim limitations of computing, estimating, stratifying, adjusting, generating, and determining various types of data are similar to a computer receiving and sending information and performing calculations.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, as discussed above with respect to integration of the abstract idea into a practical application, the additional elements of using a non-transitory computer readable medium and processors to perform the steps of the claims amount to no more than using computer related devices to automate or implement the abstract idea of assessing performance of models.
The use of a computer or processor to merely automate or implement the abstract idea cannot provide significantly more than the abstract idea itself. (See MPEP 2106.05(f) where mere instructions to apply an exception does not render an abstract idea patent eligible). There is no indication that the additional limitations alone or in combination improves the functioning of a computer or any other technology, improves another technology or technical field, or effects a transformation or reduction of a particular article to a different state or thing. Moreover, the invention may leverage well-known computing systems, environments, and/or configurations that might be suitable for use with the present invention include personal computers, server computers, hand-held or laptop devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments that include any of the above-mentioned systems or devices, and the like (specification par. 17). Therefore, the claims are not patent eligible.
In conclusion, the claims are directed to the abstract idea of assessing performance of models. The claims do not provide an inventive concept, because the claims do not recite additional elements or a combination of elements that amount to significantly more than the judicial exception of the claims. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology, and the collective functions merely provide conventional computer implementation. Therefore, whether taken individually or as an order combination, the claims are nonetheless rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
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.
Although the independent claims at issue are not identical, they are not patentably distinct from the patented independent claims. Below is a comparison of patented claim 10 to pending claim 1 below.
Claims 1, 8, and 15 are rejected on the ground of nonstatutory double patenting as being unpatentable over claim 10 of U.S. Patent No. 11,923,094 in view of Murata US2014/0236630.
Pending claim 1 recites:
A computer-implemented method comprising: extracting medical information from a set of electronic medical records associated with a population of individuals having a common medical condition; (claim 10 recites receiving medical information from a set of electronic medical records associated with the individual having a medical condition)
computing, based on the medical information and by using a predictive model, a plurality of monitoring values, the plurality of monitoring values including at least a first monitoring value and a second monitoring value for each individual within the population, wherein each of the plurality of monitoring values indicates a risk level of a plurality of risk levels; (claim 10 recites determining a plurality of monitoring values computed for the individual using the predictive model; determining a plurality of actions taken for the individual, wherein each action taken is triggered by at least one monitoring value within the plurality of monitoring values;)
determining, from the medical information, a plurality of actions taken, each action taken within the plurality of actions taken being in response to the first monitoring value and being performed before computation of the second monitoring value for each individual, each action taken corresponding to a recommended action generated by the predictive model in response to the first monitoring value, wherein the recommended action is generated prior to a first discharge of the individual from a healthcare facility; (claim 10 recites determining, for each action taken, a trend in monitoring values based on a triggering monitoring value and a reactive monitoring value, wherein the triggering monitoring value triggered the action taken and the reactive monitoring value was computed after the action taken, each action taken corresponding to a recommended action by the predictive model in response to the first monitoring value, wherein the recommended action is generated prior to a first discharge of the individual from a healthcare facility;)
associating each action taken for each individual with a trend in monitoring values and an amount of time between when the recommended action is provided and when the action is taken, the trend being based on at least the first monitoring value and the second monitoring value for each individual; (claim 10 recites associating the action taken for each individual with the trend in monitoring values; determining a plurality of time periods, wherein each time period within the plurality of time periods is an amount of time between the a time the recommended action is provided and the action being taken, wherein each time period occurs prior to the first discharge)
generating an assessment of the predictive model based on the frequency, the trend associated with the action taken for each individual, and the amount of time; generating an assessment of the predictive model based on the trend associated with the action taken for each individual and the amount of time; (claim 10 recites generating an assessment of the predictive model based on the trend associated with the action taken for each individual and the amount of time, the assessment of the predictive model indicating at least whether occurrence of the common medical condition within the population of individuals improved with use of the predictive model and indicating whether one or more time periods within the plurality of time periods is more likely than other time periods to improve occurrence of the common medical condition within the population of individuals)
adjusting the predictive model based on the generated assessment; (claim 10 recites adjusting the predictive model based on the generated assessment)
determining, using the adjusted predictive model, a typical trajectory of the medical condition for the population of individuals to reach from a first risk level of the plurality of risk levels to a second risk level of the plurality of risk levels, in response to the plurality of actions taken for the common medical condition; and (claim 10 recites determining, using the adjusted predictive model and in response to the action for the medical condition, a second time taken by an individual to reach, from the first risk level of the plurality of risk levels, to a second risk level of the plurality of risk levels)
generating an alert when a trajectory as generated using the adjusted predictive model for an individual deviates from the typical trajectory (claim 10 recites generating an alert, using the adjusted predictive model, when the second time taken by the individual to reach from the first risk level of the plurality of risk levels to a second risk level of the plurality of risk levels deviates from the first time taken by the population).
The patented claims do not specifically teach the following limitations met by Murata,
stratifying the population of individuals corresponding to their first monitoring values or the risk levels; (Murata par. 86 teaches stratification of patient population, where rankings can be by severity, complexity, acuity, risk, actionability, likelihood of benefit, or need)
estimating, for each group of individuals, a frequency with which the recommended action when taken generates a positive trend, wherein each group of individuals corresponds to a different first monitoring value or the risk level; (Murata par. 85 teaches the missed opportunities approach starts by retrieving evidence-based treatment recommendations from the literature. The invention then determines whether each patient has met the standard by identifying the specific formulation, the prescribed dose, whether prescriptions meet the standard, the level of patient adherence, the average dose taken, duration of treatment, the serum level achieved, the biologic response, measures of drug toxicity, and whether recommended drugs are used appropriately in combination. Moreover, the invention performs this analysis on all patients across the institution and at a frequency chosen by the user.)
