DETAILED ACTION
This final Office action is responsive to Applicant’s amendment filed March 26, 2026. Claims 1, 10, 13, and 17 have been amended. Claims 1-20 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 March 26, 2026 have been fully considered but they are not persuasive.
Preliminarily, it is noted that the amendments made to claim 14 overcome the previously-pending rejection of claims 14-16 under 35 U.S.C. § 112(b).
Regarding the art rejections, Applicant argues that the cited prior art references do not address the claim amendments. The Brown and Pait references have been introduced into the rejections in order to help address the claim amendments.
Regarding the rejection under 35 U.S.C. § 101, Applicant argues that “claim 10 clarifies the technical details of the filtering step, that the filtering step extracts the QC data and removes the patient data, and that the patient data remains in the local network when the QC data is provided to a cloud-based QC data management platform. This filtering step allows the user to utilize the advantages of cloud processing with less of the security concerns that typically go along with such services.” (Page 12 of Applicant’s response) Any security benefits of filtering out patient data may also generally be achieved if patient data is prevented from being shared manually. The recitation “wherein the patient data remains in the local network” does not incorporate any specific technical operations or ordered combination of additional elements. It is further noted that the limitation “wherein the patient data remains stored in the local network” alone does not necessarily filter out the patient data from the transmission of data via the external network; it could simply mean that the patient data remains stored in the local network. Even if the claims were amended to actively prevent the patient data from being shared beyond the local network, this would still be an example of generally filtering out information to share (or not share) outside of the local network (as opposed to presenting a special arrangement of technical elements to actively ensure that patient data is not shared outside of a local network, for example).
Applicant compares claim 10 of the instant application to claim 1 of the BASCOM patent (pages 12-14 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.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The 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 1-9), 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 patient data 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, and the second rule is selected based on the identified format and applied to extract the OC data and remove the patient data;
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 patient data and QC data;
receive the test result data and filter the test result data to extract the QC data and remove patient data from the test result data using a set of one or more rules, wherein a first rule identifies a format of the test result data, and a second rule is selected based on the identified format and applied to extract the OC data and remove the patient data; 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 patient data remains in the local 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 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 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.
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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i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec…; TLI Communications LLC v. AV Auto. LLC…; OIP Techs., Inc., v. Amazon.com, Inc…; buySAFE, Inc. v. Google, Inc…;
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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 1-11 and 14-20 are rejected under 35 U.S.C. 103 as being unpatentable over Balwani (US 2015/0331946) in view of Brown et al. (US 2019/0062809) in view of Pait et al. (US 2015/0006201).
[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 patient data 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 to extract the QC 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, and the second rule is selected based on the identified format and applied to extract the QC data and remove the patient data;
wherein the patient data remains in the local network.
Brown discloses:
filtering the test result data to extract the QC 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, and the second rule is selected based on the identified format and applied to extract the QC data and remove the patient data (Brown: ¶¶ 309-310 – “[0309] The hospital's LIS sends the PTO to an LIS interchange which converts the PTO request from an HL7 or ASTM format to a CSV format and the PTO is now referred to as a test order or an interchange order or formatted test order and the like. HL7 and ASTM are a set of standards used in the transfer of information between clinical instruments and Laboratory Information Systems. In this way, the sample-to-answer system is able to communicate with any hospital LIS because it is driven by multiple standard messaging protocols such as HL7 and ASTM. In this way, if the hospital's LIS system is updated the LIS interchange can be remotely updated (an update on the clinical instrument is not required). [0310] The sample-to-answer system further supports a “flat file format” i.e. non-standard file support for laboratories without automated interfaces (HL7 or ASTM). As such, tests can be imported and/or exported manually in a text format, CSV, TXT or XML formats. Automatic results can be released in XML format to a shared network location.“ Knowing how to properly format imported and exported data implies the existence of relevant instructions to process the correct format accordingly.; ¶ 349 – “Further, patient data is automatically removed in all exported run data (troubleshooting logs and raw data calculations such as nA signal from targets, non-detected targets, controls etc) for HIPPA compliance.” Knowing that patient data needs to be removed from exported information implies that there are instructions to identify and remove patient data from data exports.);
wherein the patient data remains in the local network (Brown: ¶ 346 – “Monitoring and reporting quality control is both a requirement and a best practice to ensure the accuracy of patient testing results and compliance with lab standards. With on-board QC tracking capabilities, the sample-to-answer system provides safeguards to ensure labs not only run controls when required but can easily track and report compliance. Indeed, the base station itself retains onboard QC test records to help ensure the lab runs controls when required.”; ¶ 349 – “Further, patient data is automatically removed in all exported run data (troubleshooting logs and raw data calculations such as nA signal from targets, non-detected targets, controls etc) for HIPPA compliance.”).
