Detailed Notice
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 1-37 are currently pending.
Claims 1, 2, 17, 19 and 27-33 are amended.
Claims 1-37 are rejected.
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 1-37 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:
In the instant case, claims 1-27 are directed toward a computer-implemented method (i.e., process), claims 28-32 are directed toward a non-transitory computer readable medium (i.e., manufacture), and claims 33-37 are directed toward a system (i.e., machine). Thus, each of the claims falls within one of the four statutory categories. Nevertheless, the claims fall within the judicial exception of an abstract idea.
Step 2A—Prong 1:
Independent claims 1, 28, and 33 recites steps that, under their broadest reasonable interpretations, cover performance of the limitations of a certain method of organizing human activity but for the recitation of generic computer components.
Claim 1 recites: “A computer-implemented method for providing patient-specific medical care to a patient, the method comprising: receiving patient data; based on the patient data, generating a multi-stage surgical plan for treating a spine and/or spinal region of the patient, wherein generating the multi-stage surgical plan includes: simulating, using at least one virtual model of the patient, a first treatment stage having a first surgical procedure, a first target location along the spine for the first surgical procedure, and a first period for performing the first surgical procedure, and simulating, using the at least one virtual model of the patient, a second treatment stage having a second surgical procedure, a second target location along the spine for the second surgical procedure, and a second period for performing the second surgical procedure, wherein the second treatment stage is based at least in part on a predicted outcome of the first treatment stage, the predicted outcome including one or more simulated post-operative spinal metrics of the patient associated with performing the first treatment stage, wherein the second treatment stage is spaced apart in time from the first treatment stage, and wherein stimulating the second treatment stage occurs before the first surgical procedure is performed; and transmitting the multi-stage surgical plan for surgeon review”.
The limitations of receiving patient data; based on the patient data, generating a multi-stage surgical plan for treating a spine and/or spinal region of the patient, wherein generating the multi-stage surgical plan includes: simulating, a first treatment stage having a first surgical procedure, a first target location along the spine for the first surgical procedure, and a first period for performing the first surgical procedure, and simulating, a second treatment stage having a second surgical procedure, a second target location along the spine for the second surgical procedure, and a second period for performing the second surgical procedure, wherein the second treatment stage is based at least in part on a predicted outcome of the first treatment stage, the predicted outcome including one or more simulated post-operative spinal metrics of the patient associated with performing the first treatment stage, wherein the second treatment stage is spaced apart in time from the first treatment stage, and wherein stimulating the second treatment stage occurs before the first surgical procedure is performed; and transmitting the multi-stage surgical plan for surgeon review, given the broadest reasonable interpretation, cover the abstract idea of a certain method of organizing human activity because they recite managing personal behavior or relationships or interactions between people (i.e. social activities, teaching, and following rules or instructions—in this case the aforementioned steps recite a process of receiving, generating, simulating, and transmitting, which is properly interpreted as a “personal behavior”), but instead automates the process via a computer model, 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.
Additionally, claim 28 recites: “A non-transitory computer readable medium storing computer-executable instructions for generating multi-stage surgical plans using a computing system, wherein the instructions, when executed, cause the computing system to: receive patient data; based on the patient data, generate a multi-stage surgical plan for treating a spine and/or spinal region of a patient, wherein generating the multi-stage surgical plan includes: simulating, using at least one virtual model of the patient, a first treatment stage having a first surgical procedure, a first target location along the spine for the first surgical procedure, and a first period for performing the first surgical procedure, and simulating, using the at least one virtual model of the patient, a second treatment stage having a second surgical procedure, a second target location along the spine for the second surgical procedure, and a second period for performing the second surgical procedure, wherein the second treatment stage is based at least in part on a predicted response to the first treatment stage, the predicted response including one or more simulated post-operative spinal metrics of the patient associated with performing the first treatment stage, wherein the second treatment stage is spaced apart in time from the first treatment stage, and wherein stimulating the second treatment stage occurs before the first surgical procedure is performed; and transmit the multi-stage surgical plan for surgeon review”.
The limitations of receive patient data; based on the patient data, generate a multi-stage surgical plan for treating a spine and/or spinal region of a patient, wherein generating the multi-stage surgical plan includes: simulating, a first treatment stage having a first surgical procedure, a first target location along the spine for the first surgical procedure, and a first period for performing the first surgical procedure, and simulating, a second treatment stage having a second surgical procedure, a second target location along the spine for the second surgical procedure, and a second period for performing the second surgical procedure, wherein the second treatment stage is based at least in part on a predicted response to the first treatment stage, the predicted response including one or more simulated post-operative spinal metrics of the patient associated with performing the first treatment stage, wherein the second treatment stage is spaced apart in time from the first treatment stage, and wherein stimulating the second treatment stage occurs before the first surgical procedure is performed; and transmit the multi-stage surgical plan for surgeon review, given the broadest reasonable interpretation, cover the abstract idea of a certain method of organizing human activity because they recite managing personal behavior or relationships or interactions between people (i.e. social activities, teaching, and following rules or instructions—in this case the aforementioned steps recite a process of receiving, generating, simulating, and transmitting, which is properly interpreted as a “personal behavior”), but instead automates the process via a computer model or machine learning, 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.
Additionally, claim 33 recites: “A system for providing patient-specific medical treatment, the system comprising: one or more processors; and a memory storing instructions that, when executed by the one or more processors, case the system to perform operations comprising: receive patient data; based on the patient data, generate a multi-stage surgical plan for treating a spine and/or spinal region of a patient, wherein generating the multi-stage surgical plan includes: simulating, using at least one virtual model of the patient, a first treatment stage having a first surgical procedure, a first target location along the spine for the first surgical procedure, and a first period for performing the first surgical procedure, and simulating, using the at least one virtual model of the patient, a second treatment stage having a second surgical procedure, a second target location along the spine for the second surgical procedure, and a second period for performing the second surgical procedure, wherein the second treatment stage is based at least in part on a predicted response to the first treatment stage, the predicted response including one or more simulated post-operative spinal metrics of the patient associated with performing the first treatment stage, wherein the second treatment stage is spaced apart in time from the first treatment stage, and wherein stimulating the second treatment stage occurs before the first surgical procedure is performed; and transmit the multi-stage surgical plan for surgeon review”.
The limitations of receive patient data; based on the patient data, generate a multi-stage surgical plan for treating a spine and/or spinal region of a patient, wherein generating the multi-stage surgical plan includes: simulating, a first treatment stage having a first surgical procedure, a first target location along the spine for the first surgical procedure, and a first period for performing the first surgical procedure, and simulating, a second treatment stage having a second surgical procedure, a second target location along the spine for the second surgical procedure, and a second period for performing the second surgical procedure, wherein the second treatment stage is based at least in part on a predicted response to the first treatment stage, the predicted response including one or more simulated post-operative spinal metrics of the patient associated with performing the first treatment stage, wherein the second treatment stage is spaced apart in time from the first treatment stage, and wherein stimulating the second treatment stage occurs before the first surgical procedure is performed; and transmit the multi-stage surgical plan for surgeon review, given the broadest reasonable interpretation, cover the abstract idea of a certain method of organizing human activity because they recite managing personal behavior or relationships or interactions between people (i.e. social activities, teaching, and following rules or instructions—in this case the aforementioned steps recite a process of receiving, generating, simulating, and transmitting, which is properly interpreted as a “personal behavior”), but instead automates the process via a computer model or machine learning, 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.
Dependent claims 2-27, and 29-32, and 34-37 include other limitations, as well as specific step of data to be processed, received, and applied, but these only serve to further limit the abstract idea and do not add and additional elements, and hence are nonetheless directed towards fundamentally the same abstract idea as independent claims 1, 28, and 33. However, recitation of an abstract idea is not the end of the 35 U.S.C. 101 analysis. Each of the claims must be analyzed for additional elements that indicate the abstract idea is integrated into a practical application to determine whether the claim is considered to be “directed to” an abstract idea.
Step 2A—Prong 2:
Claims 1-37 are not integrated into a practical application because the additional elements (i.e. any limitations that are not identified as part of the abstract idea) amount to no more than limitations which:
Amount to mere instructions to apply an exception—for example, the recitation of “virtual model”, “processors”, “memory”, “non-transitory computer readable medium”, and “computing system”, which amount to merely invoking a computer as a tool to perform the abstract idea, e.g. see FIG. 1, [0027, [0037], [0073]-[0075], and [0080], of the present specification, and see further MPEP 2106.05(f);
Generally linking the abstract idea to a particular technological environment or field of use, for example, “using at least one virtual model of the patient”, “one or more processors; and a memory storing instruction”, and “non-transitory computer readable medium storing computer-executable instructions for generating multi-stage surgical plans using a computing system, wherein the instructions, when executed, cause the computing system to”, which amounts to limiting the abstract idea to the field of technology/the environment of computers, see MPEP 2106.05(h); and/or
Merely acquiring information for further analysis by the system and the particular manner of acquisition is not described or shown to be important, for example, “receiving patient data”, which amounts to insignificant extra-solution activity in the form of mere data gathering because it merely functions tangentially to the main idea of the invention and serves only to bring in the data necessary for the inventions main analysis, see MPEP 2106.05(g).
Additionally, dependent claims 2-27, and 29-32, and 34-37 include other limitations, but as stated above, the limitations recited by these claims do not include any additional elements beyond those already recited in independent claims 1, 28, and 33, and hence also do not integrate the aforementioned abstract idea 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 the additional elements (i.e. the elements other than the abstract idea), as stated above, are directed towards no more than limitations that amount to mere instructions to apply the exception, and/or generally link the abstract idea to a particular technological environment or field of use, which even when reevaluated under the considerations of Step 2B of the analysis, do not amount to “significantly more” than the abstract idea.