It would have been obvious to one of ordinary skill in the art at the time the invention was filed to modify the systems and methods as taught by the patented claims to stratify the population and estimate a frequency that the recommended action is positive as taught by Murata with the motivation to there is a need for improved health analytics including analytics that create a new standard for quality improvement and cost containment activities (par. 22).
Claims 4, 11, and 18 of the instant application maps to claims 2 and 3 of the ‘094 patent. Claim 5, 12, and 19 of the instant application maps to claim 4 of the ‘094 patent. Claim 6 and 13 of the instant application maps to claim 5 of the ‘094 patent. Claim 7, 14, and 20 of the instant application maps to claim 6 of the ‘094 patent.
Claims 1, 8, and 15 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, 8, and 9 of U.S. Patent No. 11,244,764 in view of Murata US2014/0236630.
Pending claim 1 recites:
A computer-implemented method comprising: extracting medical information from a set of electronic medical records associated with a population of individuals having a common medical condition; (claim 1 recites receiving medical information from a set of electronic medical records associated with the individual having a medical condition)
computing, based on the medical information and by using a predictive model, a plurality of monitoring values, the plurality of monitoring values including at least a first monitoring value and a second monitoring value for each individual within the population, wherein each of the plurality of monitoring values indicates a risk level of a plurality of risk levels; (claim 1 recites determining a plurality of monitoring values computed for the individual using the predictive model; determining a plurality of actions taken for the individual, wherein each action taken is triggered by at least one monitoring value within the plurality of monitoring values;)
determining, from the medical information, a plurality of actions taken, each action taken within the plurality of actions taken being in response to the first monitoring value and being performed before computation of the second monitoring value for each individual, each action taken corresponding to a recommended action generated by the predictive model in response to the first monitoring value, wherein the recommended action is generated prior to a first discharge of the individual from a healthcare facility; (claim 1 recites determining, for each action taken, a trend in monitoring values based on a triggering monitoring value and a reactive monitoring value, wherein the triggering monitoring value triggered the action taken and the reactive monitoring value was computed after the action taken, each action taken corresponding to a recommended action by the predictive model in response to the first monitoring value, wherein the recommended action is generated prior to a first discharge of the individual from a healthcare facility;)
associating each action taken for each individual with a trend in monitoring values and an amount of time between when the recommended action is provided and when the action is taken, the trend being based on at least the first monitoring value and the second monitoring value for each individual; (claim 1 recites associating the action taken for each individual with the trend in monitoring values; determining a plurality of time periods, wherein each time period within the plurality of time periods is an amount of time between the a time the recommended action is provided and the action being taken, wherein each time period occurs prior to the first discharge)
determining, using the adjusted predictive model, a typical trajectory of the medical condition for the population of individuals to reach from a first risk level of the plurality of risk levels to a second risk level of the plurality of risk levels, in response to the plurality of actions taken for the common medical condition; and (claim 8 recites determining a frequency of positive trends indicating improvement of the common medical condition when the action taken was the recommended action)
estimating, for each group of individuals, a frequency with which the recommended action when taken generates a positive trend, wherein each group of individuals corresponds to a different first monitoring value or the risk level; (claim 9 recites determining, for each medical professional identified, a frequency with which the action taken by the medical professional is a recommended action and a frequency with which the action taken by the medical professional is an alternative action)
generating an assessment of the predictive model based on the frequency, the trend associated with the action taken for each individual, and the amount of time; generating an assessment of the predictive model based on the trend associated with the action taken for each individual and the amount of time; (claim 1 recites generating an assessment of the predictive model based on the trend associated with the action taken for each individual and the amount of time, the assessment of the predictive model indicating at least whether occurrence of the common medical condition within the population of individuals improved with use of the predictive model and indicating whether one or more time periods within the plurality of time periods is more likely than other time periods to improve occurrence of the common medical condition within the population of individuals)
adjusting the predictive model based on the generated assessment; (claim 1 recites adjusting the predictive model based on the generated assessment).
The new limitations not recited in the patented claims but disclosed in Murata include:
stratifying the population of individuals corresponding to their first monitoring values or the risk levels; (Murata par. 86 teaches stratification of patient population, where rankings can be by severity, complexity, acuity, risk, actionability, likelihood of benefit, or need)
generating an alert when a trajectory as generated using the adjusted predictive model for an individual deviates from the typical trajectory (Murata par. 49 teaches alerting to patient care in critical processes so that they may be corrected.)
It would have been obvious to one of ordinary skill in the art at the time the invention was filed to modify the systems and methods as taught by the patented claims to stratify the population and generate an alert for deviations as taught by Murata with the motivation to there is a need for improved health analytics including analytics that create a new standard for quality improvement and cost containment activities (par. 22).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JAY M. PATEL whose telephone number is (571)272-6793 and email is jay.patel2@uspto.gov. The examiner can normally be reached on Monday-Friday 8AM-4:30PM.
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/JAY M. PATEL/Primary Examiner, Art Unit 3686
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