DETAILED ACTION
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on September 1, 2026 has been entered. Claims 1, 5, 7, 10, 13, 17, and 20 have been amended. Claim 4 is cancelled. Claims 1-3 and 5-20 are presented for examination.
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 .
Response to Arguments
Applicant's arguments filed September 1, 2026 have been fully considered but they are not persuasive.
Regarding the art rejections, Applicant argues that the cited prior art references do not address the claim amendments. The Zhao reference has been introduced into the rejections in order to help address the claim amendments.
Regarding the rejection under 35 U.S.C. § 101, Applicant states, “The claims recite a concrete technical mechanism - comparing incoming data against stored templates of known formats to select which extraction rule applies - that confines the filtering to a particular technical implementation, rather than filtering content in the abstract.” (Page 13 of Applicant’s response) It is not clear to which “technical mechanism” Applicant refers. A human user can filter out only needed data based on a template of information. For example, a human user can choose to extract information from columns 1 and 3 as listed in a printed document. Also, a human user can choose to extract information from only a row identifying treatment results from a printed document. There is no clear “technical mechanism” presented to filter content.
Applicant compares the claims of the instant application to the eligible claims of the BASCOM patent (pages 13-14 of Applicant’s response). The Examiner does not find the claims of the instant application to be analogous to the eligible claims of the BASCOM patent. For example, BASCOM’s claims were found to use an ordered combination of technical elements that split the filtering process to perform hybrid filtering, which the Court found to be more than a generic presentation of filtering. Additionally, Applicant’s Specification does not describe a specific technical arrangement of the additional elements that performs more than generic filtering. Applicant’s claims apply multiple rules to filter the data and specify that the patient data remains in the local network (thereby implying that the patient data is filtered out before QC data is provided to a cloud-based QC data management platform). The filtering is performed at the local network in Applicant’s claims and rules are set for defining how to filter the data. There is no specific arrangement of the additional elements that is used to perform specific filtering operations, like unconventional filtering operations from a technical point of view. MPEP § 2106.05(f) explains that “limitations that confine the judicial exception to a particular, practical application of the judicial exception may amount to significantly more or integrate the judicial exception into a practical application. For example, in BASCOM, the combination of additional elements, and specifically ‘the installation of a filtering tool at a specific location, remote from the end‐users, with customizable filtering features specific to each end user’ where the filtering tool at the ISP was able to ‘identify individual accounts that communicate with the ISP server, and to associate a request for Internet content with a specific individual account,’ were held to be meaningful limitations because they confined the abstract idea of content filtering to a particular, practical application of the abstract idea. 827 F.3d at 1350-51, 119 USPQ2d at 1243.” Unlike the claims in BASCOM, Applicant’s claims do not present technical details of the filtering tool to "identify individual accounts that communicate with the ISP server, and to associate a request for Internet content with a specific individual account.”
Additionally noted is that the BASCOM patent (U.S. Patent No. 5,987,606) was issued in 1999 and the state of the art has changed significantly between 1999 and 2022 (i.e., the year of the earliest priority claim of the instant application). Technical arrangements that were not deemed to be well-understood, routine, and conventional and/or processing operations that were not deemed to be generic processing operations in 1999 may very well have become well-understood, routine, and conventional and/or generic processing operations by 2022.
On page 15 of the response, Applicant submits that the ordered combination presented in the claims “addresses a technical problem inherent to networked laboratory instrumentation: enabling cloud-based QC analytics without exposing sensitive patient test results to an external network.” Again, as explained above, it is not clear to which “technical mechanism” (or ordered combination of additional elements) Applicant refers. A human user can filter out only needed data based on a template of information. For example, a human user can choose to extract information from columns 1 and 3 as listed in a printed document. Also, a human user can choose to extract information from only a row identifying treatment results from a printed document. There is no clear “technical mechanism” presented to filter content.
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 1-3 and 5-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter.
Claims 1-3 and 5-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claimed invention is directed to “managing instruments and, in particular, to using a management device to mediate communications between an instrument and a cloud-based Quality Control (QC) data management system” (Spec: ¶ 2) without significantly more.
Step
Analysis
1: Statutory Category?
Yes – The claims fall within at least one of the four categories of patent eligible subject matter. Process (claims 1-3, 5-9), Apparatus (claims 10-16), Article of Manufacture (claims 17-20)
Independent claims:
Step
Analysis
2A – Prong 1: Judicial Exception Recited?
Yes – Aside from the additional elements identified in Step 2A – Prong 2 below, the claims recite:
[Claims 1, 17] A method/steps of providing cloud-based Quality Control (QC) data management, the method comprising:
receiving test result data for an instrument, the test result data including a patient test result and QC data;
filtering the test result data by applying a first rule and a second rule to the test result data,
wherein the first rule identifies a format of the test result data by inspecting the test result data and comparing it to a set of templates of known data formats, and the second rule is selected based on the identified format and applied to extract the OC data and remove the patient test result;
providing the QC data;
receiving a response to the QC data, the response indicating an operable status of the instrument; and
providing the response to a manager of the instrument.
[Claim 10] provide management of QC data;
generate test result data, the test result data including a patient test result and QC data;
receive the test result data and filter the test result data to extract the QC data and remove the patient test result from the test result data using a set of rules, wherein a first rule identifies a format of the test result data by inspecting the test result data and comparing it to a set of templates of known data formats, and a second rule is selected based on the identified format and applied to extract the OC data and remove the patient test result; and
process the QC data to generate a result and send the result,
forwards the result, and implements a corrective action for the instrument based on the result.
Aside from the additional elements, the aforementioned claim details exemplify the abstract idea(s) of a mental process (since the details include concepts performed in the human mind, including an observation, evaluation, judgment, and/or opinion). As explained in MPEP § 2106(a)(2)(C)(III), “The courts consider a mental process (thinking) that ‘can be performed in the human mind, or by a human using a pen and paper’ to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). As the Federal Circuit explained, ‘methods which can be performed mentally, or which are the equivalent of human mental work, are unpatentable abstract ideas the ‘basic tools of scientific and technological work’ that are open to all.’’ 654 F.3d at 1371, 99 USPQ2d at 1694 (citing Gottschalk v. Benson, 409 U.S. 63, 175 USPQ 673 (1972)).” The limitations reproduced above, as drafted, are a process that, under its broadest reasonable interpretation, covers performance of the limitations in the mind but for the recitation of generic computer components. That is, other than reciting the additional elements identified in Step 2A – Prong 2 below, nothing in the claim elements precludes the steps from practically being performed in the mind and/or by a human using a pen and paper. For example, but for the recitations of generic computer and other processing components (identified in Step 2A – Prong 2 below), the respectively recited steps/functions of the claims, as drafted and set forth above, are a process that, under its broadest reasonable interpretation, covers performance of the limitations in the mind and/or with the use of pen and paper. Aside from the general implementation of the various devices, networks, and cloud instruments (which are presented at a high level), a human user can gather test results, extract quality control data, provide the quality control data, receive a response to the quality control data, and provide the response to a manager of the instrument. A human user can select and implement a corrective action and plan for downtime. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind (and/or with pen and paper) but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claims recite an abstract idea.
Aside from the additional elements, the aforementioned claim details exemplify a method of organizing human activity (since the details include examples of commercial or legal interactions, including advertising, marketing or sales activities or behaviors, and/or business relations and managing personal behavior or relationships or interactions between people, including social activities, teaching, and following rules or instructions). More specifically, the evaluated process is related to “managing instruments and, in particular, to using a management device to mediate communications between an instrument and a cloud-based Quality Control (QC) data management system” (Spec: ¶ 2), which (under its broadest reasonable interpretation) is an example of quality control (i.e., business relationships) within an organization (i.e., organizing human activity); therefore, aside from the recitations of generic computer and other processing components (identified in Step 2A – Prong 2 below), the limitations identified in the more detailed claim listing above encompass the abstract idea of organizing human activity.
Filtering test result data is an example of filtering content. MPEP § 2106.04(a)(2)(II)(C) cites the following as an example of managing personal behavior, i.e., organizing human activity: “filtering content, BASCOM Global Internet v. AT&T Mobility, LLC, 827 F.3d 1341, 1345-46, 119 USPQ2d 1236, 1239 (Fed. Cir. 2016) (finding that filtering content was an abstract idea under step 2A, but reversing an invalidity judgment of ineligibility due to an inadequate step 2B analysis).” MPEP § 2106.04(a)(2)(III)(D) cites the following as an example of a mental process: “An application program interface for extracting and processing information from a diversity of types of hard copy documents – Content Extraction, 776 F.3d at 1345, 113 USPQ2d at 1356.”
2A – Prong 2: Integrated into a Practical Application?
No – The judicial exception(s) is/are not integrated into a practical application.
Claim 1 recites a computer-implemented method of providing cloud-based Quality Control (QC) data management. Data is received from and provided over a local and/or external network to and from various devices (including an instrument) using a cloud-based QC data management platform. A response is provided, via the local network, to middleware that manages the instrument. The use of a cloud-based management platform also presents a general link to a field of use. Claim 1 recites wherein the test result remains in the local network without being sent to the external network.
Claim 10 recites a networked computing system for providing management of QC data, the networked computing system comprising:
one or more instruments that generate test result data, the test result data including patient data and QC data;
a Laboratory Information System (LIS) coupled to the one or more instruments via a local network;
a QC data flow system coupled to the LIS via the local network, the QC data flow system including one or more computing devices configured to receive the test result data and extract the QC data from the test result data using a set of one or more rules; and
a cloud-based QC data management platform coupled to the QC data flow system via an external network, the cloud-based QC data management platform including one or more computing devices configured to process the QC data to generate a result and send the result, via the external network, to the QC data flow system,
wherein the QC data flow system forwards the result to the LIS, and the LIS implements a corrective action for the instrument based on the result, and wherein the patient test result remains in the local network without being sent to the external network.
In other words, data is received from and provided over a local and/or external network to and from various devices (including an instrument) using a cloud-based QC data management platform. The use of a Laboratory Information System (LIS) also presents a general link to a field of use.
Claim 17 recites a non-transitory computer-readable medium configured to store code comprising instructions, wherein the instructions, when executed by one or more processors, cause the one or more processors to perform the recited steps. Data is received from and provided over a local and/or external network to and from various devices (including an instrument) using a cloud-based QC data management platform. A response is provided, via the local network, to middleware that manages the instrument. The use of a cloud-based management platform also presents a general link to a field of use. Claim 17 recites wherein the test result remains in the local network without being sent to the external network.
The claims as a whole merely describe how to generally “apply” the abstract idea(s) in a computer environment. The claimed processing elements are recited at a high level of generality and are merely invoked as a tool to perform the abstract idea(s). Simply implementing the abstract idea(s) on a general-purpose processor is not a practical application of the abstract idea(s); Applicant’s specification discloses that the invention may be implemented using general-purpose processing elements and other generic components (Spec: ¶¶ 39-41).
The use of a processor/processing elements (e.g., as recited in all of the claims) facilitates generic processor operations. The use of a memory or machine-readable media with executable instructions facilitates generic processor operations.
The additional elements are recited at a high-level of generality (i.e., as generic processing elements performing generic computer functions) such that the incorporation of the additional processing elements amounts to no more than mere instructions to apply the judicial exception(s) using generic computer components. There is no indication in the Specification that the steps/functions of the claims require any inventive programming or necessitate any specialized or other inventive computer components (i.e., the steps/functions of the claims may be implemented using capabilities of general-purpose computer components). Accordingly, the additional elements do not integrate the abstract ideas into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea(s).
The processing components presented in the claims simply utilize the capabilities of a general-purpose computer and are, thus, merely tools to implement the abstract idea(s). As seen in MPEP § 2106.05(a)(I) and § 2106.05(f)(2), the court found that accelerating a process when the increased speed solely comes from the capabilities of a general-purpose computer is not sufficient to show an improvement in computer-functionality and it amounts to a mere invocation of computers or machinery as a tool to perform an existing process (see FairWarning IP, LLC v. Iatric Sys., 839 F.3d 1089, 1095, 120 USPQ2d 1293, 1296 (Fed. Cir. 2016)).