Even if Brown’s implied instructions are not seen as rules per se, Pait more explicitly defines rules for governing how patient-related data is shared and formatted (Pait: ¶¶ 23, 29 – Third party servers may be set up as devices in a cloud.; ¶¶ 40-45 – “[0040] In block 308, the patient data provider server 110 filters the patient data objects based at least in part on the access privileges of the requesting third party organization. For example, the third party organization may provide a list of the patients for which the third party organization is authorized to access patient information. Alternatively, or in addition, the patient data objects may be associated with an identifier of a third party organization, such as third party payer identifier. Thus, in one or more implementations the patient data provider server 110 may filter the patient data objects based at least in part on an identifier of the third party organization and a third party payer identifier associated with the patient data objects. [0041] In one or more implementations, if the third party organization is not authorized to view the patient data objects that include patient-identifiable data, such as patient names, etc., the patient data provider server 110 may filter the patient data objects by removing any patient-identifiable data from the patient data objects. For example, the patient data provider server 110 may anonymize the patient data objects by replacing patient-identifiable data with patient-unidentifiable data and/or by removing any patient-identifiable data from the patient data objects. [0042] In block 310, the patient data provider server 110 may map, transform, and/or normalize the filtered patient data objects based at least in part on the requesting third party organization. For example, the requesting third party organization may provide the patient data provider server 110 with one or more data mapping rules, data transformation rules, and/or data normalization rules, and the patient data provider server 110 may utilize any received rules to map, transform, and/or normalize the patient data objects. For example, a data mapping rule may be used to map the data fields of the patient data object to data fields utilized by the third party organization, a data transformation rule may be used to transform the patient data object into a data format used by the third party organization, and a data normalization rule may be used to normalize the data values of the patient data objects. For example, a data normalization rule may be used to convert any values of "M" for a gender data field to "male". [0043] In block 312, the patient data provider server 110 determines whether any data functions exist for the third party organization and/or individual users of the third party organization. For example, a third party organization may provide data functions that the third party organization would like applied to the transformed patient data objects. If, in block 312, the patient data provider server 110 determines that at least one data function exists for the requesting third party organization, the patient data provider server 110 moves to block 314. In block 314, the patient data provider server 110 applies the at least one data function to the transformed patient data objects. In one or more implementations, the patient data provider server 110 may provide a graphical user interface to the third party organizations, e.g. via one or more the third party user devices 102, 104, 106, that allows the third party organizations to create and/or manage data mapping rules, data transformation rules, data normalization rules, and/or data functions. [0044] In one or more implementations, data functions may be used to process the patient data objects to provide the third party organizations with additional insight into the patients and/or the healthcare facilities 120A-C. For example, a data function applied to the patient data objects may be used to identify potential outbreaks, and/or specific patients, to better perform programs for outpatient/home infection prevention, which may prevent the spread of illnesses to other family members that are covered by the third party organization. Similarly, a data function may be used to identify patients that missed a clinic infusion visit, multi-drug resistant organisms (MRDO), e.g. integrated culture data, resistant patterns, pathogens specific to identify patients of interest, and caterers/devices pulled from cabinets to identify those at high risk for infection.”).