Dependent claims 2-27, and 29-32, and 34-37 include other limitations, but none of these limitations are deemed significantly more than the abstract idea because, as stated above, the aforementioned dependent claims do not recite any additional elements not already recited in independent claims 1, 27, and 33, and hence do not amount to “significantly more” than the abstract idea.
Additionally, the additional elements (i.e., “receiving patient data”), add extra solution activity, which comprises limitations which amount to elements that have been recognized as well-understood, routine, and conventional activity in a particular field as demonstrated by:
Relevant court decisions (See MPEP 2106.05(d)(II)):
Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); 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); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014) (“Unlike the claims in Ultramercial, the claims at issue here specify how interactions with the Internet are manipulated to yield a desired result‐‐a result that overrides the routine and conventional sequence of events ordinarily triggered by the click of a hyperlink.” (emphasis added)).
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 1-37 are nonetheless rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
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) 1-14 and 17-33 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Nawana et al. (US 20190110784 A1), hereinafter Nawana.
Regarding claim 1 Nawana teaches a computer-implemented method for providing patient-specific medical care to a patient (Nawana, Abstract), the method comprising: receiving patient data (Nawana, [0129]: “The patient's Electronic Medical Record (EMR) can be linked by their health care provider to the diagnosis and treatment database 300. The symptoms and historical treatments identified for a particular patient can be accessed at any time in the future using the system 10, which can help facilitate continued treatment and evaluation of the patient, e.g., by allowing severity of symptoms to be tracked over time as the patient and/or other user(s) updates the system 10. Symptoms for a patient can be stored in the diagnosis and treatment database 300, e.g., in the diagnosis database 310, with a date and time stamp, which can facilitate the continued treatment and evaluation of the patient. Similarly, other data discussed herein as being related to a particular patient can be stored in the diagnosis treatment database 300, the pre-op database 302, the operation database 304, the post-op database 306, and the recovery database 308 as being associated with the patient and as having a date and time stamp. The patient's EMR, historical treatments, images, lab results, physical exam results, symptoms, etc., to the extent they are provided to the system 10, can be compared to other patient data included in the diagnosis and treatment database 300 to compile outcome predictions based on retrospective results from treatment results of patients with similar indications. This compilation can allow medical care providers and patients to make more informed treatment and procedural decisions”); based on the patient data, generating a multi-stage surgical plan for treating a spine and/or spinal region of the patient, wherein generating the multi-stage surgical plan includes (Nawana, [0144]: “the system 10 can be used in a spinal context, such as to test for the presence of cytokines (such as Fibronectin-aggrecan complex, FAC) and growth factors (such as TNF-alpha or IL-8) in the intervertebral disc of patients, in specifically DDD or herniated disc cases in the lumbar, thoracic, or cervical spine… As the system 10 continually runs these tests on more patients, and then subsequently tracks the test's validity in diagnosing the patient's condition by relating it to the patient outcome of the chosen surgical treatments for DDD and/or herniated disc, the system 10 will gain a more refined intelligence of when to prescribe the test, and when to prescribe certain medications and/or treatments (invasive or non-surgical) based on the results of the test… This identification will help in the initial diagnosis phase to develop an appropriate treatment plan based on the existence of these high-risk markers in combination with the patient's symptoms. For example, if there are clear markers that indicate that the condition will only worsen with time and that surgical intervention will be necessary, then a less invasive surgery can be done early before the condition worsens and results in more pain and disability. If the patient is lacking high risk markers, then a more conservative treatment would be recommended as a first course of action”, [0155], and [0229]): simulating, using at least one virtual model of the patient (Nawana, [0029]: “The pre-op module allows a three-dimensional electronic simulation of the selected invasive treatment to be performed on a virtual patient using a plurality of virtual instruments. The virtual patient is a model of the patient based on gathered medical data regarding the patient, and each of the plurality of virtual instruments are modeled on an actual instrument available for use in the selected invasive treatment. The pre-op module also stores the electronic simulation in a storage unit. The operation module compares an actual performance of the selected invasive treatment on the patient with the stored electronic simulation, provides electronic feedback regarding the comparison during the actual performance of the selected invasive treatment that indicates progress of the actual performance of the selected invasive treatment versus the stored electronic simulation, triggers an alarm if the comparison indicates that a step of the actual performance of the selected invasive treatment differs from the stored electronic simulation beyond a predetermined threshold amount of tolerable variance, and stores data regarding the actual performance of the selected invasive treatment in the storage unit”, [0170]: “More particularly, the pre-op module 202 can allow surgeons to electronically perform three-dimensional (3D) simulated surgeries on virtual models of patients to test surgical ease and/or potential surgical outcomes before actually performing the surgical procedure”, and [0174]-[0175]), a first treatment stage having a first surgical procedure (Nawana, [0025]: “a medical system is provided that includes a processor configured to receive plan data regarding a virtual performance of a surgical procedure on a patient, and to receive performance data regarding an actual performance of the surgical procedure on the patient. The performance data is received in real time with the actual performance of the surgical procedure. The processor is also configured to determine if the plan data varies from the performance data” and [0026]: “the processor can be configured to receive plan data regarding a plurality of virtual performances of the surgical procedure on a plurality of patients, and to receive performance data regarding a plurality actual performances of the surgical procedure on the plurality of patients”), a first target location along the spine for the first surgical procedure (Nawana ,[0158], [0174], [0243], [0244], and [0246]: “The procedure analysis module 230 can be configured to track the stereoscopic viewing device to help determine where to overlay the generated 3D model in a location where it can be visualized by the wearer of the stereoscopic viewing device. The procedure analysis module 230 can be configured to use the stereoscopic viewing device to overlay the generated 3D model on the physical object, e.g., the patient, in an anatomically correct location. In other words, the procedure analysis module 230 can be configured to project the generated 3D model of anatomy in a location corresponding to the patient's actual anatomy”), and a first period for performing the first surgical procedure (Nawana, [0025]: “The performance data is received in real time with the actual performance of the surgical procedure”, [0026]: “The performance data is received in real time with the actual performances of the surgical procedures. The processor can also be configured to determine if the plan data regarding the plurality of virtual performances varies from the performance data regarding the plurality actual performances, determine if any one or more of the determined variances are a same type of variance, and provide a recommendation to a user performing another virtual performance of the surgical procedure based on the one or more determined variances determined to be the same type of variance”, and [0041]-[0042]), and simulating, using at least one virtual model of the patient (Nawana, [0029]: “The pre-op module allows a three-dimensional electronic simulation of the selected invasive treatment to be performed on a virtual patient using a plurality of virtual instruments. The virtual patient is a model of the patient based on gathered medical data regarding the patient, and each of the plurality of virtual instruments are modeled on an actual instrument available for use in the selected invasive treatment. The pre-op module also stores the electronic simulation in a storage unit. The operation module compares an actual performance of the selected invasive treatment on the patient with the stored electronic simulation, provides electronic feedback regarding the comparison during the actual performance of the selected invasive treatment that indicates progress of the actual performance of the selected invasive treatment versus the stored electronic simulation, triggers an alarm if the comparison indicates that a step of the actual performance of the selected invasive treatment differs from the stored electronic simulation beyond a predetermined threshold amount of tolerable variance, and stores data regarding the actual performance of the selected invasive treatment in the storage unit”, [0170]: “More particularly, the pre-op module 202 can allow surgeons to electronically perform three-dimensional (3D) simulated surgeries on virtual models of patients to test surgical ease and/or potential surgical outcomes before actually performing the surgical procedure”, and [0174]-[0175]),a second treatment stage having a second surgical procedure (Nawana, [0038], [0167], [0178], and [0196]), a second target location along the spine for the second surgical procedure (Nawana, [0026], [0038], [0167], [0178], [0196], and [0262]-[0263]), and a second period for performing the second surgical procedure (Nawana, [0035] and [0295]), wherein the second treatment stage is based at least in part on a predicted outcome of the first treatment stage (Nawana, [0129]: “The patient's EMR, historical treatments, images, lab results, physical exam results, symptoms, etc., to the extent they are provided to the system 10, can be compared to other patient data included in the diagnosis and treatment database 300 to compile outcome predictions based on retrospective results from treatment results of patients with similar indications. This compilation can allow medical care providers and patients to make more informed treatment and procedural decisions”, [0186]: “During the simulated procedure, the SPP module 218 can be configured to use this predictive modeling to show where tissue and other structures are predicted to be, allowing for navigation around them. The SPP module simulation can utilize historical surgical and literature data to predict neural responses and/or changes based upon a predicted amount of retraction and/or decompression preformed. When the simulation is complete, the SPP module 218 can be configured to analyze the procedure for projected results, e.g., potential healing, potential increase in patient mobility after “X” amount of time, amount of correction, etc. The user can thus consult the projected results and decide whether to revise the surgery, such as if the projected results are less than the user would like and/or expect”, [0271], and [0284]), the predicted outcome including one or more simulated post-operative spinal metrics of the patient associated with performing the first treatment stage (Nawana, [0184]: “During the simulated procedure, the SPP module 218 can be configured to use this predictive modeling to show where tissue and other structures are predicted to be, allowing for navigation around them. The SPP module simulation can utilize historical surgical and literature data to predict neural responses and/or changes based upon a predicted amount of retraction and/or decompression preformed”, [0186]: “Users of the system 10 can run a predicted life changes module to assess potential future changes and assist in planning and refining the