There is no transformation or reduction of a particular article to a different state or thing recited in the claims.
Additionally, even when considering the operations of the additional elements as an ordered combination, the ordered combination does not amount to significantly more than what is present in the claims when each operation is considered separately.
It is noted that the operations related to receiving, transmitting, storing, and displaying data have been attributed to abstract ideas in Step 2A – Prong 1 above; however, even if these operations were seen as pre- and post- solution activities in relation to the quality control testing and performance of corrective actions, the operations of generally receiving, transmitting, storing, and/or outputting (e.g., displaying) data would still be examples of insignificant extra-solution activity.
2B: Claim(s) Provide(s) an Inventive Concept?
No – The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception(s). As discussed above with respect to integration of the abstract idea(s) into a practical application, the use of the additional elements to perform the steps identified in Step 2A – Prong 1 above amounts to no more than mere instructions to apply the exceptions using a generic computer component(s). Mere instructions to apply an exception using a generic computer component(s) cannot provide an inventive concept. The claims are not patent eligible.
As explained above, there is nothing in the claims as a whole that adds significantly more to the abstract idea(s). Even if the operations related to receiving, transmitting, storing, and displaying data were seen as pre- and post- solution activities in relation to the quality control testing and performance of corrective actions, evidence regarding operations of the additional elements that are well-understood, routine, and conventional is provided below.
MPEP § 2106.05(d)(II) sets forth the following:
The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity.
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Dependent claims:
Step
Analysis
2A – Prong 1: Judicial Exception Recited?
Yes – Aside from the additional elements identified in Step 2A – Prong 2 below, the claims recite:
[Claims 2, 18] wherein a corrective action is triggered responsive to the response.
[Claim 3] wherein the corrective action is automatically triggering preventative maintenance.
[Claims 4, 19] wherein the filtering is performed using a set of one or more rules.
[Claim 5] receiving an updated rule set;
receiving additional test result data for the instrument; and
extracting additional QC data from the additional test result data using the updated rule set.
[Claim 6] wherein the instrument is a clinical diagnostic instrument.
[Claims 7, 20] identifying a triggering event indicating that connection to the cloud-based QC data management platform is unavailable;
responsive to the triggering event, storing the QC data for up to a maximum amount of time; and
responsive to receiving an indication that a connection is available again, forwarding the stored QC data.
[Claim 8] responsive to forwarding the QC data, deleting the QC data.
[Claim 9] wherein the triggering event is user-input indicating planned downtime for the QC data management platform.
[Claim 14] identifying a triggering event indicating that connection to the cloud-based QC data management platform is unavailable;
responsive to the triggering event, storing the QC data for up to a set maximum of time; and
responsive to receiving an indication that the connection is available again, forwarding the stored QC data.
[Claim 15] responsive to forwarding the QC data, deleting the QC data.
[Claim 16] wherein the triggering event is user-input indicating planned downtime for the connection cloud-based QC data management platform.
The dependent claims further present details of the abstract ideas identified in regard to the independent claims.
Aside from the additional elements, the aforementioned claim details exemplify the abstract idea(s) of a mental process (since the details include concepts performed in the human mind, including an observation, evaluation, judgment, and/or opinion). As explained in MPEP § 2106(a)(2)(C)(III), “The courts consider a mental process (thinking) that ‘can be performed in the human mind, or by a human using a pen and paper’ to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). As the Federal Circuit explained, ‘methods which can be performed mentally, or which are the equivalent of human mental work, are unpatentable abstract ideas the ‘basic tools of scientific and technological work’ that are open to all.’’ 654 F.3d at 1371, 99 USPQ2d at 1694 (citing Gottschalk v. Benson, 409 U.S. 63, 175 USPQ 673 (1972)).” The limitations reproduced above, as drafted, are a process that, under its broadest reasonable interpretation, covers performance of the limitations in the mind but for the recitation of generic computer components. That is, other than reciting the additional elements identified in Step 2A – Prong 2 below, nothing in the claim elements precludes the steps from practically being performed in the mind and/or by a human using a pen and paper. For example, but for the recitations of generic computer and other processing components (identified in Step 2A – Prong 2 below), the respectively recited steps/functions of the claims, as drafted and set forth above, are a process that, under its broadest reasonable interpretation, covers performance of the limitations in the mind and/or with the use of pen and paper. Aside from the general implementation of the various devices, networks, and cloud instruments (which are presented at a high level), a human user can gather test results, extract quality control data, provide the quality control data, receive a response to the quality control data, and provide the response to a manager of the instrument. A human user can select and implement a corrective action and plan for downtime. A human user can also selectively delete data, including in response to a triggering event. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind (and/or with pen and paper) but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claims recite an abstract idea.
Aside from the additional elements, the aforementioned claim details exemplify a method of organizing human activity (since the details include examples of commercial or legal interactions, including advertising, marketing or sales activities or behaviors, and/or business relations and managing personal behavior or relationships or interactions between people, including social activities, teaching, and following rules or instructions). More specifically, the evaluated process is related to “managing instruments and, in particular, to using a management device to mediate communications between an instrument and a cloud-based Quality Control (QC) data management system” (Spec: ¶ 2), which (under its broadest reasonable interpretation) is an example of quality control (i.e., business relationships) within an organization (i.e., organizing human activity); therefore, aside from the recitations of generic computer and other processing components (identified in Step 2A – Prong 2 below), the limitations identified in the more detailed claim listing above encompass the abstract idea of organizing human activity.
Filtering test result data is an example of filtering content. MPEP § 2106.04(a)(2)(II)(C) cites the following as an example of managing personal behavior, i.e., organizing human activity: “filtering content, BASCOM Global Internet v. AT&T Mobility, LLC, 827 F.3d 1341, 1345-46, 119 USPQ2d 1236, 1239 (Fed. Cir. 2016) (finding that filtering content was an abstract idea under step 2A, but reversing an invalidity judgment of ineligibility due to an inadequate step 2B analysis).” MPEP § 2106.04(a)(2)(III)(D) cites the following as an example of a mental process: “An application program interface for extracting and processing information from a diversity of types of hard copy documents – Content Extraction, 776 F.3d at 1345, 113 USPQ2d at 1356.”
2A – Prong 2: Integrated into a Practical Application?
No – The judicial exception(s) is/are not integrated into a practical application.
The dependent claims include the additional elements of their independent claims.
Claim 1 recites a computer-implemented method of providing cloud-based Quality Control (QC) data management. Data is received from and provided over a local and/or external network to and from various devices (including an instrument) using a cloud-based QC data management platform. A response is provided, via the local network, to middleware that manages the instrument. The use of a cloud-based management platform also presents a general link to a field of use. Claim 1 recites wherein the patient data remains in the local network.
Claim 5 recites receiving an updated rule set from the cloud-based QC data management platform.
Claim 7 recites, responsive to the triggering event, storing the QC data on the local network for up to a maximum amount of time; and, responsive to receiving an indication that the connection to the cloud-based QC data management platform is available again, forwarding the stored QC data to the cloud-based QC data management platform.
Claim 8 recites, responsive to forwarding the QC data, deleting the QC data from the local network.
Claim 9 recites wherein the triggering event is user-input indicating planned downtime for the connection cloud-based QC data management platform.
Claim 10 recites a networked computing system for providing management of QC data, the networked computing system comprising:
one or more instruments that generate test result data, the test result data including patient data and QC data;
a Laboratory Information System (LIS) coupled to the one or more instruments via a local network;
a QC data flow system coupled to the LIS via the local network, the QC data flow system including one or more computing devices configured to receive the test result data and extract the QC data from the test result data using a set of one or more rules; and
a cloud-based QC data management platform coupled to the QC data flow system via an external network, the cloud-based QC data management platform including one or more computing devices configured to process the QC data to generate a result and send the result, via the external network, to the QC data flow system,
wherein the QC data flow system forwards the result to the LIS, and the LIS implements a corrective action for the instrument based on the result, and wherein the patient data remains in the local network.
In other words, data is received from and provided over a local and/or external network to and from various devices (including an instrument) using a cloud-based QC data management platform. The use of a Laboratory Information System (LIS) also presents a general link to a field of use.
Claim 11 recites wherein the QC data flow system is a computing device located within a geographic space that includes the instrument.
Claim 12 recites wherein the QC data flow system is a virtual machine running on the LIS.
Claim 13 recites wherein all ports of the QC data flow system except those used to receive the test result data and provide the QC data to the cloud-based QC data management platform are disabled.
Claim 14 recites, responsive to the triggering event, storing the QC data on the local network for up to a set maximum of time; and, responsive to receiving an indication that the connection to the cloud-based QC data management platform is available again, forwarding the stored QC data to the cloud-based QC data management platform.
Claim 15 recites, responsive to forwarding the QC data, deleting the QC data from the local network.
Claim 17 recites a non-transitory computer-readable medium configured to store code comprising instructions, wherein the instructions, when executed by one or more processors, cause the one or more processors to perform the recited steps. Data is received from and provided over a local and/or external network to and from various devices (including an instrument) using a cloud-based QC data management platform. A response is provided, via the local network, to middleware that manages the instrument. The use of a cloud-based management platform also presents a general link to a field of use. Claim 17 recites wherein the patient data remains in the local network.
Claim 20 recites, responsive to the triggering event, storing the QC data on the local network for up to a maximum amount of time; and, responsive to receiving an indication that the connection to the cloud-based QC data management platform is available again, forwarding the stored QC data to the cloud-based QC data management platform.
The claims as a whole merely describe how to generally “apply” the abstract idea(s) in a computer environment. The claimed processing elements are recited at a high level of generality and are merely invoked as a tool to perform the abstract idea(s). Simply implementing the abstract idea(s) on a general-purpose processor is not a practical application of the abstract idea(s); Applicant’s specification discloses that the invention may be implemented using general-purpose processing elements and other generic components (Spec: ¶¶ 39-41).
The use of a processor/processing elements (e.g., as recited in all of the claims) facilitates generic processor operations. The use of a memory or machine-readable media with executable instructions facilitates generic processor operations.
The additional elements are recited at a high-level of generality (i.e., as generic processing elements performing generic computer functions) such that the incorporation of the additional processing elements amounts to no more than mere instructions to apply the judicial exception(s) using generic computer components. There is no indication in the Specification that the steps/functions of the claims require any inventive programming or necessitate any specialized or other inventive computer components (i.e., the steps/functions of the claims may be implemented using capabilities of general-purpose computer components). Accordingly, the additional elements do not integrate the abstract ideas into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea(s).
The processing components presented in the claims simply utilize the capabilities of a general-purpose computer and are, thus, merely tools to implement the abstract idea(s). As seen in MPEP § 2106.05(a)(I) and § 2106.05(f)(2), the court found that accelerating a process when the increased speed solely comes from the capabilities of a general-purpose computer is not sufficient to show an improvement in computer-functionality and it amounts to a mere invocation of computers or machinery as a tool to perform an existing process (see FairWarning IP, LLC v. Iatric Sys., 839 F.3d 1089, 1095, 120 USPQ2d 1293, 1296 (Fed. Cir. 2016)).
There is no transformation or reduction of a particular article to a different state or thing recited in the claims.
Additionally, even when considering the operations of the additional elements as an ordered combination, the ordered combination does not amount to significantly more than what is present in the claims when each operation is considered separately.
It is noted that the operations related to receiving, transmitting, storing, and displaying data have been attributed to abstract ideas in Step 2A – Prong 1 above; however, even if these operations were seen as pre- and post- solution activities in relation to the quality control testing and performance of corrective actions, the operations of generally receiving, transmitting, storing, and/or outputting (e.g., displaying) data would still be examples of insignificant extra-solution activity.
2B: Claim(s) Provide(s) an Inventive Concept?
No – The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception(s). As discussed above with respect to integration of the abstract idea(s) into a practical application, the use of the additional elements to perform the steps identified in Step 2A – Prong 1 above amounts to no more than mere instructions to apply the exceptions using a generic computer component(s). Mere instructions to apply an exception using a generic computer component(s) cannot provide an inventive concept. The claims are not patent eligible.
