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 .
Priority
Examiner has given consideration to applicant’s Provisional Application No. 63/227,150 filed on July 29, 2021. For examining purposes of this application, the effective filing date will be July 29, 2021.
Status of the Claims
Claims 1-20 are currently pending and have been considered below.
Claims 1, 7 and 15 have been amended.
Response to Arguments
Applicant's arguments filed October 22, 2025 have been fully considered but they are not persuasive. Applicant argues on pages 6-8 under the heading Step 2A- Prong One that claims 1, 7, and 15 do not recite “Certain Methods of Organizing Human Activity” because there is no claimed human activity and because the claims cannot be practically performed in the human mind. Examiner disagrees. The Office acknowledges Applicant’s point that “generating a recommendation for a patient” may not be expressly recited in independent claims as amended; to the extent the prior characterization suggested such language in the independent claims, the characterization is withdrawn. However, the independent/ dependent claims still recite, inter alia: executing instructions by a processor to (i) retrieve patient predictors from a database, (ii) assign prediction scores, (iii) determine a diabetic retinopathy prediction via a weighted sum, and (iv) automatically pass an alert to a user. Under the broadest reasonable interpretation consistent with the specification (MPEP 2106.04(a)(2)), claims that (a) collect data, (b) analyze or evaluate the data using mathematical relationships, and (c) communicate results (e.g., an alert) that guide human decisions or actions are directed to abstract ideas—namely mental processes and certain methods of organizing human activity. See Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1353–54 (Fed. Cir. 2016) (collecting, analyzing, and displaying results is abstract); FairWarning IP, LLC v. Iatric Systems, Inc., 839 F.3d 1089, 1093–95 (Fed. Cir. 2016) (analyzing health data and generating alerts is abstract). Examiner notes that amended claim 1 and dependent claims 9 and 18 expressly involves directing or influencing human behavior and decision-making, which falls within the “certain methods of organizing human activity” grouping.
With respect to the “cannot be practically performed in the human mind” argument, courts have explained that activities involving evaluating large amounts of data, assigning scores, and computing sums or weights are mental processes even when performed with the aid of a computer. The volume of data or practicality concerns does not, by itself, remove the claim from the mental-process category. See MPEP 2106.04(a)(2)(III). See also Federal Circuit decisions below:
CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366 (Fed. Cir. 2011); (Claims to collecting and analyzing information and using rules to detect credit-card fraud were directed to an abstract mental process; the presence of computers or large volumes of data did not save eligibility.)
Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350 (Fed. Cir. 2016); (Claims that gather, analyze, and display information (even large-scale power-grid data) were directed to an abstract idea—collecting and analyzing information—and using generic computer components did not render them patentable.)
SAP Am., Inc. v. InvestPic, LLC, 898 F.3d 1161 (Fed. Cir. 2018); (Claims directed to statistical analysis and mathematical calculations were abstract; adding computer implementation and handling large data sets did not make them patent-eligible.)
Next, Applicant argues on pages 8-10 under the heading Step 2A- Prong Two that claims 1, 7, and 15 and dependent claims integrate the invention into a practical application. Specifically, Applicant argues the claims reflect a technological improvement because the “first algorithm” improves the functioning of the processor (Spec ¶¶ [0009], [0094]) and the amendments incorporate the algorithmic steps (Spec ¶ [0055]). Examiner disagrees. To integrate an exception into a practical application, the claims must recite a specific improvement to the functioning of the computer or another technology, not simply use a computer as a tool to implement the abstract idea. See MPEP 2106.04(d). The claimed “first algorithm” consists of retrieving predictors, assigning scores, computing a weighted sum, and issuing an alert. These steps describe the abstract data analysis itself, rather than a particular improvement in computer technology. The specification passages cited (¶¶ [0009], [0094]) describe improved outcomes at a high level but do not identify a particular technical mechanism that changes processor operation. MPEP 2106.04(d)(1) instructs that conclusory statements of improvement are insufficient absent claim language reflecting a specific technological advance.