surgical procedure”, [0187]: “In the illustrated embodiment, the user 52 is simulating performance of a spinal procedure, but as mentioned above, the system 10 can be used to simulate other types of surgical procedures”, [0221], [0228], [0271]: “Individual analysis of surgical procedures can help predict outcomes of the procedure and/or can help the surgeon establish best practices and learn from previous experience on a personal, confidential level as evaluated by the system 10 acting as a neutral third party. Aggregated data can help hospital administrators develop a cost per hour for OR time, which can allow the hospital to improve efficiency and lower costs”, and [0230], [0284]: “The post-op module 206 can be configured to detect and analyze any variances and can be configured to modulate future predictive models using the detected and analyzed variances”, [0324]: “Thus, the predicted outcome of rehabilitation and treatment can be predicted for the patient if they continue therapies that historical patients have followed. This can increase patient compliance to rehabilitation therapies if the patient can compare their performance to others that have had the same procedure and similar rehabilitation therapy. The patient monitoring module 244 can be configured to suggest the modification of the patient's treatment post-op plan to the patient's care provider, e.g., by providing an alert to the care provider indicating that modification of the patient's post-op treatment plan is recommended. The care provider can review the modification and determine whether to modify the patient's treatment plan. Alternatively, the patient monitoring module 244 can be configured to automatically modify the patient's post-op treatment plan and inform the patient via an alert as to the modified post-op treatment plan”), wherein the second treatment stage is spaced apart in time from the first treatment stage (Nawana, [0129]: “The symptoms and historical treatments identified for a particular patient can be accessed at any time in the future using the system 10, which can help facilitate continued treatment and evaluation of the patient, e.g., by allowing severity of symptoms to be tracked over time as the patient and/or other user(s) updates the system 10… The patient's EMR, historical treatments, images, lab results, physical exam results, symptoms, etc., to the extent they are provided to the system 10, can be compared to other patient data included in the diagnosis and treatment database 300 to compile outcome predictions based on retrospective results from treatment results of patients with similar indications. This compilation can allow medical care providers and patients to make more informed treatment and procedural decisions”, [0186]: “During the simulated procedure, the SPP module 218 can be configured to use this predictive modeling to show where tissue and other structures are predicted to be, allowing for navigation around them. The SPP module simulation can utilize historical surgical and literature data to predict neural responses and/or changes based upon a predicted amount of retraction and/or decompression preformed. When the simulation is complete, the SPP module 218 can be configured to analyze the procedure for projected results, e.g., potential healing, potential increase in patient mobility after “X” amount of time, amount of correction, etc. The user can thus consult the projected results and decide whether to revise the surgery, such as if the projected results are less than the user would like and/or expect… This incorporation can be especially helpful with patients having variable and changing anatomies, e.g., young scoliosis patients with variable and changing curvatures. Users of the system 10 can run a predicted life changes module to assess potential future changes and assist in planning and refining the surgical procedure”, [0271], and [0284]), and wherein simulating the second treatment stage occurs before the first surgical procedure is performed (Nawana, [0022], [0038]: “ For another example, the plans for a first subset of the patients can include a non-surgical treatment, the plans for a second subset of the patients can include a surgical treatment, and determining the suggested plan can include comparing outcomes of the non-surgical treatments with outcomes of the surgical treatments. Determining the suggested plan can include choosing at least a one of the plans having a best outcome among the surgical treatments and the non-surgical treatments. For yet another example, determining the effectiveness can include determining an effect of each of the plans on the at least one medical diagnosis, and determining the suggested plan can include choosing at least a one of the plans having a most desired effect on the at least one medical diagnosis. For another example, the method can include receiving performance data regarding performances of surgical procedures included in each of the plans that include performance of the surgical procedure as at least part of the medical treatment, and determining the effectiveness can include choosing at least a one of the plans based at least on the performance data. For yet another example, providing the suggested plan can include showing the suggested plan on a display”, [0184]: “When the simulation is complete, the SPP module 218 can be configured to analyze the procedure for projected results, e.g., potential healing, potential increase in patient mobility after “X” amount of time, amount of correction, etc. The user can thus consult the projected results and decide whether to revise the surgery, such as if the projected results are less than the user would like and/or expect”, [0250]: “The CPU 130 can be configured to display results of the analysis on a display 132. Although disc removal is shown in the illustrated embodiment, other material removed from the patient, such as tissue and bone, can be similarly electronically confirmed”, [0296]: “Post surgical results and metrics stored in the operation database 304 and/or in the recovery database 308, such as length of stay, infection rate, fusion rate, blood loss, etc., can be tracked by the hospital and/or surgeon and can be used to drive patient awareness around quality of care and/or used with payers to help support reimbursement negotiations”, [0299]-0302], and [0304]-[309]); and transmitting the multi-stage surgical plan for surgeon review (Nawana, [0106]: “a patient and one or more medical professionals involved with treating the patient can electronically access a comprehensive treatment planning, support, and review system, e.g., using one or more web pages. The system can provide recommendations regarding diagnosis, non-surgical treatment, surgical treatment, and recovery from the surgical treatment based on data gathered from the patient and the medical professional(s), thereby helping to improve accuracy in diagnosis and effectiveness of treatment” and [0163]: “These other at-home tools can be uploaded to the patient's record in the treatment database 312, where the data can be accessed and reviewed by, e.g., the patient's surgeon”).
Regarding claim 2 Nawana teaches the computer-implemented method of claim 1 wherein the second surgical procedure is a same type of procedure as the first surgical procedure (Nawana, [0170]: “The simulated surgeries can include variations of the same surgical procedure on a patient so as to try different surgical instruments and/or different surgical strategies”).
Regarding claim 3 Nawana teaches the computer-implemented method of claim 2 wherein the first surgical procedure is a first spinal fusion procedure, and wherein the second surgical procedure is a second spinal fusion procedure (Nawana, [0229], [0318], and [0319]).
Regarding claim 4 Nawana teaches the computer-implemented method of claim 1 wherein the first surgical procedure is a first interbody procedure, and wherein the second surgical procedure is a procedure to provide fixation (Nawana, [0229], [0318], and [0319]).
Regarding claim 5 Nawana teaches the computer-implemented method of claim 1 wherein the first surgical procedure is a different type of procedure than the second surgical procedure (Nawana, [0026], [0042], [0142], [0170], and [0242]).
Regarding claim 6 Nawana teaches the computer-implemented method of claim 1 wherein the first target location and the second target location are different (Nawana, [0026], [0042], [0142], [0170], and [0242]).
Regarding claim 7 Nawana teaches the computer-implemented method of claim 6 wherein the first target location includes a first range of vertebrae and the second target location includes a second range of vertebrae (Nawana, [0026], [0042], [0142], [0170], and [0242]).
Regarding claim 8 Nawana teaches the computer-implemented method of claim 7 wherein the first range of vertebrae overlap with the second range of vertebrae (Nawana, [0026], [0042], [0142], [0170], [0213], and [0242]).
Regarding claim 9 Nawana teaches the computer-implemented method of claim 7 wherein the first range of vertebrae are spaced apart from the second range of vertebrae by at least one vertebra not included in the first range or the second range (Nawana, [0181], [0221], and [0231]).
Regarding claim 10 Nawana teaches the computer-implemented method of claim 1 wherein the first surgical procedure includes an anterior approach and the second surgical procedure includes a posterior approach (Nawana, [0228]-[0229] and [0231]).
Regarding claim 11 Nawana teaches the computer-implemented, method of claim 1 wherein the first surgical procedure includes a lateral approach and the second surgical procedure includes a posterior approach (Nawana, [0221], [0228]-[0229], and [0231]).
Regarding claim 12 Nawana teaches the computer-implemented method of claim 1 wherein the second period for performing the second surgical procedure is set based on a fixed duration from the first period for performing the first surgical procedure (Nawana, [0026]: “a different duration of a step in the actual performance of the surgical procedure than in the virtual performance of the surgical procedure”, [0221], [0248], [0281], and [0292]).
Regarding claim 13 Nawana teaches the computer-implemented method of claim 1 wherein the second period for performing the second surgical procedure is set based on a patient metric crossing a predefined threshold (Nawana, [0034], [0148], [0154], and [0308]).
Regarding claim 14 Nawana teaches the computer-implemented method of claim 1 wherein the second treatment stage is spaced apart from the first treatment stage by at least about 6 months (Nawana, [0132]).
Regarding claim 17 Nawana teaches The computer-implemented method of claim 1 wherein: simulating the first treatment stage includes simulating the predicted outcome of the first treatment stage ([0022] and [0038]: “For another example, the plans for a first subset of the patients can include a non-surgical treatment, the plans for a second subset of the patients can include a surgical treatment, and determining the suggested plan can include comparing outcomes of the non-surgical treatments with outcomes of the surgical treatments. Determining the suggested plan can include choosing at least a one of the plans having a best outcome among the surgical treatments and the non-surgical treatments. For still another example, determining the effectiveness can include determining an effect of each of the plans on the at least one medical diagnosis, and determining the suggested plan can include choosing at least a one of the plans having a most desired effect on the at least one medical diagnosis. For another example, the processor can be configured to receive performance data regarding performances of surgical procedures included in each of the plans that include performance of the surgical procedure as at least part of the medical treatment, and determining the effectiveness can include choosing at least a one of the plans based at least on the performance data. For another example, the system can include a display, and providing the suggested plan can include showing the suggested plan on the display’), wherein simulating the predicted outcome of the first treatment stage includes generating a first virtual model of predicted patient anatomy if the first treatment stage were performed (Nawana, FIG. 9, [0029], [0034], [0170], and [0174]-[0177]); and simulating the second treatment stage includes simulating a predicted outcome of the second treatment stage, wherein simulating the predicted outcome of the second treatment stage includes generating a second virtual model of predicted patient anatomy if the second treatment stage were performed (Nawana, [0022], [0024], [0032], [0034], [0170], [0174]-[0177], and [0306]).