As explained above, there is nothing in the claims as a whole that adds significantly more to the abstract idea(s). Even if the operations related to receiving, transmitting, storing, and displaying data were seen as pre- and post- solution activities in relation to the quality control testing and performance of corrective actions, evidence regarding operations of the additional elements that are well-understood, routine, and conventional is provided below.
MPEP § 2106.05(d)(II) sets forth the following:
The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity.
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Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-3, 5-11, and 14-20 are rejected under 35 U.S.C. 103 as being unpatentable over Balwani (US 2015/0331946) in view of Zhao et al. (WO 2013/123085 A1).
[Claim 1] Balwani discloses a computer-implemented method of providing cloud-based Quality Control (QC) data management (¶ 47 – “Referring now to FIG. 3, at least one exemplary embodiment of a system for use with at least one method herein will now be described. FIG. 3 shows that in this embodiment, information can be sent from the device 100 through a network 70 to the cloud 110. By way of non-limiting example, the cloud 110 comprises one or more servers 120 in one or more data networks. Server 120 may be a cluster of servers. In one non-limiting example, a database on one or more of the servers 120 may be a cluster database. By way of non-limiting example, the cloud 110 comprises one or more computing devices in communication with one or more data networks. As seen in FIG. 3, data is then sent from the cloud 110 through a network 72 to the physical laboratory 10 with co-located or locally connected LIS 30 therein.”; ¶ 161 – “Calibration and/or maintenance may occur on a periodic basis. In some embodiments, device calibration and/or maintenance may automatically occur at regular or irregular intervals. Device calibration and/or maintenance may occur when one or more condition is detected from the device. For example, if a component appears to be faulty, the device may run a diagnostic on associated components. Device calibration and/or maintenance may occur at the instruction of an operator of the device. Device calibration and/or maintenance may also occur upon automated instruction from an external device. The calibration and quality control (QC) cartridge is briefly described in the next paragraph. The goal of the calibration cartridge is to enable the quantitative assessment and adjustment of each module/detector of the device. For example, by performing a variety of assay steps, functionality is tested/evaluated for the pipette, gantry, centrifuge, cameras, spectrometer, nucleic acid amplification module, thermal control unit, and cytometer. Each measurement made during calibration cartridge runs with reagent controls may be compared to device requirements for precision. By way of non-limiting example, there is a pass fail outcome for these results. If re-calibration is required, the data generated is used to recalibrate the device (such as the device sensors and pipettes). Recalibration ensures that each device is accurate. Some QC can also be performed automatically in the device without introducing a cartridge. For example, the light sources in the device can be used to periodically QC the optical sensors in the device. An external device or control may maintain a device calibration schedule and/or device maintenance schedule for a plurality of devices. Device calibration and/or maintenance may occur on a time-based schedule or a use-based schedule. For example, devices that are used more frequently than others may be calibrated and/or maintained more frequently and/or vice versa. QC data may be indexed with data stored, for example, on the sample processing device or an external device.”; ¶ 171 – “In some embodiments, an alert may be provided if someone is trying to open a device, or if someone comes within the device's proximity. In some instances, an alert may be provided if the device housing is breached. Similarly, an alert may be provided if the device falls, tips over, or if an error is detected. The device may encompass a stabilization system with, optionally, shock absorbance and dampening capabilities to prevent it from tipping when for example moving in vehicles at high speeds. In some instances, if the device detects that the device is being opened, approached, or tampered with, a camera on the device may capture an image of the device surroundings. The device may capture an image of the individual trying to open the device. The data associated with the device may be sent to the cloud or an external device. The device associated with the tampering of the device, such as an image of an individual tampering with the device may be transmitted from the device. The data associated with the device, which may include one or more image, may be stored in the device. In the event that the device is not able to immediately transmit the data, the data may be transmitted once the device is able and/or connected to a network.”), the method comprising:
receiving, via a local network, test result data for an instrument, the test result data including a patient test result and QC data (¶ 68 – “In some embodiments, the system can be configured such as the system with the LIS 30 will be there to receive results from a reference laboratory. A reference laboratory may be one that performs sample testing but is not the laboratory that reports out the results to the patient and/or physician. In this non-limiting example, the system may have one or more sample processing devices 100 that report data to a reference laboratory that finalizes the results and sends the data to the receiving laboratory, or sends the receiving laboratory the raw sample data through a pathways such as through a gateway including but not limited to a broker application and/or listener application 50. Service provided by a reference laboratory allows for greater capacity for the receiving laboratory to process samples and send out test results while still maintaining a seamless interaction between the laboratory and the patient or physician. Even if one laboratory such as a reference laboratory has looked at the test results, the receiving laboratory still reviews and signs off on the test results. The results may then be relayed as results certified by the receiving laboratory. By way of example and not limitation, three scenarios include, but are not limited to: analyzer device to LIS, reference lab to another lab, or lab providing service directly to doctor.”; ¶ 104 – “In one embodiment, it may be desirable that the perception to the LIS is that to the that all the devices are “local” in the sense that they provide data to the LIS as if they were part of the local system physically coupled by wired connections to the LIS but are instead coupled to the LIS through a data network comprising components such as but not limited to a LAN, WAN, or external computer processor(s) that may define a “cloud” network.”; ¶¶ 162, 167-168 – QC data may be transmitted (including received) locally and/or to (received by) an external device.);
providing, via an external network, the QC data to a cloud-based QC data management platform (¶¶ 162, 167-168 – QC data may be transmitted (including received) locally and/or to (received by) an external device.; ¶ 47 – “Referring now to FIG. 3, at least one exemplary embodiment of a system for use with at least one method herein will now be described. FIG. 3 shows that in this embodiment, information can be sent from the device 100 through a network 70 to the cloud 110. By way of non-limiting example, the cloud 110 comprises one or more servers 120 in one or more data networks. Server 120 may be a cluster of servers. In one non-limiting example, a database on one or more of the servers 120 may be a cluster database. By way of non-limiting example, the cloud 110 comprises one or more computing devices in communication with one or more data networks. As seen in FIG. 3, data is then sent from the cloud 110 through a network 72 to the physical laboratory 10 with co-located or locally connected LIS 30 therein.”);
receiving, from the cloud-based QC data management platform, a response to the QC data, the response indicating an operable status of the instrument (¶¶ 82-84 – Status indicators for the sample processing units (SPUs) may be displayed. Additional information related to quality control (QC), like temperature of a cartridge, may be displayed (as specifically discussed in ¶¶ 61, 84, 168). The disclosed invention may be cloud-based (¶¶ 61, 59, 67).); and
providing the response, via the local network, to middleware that manages the instrument (¶ 40 – “Referring now to FIG. 1A, when a plurality of biological sample analyzers 12 are in a laboratory 10, there is typically at least one connectivity hub 20 such as but not limited to a data connectivity hub such as a USB hub, wifi hub, or other data protocol hub that physically connects the sample analyzers 12 to the LIS 30. In some cases, there is a terminal 22 (instead of a USB hub) that connects to the multiple sample analyzers 12. Optionally, there may be multiple terminals 22, multiple hubs 20, and/or multiple sets of analyzers 12. There can be multiple computers, terminals, or servers that are brokers that run middleware to send the information to LIS 30. These computers, terminals, or servers are also running the LIS software, which allows the data to be sent to a database in the LIS 30.”; ¶¶ 82-84 – Status indicators for the sample processing units (SPUs) may be displayed. Additional information related to quality control (QC), like temperature of a cartridge, may be displayed (as specifically discussed in ¶¶ 61, 84, 168). The disclosed invention may be cloud-based (¶¶ 61, 59, 67). As explained in ¶ 61, “the performance of the device are fed to the laboratory managed director or authorized personnel who can look at the device information including performance information remotely and once they are satisfied they can green-light sending the data/result to LIS 30. Optionally, the data is sent directly to LIS 30, but laboratory managed director or authorized personnel can go see the individual machine performance if the data to LIS 30 triggers certain flag. In this non-limiting example, the laboratory managed director or authorized personnel can touch-click expand, see the quality of the data, performance, and/or replicates to verify if they trust the data.” The displayed information may be acted upon. “For at least some embodiments herein, the advantage here is that analytical and/or sample processing device can be anywhere in the world but laboratory director can trust it based on knowledge about the device and its recent performance history. Optionally, some embodiments may configure the remote device to have limited local user control of the device. Additionally, the laboratory director can push quality control (QC) out to the analytical or sample processing device to tell it to run calibrator(s) or to shut it down until someone runs a calibrator (taking the device off-line) until a control cartridge and/or control protocol is run.” (Balwani: ¶ 63); ¶ 67 – “In one embodiment herein, the device 100 has a connection to LIS 30 that is wireless. Optionally, some may view this as a brokerless LIS system. In the embodiment, the cloud 110 is the broker. Optionally, there is a pairing mechanism that associates certain machines or servers in the cloud with certain listener applications 50. Optionally, an administrator can set which machines or servers are in the environment. The system can also search the network to see which machines or servers are in the environment. If the device is not on the same LAN, it is still accessible on WAN. This listener application 50 is only listening for its designated set of machines.” In other words, the devices of the system may be accessed and/or controlled, including via a LAN or WAN, with assistance of the cloud.).
Balwani receives test result data including patient data and QC data (as discussed above); however, Balwani does not explicitly disclose:
filtering the test result data by applying a first rule and a second rule to the test result data,
wherein the first rule identifies a format of the test result data by inspecting the test result data and comparing it to a set of templates of known data formats, and the second rule is selected based on the identified format and applied to extract the QC data and remove the patient test result;
wherein the patient test result remains in the local network without being sent to the external network.
Zhao allows for specified metadata to be stripped from 3D medical image data using an anonymization template so that an anonymized version of the 3D medical image data can be sent to another system, such as a cloud service (Zhao: ¶ 31 – “Database 110 may be a data store to store medical data such as digital imaging and communications in medicine (DICOM) compatible data or other image data.”; ¶ 104 – “Figure 11 is a screenshot illustrating examples of GUIs for configuring anonymous data gateway management according to certain embodiments of the invention. GUI 1100 can be presented by activating link 1008 of Figure 10A. Referring to Figure 11, GUI 1100 allows a user to specify items to be anonymized, where each item is specified in one of the entries listed in GUI 1100. Each item is referenced by its DICOM tag 1101, name 1102, original value 1103 to be replaced, and replacement value 1104 to replace the corresponding original value.“; ¶ 105 – “Figure 13 is a flow diagram illustrating a method for anonymizing medical data according to another embodiment of the invention. Method 1300 may be performed by any of data gateway managers 901-902, 921 of Figure 9. Referring to Figure 13, at block 1301, a local device (e.g., gateway manager/router/computer) receives a 3D medical image data captured by a medical imaging device. At block 1302, the 3D medical image data is anonymized including removing certain metadata associated with the 3D medical image data based on an anonymization template. At block 1303, the anonymized 3D medical image data is then automatically uploaded to a cloud server, using a network connection established via an internet port of the local device.“).
Zhao’s anonymization is performed using a set of one or more rules (Zhao: Abstract – “According to one embodiment, a local device receives 3D medical image data captured by a medical imaging device. The 3D medical image is anonymized by removing certain metadata associated with the 3D medical image data based on an anonymization template. The local device automatically uploads the anonymized 3D medical image data to a cloud server over a network based on a set of one or more rules, using a network connection established via an internet port of the local device. The cloud server is configured to provide medical image processing services to a plurality of users using a plurality of image processing tools provided by the cloud server.”; ¶ 97 – “Generally, patient identifying data needs to be removed from the image data before they are transferred or during transfer. This is referred to as 'anonymization." This can be done in a number of ways and can also be automated using rules such as based on birth date, upload date, institution, etc.”; ¶ 27 -- “According to some embodiments, a cloud-based medical image processing system includes a data gateway manager to automatically and/or manually transfer medical data to/from data providers such as medical institutes. Such data gateway management may be performed based on a set of rules or policies, which may be configured by an administrator or authorized personnel.”).