Next, Applicant argues on pages 10-12 under the heading Step 2B that claims 1, 7, and 15 and dependent claims amount to significantly more than the judicial exception itself. Applicant argues that “when the examiner has concluded that certain claim elements recite well understood, routine, conventional activities in the relevant field, the examiner must expressly support the rejection in writing with one of the four options specified in Subsection III.” MPEP 2106.07(a). (emphasis in original). While this is true, Examiner never cited that “certain claim elements recite well understood, routine, conventional activities in the relevant field”. On the contrary, Examiner cited that the additional elements “amount to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept.”
The rejection of claims 1–20 under 35 U.S.C. § 101 is therefore maintained.
Next, Applicant argues on pages 12-14, prior art reference Kalkstein “generate a plurality of prediction scores, each prediction score being assigned to a particular patient predictor of at least five patient predictors in a database storing at least one patient record having first data, each prediction score further being assigned according to levels of the particular patient predictor” as seen in amended claim 1. Also, Applicant argues that Kalkstein’s clinical outcome prediction scores are not “prediction score[s] being assigned to ... a particular patient predictor ... according to levels of the particular patient predictor.” Examiner disagrees. As seen in Figure 9 Continued below, the items listed under “Analyte” are analogous to Applicant’s Patient Predictor and “Trend” is analogous to Applicant’s Prediction Score. As can be seen from Figure 9 Continued below, there are a “plurality of prediction scores, each prediction score being assigned to a particular patient predictor of at least five patient predictors…”
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Next Applicant argues that Kalkstein fails to teach “a weighted sum of the plurality of predictions scores” as set forth in claim 1. Applicant argues that Kalkstein teaches that a weighted sum / weighted average is taken of the scores of clinical outcome predictions to generate a "value" used to compare the individual against other individuals. [0147]. Examiner disagrees. As shown above, the items listed under “Analyte” are analogous to Applicant’s Patient Predictor and “Trend” is analogous to Applicant’s Prediction Score. Therefore, paragraph 147 as seen below teaches the limitation of “weighted sum of the plurality of predictions scores”.
[147] In another implementation, a value is computed for each individual as an aggregation (e.g., weighted sum and/or weighted average) of the scores of the clinical outcome predictions of the respective individual. The statistical distance requirement may be defined as the aggregated values of the scores of the individuals that are closest to the aggregated value of the scores of the target individual.
Applicant's arguments on page 14 fail to comply with 37 CFR 1.111(b) because they amount to a general allegation that the claims define a patentable invention without specifically pointing out how the language of the claims patentably distinguishes them from the references.
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 rejected under 35 U.S.C. 101 because the claimed invention is directed to to an abstract idea without significantly more.
Step 1
In the instant case, claims 1-20 are directed to a to a non-transitory computer readable medium (i.e. a manufacture). Thus, the claims fall within one of the four statutory categories. Nonetheless, the claims fall within the judicial exception of an abstract idea. (Step 1- Yes)
Step 2A- Prong 1
Independent claims 1, 7, and 15 recites steps that, under their broadest reasonable interpretations, cover Certain Methods of Organizing Human Activity and Mental Processes. Specifically,
Claim 1 recites:
generate a plurality of prediction scores, each prediction score being assigned to a particular patient predictor of at least five patient predictors in a database storing at least one patient record having first data, each prediction score further being assigned according to levels of the particular patient predictor;
determine a diabetic retinopathy prediction based at least in part on a weighted sum of the plurality of prediction scores; and
pass an alert to a user responsive to the diabetic retinopathy prediction being within a predetermined range.
Claim 7 recites:
generate a plurality of prediction scores, each prediction score being assigned to a particular patient predictor of at least five patient predictors in a database storing at least one patient record having first data, each prediction score further being assigned according to levels of the particular patient predictor;
determine a diabetic retinopathy prediction based at least in part on a weighted sum of the plurality of prediction scores; and
update the first data with second data responsive to the diabetic retinopathy prediction being within a predetermined range.
Claim 15 recites:
generate a plurality of prediction scores, each prediction score being assigned to a particular patient predictor of at least five patient predictors in a database storing at least one patient record having first data, each prediction score further being assigned according to levels of the particular patient predictor;
determine, by a first algorithm, a diabetic retinopathy prediction based at least in part on a weighted sum of the plurality of prediction scores; and
pass data indicative of the diabetic retinopathy prediction to a second algorithm responsive to the diabetic retinopathy prediction being within a predetermined range.