Regarding claim 18 Nawana teaches the computer-implemented method of claim 17, further comprising determining an order for performing the first treatment stage and the second treatment stage based at least in part on the simulated outcomes (Nawana, FIG. 9, [0029], [0034], [0170], and [0174]-[0177]).
Regarding claim 19 Nawana teaches The computer-implemented method of claim 17 wherein simulating the predicted outcome of the first treatment stage include simulating the predicted outcome under a variety of patient conditions, and wherein the first surgical procedure, the first target location, and/or the first period are determined based in part on the simulated outcome (Nawana, [0005]: “ the conservative, non-surgical treatment fails to adequately address the diagnosis, e.g., fails to adequately remedy the patient's symptom(s), or if the physician determines that the patient's condition is such that an approach more aggressive than a conservative, non-surgical treatment is needed to achieve desired results, the physician typically modifies the treatment plan to include a less conservative treatment”, [0022], [0024], [0032], [0034], [0131]: “FIG. 5 illustrates one embodiment of symptom input to the system 10 by a user 24 via a client terminal in the form of a touch screen tablet 26. Although the touch screen tablet 26 is shown in the illustrated embodiment, the system 10 can allow for symptom selection in other ways, such as by other touch screen devices, by other client terminals, by mouse selection, by drop-down text menu, etc. The touch screen tablet 26 shows an interface allowing user selection of area(s) of a body in which symptom(s) manifest, but symptom(s) and their locations in the body can be identified and entered by a user in other ways, such as by text, pointer device selection (e.g., mouse clicking, touch via stylus pen, etc.), drop-down menu, etc. The diagnosis module 210 can be configured to provide the user with a variety of symptoms for selection based on the user's selected area(s) of the body in which symptom(s) manifest. The variety of symptoms can be stored in the diagnosis database 310 for selection based on a user's input and for display to the user. For non-limiting example, if a patient selects a hip area as having pain, the diagnosis module 210 can be configured to retrieve from the diagnosis database 310 one or more possible additional symptoms associated with hip pain, e.g., swelling, pain during movement, pain when stationary, stiffness following a period of inactivity, etc., that the user can further select to help better define the user's condition”, [0170], [0174]-[0177], and [0306]).
Regarding claim 20 Nawana teaches the computer-implemented method of claim 19 wherein the variety of patient conditions include different values for at least one of patient weight, patient BMI, or patient disability score (Nawana, [0144], [0148], and [0180]).
Regarding claim 21 Nawana teaches The computer-implemented method of claim 1, further comprising: generating a first virtual model of patient anatomy, the first virtual model associated with the first treatment stage; and generating a second virtual model of patient anatomy, the second virtual model associated with the second treatment stage, wherein the second virtual model incudes a predicted correction to patient anatomy to occur during first treatment phase (Nawana, [0022], [0024], [0032], [0034], [0170], [0174]-[0177], and [0306]).
Regarding claim 22 Nawana teaches the computer-implemented method of claim 1, further comprising simulating a change in patient anatomy over time between the first treatment stage and the second treatment stage (Nawana, [0170], [0174]-[0177], [0179]-[0187], and [0190]).
Regarding claim 23 Nawana teaches the computer-implemented method of claim 22 wherein transmitting the multi-stage surgical plan for review includes transmitting simulated changes in the patient anatomy at discrete intervals between the first treatment stage and the second treatment stage (Nawana, [0170], [0174]-[0177], [0179]-[0187], and [0190]).
Regarding claim 24 Nawana teaches the computer-implemented method of claim 22 wherein the simulated changes are shown using virtual models of patient anatomy (Nawana, [0170], [0174]-[0177], [0179]-[0187], and [0190]).
Regarding claim 25 Nawana teaches The computer-implemented method of claim 1 wherein determining the second treatment stage includes: determining a first alternative second treatment stage and a second alternative second treatment stage different than the first alternative second treatment stage (Nawana, [0026], [0038], [0167], [0178], [0196], and [0262]-[0263]); and generating one or more selection criteria for selecting between the first alternative second treatment stage and the second alternative second treatment stage (Nawana, [0026], [0038], [0167], [0178], [0196], and [0262]-[0263]).
Regarding claim 26 Nawana teaches the computer-implemented method of claim 25 wherein the one or more selection criteria include patient metric thresholds following the first treatment stage (Nawana, [0212], [0236], and [0296]).
Regarding claim 27 Nawana teaches the computer-implemented method of claim 1, further comprising: defining a successful outcome for each treatment stage, the successful outcome and calculating a probability of achieving the successful outcome for reach treatment stage (Nawana, [0202], [0204], and [0246]).
Regarding claim 28 Nawana teaches a non-transitory computer readable medium storing computer-executable instructions for generating multi-stage surgical plans using a computing system, wherein the instructions, when executed (Nawana, Abstract and [0111]), cause the computing system to: receiving patient data (Nawana, [0129]: “The patient's Electronic Medical Record (EMR) can be linked by their health care provider to the diagnosis and treatment database 300. The symptoms and historical treatments identified for a particular patient can be accessed at any time in the future using the system 10, which can help facilitate continued treatment and evaluation of the patient, e.g., by allowing severity of symptoms to be tracked over time as the patient and/or other user(s) updates the system 10. Symptoms for a patient can be stored in the diagnosis and treatment database 300, e.g., in the diagnosis database 310, with a date and time stamp, which can facilitate the continued treatment and evaluation of the patient. Similarly, other data discussed herein as being related to a particular patient can be stored in the diagnosis treatment database 300, the pre-op database 302, the operation database 304, the post-op database 306, and the recovery database 308 as being associated with the patient and as having a date and time stamp. The patient's EMR, historical treatments, images, lab results, physical exam results, symptoms, etc., to the extent they are provided to the system 10, can be compared to other patient data included in the diagnosis and treatment database 300 to compile outcome predictions based on retrospective results from treatment results of patients with similar indications. This compilation can allow medical care providers and patients to make more informed treatment and procedural decisions”); based on the patient data, generating a multi-stage surgical plan for treating a spine and/or spinal region of the patient, wherein generating the multi-stage surgical plan includes (Nawana, [0144]: “the system 10 can be used in a spinal context, such as to test for the presence of cytokines (such as Fibronectin-aggrecan complex, FAC) and growth factors (such as TNF-alpha or IL-8) in the intervertebral disc of patients, in specifically DDD or herniated disc cases in the lumbar, thoracic, or cervical spine… As the system 10 continually runs these tests on more patients, and then subsequently tracks the test's validity in diagnosing the patient's condition by relating it to the patient outcome of the chosen surgical treatments for DDD and/or herniated disc, the system 10 will gain a more refined intelligence of when to prescribe the test, and when to prescribe certain medications and/or treatments (invasive or non-surgical) based on the results of the test… This identification will help in the initial diagnosis phase to develop an appropriate treatment plan based on the existence of these high-risk markers in combination with the patient's symptoms. For example, if there are clear markers that indicate that the condition will only worsen with time and that surgical intervention will be necessary, then a less invasive surgery can be done early before the condition worsens and results in more pain and disability. If the patient is lacking high risk markers, then a more conservative treatment would be recommended as a first course of action”, [0155], and [0229]): simulating, using the at least one virtual model of the patient (Nawana, [0029]: “The pre-op module allows a three-dimensional electronic simulation of the selected invasive treatment to be performed on a virtual patient using a plurality of virtual instruments. The virtual patient is a model of the patient based on gathered medical data regarding the patient, and each of the plurality of virtual instruments are modeled on an actual instrument available for use in the selected invasive treatment. The pre-op module also stores the electronic simulation in a storage unit. The operation module compares an actual performance of the selected invasive treatment on the patient with the stored electronic simulation, provides electronic feedback regarding the comparison during the actual performance of the selected invasive treatment that indicates progress of the actual performance of the selected invasive treatment versus the stored electronic simulation, triggers an alarm if the comparison indicates that a step of the actual performance of the selected invasive treatment differs from the stored electronic simulation beyond a predetermined threshold amount of tolerable variance, and stores data regarding the actual performance of the selected invasive treatment in the storage unit”, [0170]: “More particularly, the pre-op module 202 can allow surgeons to electronically perform three-dimensional (3D) simulated surgeries on virtual models of patients to test surgical ease and/or potential surgical outcomes before actually performing the surgical procedure”, and [0174]-[0175]), determining a first treatment stage having a first surgical procedure (Nawana, [0025]: “a medical system is provided that includes a processor configured to receive plan data regarding a virtual performance of a surgical procedure on a patient, and to receive performance data regarding an actual performance of the surgical procedure on the patient. The performance data is received in real time with the actual performance of the surgical procedure. The processor is also configured to determine if the plan data varies from the performance data” and [0026]: “the processor can be configured to receive plan data regarding a plurality of virtual performances of the surgical procedure on a plurality of patients, and to receive performance data regarding a plurality actual performances of the surgical procedure on the plurality of patients”), a first target location along the spine for the first surgical procedure (Nawana ,[0158], [0174], [0243], [0244], and [0246]: “The procedure analysis module 230 can be configured to track the stereoscopic viewing device to help determine where to overlay the generated 3D model in a location where it can be visualized by the wearer of the stereoscopic viewing device. The procedure analysis module 230 can be configured to use the stereoscopic viewing device to overlay the generated 3D model on the physical object, e.g., the patient, in an anatomically correct location. In other words, the procedure analysis module 230 can be configured to project the generated 3D model of anatomy in a location corresponding to the patient's actual anatomy”), and a first period