Rules also define the access privileges attributed to different users and/or roles (Zhao: ¶ 53 – “Referring back to Figure 2, according to one embodiment, server 109 further includes access control system 210 to control access of resources (e.g., image processing tools) and/or medical data stored in medical data store 206 from clients 202-203. Clients 202-203 may or may not access certain portions of resources and/or medicate data stored in medical data store 206 dependent upon their respective access privileges. The access privileges may be determined or configured based on a set of role-based rules or policies, as shown in Figures 3A-3D. For example, some users with certain roles can only access some of the tools provided by the system as shown in Figure 3A. Examples of some of the tools available are listed at the end of this document, and include vessel centerline extraction, calcium scoring and others. Some users with certain roles are limited to some patient information as shown in Figure 3B. Some users with certain roles can only perform certain steps or stages of the medical image processes as shown in Figure 3C. Steps or stages are incorporated into the tools (listed at the end of this document) and might include identifying and/or measuring instructions, validation of previously performed steps or stages and others. Some users with certain roles are limited to certain types of processes as shown in Figure 3D.”; ¶ 54 – “Note that the rules or policies as shown in Figures 3A-3D are described for the purpose of illustration only; other rules and formats may also be applied. According to some embodiments, access levels can be configured based on a variety of parameters, such as, for example, types of tools or steps within a tool, functions (e.g., uploading, downloading, viewing, manipulating, auditing, validating, etc.), ability to give others access (e.g., second opinion, referrals, experts, family, friend etc.), patients, volume (e.g., may only have access to certain volume of images/month for example, dependent upon a licensing agreement), medical institution, specialty, reimbursement or billing code (e.g., may only have access to perform certain procedures that are reimbursed by insurance), admin access level, clinical trial or research project, and way of viewing data - some may only be able to see individual patients, some aggregate data which can be sliced different ways, etc.”; ¶ 99 – “The anonymization can be done in a number of ways including, but not limited to, blanking or masking out characters in the DICOM header, replacing characters in the DICOM header with non-identifying characters, substitution, encryption, transformation, etc. Depending on the anonymization methods, de-anonymization, or partial de-anonymization, may be possible. For example in a clinical trial, if a patient is experiencing unacceptable side effects, it would be desirable to de-anonymize their clinical trial data to determine whether the patient was taking a placebo or a drug. The access control would be necessary so that only those users with certain privileges would be allowed to de-anonymize the data.”).
In other words, as seen in Zhao, by creating anonymized records that conform to anonymization templates, patient data is filtered by applying a first rule and a second rule to the patient data. Users can define templates to specify which data may be shared and which may not be shared and access rules are specified, thereby suggesting that a first rule identifies a format of the patient data by inspecting the patient data and comparing it to a set of templates of known data formats, and a second rule is selected based on the identified format and applied to extract the QC data and remove certain patient data. This is how the patient record information is filtered to incorporate only certain data from the record in the anonymized template that is used to send information to an external system, like a cloud. Given that specified patient data is excluded from the anonymized template that is used to send information to an external system, this suggests wherein specified patient data remains in the local network without being sent to the external network. Since Zhao manages records with 3D medical image data captured by a medical imaging device, this suggests that test results for patients may be part of records that are anonymized.
The Examiner submits that it would have been obvious to one of ordinary skill in the art before the effective filing date of Applicant’s invention to modify Balwani to perform the step of filtering the test result data by applying a first rule and a second rule to the test result data,
wherein the first rule identifies a format of the test result data by inspecting the test result data and comparing it to a set of templates of known data formats, and the second rule is selected based on the identified format and applied to extract the QC data and remove the patient test result;
wherein the patient test result remains in the local network without being sent to the external network
in order to facilitate sharing of medical data on an as-needed basis to improve customer service, billing models, etc. along with the ability to track FDA and HIPAA compliance (as suggested in ¶ 56 of Zhao: “Referring back to Figure 2, according to one embodiment, server 109 may further include a tracking system (not shown), which may be integrated with server 109 or alternatively maintained by a third party vendor and accessible by server 109. The tracking system is configured to monitor and track user activities with respect to medical data stored in medical data store 206. Because of certain FDA requirements, there is a need to track what users have accessed the software, when, and the steps they have used within the software. There is also a need to track overall trends in software use, for example how long it takes a user to complete a certain type of case, or certain steps, billing trends etc. According to some embodiments, the tracking system is configured to track users who log in and utilize the software, steps the users perform, date and time of the accesses, etc. The tracking system can be used to analyze volumes used on, and performance of, the system. The tracking system can be used to track FD A/HIP AA compliance. It can also be utilized by insurance companies to track billing codes and costs. It can be used to determine trends (time to analyze certain types of cases etc.) Analysis of tracked data can also be used to identify different user types, for example expert users, casual users, technicians, physicians, etc. This information can then be used to improve the software product, upsell, improve customer service, improve billing models, etc. The tracking system can be used to track aggregate data as well as detailed data.”). Benefits specific to the use of Zhao’s anonymization, particularly in a cloud-based environment and to facilitate quality control and data mining, are also discussed in ¶¶ 34 and 59-61 of Zhao.
Zhao also describes templates in the sense of data formats and Zhao allows for functions to be applied to certain data based on their respective data sources (Zhao: ¶ 67 – “The data mining system provides a dynamic snapshot of vital measurements and relevant findings across all studies in the medical data store 206 for a particular patient. The data mining system supports access to multiple data sources, cross-modality comparison, cross-data source comparisons and the like. In some embodiments, the data mining system allows data elements to be registered or subscribed so that a user, administrator and/or system setting may specify how to retrieve certain data through a variety of communications protocols (e.g., SQL, extensible markup language (XML), etc.), what functions can be applied to certain data, in which modality(ies) and/or data source(s) can a certain data element be found, whether data is enumerated and/or numeric data, etc.”). In this regard (where the templates may additionally or alternatively be viewed as data formats), Zhao further suggests that it would have been further obvious to one of ordinary skill in the art before the effective filing date of Applicant’s invention to modify Balwani wherein the first rule identifies a format of the test result data by inspecting the test result data and comparing it to a set of templates of known data formats, and the second rule is selected based on the identified format and applied to extract the QC data and remove the patient test result in order to facilitate data aggregation, data filtering, and/or data mining across various data sources, thereby allowing more convenient access to more numerous data sources.
[Claim 2] Balwani discloses wherein a corrective action is triggered responsive to the response (¶ 158 – “In some embodiments the device may be capable of performing on-board calibration and/or controls. The device may be capable of performing one or more diagnostic step (e.g., preparation step and/or assay step). If the results fall outside an expected range, a portion of the device may be cleaned and/or replaced. The results may also be useful for calibrating the device. On-board calibration and/or controls may occur without requiring human intervention. Calibration and controls may occur within a device housing.”; ¶ 159 – “A device may also be capable of performing on-board maintenance. If during a calibration, operation of device, diagnostic testing, or any other point in time a condition requiring repair and/or maintenance of the device is detected, the device may institute one or more automated procedures to perform said maintenance and/or repair. Any description of maintenance may include repair, cleaning, and/or adjustments. For example, a device may detect that a component is loose and may automatically tighten the component. The device may also detect that a wash or diluents level is running low in a module and provide an alert to add more wash or diluents, or bring over wash or diluents from another module.”).
[Claim 3] Balwani discloses wherein the corrective action is automatically triggering preventative maintenance (¶ 158 – “In some embodiments the device may be capable of performing on-board calibration and/or controls. The device may be capable of performing one or more diagnostic step (e.g., preparation step and/or assay step). If the results fall outside an expected range, a portion of the device may be cleaned and/or replaced. The results may also be useful for calibrating the device. On-board calibration and/or controls may occur without requiring human intervention. Calibration and controls may occur within a device housing.”; ¶ 159 – “A device may also be capable of performing on-board maintenance. If during a calibration, operation of device, diagnostic testing, or any other point in time a condition requiring repair and/or maintenance of the device is detected, the device may institute one or more automated procedures to perform said maintenance and/or repair. Any description of maintenance may include repair, cleaning, and/or adjustments. For example, a device may detect that a component is loose and may automatically tighten the component. The device may also detect that a wash or diluents level is running low in a module and provide an alert to add more wash or diluents, or bring over wash or diluents from another module.”).
[Claim 5] As discussed in the rejection of the independent claim above, Balwani addresses the use of a cloud-based QC data management platform (Balwani: ¶¶ 47, 161, 171). Balwani also receives additional test result data for the instrument (Balwani: ¶¶ 68, 104, 162, 167-168). Balwani does not explicitly disclose:
receiving an updated rule set from the cloud-based QC data management platform;
receiving additional test result data for the instrument; and
extracting additional QC data from the additional test result data using the updated rule set.
Zhao’s anonymization is performed using a set of one or more rules (Zhao: Abstract – “According to one embodiment, a local device receives 3D medical image data captured by a medical imaging device. The 3D medical image is anonymized by removing certain metadata associated with the 3D medical image data based on an anonymization template. The local device automatically uploads the anonymized 3D medical image data to a cloud server over a network based on a set of one or more rules, using a network connection established via an internet port of the local device. The cloud server is configured to provide medical image processing services to a plurality of users using a plurality of image processing tools provided by the cloud server.”; ¶ 97 – “Generally, patient identifying data needs to be removed from the image data before they are transferred or during transfer. This is referred to as 'anonymization." This can be done in a number of ways and can also be automated using rules such as based on birth date, upload date, institution, etc.”; ¶ 27 -- “According to some embodiments, a cloud-based medical image processing system includes a data gateway manager to automatically and/or manually transfer medical data to/from data providers such as medical institutes. Such data gateway management may be performed based on a set of rules or policies, which may be configured by an administrator or authorized personnel.”).
Rules also define the access privileges attributed to different users and/or roles (Zhao: ¶ 53 – “Referring back to Figure 2, according to one embodiment, server 109 further includes access control system 210 to control access of resources (e.g., image processing tools) and/or medical data stored in medical data store 206 from clients 202-203. Clients 202-203 may or may not access certain portions of resources and/or medicate data stored in medical data store 206 dependent upon their respective access privileges. The access privileges may be determined or configured based on a set of role-based rules or policies, as shown in Figures 3A-3D. For example, some users with certain roles can only access some of the tools provided by the system as shown in Figure 3A. Examples of some of the tools available are listed at the end of this document, and include vessel centerline extraction, calcium scoring and others. Some users with certain roles are limited to some patient information as shown in Figure 3B. Some users with certain roles can only perform certain steps or stages of the medical image processes as shown in Figure 3C. Steps or stages are incorporated into the tools (listed at the end of this document) and might include identifying and/or measuring instructions, validation of previously performed steps or stages and others. Some users with certain roles are limited to certain types of processes as shown in Figure 3D.”; ¶ 54 – “Note that the rules or policies as shown in Figures 3A-3D are described for the purpose of illustration only; other rules and formats may also be applied. According to some embodiments, access levels can be configured based on a variety of parameters, such as, for example, types of tools or steps within a tool, functions (e.g., uploading, downloading, viewing, manipulating, auditing, validating, etc.), ability to give others access (e.g., second opinion, referrals, experts, family, friend etc.), patients, volume (e.g., may only have access to certain volume of images/month for example, dependent upon a licensing agreement), medical institution, specialty, reimbursement or billing code (e.g., may only have access to perform certain procedures that are reimbursed by insurance), admin access level, clinical trial or research project, and way of viewing data - some may only be able to see individual patients, some aggregate data which can be sliced different ways, etc.”; ¶ 99 – “The anonymization can be done in a number of ways including, but not limited to, blanking or masking out characters in the DICOM header, replacing characters in the DICOM header with non-identifying characters, substitution, encryption, transformation, etc. Depending on the anonymization methods, de-anonymization, or partial de-anonymization, may be possible. For example in a clinical trial, if a patient is experiencing unacceptable side effects, it would be desirable to de-anonymize their clinical trial data to determine whether the patient was taking a placebo or a drug. The access control would be necessary so that only those users with certain privileges would be allowed to de-anonymize the data.”).