Except for the recitation of “non-transitory computer readable medium” in the preamble and “database” in the body of the claim, the above recited functions when considered as a whole, cover performance of the limitation as certain methods of organizing human activity. For example, a patient could provide several symptoms or other predicators to a doctor during an appointment, and the doctor might analyze the received predicators to make a diagnostic decision such as a list of potential diagnoses for the patient with associated degrees of urgency, severity, risk, etc. Also, generating a recommendation for a patient that includes a recommended procedure to treat a condition is diagnosing or determining a patient's health status and also falls under the abstract concept of managing personal behaviors of people. It is important to note that the examples provided by the MPEP such as social activities, teaching, and following rules or instructions are provided as examples and not an exclusive listing and MPEP 2106.04(a)(2) II C stating certain activity between a person and a computer may fall within the “certain methods of organizing human activity” grouping. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation as managing interactions between people, then it falls within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas. Accordingly, the claim recites an abstract idea. Claims 7 and 15 are also abstract for similar reasons.
Similarly, except for the recitation of “non-transitory computer readable medium” in the preamble and “database” in the body of the claim, the above limitations, under their broadest reasonable interpretation, cover performance of the limitation as mental processes. The claims recite actions that can be concepts performed in the mind of a person or with pen and paper. For example, a patient could provide several symptoms or other predicators to a doctor during an appointment, and the doctor could write everything down with pen and paper and then make a diagnostic decision by writing down a list of potential diagnoses for the patient with associated degrees of urgency, severity, risk, etc. See also MPEP 2106.04(a)(2) III C where using a generic computer for a judicial exception has been found to be abstract. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation as a mental process, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea. Claims 7 and 15 are also abstract for similar reasons. (Step 2A-Prong 1: YES. The claims are abstract).
Step 2A- Prong 2
This judicial exception is not integrated into a practical application. In particular, the claims only recite: “non-transitory computer readable medium” in the preamble and “database” in the body of the claims 1, 7 and 15. The computer hardware (non-transitory computer readable medium and database) are recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using a generic computer component. See Applicant's specification paragraphs 29-30 and 32 about implementation using various computing devices and MPEP 2106.05(f) where applying a computer as a tool is not indicative of significantly more. Accordingly, these additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Therefore claims 1, 7, and 15 are directed to an abstract idea without a practical application. (Step 2A-Prong 2: NO. The additional claimed elements are not integrated into a practical application).
Step 2B
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, when considered separately and as an ordered combination, they do not add significantly more (also known as an “inventive concept’) to the exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of “non-transitory computer readable medium” and “database” amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Accordingly, these additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Thus claims 1, 7, and 15 are not patent eligible. (Step 2B: NO. The claims do not provide significantly more).
Dependent claims 2-6, 8-14, and 16-20 further define the abstract idea that is present in their respective independent claims 1, 7, and 15 and thus correspond to Certain Methods of Organizing Human Activity and Mental Processes and hence are abstract for the reasons presented above. The dependent claims include a display (see claims 6, 9 and 18) as an additional element, however it has been determined to be generic, and therefore considered to be insignificant extra-solution activity (see MPEP 2106.05(g)). The dependent claims themselves are abstract or further limit abstract concepts. Therefore, the claims 2-6, 8-14, and 16-20 are directed to an abstract idea. Thus, the claims 1-20 are not patent-eligible.
Claim Rejections - 35 USC § 102
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.
Claim(s) 1-3, 5-13, and 15 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Kalkstein et al., U.S. Patent Application Publication 2020/0395129 (See PTO-892, Ref A).