for performing the first surgical procedure (Nawana, [0025]: “The performance data is received in real time with the actual performance of the surgical procedure”, [0026]: “The performance data is received in real time with the actual performances of the surgical procedures. The processor can also be configured to determine if the plan data regarding the plurality of virtual performances varies from the performance data regarding the plurality actual performances, determine if any one or more of the determined variances are a same type of variance, and provide a recommendation to a user performing another virtual performance of the surgical procedure based on the one or more determined variances determined to be the same type of variance”, and [0041]-[0042]), simulating, using the at least one virtual model of the patient (Nawana, [0029]: “The pre-op module allows a three-dimensional electronic simulation of the selected invasive treatment to be performed on a virtual patient using a plurality of virtual instruments. The virtual patient is a model of the patient based on gathered medical data regarding the patient, and each of the plurality of virtual instruments are modeled on an actual instrument available for use in the selected invasive treatment. The pre-op module also stores the electronic simulation in a storage unit. The operation module compares an actual performance of the selected invasive treatment on the patient with the stored electronic simulation, provides electronic feedback regarding the comparison during the actual performance of the selected invasive treatment that indicates progress of the actual performance of the selected invasive treatment versus the stored electronic simulation, triggers an alarm if the comparison indicates that a step of the actual performance of the selected invasive treatment differs from the stored electronic simulation beyond a predetermined threshold amount of tolerable variance, and stores data regarding the actual performance of the selected invasive treatment in the storage unit”, [0170]: “More particularly, the pre-op module 202 can allow surgeons to electronically perform three-dimensional (3D) simulated surgeries on virtual models of patients to test surgical ease and/or potential surgical outcomes before actually performing the surgical procedure”, and [0174]-[0175]), a second treatment stage having a second surgical procedure (Nawana, [0038], [0167], [0178], and [0196]), a second target location along the spine for the second surgical procedure (Nawana, [0026], [0038], [0167], [0178], [0196], and [0262]-[0263]), and a second period for performing the second surgical procedure (Nawana, [0035] and [0295]), wherein the second treatment stage is based at least in part on a predicted outcome of the first treatment stage (Nawana, [0129]: “The patient's EMR, historical treatments, images, lab results, physical exam results, symptoms, etc., to the extent they are provided to the system 10, can be compared to other patient data included in the diagnosis and treatment database 300 to compile outcome predictions based on retrospective results from treatment results of patients with similar indications. This compilation can allow medical care providers and patients to make more informed treatment and procedural decisions”, [0186]: “During the simulated procedure, the SPP module 218 can be configured to use this predictive modeling to show where tissue and other structures are predicted to be, allowing for navigation around them. The SPP module simulation can utilize historical surgical and literature data to predict neural responses and/or changes based upon a predicted amount of retraction and/or decompression preformed. When the simulation is complete, the SPP module 218 can be configured to analyze the procedure for projected results, e.g., potential healing, potential increase in patient mobility after “X” amount of time, amount of correction, etc. The user can thus consult the projected results and decide whether to revise the surgery, such as if the projected results are less than the user would like and/or expect”, [0271], and [0284]), the predicted response including one or more simulated post-operative spinal metrics of the patient associated with performing the first treatment stage (Nawana, [0184]: “During the simulated procedure, the SPP module 218 can be configured to use this predictive modeling to show where tissue and other structures are predicted to be, allowing for navigation around them. The SPP module simulation can utilize historical surgical and literature data to predict neural responses and/or changes based upon a predicted amount of retraction and/or decompression preformed”, [0186]: “Users of the system 10 can run a predicted life changes module to assess potential future changes and assist in planning and refining the surgical procedure”, [0187]: “In the illustrated embodiment, the user 52 is simulating performance of a spinal procedure, but as mentioned above, the system 10 can be used to simulate other types of surgical procedures”, [0221], [0228], [0271]: “Individual analysis of surgical procedures can help predict outcomes of the procedure and/or can help the surgeon establish best practices and learn from previous experience on a personal, confidential level as evaluated by the system 10 acting as a neutral third party. Aggregated data can help hospital administrators develop a cost per hour for OR time, which can allow the hospital to improve efficiency and lower costs”, and [0230], [0284]: “The post-op module 206 can be configured to detect and analyze any variances and can be configured to modulate future predictive models using the detected and analyzed variances”, [0324]: “Thus, the predicted outcome of rehabilitation and treatment can be predicted for the patient if they continue therapies that historical patients have followed. This can increase patient compliance to rehabilitation therapies if the patient can compare their performance to others that have had the same procedure and similar rehabilitation therapy. The patient monitoring module 244 can be configured to suggest the modification of the patient's treatment post-op plan to the patient's care provider, e.g., by providing an alert to the care provider indicating that modification of the patient's post-op treatment plan is recommended. The care provider can review the modification and determine whether to modify the patient's treatment plan. Alternatively, the patient monitoring module 244 can be configured to automatically modify the patient's post-op treatment plan and inform the patient via an alert as to the modified post-op treatment plan”), wherein the second treatment stage is spaced apart in time from the first treatment stage (Nawana, [0129]: “The symptoms and historical treatments identified for a particular patient can be accessed at any time in the future using the system 10, which can help facilitate continued treatment and evaluation of the patient, e.g., by allowing severity of symptoms to be tracked over time as the patient and/or other user(s) updates the system 10… The patient's EMR, historical treatments, images, lab results, physical exam results, symptoms, etc., to the extent they are provided to the system 10, can be compared to other patient data included in the diagnosis and treatment database 300 to compile outcome predictions based on retrospective results from treatment results of patients with similar indications. This compilation can allow medical care providers and patients to make more informed treatment and procedural decisions”, [0186]: “During the simulated procedure, the SPP module 218 can be configured to use this predictive modeling to show where tissue and other structures are predicted to be, allowing for navigation around them. The SPP module simulation can utilize historical surgical and literature data to predict neural responses and/or changes based upon a predicted amount of retraction and/or decompression preformed. When the simulation is complete, the SPP module 218 can be configured to analyze the procedure for projected results, e.g., potential healing, potential increase in patient mobility after “X” amount of time, amount of correction, etc. The user can thus consult the projected results and decide whether to revise the surgery, such as if the projected results are less than the user would like and/or expect… This incorporation can be especially helpful with patients having variable and changing anatomies, e.g., young scoliosis patients with variable and changing curvatures. Users of the system 10 can run a predicted life changes module to assess potential future changes and assist in planning and refining the surgical procedure”, [0271], and [0284]), and wherein simulating the second treatment stage occurs before the first surgical procedure is performed (Nawana, [0022], [0038]: “ For another example, the plans for a first subset of the patients can include a non-surgical treatment, the plans for a second subset of the patients can include a surgical treatment, and determining the suggested plan can include comparing outcomes of the non-surgical treatments with outcomes of the surgical treatments. Determining the suggested plan can include choosing at least a one of the plans having a best outcome among the surgical treatments and the non-surgical treatments. For yet another example, determining the effectiveness can include determining an effect of each of the plans on the at least one medical diagnosis, and determining the suggested plan can include choosing at least a one of the plans having a most desired effect on the at least one medical diagnosis. For another example, the method can include receiving performance data regarding performances of surgical procedures included in each of the plans that include performance of the surgical procedure as at least part of the medical treatment, and determining the effectiveness can include choosing at least a one of the plans based at least on the performance data. For yet another example, providing the suggested plan can include showing the suggested plan on a display”, [0184]: “When the simulation is complete, the SPP module 218 can be configured to analyze the procedure for projected results, e.g., potential healing, potential increase in patient mobility after “X” amount of time, amount of correction, etc. The user can thus consult the projected results and decide whether to revise the surgery, such as if the projected results are less than the user would like and/or expect”, [0250]: “he CPU 130 can be configured to display results of the analysis on a display 132. Although disc removal is shown in the illustrated embodiment, other material removed from the patient, such as tissue and bone, can be similarly electronically confirmed”, [0296]: “Post surgical results and metrics stored in the operation database 304 and/or in the recovery database 308, such as length of stay, infection rate, fusion rate, blood loss, etc., can be tracked by the hospital and/or surgeon and can be used to drive patient awareness around quality of care and/or used with payers to help support reimbursement negotiations”, [0299]-0302], and [0304]-[309]); and transmitting the multi-stage surgical plan for surgeon review (Nawana, [0106]: “a patient and one or more medical professionals involved with treating the patient can electronically access a comprehensive treatment planning, support, and review system, e.g., using one or more web pages. The system can provide recommendations regarding diagnosis, non-surgical treatment, surgical treatment, and recovery from the surgical treatment based on data gathered from the patient and the medical professional(s), thereby helping to improve accuracy in diagnosis and effectiveness of treatment” and [0163]: “These other at-home tools can be uploaded to the patient's record in the treatment database 312, where the data can be accessed and reviewed by, e.g., the patient's surgeon”).