In other words, as seen in Zhao, by creating anonymized records that conform to anonymization templates, patient data is filtered by applying a first rule and a second rule to the patient data. Users can define templates to specify which data may be shared and which may not be shared and access rules are specified, thereby suggesting that a first rule identifies a format of the patient data by inspecting the patient data and comparing it to a set of templates of known data formats, and a second rule is selected based on the identified format and applied to extract the QC data and remove certain patient data. This is how the patient record information is filtered to incorporate only certain data from the record in the anonymized template that is used to send information to an external system, like a cloud. Given that specified patient data is excluded from the anonymized template that is used to send information to an external system, this suggests wherein specified patient data remains in the local network without being sent to the external network. Since Zhao manages records with 3D medical image data captured by a medical imaging device, this suggests that test results for patients may be part of records that are anonymized.
Also explained in Zhao, an administrator or authorized personnel can choose from various rules to configure the anonymization template (as mentioned above), thereby suggesting that rule sets may be updated (e.g., for different uses, templates, roles, etc.). Given that specified patient data in Zhao is excluded from the anonymized template that is used to send information to an external system, this suggests wherein specified patient data remains in the local network without being sent to the external network. Since Zhao manages records with 3D medical image data captured by a medical imaging device, this suggests that test results for patients may be part of records that are anonymized.
The Examiner submits that it would have been obvious to one of ordinary skill in the art before the effective filing date of Applicant’s invention to modify Balwani to perform the steps of:
receiving an updated rule set from the cloud-based QC data management platform;
receiving additional test result data for the instrument; and
extracting additional QC data from the additional test result data using the updated rule set
in order to facilitate sharing of medical data on an as-needed basis to improve customer service, billing models, etc. along with the ability to track FDA and HIPAA compliance (as suggested in ¶ 56 of Zhao: “Referring back to Figure 2, according to one embodiment, server 109 may further include a tracking system (not shown), which may be integrated with server 109 or alternatively maintained by a third party vendor and accessible by server 109. The tracking system is configured to monitor and track user activities with respect to medical data stored in medical data store 206. Because of certain FDA requirements, there is a need to track what users have accessed the software, when, and the steps they have used within the software. There is also a need to track overall trends in software use, for example how long it takes a user to complete a certain type of case, or certain steps, billing trends etc. According to some embodiments, the tracking system is configured to track users who log in and utilize the software, steps the users perform, date and time of the accesses, etc. The tracking system can be used to analyze volumes used on, and performance of, the system. The tracking system can be used to track FD A/HIP AA compliance. It can also be utilized by insurance companies to track billing codes and costs. It can be used to determine trends (time to analyze certain types of cases etc.) Analysis of tracked data can also be used to identify different user types, for example expert users, casual users, technicians, physicians, etc. This information can then be used to improve the software product, upsell, improve customer service, improve billing models, etc. The tracking system can be used to track aggregate data as well as detailed data.”). Benefits specific to the use of Zhao’s anonymization, particularly in a cloud-based environment and to facilitate quality control and data mining, are also discussed in ¶¶ 34 and 59-61 of Zhao.
[Claim 6] Balwani discloses wherein the instrument is a clinical diagnostic instrument (¶ 158 – “In some embodiments the device may be capable of performing on-board calibration and/or controls. The device may be capable of performing one or more diagnostic step (e.g., preparation step and/or assay step).”; ¶ 38 – “As used herein, the term “point of service location” may include locations where a subject may receive a service (e.g. testing, monitoring, treatment, diagnosis, guidance, sample collection, ID verification, medical services, non-medical services, etc.)…”).
[Claim 7] Balwani discloses identifying a triggering event indicating that connection to the cloud-based QC data management platform is unavailable (¶ 173 – “Optionally, the device may include one or more location sensing device. For example, the device may have a GPS tracker within the device. When any tampering with the device is detected, the location of the device may be transmitted from the device. The location may be transmitted to an external device or the cloud. In some instances, the location of the device may be continuously broadcast once the tampering is detected, or may be transmitted at one or more intervals or other detected events. An owner or entity associated with the device may be able to track the location of the device. In some instances, a plurality of location sensors may be provided so that even the device is taken apart and/or one or more location sensor is found and destroyed, it may be possible to track other parts of the device. In the event that the device is unable to transmit the device location at a particular moment, the device may be able to store the device location and transmit it once it is able.” Data related to tampering, such as location data, is an example of QC data.);
responsive to the triggering event, storing the QC data on the local network (¶ 173 – “Optionally, the device may include one or more location sensing device. For example, the device may have a GPS tracker within the device. When any tampering with the device is detected, the location of the device may be transmitted from the device. The location may be transmitted to an external device or the cloud. In some instances, the location of the device may be continuously broadcast once the tampering is detected, or may be transmitted at one or more intervals or other detected events. An owner or entity associated with the device may be able to track the location of the device. In some instances, a plurality of location sensors may be provided so that even the device is taken apart and/or one or more location sensor is found and destroyed, it may be possible to track other parts of the device. In the event that the device is unable to transmit the device location at a particular moment, the device may be able to store the device location and transmit it once it is able.” Data related to tampering, such as location data, is an example of QC data.); and
responsive to receiving an indication that the connection to the cloud-based QC data management platform is available again, forwarding the stored QC data to the cloud-based QC data management platform (¶ 173 – “Optionally, the device may include one or more location sensing device. For example, the device may have a GPS tracker within the device. When any tampering with the device is detected, the location of the device may be transmitted from the device. The location may be transmitted to an external device or the cloud. In some instances, the location of the device may be continuously broadcast once the tampering is detected, or may be transmitted at one or more intervals or other detected events. An owner or entity associated with the device may be able to track the location of the device. In some instances, a plurality of location sensors may be provided so that even the device is taken apart and/or one or more location sensor is found and destroyed, it may be possible to track other parts of the device. In the event that the device is unable to transmit the device location at a particular moment, the device may be able to store the device location and transmit it once it is able.” Data related to tampering, such as location data, is an example of QC data.).
Balwani does not explicitly disclose that storing the QC data on the local network (responsive to the triggering event) is performed for up to a maximum amount of time; however, Balwani explains that “LIS can also react when an event is noted in the device 100 and then poll the device when LIS 30 needs the data. Data can also be deleted from device 100 after it is pulled into LIS 30.” (Balwani: ¶ 56) In other words, Balwani suggests deleting data from a device once it is no longer needed at the device. Balwani further explains a scenario in which deleting patient information from a device promotes security and protection of the patient’s private health data (Balwani: ¶ 176 – “In one embodiment, the device and the external controller maintain a security mechanism by which no unauthorized person with physical access to the device may be able to retrieve test information and link it back to an individual, thus protecting the privacy of patient health data. An example of this would be where the device captures user identification information, send it to the external device or cloud, receives a secret key from the cloud and erases all patient information from the device. In such a scenario, if the devices send any further data about that patient to the external device, it will be referred to link through the secret key already obtained from the external device.”). Given that, when a device cannot transmit QC-related information (like location data), the device stores the information until connection is reestablished, this suggests that Balwani is prepared to transfer data whenever possible and to delete information from devices to maintain security and protection of the patient’s private health data, thereby also suggesting that deleting data after a maximum time of a connection being lost would have also helped to maintain security and protection of the patient’s private health data while also preserving valuable storage resources of the devices. The Examiner submits that it would have been obvious to one of ordinary skill in the art before the effective filing date of Applicant’s invention to modify Balwani such that storing the QC data on the local network (responsive to the triggering event) is performed for up to a maximum amount of time in order to help maintain security and protection of the patient’s private health data (as suggested in ¶ 176 of Balwani) while also preserving valuable storage resources of the devices.
[Claim 8] Balwani does not explicitly disclose, responsive to forwarding the QC data, deleting the QC data from the local network; however, Balwani explains that “LIS can also react when an event is noted in the device 100 and then poll the device when LIS 30 needs the data. Data can also be deleted from device 100 after it is pulled into LIS 30.” (Balwani: ¶ 56) In other words, Balwani suggests deleting data from a device once it is no longer needed at the device. Balwani further explains a scenario in which deleting patient information from a device promotes security and protection of the patient’s private health data (Balwani: ¶ 176 – “In one embodiment, the device and the external controller maintain a security mechanism by which no unauthorized person with physical access to the device may be able to retrieve test information and link it back to an individual, thus protecting the privacy of patient health data. An example of this would be where the device captures user identification information, send it to the external device or cloud, receives a secret key from the cloud and erases all patient information from the device. In such a scenario, if the devices send any further data about that patient to the external device, it will be referred to link through the secret key already obtained from the external device.”). Given that, when a device cannot transmit QC-related information (like location data), the device stores the information until connection is reestablished, this suggests that Balwani is prepared to transfer data whenever possible and to delete information from devices to maintain security and protection of the patient’s private health data, thereby also suggesting that deleting data after a maximum time of a connection being lost would have also helped to maintain security and protection of the patient’s private health data while also preserving valuable storage resources of the devices. The Examiner submits that it would have been obvious to one of ordinary skill in the art before the effective filing date of Applicant’s invention to modify Balwani to, responsive to forwarding the QC data, delete the QC data from the local network in order to help maintain security and protection of the patient’s private health data (as suggested in ¶ 176 of Balwani) while also preserving valuable storage resources of the devices.
[Claim 9] Balwani discloses wherein the triggering event is user-input indicating planned downtime for the QC data management platform (¶ 63 – “Additionally, the laboratory director can push quality control (QC) out to the analytical or sample processing device to tell it to run calibrator(s) or to shut it down until someone runs a calibrator (taking the device off-line) until a control cartridge and/or control protocol is run.”; ¶ 158 – “In some embodiments the device may be capable of performing on-board calibration and/or controls. The device may be capable of performing one or more diagnostic step (e.g., preparation step and/or assay step). If the results fall outside an expected range, a portion of the device may be cleaned and/or replaced. The results may also be useful for calibrating the device. On-board calibration and/or controls may occur without requiring human intervention. Calibration and controls may occur within a device housing.”; ¶ 159 – “A device may also be capable of performing on-board maintenance. If during a calibration, operation of device, diagnostic testing, or any other point in time a condition requiring repair and/or maintenance of the device is detected, the device may institute one or more automated procedures to perform said maintenance and/or repair. Any description of maintenance may include repair, cleaning, and/or adjustments. For example, a device may detect that a component is loose and may automatically tighten the component. The device may also detect that a wash or diluents level is running low in a module and provide an alert to add more wash or diluents, or bring over wash or diluents from another module.”; ¶ 47 – “Referring now to FIG. 3, at least one exemplary embodiment of a system for use with at least one method herein will now be described. FIG. 3 shows that in this embodiment, information can be sent from the device 100 through a network 70 to the cloud 110. By way of non-limiting example, the cloud 110 comprises one or more servers 120 in one or more data networks. Server 120 may be a cluster of servers. In one non-limiting example, a database on one or more of the servers 120 may be a cluster database. By way of non-limiting example, the cloud 110 comprises one or more computing devices in communication with one or more data networks. As seen in FIG. 3, data is then sent from the cloud 110 through a network 72 to the physical laboratory 10 with co-located or locally connected LIS 30 therein.).