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 to extract the QC 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, and the second rule is selected based on the identified format and applied to extract the QC data and remove the patient data;
wherein the patient data remains in the local network
because “the sample-to-answer system is able to communicate with any hospital LIS because it is driven by multiple standard messaging protocols such as HL7 and ASTM. In this way, if the hospital's LIS system is updated the LIS interchange can be remotely updated (an update on the clinical instrument is not required)” (Brown: ¶ 309) and since “[m]onitoring and reporting quality control is both a requirement and a best practice to ensure the accuracy of patient testing results and compliance with lab standards” (Brown: ¶ 346) and “for HIPPA compliance” (Brown: ¶ 349).
[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 4] Balwani does not explicitly disclose wherein the filtering is performed using a set of one or more rules.
However, Brown discloses wherein the filtering is performed using a set of one or more rules (Brown: ¶¶ 309-310 – “[0309] The hospital's LIS sends the PTO to an LIS interchange which converts the PTO request from an HL7 or ASTM format to a CSV format and the PTO is now referred to as a test order or an interchange order or formatted test order and the like. HL7 and ASTM are a set of standards used in the transfer of information between clinical instruments and Laboratory Information Systems. In this way, the sample-to-answer system is able to communicate with any hospital LIS because it is driven by multiple standard messaging protocols such as HL7 and ASTM. In this way, if the hospital's LIS system is updated the LIS interchange can be remotely updated (an update on the clinical instrument is not required). [0310] The sample-to-answer system further supports a “flat file format” i.e. non-standard file support for laboratories without automated interfaces (HL7 or ASTM). As such, tests can be imported and/or exported manually in a text format, CSV, TXT or XML formats. Automatic results can be released in XML format to a shared network location.“ Knowing how to properly format imported and exported data implies the existence of relevant instructions to process the correct format accordingly.; ¶ 349 – “Further, patient data is automatically removed in all exported run data (troubleshooting logs and raw data calculations such as nA signal from targets, non-detected targets, controls etc) for HIPPA compliance.” Knowing that patient data needs to be removed from exported information implies that there are instructions to identify and remove patient data from data exports.).
Even if Brown’s implied instructions are not seen as rules per se, Pait more explicitly defines rules for governing how patient-related data is shared and formatted (Pait: ¶¶ 23, 29 – Third party servers may be set up as devices in a cloud.; ¶¶ 40-45 – “[0040] In block 308, the patient data provider server 110 filters the patient data objects based at least in part on the access privileges of the requesting third party organization. For example, the third party organization may provide a list of the patients for which the third party organization is authorized to access patient information. Alternatively, or in addition, the patient data objects may be associated with an identifier of a third party organization, such as third party payer identifier. Thus, in one or more implementations the patient data provider server 110 may filter the patient data objects based at least in part on an identifier of the third party organization and a third party payer identifier associated with the patient data objects. [0041] In one or more implementations, if the third party organization is not authorized to view the patient data objects that include patient-identifiable data, such as patient names, etc., the patient data provider server 110 may filter the patient data objects by removing any patient-identifiable data from the patient data objects. For example, the patient data provider server 110 may anonymize the patient data objects by replacing patient-identifiable data with patient-unidentifiable data and/or by removing any patient-identifiable data from the patient data objects. [0042] In block 310, the patient data provider server 110 may map, transform, and/or normalize the filtered patient data objects based at least in part on the requesting third party organization. For example, the requesting third party organization may provide the patient data provider server 110 with one or more data mapping rules, data transformation rules, and/or data normalization rules, and the patient data provider server 110 may utilize any received rules to map, transform, and/or normalize the patient data objects. For example, a data mapping rule may be used to map the data fields of the patient data object to data fields utilized by the third party organization, a data transformation rule may be used to transform the patient data object into a data format used by the third party organization, and a data normalization rule may be used to normalize the data values of the patient data objects. For example, a data normalization