Regarding claim 29 Nawana teaches the non-transitory computer readable medium of claim 28, whereinoutcome of the first treatment stage using the at least one virtual model (Nawana, [0029]: “The pre-op module allows a three-dimensional electronic simulation of the selected invasive treatment to be performed on a virtual patient using a plurality of virtual instruments. The virtual patient is a model of the patient based on gathered medical data regarding the patient, and each of the plurality of virtual instruments are modeled on an actual instrument available for use in the selected invasive treatment. The pre-op module also stores the electronic simulation in a storage unit. The operation module compares an actual performance of the selected invasive treatment on the patient with the stored electronic simulation, provides electronic feedback regarding the comparison during the actual performance of the selected invasive treatment that indicates progress of the actual performance of the selected invasive treatment versus the stored electronic simulation, triggers an alarm if the comparison indicates that a step of the actual performance of the selected invasive treatment differs from the stored electronic simulation beyond a predetermined threshold amount of tolerable variance, and stores data regarding the actual performance of the selected invasive treatment in the storage unit”, [0170]: “More particularly, the pre-op module 202 can allow surgeons to electronically perform three-dimensional (3D) simulated surgeries on virtual models of patients to test surgical ease and/or potential surgical outcomes before actually performing the surgical procedure”, and [0174]-[0175]); and simulating the second treatment stage incudes simulating an outcome of the second treatment stage using the at least one virtual model (Nawana, [0022], [0024], [0032], [0034], [0170], [0174]-[0177], and [0306]).
Regarding claim 30 Nawana teaches the non-transitory computer readable medium of claim 29 wherein the instructions, when executed, further cause the computing system to modify at least one of the first treatment stage or the second treatment stage based at least in part on the simulated outcome for the first treatment stage of the second treatment stage (Nawana, [0161], [0165], and [0167]).
Regarding claim 31 Nawana teaches the non-transitory computer readable medium of claim 29 wherein the simulations include predicted patient metrics associated with performing the first treatment stage and the second treatment stage (Nawana, [0184] and [0271]).
Regarding claim 32 Nawana teaches the non-transitory computer readable medium of claim 29 wherein a time between the first treatment stage and the second treatment stage is identified based on the simulated outcome for the first treatment stage and the second treatment stage (Nawana, [0026], [0038], [0167], [0178], [0196], and [0262]-[0263]).
Regarding claim 33 Nawana teaches a system for providing patient-specific medical treatment (Nawana, Abstract), the system comprising: one or more processors (Nawana, [0109]); and a memory storing instructions that, when executed by the one or more processors, case the system to perform operations comprising (Nawana, [0109]): receiving patient data (Nawana, [0129]: “The patient's Electronic Medical Record (EMR) can be linked by their health care provider to the diagnosis and treatment database 300. The symptoms and historical treatments identified for a particular patient can be accessed at any time in the future using the system 10, which can help facilitate continued treatment and evaluation of the patient, e.g., by allowing severity of symptoms to be tracked over time as the patient and/or other user(s) updates the system 10. Symptoms for a patient can be stored in the diagnosis and treatment database 300, e.g., in the diagnosis database 310, with a date and time stamp, which can facilitate the continued treatment and evaluation of the patient. Similarly, other data discussed herein as being related to a particular patient can be stored in the diagnosis treatment database 300, the pre-op database 302, the operation database 304, the post-op database 306, and the recovery database 308 as being associated with the patient and as having a date and time stamp. The patient's EMR, historical treatments, images, lab results, physical exam results, symptoms, etc., to the extent they are provided to the system 10, can be compared to other patient data included in the diagnosis and treatment database 300 to compile outcome predictions based on retrospective results from treatment results of patients with similar indications. This compilation can allow medical care providers and patients to make more informed treatment and procedural decisions”); based on the patient data, generating a multi-stage surgical plan for treating a spine and/or spinal region of the patient, wherein generating the multi-stage surgical plan includes (Nawana, [0144]: “the system 10 can be used in a spinal context, such as to test for the presence of cytokines (such as Fibronectin-aggrecan complex, FAC) and growth factors (such as TNF-alpha or IL-8) in the intervertebral disc of patients, in specifically DDD or herniated disc cases in the lumbar, thoracic, or cervical spine… As the system 10 continually runs these tests on more patients, and then subsequently tracks the test's validity in diagnosing the patient's condition by relating it to the patient outcome of the chosen surgical treatments for DDD and/or herniated disc, the system 10 will gain a more refined intelligence of when to prescribe the test, and when to prescribe certain medications and/or treatments (invasive or non-surgical) based on the results of the test… This identification will help in the initial diagnosis phase to develop an appropriate treatment plan based on the existence of these high-risk markers in combination with the patient's symptoms. For example, if there are clear markers that indicate that the condition will only worsen with time and that surgical intervention will be necessary, then a less invasive surgery can be done early before the condition worsens and results in more pain and disability. If the patient is lacking high risk markers, then a more conservative treatment would be recommended as a first course of action”, [0155], and [0229]): simulating, using at least one virtual model of the patient (Nawana, [0029]: “The pre-op module allows a three-dimensional electronic simulation of the selected invasive treatment to be performed on a virtual patient using a plurality of virtual instruments. The virtual patient is a model of the patient based on gathered medical data regarding the patient, and each of the plurality of virtual instruments are modeled on an actual instrument available for use in the selected invasive treatment. The pre-op module also stores the electronic simulation in a storage unit. The operation module compares an actual performance of the selected invasive treatment on the patient with the stored electronic simulation, provides electronic feedback regarding the comparison during the actual performance of the selected invasive treatment that indicates progress of the actual performance of the selected invasive treatment versus the stored electronic simulation, triggers an alarm if the comparison indicates that a step of the actual performance of the selected invasive treatment differs from the stored electronic simulation beyond a predetermined threshold amount of tolerable variance, and stores data regarding the actual performance of the selected invasive treatment in the storage unit”, [0170]: “More particularly, the pre-op module 202 can allow surgeons to electronically perform three-dimensional (3D) simulated surgeries on virtual models of patients to test surgical ease and/or potential surgical outcomes before actually performing the surgical procedure”, and [0174]-[0175]), a first treatment stage having a first surgical procedure (Nawana, [0025]: “a medical system is provided that includes a processor configured to receive plan data regarding a virtual performance of a surgical procedure on a patient, and to receive performance data regarding an actual performance of the surgical procedure on the patient. The performance data is received in real time with the actual performance of the surgical procedure. The processor is also configured to determine if the plan data varies from the performance data” and [0026]: “the processor can be configured to receive plan data regarding a plurality of virtual performances of the surgical procedure on a plurality of patients, and to receive performance data regarding a plurality actual performances of the surgical procedure on the plurality of patients”), a first target location along the spine for the first surgical procedure (Nawana ,[0158], [0174], [0243], [0244], and [0246]: “The procedure analysis module 230 can be configured to track the stereoscopic viewing device to help determine where to overlay the generated 3D model in a location where it can be visualized by the wearer of the stereoscopic viewing device. The procedure analysis module 230 can be configured to use the stereoscopic viewing device to overlay the generated 3D model on the physical object, e.g., the patient, in an anatomically correct location. In other words, the procedure analysis module 230 can be configured to project the generated 3D model of anatomy in a location corresponding to the patient's actual anatomy”), and a first period for performing the first surgical procedure (Nawana, [0025]: “The performance data is received in real time with the actual performance of the surgical procedure”, [0026]: “The performance data is received in real time with the actual performances of the surgical procedures. The processor can also be configured to determine if the plan data regarding the plurality of virtual performances varies from the performance data regarding the plurality actual performances, determine if any one or more of the determined variances are a same type of variance, and provide a recommendation to a user performing another virtual performance of the surgical procedure based on the one or more determined variances determined to be the same type of variance”, and [0041]-[0042]), and simulating, using the at least one virtual model of the patient (Nawana, [0029]: “The pre-op module allows a three-dimensional electronic simulation of the selected invasive treatment to be performed on a virtual patient using a plurality of virtual instruments. The virtual patient is a model of the patient based on gathered medical data regarding the patient, and each of the plurality of virtual instruments are modeled on an actual instrument available for use in the selected invasive treatment. The pre-op module also stores the electronic simulation in a storage unit. The operation module compares an actual performance of the selected invasive treatment on the patient with the stored electronic simulation, provides electronic feedback regarding the comparison during the actual performance of the selected invasive treatment that indicates progress of the actual performance of the selected invasive treatment versus the stored electronic simulation, triggers an alarm if the comparison indicates that a step of the actual performance of the selected invasive treatment differs from the stored electronic simulation beyond a predetermined threshold amount of tolerable variance, and stores data regarding the actual performance of the selected invasive treatment in the storage unit”, [0170]: “More particularly, the pre-op module 202 can allow surgeons to electronically perform three-dimensional (3D) simulated surgeries on virtual models of patients to test surgical ease and/or potential surgical outcomes before actually performing the surgical procedure”, and [0174]-[0175]), a second treatment stage having a second surgical procedure (Nawana, [0038], [0167], [0178], and [0196]), a second target location along the spine for the second surgical procedure (Nawana, [0026], [0038], [0167], [0178], [0196], and [0262]-[0263]), and a second period for performing the second surgical procedure (Nawana, [0035] and [0295]), wherein the second treatment stage is based at least in part on a predicted outcome of the first treatment stage (Nawana, [0129]: “The patient's EMR, historical treatments, images, lab results, physical exam results, symptoms, etc., to the extent they are provided to the system 10, can be compared to other patient data included in the diagnosis and treatment database 300 to compile outcome predictions based on retrospective results from treatment results of patients with similar indications. This compilation can allow medical care providers and patients to make more informed treatment and procedural