[Claim 10] Balwani discloses a networked computing system for providing management of QC data, the networked computing system (¶ 47 – “Referring now to FIG. 3, at least one exemplary embodiment of a system for use with at least one method herein will now be described. FIG. 3 shows that in this embodiment, information can be sent from the device 100 through a network 70 to the cloud 110. By way of non-limiting example, the cloud 110 comprises one or more servers 120 in one or more data networks. Server 120 may be a cluster of servers. In one non-limiting example, a database on one or more of the servers 120 may be a cluster database. By way of non-limiting example, the cloud 110 comprises one or more computing devices in communication with one or more data networks. As seen in FIG. 3, data is then sent from the cloud 110 through a network 72 to the physical laboratory 10 with co-located or locally connected LIS 30 therein.”; ¶ 161 – “Calibration and/or maintenance may occur on a periodic basis. In some embodiments, device calibration and/or maintenance may automatically occur at regular or irregular intervals. Device calibration and/or maintenance may occur when one or more condition is detected from the device. For example, if a component appears to be faulty, the device may run a diagnostic on associated components. Device calibration and/or maintenance may occur at the instruction of an operator of the device. Device calibration and/or maintenance may also occur upon automated instruction from an external device. The calibration and quality control (QC) cartridge is briefly described in the next paragraph. The goal of the calibration cartridge is to enable the quantitative assessment and adjustment of each module/detector of the device. For example, by performing a variety of assay steps, functionality is tested/evaluated for the pipette, gantry, centrifuge, cameras, spectrometer, nucleic acid amplification module, thermal control unit, and cytometer. Each measurement made during calibration cartridge runs with reagent controls may be compared to device requirements for precision. By way of non-limiting example, there is a pass fail outcome for these results. If re-calibration is required, the data generated is used to recalibrate the device (such as the device sensors and pipettes). Recalibration ensures that each device is accurate. Some QC can also be performed automatically in the device without introducing a cartridge. For example, the light sources in the device can be used to periodically QC the optical sensors in the device. An external device or control may maintain a device calibration schedule and/or device maintenance schedule for a plurality of devices. Device calibration and/or maintenance may occur on a time-based schedule or a use-based schedule. For example, devices that are used more frequently than others may be calibrated and/or maintained more frequently and/or vice versa. QC data may be indexed with data stored, for example, on the sample processing device or an external device.”; ¶ 171 – “In some embodiments, an alert may be provided if someone is trying to open a device, or if someone comes within the device's proximity. In some instances, an alert may be provided if the device housing is breached. Similarly, an alert may be provided if the device falls, tips over, or if an error is detected. The device may encompass a stabilization system with, optionally, shock absorbance and dampening capabilities to prevent it from tipping when for example moving in vehicles at high speeds. In some instances, if the device detects that the device is being opened, approached, or tampered with, a camera on the device may capture an image of the device surroundings. The device may capture an image of the individual trying to open the device. The data associated with the device may be sent to the cloud or an external device. The device associated with the tampering of the device, such as an image of an individual tampering with the device may be transmitted from the device. The data associated with the device, which may include one or more image, may be stored in the device. In the event that the device is not able to immediately transmit the data, the data may be transmitted once the device is able and/or connected to a network.”) comprising:
one or more instruments that generate test result data, the test result data including a patient test result and QC data (¶ 68 – “In some embodiments, the system can be configured such as the system with the LIS 30 will be there to receive results from a reference laboratory. A reference laboratory may be one that performs sample testing but is not the laboratory that reports out the results to the patient and/or physician. In this non-limiting example, the system may have one or more sample processing devices 100 that report data to a reference laboratory that finalizes the results and sends the data to the receiving laboratory, or sends the receiving laboratory the raw sample data through a pathways such as through a gateway including but not limited to a broker application and/or listener application 50. Service provided by a reference laboratory allows for greater capacity for the receiving laboratory to process samples and send out test results while still maintaining a seamless interaction between the laboratory and the patient or physician. Even if one laboratory such as a reference laboratory has looked at the test results, the receiving laboratory still reviews and signs off on the test results. The results may then be relayed as results certified by the receiving laboratory. By way of example and not limitation, three scenarios include, but are not limited to: analyzer device to LIS, reference lab to another lab, or lab providing service directly to doctor.”; ¶ 104 – “In one embodiment, it may be desirable that the perception to the LIS is that to the that all the devices are “local” in the sense that they provide data to the LIS as if they were part of the local system physically coupled by wired connections to the LIS but are instead coupled to the LIS through a data network comprising components such as but not limited to a LAN, WAN, or external computer processor(s) that may define a “cloud” network.”; ¶¶ 162, 167-168 – QC data may be transmitted (including received) locally and/or to (received by) an external device.);
a Laboratory Information System (LIS) coupled to the one or more instruments via a local network (¶ 68 – “In some embodiments, the system can be configured such as the system with the LIS 30 will be there to receive results from a reference laboratory. A reference laboratory may be one that performs sample testing but is not the laboratory that reports out the results to the patient and/or physician. In this non-limiting example, the system may have one or more sample processing devices 100 that report data to a reference laboratory that finalizes the results and sends the data to the receiving laboratory, or sends the receiving laboratory the raw sample data through a pathways such as through a gateway including but not limited to a broker application and/or listener application 50. Service provided by a reference laboratory allows for greater capacity for the receiving laboratory to process samples and send out test results while still maintaining a seamless interaction between the laboratory and the patient or physician. Even if one laboratory such as a reference laboratory has looked at the test results, the receiving laboratory still reviews and signs off on the test results. The results may then be relayed as results certified by the receiving laboratory. By way of example and not limitation, three scenarios include, but are not limited to: analyzer device to LIS, reference lab to another lab, or lab providing service directly to doctor.”; ¶ 104 – “In one embodiment, it may be desirable that the perception to the LIS is that to the that all the devices are “local” in the sense that they provide data to the LIS as if they were part of the local system physically coupled by wired connections to the LIS but are instead coupled to the LIS through a data network comprising components such as but not limited to a LAN, WAN, or external computer processor(s) that may define a “cloud” network.”; ¶¶ 162, 167-168 – QC data may be transmitted (including received) locally and/or to (received by) an external device.);
a QC data flow system coupled to the LIS via the local network, the QC data flow system including one or more computing devices configured to receive the test result data (¶¶ 162, 167-168 – QC data may be transmitted (including received) locally and/or to (received by) an external device.; ¶ 47 – “Referring now to FIG. 3, at least one exemplary embodiment of a system for use with at least one method herein will now be described. FIG. 3 shows that in this embodiment, information can be sent from the device 100 through a network 70 to the cloud 110. By way of non-limiting example, the cloud 110 comprises one or more servers 120 in one or more data networks. Server 120 may be a cluster of servers. In one non-limiting example, a database on one or more of the servers 120 may be a cluster database. By way of non-limiting example, the cloud 110 comprises one or more computing devices in communication with one or more data networks. As seen in FIG. 3, data is then sent from the cloud 110 through a network 72 to the physical laboratory 10 with co-located or locally connected LIS 30 therein.”; ¶ 68 – “In some embodiments, the system can be configured such as the system with the LIS 30 will be there to receive results from a reference laboratory. A reference laboratory may be one that performs sample testing but is not the laboratory that reports out the results to the patient and/or physician. In this non-limiting example, the system may have one or more sample processing devices 100 that report data to a reference laboratory that finalizes the results and sends the data to the receiving laboratory, or sends the receiving laboratory the raw sample data through a pathways such as through a gateway including but not limited to a broker application and/or listener application 50. Service provided by a reference laboratory allows for greater capacity for the receiving laboratory to process samples and send out test results while still maintaining a seamless interaction between the laboratory and the patient or physician. Even if one laboratory such as a reference laboratory has looked at the test results, the receiving laboratory still reviews and signs off on the test results. The results may then be relayed as results certified by the receiving laboratory. By way of example and not limitation, three scenarios include, but are not limited to: analyzer device to LIS, reference lab to another lab, or lab providing service directly to doctor.”; ¶ 104 – “In one embodiment, it may be desirable that the perception to the LIS is that to the that all the devices are “local” in the sense that they provide data to the LIS as if they were part of the local system physically coupled by wired connections to the LIS but are instead coupled to the LIS through a data network comprising components such as but not limited to a LAN, WAN, or external computer processor(s) that may define a “cloud” network.”; ¶¶ 162, 167-168 – QC data may be transmitted (including received) locally and/or to (received by) an external device.); and
a cloud-based QC data management platform coupled to the QC data flow system via an external network, the cloud-based QC data management platform including one or more computing devices configured to process the QC data to generate a result and send the result, via the external network, to the QC data flow system (¶¶ 162, 167-168 – QC data may be transmitted (including received) locally and/or to (received by) an external device.; ¶ 47 – “Referring now to FIG. 3, at least one exemplary embodiment of a system for use with at least one method herein will now be described. FIG. 3 shows that in this embodiment, information can be sent from the device 100 through a network 70 to the cloud 110. By way of non-limiting example, the cloud 110 comprises one or more servers 120 in one or more data networks. Server 120 may be a cluster of servers. In one non-limiting example, a database on one or more of the servers 120 may be a cluster database. By way of non-limiting example, the cloud 110 comprises one or more computing devices in communication with one or more data networks. As seen in FIG. 3, data is then sent from the cloud 110 through a network 72 to the physical laboratory 10 with co-located or locally connected LIS 30 therein.”; ¶ 40 – “Referring now to FIG. 1A, when a plurality of biological sample analyzers 12 are in a laboratory 10, there is typically at least one connectivity hub 20 such as but not limited to a data connectivity hub such as a USB hub, wifi hub, or other data protocol hub that physically connects the sample analyzers 12 to the LIS 30. In some cases, there is a terminal 22 (instead of a USB hub) that connects to the multiple sample analyzers 12. Optionally, there may be multiple terminals 22, multiple hubs 20, and/or multiple sets of analyzers 12. There can be multiple computers, terminals, or servers that are brokers that run middleware to send the information to LIS 30. These computers, terminals, or servers are also running the LIS software, which allows the data to be sent to a database in the LIS 30.”; ¶¶ 82-84 – Status indicators for the sample processing units (SPUs) may be displayed. Additional information related to quality control (QC), like temperature of a cartridge, may be displayed (as specifically discussed in ¶¶ 61, 84, 168). The disclosed invention may be cloud-based (¶¶ 61, 59, 67). As explained in ¶ 61, “the performance of the device are fed to the laboratory managed director or authorized personnel who can look at the device information including performance information remotely and once they are satisfied they can green-light sending the data/result to LIS 30. Optionally, the data is sent directly to LIS 30, but laboratory managed director or authorized personnel can go see the individual machine performance if the data to LIS 30 triggers certain flag. In this non-limiting example, the laboratory managed director or authorized personnel can touch-click expand, see the quality of the data, performance, and/or replicates to verify if they trust the data.” The displayed information may be acted upon. “For at least some embodiments herein, the advantage here is that analytical and/or sample processing device can be anywhere in the world but laboratory director can trust it based on knowledge about the device and its recent performance history. Optionally, some embodiments may configure the remote device to have limited local user control of the device. Additionally, the laboratory director can push quality control (QC) out to the analytical or sample processing device to tell it to run calibrator(s) or to shut it down until someone runs a calibrator (taking the device off-line) until a control cartridge and/or control protocol is run.” (Balwani: ¶ 63); ¶ 67 – “In one embodiment herein, the device 100 has a connection to LIS 30 that is wireless. Optionally, some may view this as a brokerless LIS system. In the embodiment, the cloud 110 is the broker. Optionally, there is a pairing mechanism that associates certain machines or servers in the cloud with certain listener applications 50. Optionally, an administrator can set which machines or servers are in the environment. The system can also search the network to see which machines or servers are in the environment. If the device is not on the same LAN, it is still accessible on WAN. This listener application 50 is only listening for its designated set of machines.” In other words, the devices of the system may be accessed and/or controlled, including via a LAN or WAN, with assistance of the cloud.),
wherein the QC data flow system forwards the result to the LIS, and the LIS implements a corrective action for the instrument based on the result (¶ 158 – “In some embodiments the device may be capable of performing on-board calibration and/or controls. The device may be capable of performing one or more diagnostic step (e.g., preparation step and/or assay step). If the results fall outside an expected range, a portion of the device may be cleaned and/or replaced. The results may also be useful for calibrating the device. On-board calibration and/or controls may occur without requiring human intervention. Calibration and controls may occur within a device housing.”; ¶ 159 – “A device may also be capable of performing on-board maintenance. If during a calibration, operation of device, diagnostic testing, or any other point in time a condition requiring repair and/or maintenance of the device is detected, the device may institute one or more automated procedures to perform said maintenance and/or repair. Any description of maintenance may include repair, cleaning, and/or adjustments. For example, a device may detect that a component is loose and may automatically tighten the component. The device may also detect that a wash or diluents level is running low in a module and provide an alert to add more wash or diluents, or bring over wash or diluents from another module.”; ¶ 104 – “In one embodiment, it may be desirable that the perception to the LIS is that to the that all the devices are “local” in the sense that they provide data to the LIS as if they were part of the local system physically coupled by wired connections to the LIS but are instead coupled to the LIS through a data network comprising components such as but not limited to a LAN, WAN, or external computer processor(s) that may define a “cloud” network.”; ¶¶ 162, 167-168 – QC data may be transmitted (including received) locally and/or to (received by) an external device.; ¶ 47 – “Referring now to FIG. 3, at least one exemplary embodiment of a system for use with at least one method herein will now be described. FIG. 3 shows that in this embodiment, information can be sent from the device 100 through a network 70 to the cloud 110. By way of non-limiting example, the cloud 110 comprises one or more servers 120 in one or more data networks. Server 120 may be a cluster of servers. In one non-limiting example, a database on one or more of the servers 120 may be a cluster database. By way of non-limiting example, the cloud 110 comprises one or more computing devices in communication with one or more data networks. As seen in FIG. 3, data is then sent from the cloud 110 through a network 72 to the physical laboratory 10 with co-located or locally connected LIS 30 therein.”).