As per claim 1, Kalkstein teaches a non-transitory computer readable medium having computer executable instructions that when executed cause a processor to (see paragraph 82):
generate a plurality of prediction scores, each prediction score being assigned to a particular patient predictor of at least five patient predictors in a database storing at least one patient record having first data, each prediction score further being assigned according to levels of the particular patient predictor (see Figure 9 Continued, and paragraph 25, 108, 190);
determine a diabetic retinopathy prediction based at least in part on a weighted sum of the plurality of prediction scores (see paragraphs 108, computes a set of clinical outcome prediction scores, 147, a value is computed for each individual as an aggregation (e.g., weighted sum and/or weighted average) of the scores of the clinical outcome predictions of the respective individual, and 159, J denotes diabetic retinopathy); and
pass an alert to a user responsive to the diabetic retinopathy prediction being within a predetermined range data (see paragraphs 180, provided for presentation on the client terminal, 181, GUI 400 presenting computation of the prevalence of clinical outcomes, and Figure 4, see paragraph 132, The score may be indicative of the computed probability of the patient developing the clinical outcome within the upcoming predefined interval (e.g., within the next 1, 3, or 5 years). The score of the clinical outcome may be associated with a weight, for example, relatively more serious medical conditions (e.g., cancer, death), are associate with relatively larger weights in comparison to relatively less serious medical conditions (e.g., trigeminal neuralgia).).
As per claim 2, Kalkstein teaches the non-transitory computer readable medium of claim 1 as seen above. Kalkstein further teaches wherein the user is at least one of a patient and a physician (see paragraph 191, client terminals of users (e.g., patients 1004A, physicians 1004B).
As per claim 3, Kalkstein teaches the non-transitory computer readable medium of claim 1 as seen above. Kalkstein further teaches wherein the alert is provided in at least one of an aural form or a visual form (see paragraphs 180, provided for presentation on the client terminal, 181, GUI 400 presenting computation of the prevalence of clinical outcomes, and Figure 4).
As per claim 5, Kalkstein teaches the non-transitory computer readable medium of claim 1 as seen above. Kalkstein further teaches wherein the at least five patient predictors are in a range from five patient predictors to ten patient predictors (see Figure 7, items 700 and 702).
As per claim 6, Kalkstein teaches the non-transitory computer readable medium of claim 1 as seen above. Kalkstein further teaches to display a user interface on a display, the user interface having a plurality of fields operable to receive input from a user, the input indicative of the at least five patient predictors (see paragraphs 79 physical user interfaces (e.g., display), 106-107, and Figure 2, items 202 and 218).
As per claim 7, Kalkstein teaches a non-transitory computer readable medium having computer executable instructions that when executed cause a processor to (see paragraph 82):
generate a plurality of prediction scores, each prediction score being assigned to a particular patient predictor of at least five patient predictors in a database storing at least one patient record having first data, each prediction score further being assigned according to levels of the particular patient predictor (see Figure 9 Continued, and paragraph 25, 108, 190);
determine a diabetic retinopathy prediction based at least in part on a weighted sum of the plurality of prediction scores (see paragraphs 108, computes a set of clinical outcome prediction scores, 147, a value is computed for each individual as an aggregation (e.g., weighted sum and/or weighted average) of the scores of the clinical outcome predictions of the respective individual, and 159, J denotes diabetic retinopathy); and
update the first data with second data responsive to the diabetic retinopathy prediction being within a predetermined range (see paragraph 124-125, additional data is extracted from a medical record of the respective patient, for example, from the patient's EHR 210A. The additional data is added to the training and/or validation datasets. The additional data may include demographic parameters, for example, age, and gender, and 131-132, The score may be indicative of the computed probability of the patient developing the clinical outcome within the upcoming predefined interval (e.g., within the next 1, 3, or 5 years). The score of the clinical outcome may be associated with a weight, for example, relatively more serious medical conditions (e.g., cancer, death), are associate with relatively larger weights in comparison to relatively less serious medical conditions (e.g., trigeminal neuralgia).)).
As per claim 8, Kalkstein teaches the non-transitory computer readable medium of claim 7 as seen above. Kalkstein further teaches wherein the at least five patient predictors are in a range from five patient predictors to ten patient predictors (see Figure 7, items 700 and 702)
As per claim 9, Kalkstein teaches the non-transitory computer readable medium of claim 7 as seen above. Kalkstein further teaches to display a user interface on a display (see paragraph 79), the user interface having a plurality of fields operable to receive input from a user, the input indicative of the at least five patient predictors (see paragraphs 79 physical user interfaces (e.g., display), 106-107, and Figure 2, items 202 and 218).