decisions”, [0186]: “During the simulated procedure, the SPP module 218 can be configured to use this predictive modeling to show where tissue and other structures are predicted to be, allowing for navigation around them. The SPP module simulation can utilize historical surgical and literature data to predict neural responses and/or changes based upon a predicted amount of retraction and/or decompression preformed. When the simulation is complete, the SPP module 218 can be configured to analyze the procedure for projected results, e.g., potential healing, potential increase in patient mobility after “X” amount of time, amount of correction, etc. The user can thus consult the projected results and decide whether to revise the surgery, such as if the projected results are less than the user would like and/or expect”, [0271], and [0284]), the predicted response including one or more simulated post-operative spinal metrics of the patient associated with performing the first treatment stage (Nawana, [0184]: “During the simulated procedure, the SPP module 218 can be configured to use this predictive modeling to show where tissue and other structures are predicted to be, allowing for navigation around them. The SPP module simulation can utilize historical surgical and literature data to predict neural responses and/or changes based upon a predicted amount of retraction and/or decompression preformed”, [0186]: “Users of the system 10 can run a predicted life changes module to assess potential future changes and assist in planning and refining the surgical procedure”, [0187]: “In the illustrated embodiment, the user 52 is simulating performance of a spinal procedure, but as mentioned above, the system 10 can be used to simulate other types of surgical procedures”, [0221], [0228], [0271]: “Individual analysis of surgical procedures can help predict outcomes of the procedure and/or can help the surgeon establish best practices and learn from previous experience on a personal, confidential level as evaluated by the system 10 acting as a neutral third party. Aggregated data can help hospital administrators develop a cost per hour for OR time, which can allow the hospital to improve efficiency and lower costs”, and [0230], [0284]: “The post-op module 206 can be configured to detect and analyze any variances and can be configured to modulate future predictive models using the detected and analyzed variances”, [0324]: “Thus, the predicted outcome of rehabilitation and treatment can be predicted for the patient if they continue therapies that historical patients have followed. This can increase patient compliance to rehabilitation therapies if the patient can compare their performance to others that have had the same procedure and similar rehabilitation therapy. The patient monitoring module 244 can be configured to suggest the modification of the patient's treatment post-op plan to the patient's care provider, e.g., by providing an alert to the care provider indicating that modification of the patient's post-op treatment plan is recommended. The care provider can review the modification and determine whether to modify the patient's treatment plan. Alternatively, the patient monitoring module 244 can be configured to automatically modify the patient's post-op treatment plan and inform the patient via an alert as to the modified post-op treatment plan”), wherein the second treatment stage is spaced apart in time from the first treatment stage (Nawana, [0129]: “The symptoms and historical treatments identified for a particular patient can be accessed at any time in the future using the system 10, which can help facilitate continued treatment and evaluation of the patient, e.g., by allowing severity of symptoms to be tracked over time as the patient and/or other user(s) updates the system 10… The patient's EMR, historical treatments, images, lab results, physical exam results, symptoms, etc., to the extent they are provided to the system 10, can be compared to other patient data included in the diagnosis and treatment database 300 to compile outcome predictions based on retrospective results from treatment results of patients with similar indications. This compilation can allow medical care providers and patients to make more informed treatment and procedural decisions”, [0186]: “During the simulated procedure, the SPP module 218 can be configured to use this predictive modeling to show where tissue and other structures are predicted to be, allowing for navigation around them. The SPP module simulation can utilize historical surgical and literature data to predict neural responses and/or changes based upon a predicted amount of retraction and/or decompression preformed. When the simulation is complete, the SPP module 218 can be configured to analyze the procedure for projected results, e.g., potential healing, potential increase in patient mobility after “X” amount of time, amount of correction, etc. The user can thus consult the projected results and decide whether to revise the surgery, such as if the projected results are less than the user would like and/or expect… This incorporation can be especially helpful with patients having variable and changing anatomies, e.g., young scoliosis patients with variable and changing curvatures. Users of the system 10 can run a predicted life changes module to assess potential future changes and assist in planning and refining the surgical procedure”, [0271], and [0284]); wherein simulating the second treatment stage occurs before the first surgical procedure is performed (Nawana, [0022], [0038]: “ For another example, the plans for a first subset of the patients can include a non-surgical treatment, the plans for a second subset of the patients can include a surgical treatment, and determining the suggested plan can include comparing outcomes of the non-surgical treatments with outcomes of the surgical treatments. Determining the suggested plan can include choosing at least a one of the plans having a best outcome among the surgical treatments and the non-surgical treatments. For yet another example, determining the effectiveness can include determining an effect of each of the plans on the at least one medical diagnosis, and determining the suggested plan can include choosing at least a one of the plans having a most desired effect on the at least one medical diagnosis. For another example, the method can include receiving performance data regarding performances of surgical procedures included in each of the plans that include performance of the surgical procedure as at least part of the medical treatment, and determining the effectiveness can include choosing at least a one of the plans based at least on the performance data. For yet another example, providing the suggested plan can include showing the suggested plan on a display”, [0184]: “When the simulation is complete, the SPP module 218 can be configured to analyze the procedure for projected results, e.g., potential healing, potential increase in patient mobility after “X” amount of time, amount of correction, etc. The user can thus consult the projected results and decide whether to revise the surgery, such as if the projected results are less than the user would like and/or expect”, [0250]: “he CPU 130 can be configured to display results of the analysis on a display 132. Although disc removal is shown in the illustrated embodiment, other material removed from the patient, such as tissue and bone, can be similarly electronically confirmed”, [0296]: “Post surgical results and metrics stored in the operation database 304 and/or in the recovery database 308, such as length of stay, infection rate, fusion rate, blood loss, etc., can be tracked by the hospital and/or surgeon and can be used to drive patient awareness around quality of care and/or used with payers to help support reimbursement negotiations”, [0299]-0302], and [0304]-[309]); and transmitting the multi-stage surgical plan for surgeon review (Nawana, [0106]: “a patient and one or more medical professionals involved with treating the patient can electronically access a comprehensive treatment planning, support, and review system, e.g., using one or more web pages. The system can provide recommendations regarding diagnosis, non-surgical treatment, surgical treatment, and recovery from the surgical treatment based on data gathered from the patient and the medical professional(s), thereby helping to improve accuracy in diagnosis and effectiveness of treatment” and [0163]: “These other at-home tools can be uploaded to the patient's record in the treatment database 312, where the data can be accessed and reviewed by, e.g., the patient's surgeon”).
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) 15-16 and 34-37 are rejected under 35 U.S.C. 103 as being unpatentable over Nawana et al. (US 20190110784 A1), hereinafter Nawana, in view of Ryan et al. (US 20180303552 A1), hereinafter Ryan.
Regarding claim 15 Nawana does not teach the second treatment stage is spaced apart from the first treatment stage by at least about 1 year.
However, Ryan teaches the second treatment stage is spaced apart from the first treatment stage by at least about 1 year (Ryan, [0102]).
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Nawana to incorporate the teachings of Ryan and account for developing patient-specific spinal treatments, operations, and procedures by iterative virtuous cycles (Nawana, Abstract and [0003]).
Regarding claim 16 Nawana does not teach the second treatment stage is spaced apart from the first treatment stage by at least about 3 years.
However, Ryan teaches the second treatment stage is spaced apart from the first treatment stage by at least about 3 years (Ryan, [0102]).
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Nawana to incorporate the teachings of Ryan and account for developing patient-specific spinal treatments, operations, and procedures by iterative virtuous cycles (Nawana, Abstract and [0003]).
Regarding claim 34 Nawana does not teach the operation of generating the multi-stage surgical plan is performed at least in part by a trained machine learning model.
However, Ryan teaches the operation of generating the multi-stage surgical plan is performed at least in part by a trained machine learning model (Ryan, [0052], [0056]-[0057], [0099], and [0100]).
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Nawana to incorporate the teachings of Ryan and account for developing patient-specific spinal treatments, operations, and procedures by iterative virtuous cycles (Nawana, Abstract and [0003]).
Regarding claim 35 Nawana does not teach the trained machine learning model compares the patient data to reference patient data to determine one or more aspects of the multi-stage surgical plan.
However, Ryan teaches the trained machine learning model compares the patient data to reference patient data to determine one or more aspects of the multi-stage surgical plan (Ryan, [0052], [0056]-[0057], [0099], and [0100]).
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Nawana to incorporate the teachings of Ryan and account for developing patient-specific spinal treatments, operations, and procedures by iterative virtuous cycles (Nawana, Abstract and [0003]).
Regarding claim 36 Nawana further teaches the first treatment stage and the second treatment stage are spaced apart in time by at least 6 months (Nawana, [0132]).
Regarding claim 37 Nawana further teaches generate a first virtual model showing predicted patient anatomy following the first treatment stage; and generate a second virtual model showing predicted patient anatomy following the second treatment stage, wherein the first virtual model and the second virtual model are transmitted with the multi-stage surgical plan for surgeon review (Nawana, [0022], [0024], [0032], [0034], [0170], [0174]-[0177], and [0306]).
Response to Arguments
Applicant's arguments filed 02/26/2026 have been fully considered but they are not persuasive. Regarding the 35 U.S.C. 101 Rejection, Applicant argues the claims do not recite an abstract idea. Examiner respectfully disagrees. Under broadest reasonable interpretation, the limitations of “receiving…”, “generating…”, “simulating…”, and “transmitting…” are steps a person, persons, or person with a computer tool can perform (see MPEP 2106.04(a)(2) states “the sub-groupings encompass both activity of a single person (for example, a person following a set of instructions or a person signing a contract online) and activity that involves multiple people (such as a commercial interaction), and thus, certain activity between a person and a computer (for example a method of anonymous loan shopping that a person conducts using a mobile phone) may fall within the “certain methods of organizing human activity” grouping”).