Balwani receives test result data including patient data and QC data (as discussed above); however, Balwani does not explicitly:
filter the test result data to extract the QC data and remove the patient test result from the test result data using a set of rules, wherein a first rule identifies a format of the test result data by inspecting the test result data and comparing it to a set of templates of known data formats, and the second rule is selected based on the identified format and applied to extract the QC data and remove the patient test result;
wherein the patient test result remains in the local network without being sent to the external network.
Zhao allows for specified metadata to be stripped from 3D medical image data using an anonymization template so that an anonymized version of the 3D medical image data can be sent to another system, such as a cloud service (Zhao: ¶ 31 – “Database 110 may be a data store to store medical data such as digital imaging and communications in medicine (DICOM) compatible data or other image data.”; ¶ 104 – “Figure 11 is a screenshot illustrating examples of GUIs for configuring anonymous data gateway management according to certain embodiments of the invention. GUI 1100 can be presented by activating link 1008 of Figure 10A. Referring to Figure 11, GUI 1100 allows a user to specify items to be anonymized, where each item is specified in one of the entries listed in GUI 1100. Each item is referenced by its DICOM tag 1101, name 1102, original value 1103 to be replaced, and replacement value 1104 to replace the corresponding original value.“; ¶ 105 – “Figure 13 is a flow diagram illustrating a method for anonymizing medical data according to another embodiment of the invention. Method 1300 may be performed by any of data gateway managers 901-902, 921 of Figure 9. Referring to Figure 13, at block 1301, a local device (e.g., gateway manager/router/computer) receives a 3D medical image data captured by a medical imaging device. At block 1302, the 3D medical image data is anonymized including removing certain metadata associated with the 3D medical image data based on an anonymization template. At block 1303, the anonymized 3D medical image data is then automatically uploaded to a cloud server, using a network connection established via an internet port of the local device.“).
Zhao’s anonymization is performed using a set of one or more rules (Zhao: Abstract – “According to one embodiment, a local device receives 3D medical image data captured by a medical imaging device. The 3D medical image is anonymized by removing certain metadata associated with the 3D medical image data based on an anonymization template. The local device automatically uploads the anonymized 3D medical image data to a cloud server over a network based on a set of one or more rules, using a network connection established via an internet port of the local device. The cloud server is configured to provide medical image processing services to a plurality of users using a plurality of image processing tools provided by the cloud server.”; ¶ 97 – “Generally, patient identifying data needs to be removed from the image data before they are transferred or during transfer. This is referred to as 'anonymization." This can be done in a number of ways and can also be automated using rules such as based on birth date, upload date, institution, etc.”; ¶ 27 -- “According to some embodiments, a cloud-based medical image processing system includes a data gateway manager to automatically and/or manually transfer medical data to/from data providers such as medical institutes. Such data gateway management may be performed based on a set of rules or policies, which may be configured by an administrator or authorized personnel.”).
Rules also define the access privileges attributed to different users and/or roles (Zhao: ¶ 53 – “Referring back to Figure 2, according to one embodiment, server 109 further includes access control system 210 to control access of resources (e.g., image processing tools) and/or medical data stored in medical data store 206 from clients 202-203. Clients 202-203 may or may not access certain portions of resources and/or medicate data stored in medical data store 206 dependent upon their respective access privileges. The access privileges may be determined or configured based on a set of role-based rules or policies, as shown in Figures 3A-3D. For example, some users with certain roles can only access some of the tools provided by the system as shown in Figure 3A. Examples of some of the tools available are listed at the end of this document, and include vessel centerline extraction, calcium scoring and others. Some users with certain roles are limited to some patient information as shown in Figure 3B. Some users with certain roles can only perform certain steps or stages of the medical image processes as shown in Figure 3C. Steps or stages are incorporated into the tools (listed at the end of this document) and might include identifying and/or measuring instructions, validation of previously performed steps or stages and others. Some users with certain roles are limited to certain types of processes as shown in Figure 3D.”; ¶ 54 – “Note that the rules or policies as shown in Figures 3A-3D are described for the purpose of illustration only; other rules and formats may also be applied. According to some embodiments, access levels can be configured based on a variety of parameters, such as, for example, types of tools or steps within a tool, functions (e.g., uploading, downloading, viewing, manipulating, auditing, validating, etc.), ability to give others access (e.g., second opinion, referrals, experts, family, friend etc.), patients, volume (e.g., may only have access to certain volume of images/month for example, dependent upon a licensing agreement), medical institution, specialty, reimbursement or billing code (e.g., may only have access to perform certain procedures that are reimbursed by insurance), admin access level, clinical trial or research project, and way of viewing data - some may only be able to see individual patients, some aggregate data which can be sliced different ways, etc.”; ¶ 99 – “The anonymization can be done in a number of ways including, but not limited to, blanking or masking out characters in the DICOM header, replacing characters in the DICOM header with non-identifying characters, substitution, encryption, transformation, etc. Depending on the anonymization methods, de-anonymization, or partial de-anonymization, may be possible. For example in a clinical trial, if a patient is experiencing unacceptable side effects, it would be desirable to de-anonymize their clinical trial data to determine whether the patient was taking a placebo or a drug. The access control would be necessary so that only those users with certain privileges would be allowed to de-anonymize the data.”).
In other words, as seen in Zhao, by creating anonymized records that conform to anonymization templates, patient data is filtered by applying a first rule and a second rule to the patient data. Users can define templates to specify which data may be shared and which may not be shared and access rules are specified, thereby suggesting that a first rule identifies a format of the patient data by inspecting the patient data and comparing it to a set of templates of known data formats, and a second rule is selected based on the identified format and applied to extract the QC data and remove certain patient data. This is how the patient record information is filtered to incorporate only certain data from the record in the anonymized template that is used to send information to an external system, like a cloud. Given that specified patient data is excluded from the anonymized template that is used to send information to an external system, this suggests wherein specified patient data remains in the local network without being sent to the external network. Since Zhao manages records with 3D medical image data captured by a medical imaging device, this suggests that test results for patients may be part of records that are anonymized.
The Examiner submits that it would have been obvious to one of ordinary skill in the art before the effective filing date of Applicant’s invention to modify Balwani to filter the test result data to extract the QC data and remove the patient test result from the test result data using a set of rules, wherein a first rule identifies a format of the test result data by inspecting the test result data and comparing it to a set of templates of known data formats, and the second rule is selected based on the identified format and applied to extract the QC data and remove the patient test result;
wherein the patient test result remains in the local network without being sent to the external network
in order to facilitate sharing of medical data on an as-needed basis to improve customer service, billing models, etc. along with the ability to track FDA and HIPAA compliance (as suggested in ¶ 56 of Zhao: “Referring back to Figure 2, according to one embodiment, server 109 may further include a tracking system (not shown), which may be integrated with server 109 or alternatively maintained by a third party vendor and accessible by server 109. The tracking system is configured to monitor and track user activities with respect to medical data stored in medical data store 206. Because of certain FDA requirements, there is a need to track what users have accessed the software, when, and the steps they have used within the software. There is also a need to track overall trends in software use, for example how long it takes a user to complete a certain type of case, or certain steps, billing trends etc. According to some embodiments, the tracking system is configured to track users who log in and utilize the software, steps the users perform, date and time of the accesses, etc. The tracking system can be used to analyze volumes used on, and performance of, the system. The tracking system can be used to track FD A/HIP AA compliance. It can also be utilized by insurance companies to track billing codes and costs. It can be used to determine trends (time to analyze certain types of cases etc.) Analysis of tracked data can also be used to identify different user types, for example expert users, casual users, technicians, physicians, etc. This information can then be used to improve the software product, upsell, improve customer service, improve billing models, etc. The tracking system can be used to track aggregate data as well as detailed data.”). Benefits specific to the use of Zhao’s anonymization, particularly in a cloud-based environment and to facilitate quality control and data mining, are also discussed in ¶¶ 34 and 59-61 of Zhao.
Zhao also describes templates in the sense of data formats and Zhao allows for functions to be applied to certain data based on their respective data sources (Zhao: ¶ 67 – “The data mining system provides a dynamic snapshot of vital measurements and relevant findings across all studies in the medical data store 206 for a particular patient. The data mining system supports access to multiple data sources, cross-modality comparison, cross-data source comparisons and the like. In some embodiments, the data mining system allows data elements to be registered or subscribed so that a user, administrator and/or system setting may specify how to retrieve certain data through a variety of communications protocols (e.g., SQL, extensible markup language (XML), etc.), what functions can be applied to certain data, in which modality(ies) and/or data source(s) can a certain data element be found, whether data is enumerated and/or numeric data, etc.”). In this regard (where the templates may additionally or alternatively be viewed as data formats), Zhao further suggests that it would have been further obvious to one of ordinary skill in the art before the effective filing date of Applicant’s invention to modify Balwani wherein the first rule identifies a format of the test result data by inspecting the test result data and comparing it to a set of templates of known data formats, and the second rule is selected based on the identified format and applied to extract the QC data and remove the patient test result in order to facilitate data aggregation, data filtering, and/or data mining across various data sources, thereby allowing more convenient access to more numerous data sources.
[Claim 11] Balwani discloses wherein the QC data flow system is a computing device located within a geographic space that includes the instrument (¶ 68 – “In some embodiments, the system can be configured such as the system with the LIS 30 will be there to receive results from a reference laboratory. A reference laboratory may be one that performs sample testing but is not the laboratory that reports out the results to the patient and/or physician. In this non-limiting example, the system may have one or more sample processing devices 100 that report data to a reference laboratory that finalizes the results and sends the data to the receiving laboratory, or sends the receiving laboratory the raw sample data through a pathways such as through a gateway including but not limited to a broker application and/or listener application 50. Service provided by a reference laboratory allows for greater capacity for the receiving laboratory to process samples and send out test results while still maintaining a seamless interaction between the laboratory and the patient or physician. Even if one laboratory such as a reference laboratory has looked at the test results, the receiving laboratory still reviews and signs off on the test results. The results may then be relayed as results certified by the receiving laboratory. By way of example and not limitation, three scenarios include, but are not limited to: analyzer device to LIS, reference lab to another lab, or lab providing service directly to doctor.”; ¶ 104 – “In one embodiment, it may be desirable that the perception to the LIS is that to the that all the devices are “local” in the sense that they provide data to the LIS as if they were part of the local system physically coupled by wired connections to the LIS but are instead coupled to the LIS through a data network comprising components such as but not limited to a LAN, WAN, or external computer processor(s) that may define a “cloud” network.”; ¶¶ 162, 167-168 – QC data may be transmitted (including received) locally and/or to (received by) an external device.).