As per claim 10, Kalkstein teaches the non-transitory computer readable medium of claim 9 as seen above. Kalkstein further teaches wherein the user is at least one of a patient and a physician (see paragraph 191, client terminals of users (e.g., patients 1004A, physicians 1004B)).
As per claim 11, Kalkstein teaches the non-transitory computer readable medium of claim 7 as seen above. Kalkstein further teaches to pass an alert to a user responsive to the diabetic retinopathy prediction being within a predetermined range (see paragraphs 180, provided for presentation on the client terminal, 181, GUI 400 presenting computation of the prevalence of clinical outcomes, and Figure 4, see paragraph 132, The score may be indicative of the computed probability of the patient developing the clinical outcome within the upcoming predefined interval (e.g., within the next 1, 3, or 5 years). The score of the clinical outcome may be associated with a weight, for example, relatively more serious medical conditions (e.g., cancer, death), are associate with relatively larger weights in comparison to relatively less serious medical conditions (e.g., trigeminal neuralgia).).
As per claim 12, Kalkstein teaches the non-transitory computer readable medium of claim 11 as seen above. Kalkstein further teaches wherein the user is at least one of a patient and a physician (see paragraph 191, client terminals of users (e.g., patients 1004A, physicians 1004B).
As per claim 13, Kalkstein teaches the non-transitory computer readable medium of claim 11 as seen above. Kalkstein further teaches wherein the alert is provided in at least one of an aural form or a visual form (see paragraphs 180, provided for presentation on the client terminal, 181, GUI 400 presenting computation of the prevalence of clinical outcomes, and Figure 4).
As per claim 15, Kalkstein teaches non-transitory computer readable medium having computer executable instructions that when executed cause a processor to:
generate a plurality of prediction scores, each prediction score being assigned to a particular patient predictor of at least five patient predictors in a database storing at least one patient record having first data, each prediction score further being assigned according to levels of the particular patient predictor (see Figure 9 Continued, and paragraph 25, 108, 190);
determine, by a first algorithm, a diabetic retinopathy prediction based at least in part on a weighted sum of the plurality of prediction scores (see paragraphs 108, computes a set of clinical outcome prediction scores, 147, a value is computed for each individual as an aggregation (e.g., weighted sum and/or weighted average) of the scores of the clinical outcome predictions of the respective individual, and 159, J denotes diabetic retinopathy); and
pass data indicative of the diabetic retinopathy prediction to a second algorithm responsive to the diabetic retinopathy prediction being within a predetermined range (see paragraph 124-125, additional data is extracted from a medical record of the respective patient, for example, from the patient's EHR 210A. The additional data is added to the training and/or validation datasets. The additional data may include demographic parameters, for example, age, and gender, and 131-132, The score may be indicative of the computed probability of the patient developing the clinical outcome within the upcoming predefined interval (e.g., within the next 1, 3, or 5 years). The score of the clinical outcome may be associated with a weight, for example, relatively more serious medical conditions (e.g., cancer, death), are associate with relatively larger weights in comparison to relatively less serious medical conditions (e.g., trigeminal neuralgia).)).
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.
Claim(s) 4 and 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kalkstein et al., U.S. Patent Application Publication 2020/0395129 (See PTO-892, Ref A) in view of Bedworth et al., U.S. Patent Application Publication 2017/0100030 (See PTO-892, Ref B).
As per claim 4, Kalkstein teaches the non-transitory computer readable medium of claim 1 as seen above. Kalkstein does not explicitly teach wherein the alert is indicative of at least one of an eye examination recommendation and an eye examination frequency.