Applicant argues any alleged abstract idea is integrated into a practical application because the claims recite an improvement in the technical field. More specifically, the claims recite a technical process for using at least one virtual model of a patient to perform simulations of treatment stages to generate a multi-stage surgical plan. Examiner respectfully disagrees. The use of the virtual model is recited at a high level such that it amounts to “apply it”. MPEP 2106.05(a) states “Merely adding generic computer components to perform the method is not sufficient. Thus, the claim must include more than mere instructions to perform the method on a generic component or machinery to qualify as an improvement to an existing technology” and MPEP 2106.05(f) states “Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Similarly, “claiming the improved speed or efficiency inherent with applying the abstract idea on a computer” does not integrate a judicial exception into a practical application or provide an inventive concept. Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015)”.
Applicant argues the claims are similar to Example #42, claim 1. Examiner respectfully disagrees. Claim 1 of Example #42 was eligible because the additional elements recite “a specific improvement over prior art systems by allowing remote users to share information in real time in a standardized the additional elements recite a specific improvement over prior art systems by allowing remote users to share information in real time in a standardized”. The present application and claims do not recite similar features of “providing remote access to users over a network so any one of the users can update the information about the patient’s condition in the collection of medical records in real time through a graphical user interface, wherein the one of the users provides the updated information in a non-standardized format dependent on the hardware and software platform used by the one of the users”, “converting, by a content server, the non-standardized updated information into the standardized format”, and “automatically generating a message containing the updated information about the patient’s condition by the content server whenever updated information has been stored and… transmitting the message to all of the users over the computer network in real time, so that each user has immediate access to up-to-date patient information”. Instead, the present application is directed towards virtual model(s) for treating a patient’s spine and/or spinal region. Therefore, the claims are not similar to Example #42, claim 1.
Applicant argues the claims are similar to Example #49, claim 2. Examiner respectfully disagrees. Example #49, claim 2 is eligible because of its dependency from claim 1 and that it further limits the specific treatment as being “Compound X eye drops”, and thus recites a particular treatment. The present application does not recite a particular treatment, but rather provides a surgical plan for treating a patient’s spine or spinal region. MPEP 2106.04(d)(2) states “Examiners should keep in mind that in order to qualify as a “treatment” or “prophylaxis” limitation for purposes of this consideration, the claim limitation in question must affirmatively recite an action that effects a particular treatment or prophylaxis for a disease or medical condition. An example of such a limitation is a step of “administering amazonic acid to a patient” or a step of “administering a course of plasmapheresis to a patient.” If the limitation does not actually provide a treatment or prophylaxis, e.g., it is merely an intended use of the claimed invention or a field of use limitation, then it cannot integrate a judicial exception under the “treatment or prophylaxis” consideration. For example, a step of “prescribing a topical steroid to a patient with eczema” is not a positive limitation because it does not require that the steroid actually be used by or on the patient, and a recitation that a claimed product is a “pharmaceutical composition” or that a “feed dispenser is operable to dispense a mineral supplement” are not affirmative limitations because they are merely indicating how the claimed invention might be used” and “ Conversely, consider a claim that recites the same abstract idea and “administering a suitable medication to a patient.” This administration step is not particular, and is instead merely instructions to “apply” the exception in a generic way. Thus, the administration step does not integrate the mental analysis step into a practical application”.
Applicant argues the claims recite features, which alone or in combination, amount to significantly more than the abstract idea. More specifically, the claims recite a combination of additional elements that present a specific implementation for treating the spine and/or spinal region. Examiner respectfully disagrees. The additional elements, alone or in combination, are recited at a high level of generality that they amount to apply the abstract idea to the additional elements. MPEP 2106.05 states “Based on this analysis, the Court concluded that the claims amounted to “‘nothing significantly more’ than an instruction to apply the abstract idea of intermediated settlement using some unspecified, generic computer”, and therefore held the claims ineligible because they were directed to a judicial exception and failed the second part of the Alice/Mayo test. Alice Corp., 573 U.S. at 225-27, 110 USPQ2d at 1984” and MPEP 2106.05(f) stats “Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Similarly, “claiming the improved speed or efficiency inherent with applying the abstract idea on a computer” does not integrate a judicial exception into a practical application or provide an inventive concept. Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015)”. It is also noted, that although the claims also have a prior art rejection, 2106.05 states “Specifically, lack of novelty under 35 U.S.C. 102 or obviousness under 35 U.S.C. 103 of a claimed invention does not necessarily indicate that additional elements are well-understood, routine, conventional elements. Because they are separate and distinct requirements from eligibility, patentability of the claimed invention under 35 U.S.C. 102 and 103 with respect to the prior art is neither required for, nor a guarantee of, patent eligibility under 35 U.S.C. 101. The distinction between eligibility (under 35 U.S.C. 101) and patentability over the art (under 35 U.S.C. 102 and/or 103) is further discussed in MPEP § 2106.05(d)”. Therefore, the 35 U.S.C. 101 Rejection is maintained.
Regarding the 35 U.S.C. 102 Rejection, Applicant argues the prior art, Nawana, does not teach “wherein the second treatment stage is based at least in part on a predicted outcome of the first treatment stage, the predicted outcome including one or more simulated post-operative spinal metrics of the patient associated with performing the first treatment stage”. Examiner respectfully disagrees. Nawana recites [0022] “the plans for a second subset of the patients can include a surgical treatment, and determining the suggested plan can include comparing outcomes of the non-surgical treatments with outcomes of the surgical treatments… the processor can be configured to receive performance data regarding performances of surgical procedures included in each of the plans that include performance of the surgical procedure as at least part of the medical treatment, and determining the effectiveness can include choosing at least a one of the plans based at least on the performance data”, [0029] “The post-op module compares the stored electronic simulation with the stored data regarding the actual performance of the selected invasive treatment, and, based on the comparison of the stored electronic simulation with the stored data regarding the actual performance of the selected invasive treatment, determines a variance between the stored electronic simulation and the stored data regarding the actual performance of the selected invasive treatment in the storage unit. The recovery module provides a recommended post-op treatment plan for the patient based on at least the stored data regarding the actual performance of the selected invasive treatment, allows selection of a post-op treatment for the patient from a plurality of available post-op treatments including at least the recommended post-op treatment, receives information regarding compliance of the patient with the selected post-op treatment plan, and provides a recommended follow-up treatment for the patient based at least on the information regarding compliance of the patient with the recommended post-op treatment plan”, [0170] “the pre-op module 202 can allow surgeons to electronically perform three-dimensional (3D) simulated surgeries on virtual models of patients to test surgical ease and/or potential surgical outcomes before actually performing the surgical procedure. The simulated surgeries can include variations of the same surgical procedure on a patient so as to try different surgical instruments and/or different surgical strategies”, [0204] “The operation module 204 can also track various aspects of the surgical procedure, e.g., instrument use, personnel activity, patient radiation exposure without the patient having to wear a radiation monitoring device such as a dosimeter. patient vital signs, etc., which can allow for mid-course corrections, help inform surgical staff of their surgical duties, and/or facilitate post-op analysis of the surgical procedure by the post-op module 206, as discussed further below. The information tracked by the operation module 204 can also be used by the system 10, e.g., by the recovery module 208, to facilitate patient recovery and continued treatment post-surgery, as discussed further below. The information tracked by the operation module 204 can also be used by the system 10, e.g., by the diagnosis and treatment module 200 and/or the pre-op module 202, in recommending and/or planning future surgeries involving the patient and/or other patients in circumstances similar to the patient on which the surgical procedure was performed. In this way, the system 10 can become smarter over time in various ways, such as by analyzing and recommending effective treatments in view of historical surgical outcomes, by providing recommended surgical strategies in view of a particular surgeon's historical performance in certain types of surgeries and/or with certain types of surgical instruments, and/or by providing recommended surgical strategies in view of multiple different surgeons' historical performance in certain types of surgeries and/or with certain types of surgical instrument”, and [0272] “The system 10, e.g., the post-op module 206, can be configured to perform an analysis on the collected data through one or more algorithms to generate potential new innovations to the surgical procedure, such as a combining of steps, introduction of a new tool from a different procedure, adjustment of a physical location of OR staff or equipment, etc. These generated innovations can then be available for review by users of the system 10, e.g., a user planning a new surgical procedure, and can be integrated into future cases. The system 10 can be configured to record when the innovation was used and can be configured to track the outcomes of these procedures to compare against the outcomes from similar patients/procedures before the innovation was used. The system 10 can be configured to determine through comparison how effective the innovation was, resulting in further learning of the system 10 on how and when to generate the most effective innovations. This analysis can also help the system 10 determine if it would be beneficial to continue recommending this innovation to users and eventually include it as a standardized part of the procedure or to remove it due to its lack of effectiveness”, as well as FIG. 2 and FIG. 9. Therefore, the 35 U.S.C. 102 Rejection is maintained.
Regarding the 35 U.S.C. 103 Rejection, Applicant argues the prior art Ryan, fails to cure the deficiencies of Nawana. Examiner respectfully disagrees because the independent claims are taught by the prior art, Nawana, as shown above. Therefore, the 35 U.S.C. 103 Rejection is maintained.
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.
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/R.S.S./Examiner, Art Unit 3681
/PETER H CHOI/Supervisory Patent Examiner, Art Unit 3681
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