[Claim 14] Balwani discloses identifying a triggering event indicating that connection to the cloud-based QC data management platform is unavailable (¶ 173 – “Optionally, the device may include one or more location sensing device. For example, the device may have a GPS tracker within the device. When any tampering with the device is detected, the location of the device may be transmitted from the device. The location may be transmitted to an external device or the cloud. In some instances, the location of the device may be continuously broadcast once the tampering is detected, or may be transmitted at one or more intervals or other detected events. An owner or entity associated with the device may be able to track the location of the device. In some instances, a plurality of location sensors may be provided so that even the device is taken apart and/or one or more location sensor is found and destroyed, it may be possible to track other parts of the device. In the event that the device is unable to transmit the device location at a particular moment, the device may be able to store the device location and transmit it once it is able.” Data related to tampering, such as location data, is an example of QC data.);
responsive to the triggering event, storing the QC data on the local network (¶ 173 – “Optionally, the device may include one or more location sensing device. For example, the device may have a GPS tracker within the device. When any tampering with the device is detected, the location of the device may be transmitted from the device. The location may be transmitted to an external device or the cloud. In some instances, the location of the device may be continuously broadcast once the tampering is detected, or may be transmitted at one or more intervals or other detected events. An owner or entity associated with the device may be able to track the location of the device. In some instances, a plurality of location sensors may be provided so that even the device is taken apart and/or one or more location sensor is found and destroyed, it may be possible to track other parts of the device. In the event that the device is unable to transmit the device location at a particular moment, the device may be able to store the device location and transmit it once it is able.” Data related to tampering, such as location data, is an example of QC data.); and
responsive to receiving an indication that the connection to the cloud-based QC data management platform is available again, forwarding the stored QC data to the cloud-based QC data management platform (¶ 173 – “Optionally, the device may include one or more location sensing device. For example, the device may have a GPS tracker within the device. When any tampering with the device is detected, the location of the device may be transmitted from the device. The location may be transmitted to an external device or the cloud. In some instances, the location of the device may be continuously broadcast once the tampering is detected, or may be transmitted at one or more intervals or other detected events. An owner or entity associated with the device may be able to track the location of the device. In some instances, a plurality of location sensors may be provided so that even the device is taken apart and/or one or more location sensor is found and destroyed, it may be possible to track other parts of the device. In the event that the device is unable to transmit the device location at a particular moment, the device may be able to store the device location and transmit it once it is able.” Data related to tampering, such as location data, is an example of QC data.).
Balwani does not explicitly disclose that storing the QC data on the local network (responsive to the triggering event) is performed for up to a set maximum amount of time; however, Balwani explains that “LIS can also react when an event is noted in the device 100 and then poll the device when LIS 30 needs the data. Data can also be deleted from device 100 after it is pulled into LIS 30.” (Balwani: ¶ 56) In other words, Balwani suggests deleting data from a device once it is no longer needed at the device. Balwani further explains a scenario in which deleting patient information from a device promotes security and protection of the patient’s private health data (Balwani: ¶ 176 – “In one embodiment, the device and the external controller maintain a security mechanism by which no unauthorized person with physical access to the device may be able to retrieve test information and link it back to an individual, thus protecting the privacy of patient health data. An example of this would be where the device captures user identification information, send it to the external device or cloud, receives a secret key from the cloud and erases all patient information from the device. In such a scenario, if the devices send any further data about that patient to the external device, it will be referred to link through the secret key already obtained from the external device.”). Given that, when a device cannot transmit QC-related information (like location data), the device stores the information until connection is reestablished, this suggests that Balwani is prepared to transfer data whenever possible and to delete information from devices to maintain security and protection of the patient’s private health data, thereby also suggesting that deleting data after a set maximum time of a connection being lost would have also helped to maintain security and protection of the patient’s private health data while also preserving valuable storage resources of the devices. The Examiner submits that it would have been obvious to one of ordinary skill in the art before the effective filing date of Applicant’s invention to modify Balwani such that storing the QC data on the local network (responsive to the triggering event) is performed for up to a set maximum amount of time in order to help maintain security and protection of the patient’s private health data (as suggested in ¶ 176 of Balwani) while also preserving valuable storage resources of the devices.
[Claim 15] Balwani does not explicitly disclose, responsive to forwarding the QC data, deleting the QC data from the local network; however, Balwani explains that “LIS can also react when an event is noted in the device 100 and then poll the device when LIS 30 needs the data. Data can also be deleted from device 100 after it is pulled into LIS 30.” (Balwani: ¶ 56) In other words, Balwani suggests deleting data from a device once it is no longer needed at the device. Balwani further explains a scenario in which deleting patient information from a device promotes security and protection of the patient’s private health data (Balwani: ¶ 176 – “In one embodiment, the device and the external controller maintain a security mechanism by which no unauthorized person with physical access to the device may be able to retrieve test information and link it back to an individual, thus protecting the privacy of patient health data. An example of this would be where the device captures user identification information, send it to the external device or cloud, receives a secret key from the cloud and erases all patient information from the device. In such a scenario, if the devices send any further data about that patient to the external device, it will be referred to link through the secret key already obtained from the external device.”). Given that, when a device cannot transmit QC-related information (like location data), the device stores the information until connection is reestablished, this suggests that Balwani is prepared to transfer data whenever possible and to delete information from devices to maintain security and protection of the patient’s private health data, thereby also suggesting that deleting data after a maximum time of a connection being lost would have also helped to maintain security and protection of the patient’s private health data while also preserving valuable storage resources of the devices. The Examiner submits that it would have been obvious to one of ordinary skill in the art before the effective filing date of Applicant’s invention to modify Balwani to, responsive to forwarding the QC data, delete the QC data from the local network in order to help maintain security and protection of the patient’s private health data (as suggested in ¶ 176 of Balwani) while also preserving valuable storage resources of the devices.
[Claim 16] Balwani discloses wherein the triggering event is user-input indicating planned downtime for the connection cloud-based QC data management platform (¶ 63 – “Additionally, the laboratory director can push quality control (QC) out to the analytical or sample processing device to tell it to run calibrator(s) or to shut it down until someone runs a calibrator (taking the device off-line) until a control cartridge and/or control protocol is run.”; ¶ 158 – “In some embodiments the device may be capable of performing on-board calibration and/or controls. The device may be capable of performing one or more diagnostic step (e.g., preparation step and/or assay step). If the results fall outside an expected range, a portion of the device may be cleaned and/or replaced. The results may also be useful for calibrating the device. On-board calibration and/or controls may occur without requiring human intervention. Calibration and controls may occur within a device housing.”; ¶ 159 – “A device may also be capable of performing on-board maintenance. If during a calibration, operation of device, diagnostic testing, or any other point in time a condition requiring repair and/or maintenance of the device is detected, the device may institute one or more automated procedures to perform said maintenance and/or repair. Any description of maintenance may include repair, cleaning, and/or adjustments. For example, a device may detect that a component is loose and may automatically tighten the component. The device may also detect that a wash or diluents level is running low in a module and provide an alert to add more wash or diluents, or bring over wash or diluents from another module.”; ¶ 47 – “Referring now to FIG. 3, at least one exemplary embodiment of a system for use with at least one method herein will now be described. FIG. 3 shows that in this embodiment, information can be sent from the device 100 through a network 70 to the cloud 110. By way of non-limiting example, the cloud 110 comprises one or more servers 120 in one or more data networks. Server 120 may be a cluster of servers. In one non-limiting example, a database on one or more of the servers 120 may be a cluster database. By way of non-limiting example, the cloud 110 comprises one or more computing devices in communication with one or more data networks. As seen in FIG. 3, data is then sent from the cloud 110 through a network 72 to the physical laboratory 10 with co-located or locally connected LIS 30 therein.).
[Claims 17-20] Claims 17-20 recite limitations already addressed by the rejections of claims 1, 2, 5, and 7 above; therefore, the same rejections apply. Furthermore, Balwani discloses a non-transitory computer-readable medium configured to store code comprising instructions, wherein the instructions, when executed by one or more processors, cause the one or more processors to perform the disclosed steps (Balwani: ¶¶ 177-191).
Claim 12 is rejected under 35 U.S.C. 103 as being unpatentable over Balwani (US 2015/0331946) in view of Zhao et al. (WO 2013/123085 A1), as applied to claim 10 above, in view of Madhav et al. (US 2016/0164914).
[Claim 12] Balwani refers to use of a virtual circuit (Balwani: ¶ 96) as well as a QC data flow system and a LIS (Balwani: ¶¶ 47, 68, 161, 171); however, Balwani does not explicitly disclose wherein the QC data flow system is a virtual machine running on the LIS. Madhav states, “One advantage of using a cloud operating multiple VMs instead of hardware is that some or a portion of traditional dedicated hardware devices such as routers and switches may not be required to build a network. Alternatively, a cloud can also combine VMs with existing hardware devices to optimize the performance of VN.” (Madhav: ¶ 29) Madhav solves a common problem in a laboratory and testing environment integrated in a cloud. “While some components or devices can be virtualized, others are still physical machines with hardware components placed in the vicinity of premise(s), such as laboratories, testing sites, demo sites, manufacturing facilities, and so forth. However, a problem associated with devices and/or components situated in various clouds is that a seamless communication between such components located in different clouds is difficult to achieve. A conventional approach to resolve this problem typically requires cumbersome information technology (“IT”) steps requiring skilled IT administrator(s) to setup each direct connection. For example, the steps may require a skilled IT person to setup communication between devices located in different cloud locations. The manual steps may involve in opening firewalls for certain private clouds and additional scripts may be needed to setup certain connections or links.” (Madhav: ¶ 3) The Examiner submits that it would have been obvious to one of ordinary skill in the art before the effective filing date of Applicant’s invention to modify Balwani wherein the QC data flow system is a virtual machine running on the LIS in order to minimize the number of hardware resources required to build a network and to optimize the performance of Balwani’s cloud network (as suggested in ¶ 29 of Madhav).
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over Balwani (US 2015/0331946) in view of Zhao et al. (WO 2013/123085 A1), as applied to claim 10 above, in view of Haggart et al. (US 2021/0203547).
[Claim 13] Balwani enables a user to control the opening of data ports (Balwani: ¶ 69) and Balwani’s QC data management platform is cloud-based (Balwani: ¶ 47 – “Referring now to FIG. 3, at least one exemplary embodiment of a system for use with at least one method herein will now be described. FIG. 3 shows that in this embodiment, information can be sent from the device 100 through a network 70 to the cloud 110. By way of non-limiting example, the cloud 110 comprises one or more servers 120 in one or more data networks. Server 120 may be a cluster of servers. In one non-limiting example, a database on one or more of the servers 120 may be a cluster database. By way of non-limiting example, the cloud 110 comprises one or more computing devices in communication with one or more data networks. As seen in FIG. 3, data is then sent from the cloud 110 through a network 72 to the physical laboratory 10 with co-located or locally connected LIS 30 therein.”); however, Balwani does not explicitly disclose wherein all ports of the QC data flow system except those used to receive the test result data and provide the QC data to the cloud-based QC data management platform are disabled. In a cloud and virtual machine environment, Haggart describes how ports may be opened or closed as needed (Haggart: ¶¶ 207, 208, 275). Haggart specifically explains that “the CMR service system 185 may utilize the received information to identify ports (as discussed herein) to configure software, hardware, and/or virtual network devices to ensure needed ports are open (and, optionally, to close any unneeded ports or ports that may represent a security risk).” (Haggart: ¶ 109) The Examiner submits that it would have been obvious to one of ordinary skill in the art before the effective filing date of Applicant’s invention to modify Balwani wherein all ports of the QC data flow system except those used to receive the test result data and provide the QC data to the cloud-based QC data management platform are disabled in order to minimize security risks that would otherwise be imposed by needlessly maintaining open connections where not needed in Balwani’s cloud-based system.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Molina (US 2019/0287672): ¶ 87 – “In some embodiments, studies stored in cloud-based library (prior uploaded studies 306 of FIG. 3) can be anonymous and imaging metadata can contain non-identifying user ID. Referring to FIG. 2, according to some embodiments, as it pertains to privacy and security of uploaded imaging data, some embodiments comprising cloud-based imaging systems can contain an access control system 204, and various private information protection mechanisms such as anonymizing server application 201 (of anonymous data storage) to de-identify uploaded medical imaging studies. For example, similar to the disclosure in International Patent Application No. WO2013123085A1, an anonymization template comprises a plurality of DICOM entries, each entry corresponding to a data item of a medical image to be anonymized, via deletion of the data entry with the option for replacement with an anonymous consumer user ID.”
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SUSANNA M DIAZ whose telephone number is (571)272-6733. The examiner can normally be reached M-F, 8 am-4:30 pm.
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/SUSANNA M. DIAZ/
Primary Examiner
Art Unit 3625A
Prosecution Insights