Bedworth teaches wherein the alert is indicative of at least one of an eye examination recommendation and an eye examination frequency (see paragraph 54 and 110, If the user selects the ‘Make Diagnosis’ button, at block 312, the treatment recommendation module 240 determines information related to a diagnosis and a management/treatment recommendation based on the inputs provided by the user. Information related to a diagnosis may include no evidence of retinopathy, mild NPDR, moderate NPDR, severe NPDR, PDR, no diabetic macular edema, diabetic macular edema, clinically significant macular edema, or no diagnosis/ungradable. Information related to treatment recommendation may include a recommendation for reevaluation and/or a recommendation for a referral (e.g, reevaluate in 1 year, reevaluate in 6 months, refer to ophthalmologist within 4 months, refer to ophthalmologist within 2 months, refer to ophthalmologist within 6 months, and refer for dilated eye examination).).
Therefore, it would be prima facie obvious to a person of ordinary skill in the art before the effective filing date of the invention to combine the teachings of Kalkstein and Bedworth to recommend an eye examination because early treatment can slow the progression of retinopathy as taught by Bedworth (see paragraph 55).
As per claim 14, Kalkstein teaches the non-transitory computer readable medium of claim 11 as seen above. Kalkstein does not explicitly teach wherein the alert is indicative of at least one of an eye examination recommendation and an eye examination frequency.
Bedworth teaches wherein the alert is indicative of at least one of an eye examination recommendation and an eye examination frequency (see paragraph 54 and 110).
Therefore, it would be prima facie obvious to a person of ordinary skill in the art before the effective filing date of the invention to combine the teachings of Kalkstein and Bedworth to recommend an eye examination because early treatment can slow the progression of retinopathy as taught by Bedworth (see paragraph 55).
Claim(s) 16-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kalkstein et al., U.S. Patent Application Publication 2020/0395129 (See PTO-892, Ref A) in view of Oren et al., U.S. Patent Application Publication 2019/0034590 (See PTO-892, Ref C).
As per claim 16, Kalkstein teaches the non-transitory computer readable medium of claim 15 as seen above. Oren further teaches wherein the second algorithm is operable to generate a readmission prediction (see paragraph 99, We predicted a future unplanned readmission within the subsequent 30 days after a discharge from a hospitalization, given all of the data elements above during and prior to the admission.).
Therefore, it would be prima facie obvious to a person of ordinary skill in the art before the effective filing date of the invention to combine the teachings of Kalkstein and Oren to generate a readmission prediction because it would assist healthcare providers to allocate their attention efficiently among the overabundance of information from diverse sources as taught by Oren (see paragraph 4).
As per claim 17, Kalkstein teaches the non-transitory computer readable medium of claim 15 as seen above. Kalkstein further teaches wherein the at least five patient predictors are in a range from five patient predictors to ten patient predictors (see Figure 7, items 700 and 702).
As per claim 18, Kalkstein teaches the non-transitory computer readable medium of claim 15 as seen above. Kalkstein further teaches to display a user interface on a display, the user interface having a plurality of fields operable to receive input from a user, the input indicative of the at least five patient predictors (see paragraphs 79 physical user interfaces (e.g., display), 106-107, and Figure 2, items 202 and 218).
As per claim 19, Kalkstein teaches the non-transitory computer readable medium of claim 18 as seen above. Kalkstein further teaches wherein the user is at least one of a patient and a physician (see paragraph 191, client terminals of users (e.g., patients 1004A, physicians 1004B).
As per claim 20, Kalkstein teaches the non-transitory computer readable medium of claim 16 as seen above. Kalkstein further teaches to pass an alert to a user being within a predetermined range. Oren further teaches the concept of a readmission prediction (see paragraph 99, We predicted a future unplanned readmission within the subsequent 30 days after a discharge from a hospitalization, given all of the data elements above during and prior to the admission.).
Therefore, it would be prima facie obvious to a person of ordinary skill in the art before the effective filing date of the invention to combine the teachings of Kalkstein and Oren to pass an alert to a user responsive to readmission prediction being within a predetermined range because it would assist healthcare providers to allocate their attention efficiently among the overabundance of information from diverse sources as taught by Oren (see paragraph 4).
Conclusion
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 SHAHID R MERCHANT whose telephone number is (571)270-1360. The examiner can normally be reached M-F 7:30-5.
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/Shahid Merchant/ Supervisory Patent Examiner, Art Unit 3684