rule may be used to convert any values of "M" for a gender data field to "male". [0043] In block 312, the patient data provider server 110 determines whether any data functions exist for the third party organization and/or individual users of the third party organization. For example, a third party organization may provide data functions that the third party organization would like applied to the transformed patient data objects. If, in block 312, the patient data provider server 110 determines that at least one data function exists for the requesting third party organization, the patient data provider server 110 moves to block 314. In block 314, the patient data provider server 110 applies the at least one data function to the transformed patient data objects. In one or more implementations, the patient data provider server 110 may provide a graphical user interface to the third party organizations, e.g. via one or more the third party user devices 102, 104, 106, that allows the third party organizations to create and/or manage data mapping rules, data transformation rules, data normalization rules, and/or data functions. [0044] In one or more implementations, data functions may be used to process the patient data objects to provide the third party organizations with additional insight into the patients and/or the healthcare facilities 120A-C. For example, a data function applied to the patient data objects may be used to identify potential outbreaks, and/or specific patients, to better perform programs for outpatient/home infection prevention, which may prevent the spread of illnesses to other family members that are covered by the third party organization. Similarly, a data function may be used to identify patients that missed a clinic infusion visit, multi-drug resistant organisms (MRDO), e.g. integrated culture data, resistant patterns, pathogens specific to identify patients of interest, and caterers/devices pulled from cabinets to identify those at high risk for infection.”).
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 filtering is performed using a set of one or more rules because “the sample-to-answer system is able to communicate with any hospital LIS because it is driven by multiple standard messaging protocols such as HL7 and ASTM. In this way, if the hospital's LIS system is updated the LIS interchange can be remotely updated (an update on the clinical instrument is not required)” (Brown: ¶ 309) and since “[m]onitoring and reporting quality control is both a requirement and a best practice to ensure the accuracy of patient testing results and compliance with lab standards” (Brown: ¶ 346) and “for HIPPA compliance” (Brown: ¶ 349).
[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.
However, Brown states, “The hospital's LIS sends the PTO to an LIS interchange which converts the PTO request from an HL7 or ASTM format to a CSV format and the PTO is now referred to as a test order or an interchange order or formatted test order and the like. HL7 and ASTM are a set of standards used in the transfer of information between clinical instruments and Laboratory Information Systems. In this way, the sample-to-answer system is able to communicate with any hospital LIS because it is driven by multiple standard messaging protocols such as HL7 and ASTM. In this way, if the hospital's LIS system is updated the LIS interchange can be remotely updated (an update on the clinical instrument is not required).” (Brown: ¶ 309) In other words, formatting may be modified to handle system updates. Furthermore, Brown extracts QC data from the test result data (Brown: ¶¶ 309-310 – “[0309] The hospital's LIS sends the PTO to an LIS interchange which converts the PTO request from an HL7 or ASTM format to a CSV format and the PTO is now referred to as a test order or an interchange order or formatted test order and the like. HL7 and ASTM are a set of standards used in the transfer of information between clinical instruments and Laboratory Information Systems. In this way, the sample-to-answer system is able to communicate with any hospital LIS because it is driven by multiple standard messaging protocols such as HL7 and ASTM. In this way, if the hospital's LIS system is updated the LIS interchange can be remotely updated (an update on the clinical instrument is not required). [0310] The sample-to-answer system further supports a “flat file format” i.e. non-standard file support for laboratories without automated interfaces (HL7 or ASTM). As such, tests can be imported and/or exported manually in a text format, CSV, TXT or XML formats. Automatic results can be released in XML format to a shared network location.“ Knowing how to properly format imported and exported data implies the existence of relevant instructions to process the correct format accordingly.; ¶ 349 – “Further, patient data is automatically removed in all exported run data (troubleshooting logs and raw data calculations such as nA signal from targets, non-detected targets, controls etc) for HIPPA compliance.” Knowing that patient data needs to be removed from exported information implies that there are instructions to identify and remove patient data from data exports.).
Even if Brown’s implied instructions are not seen as rules per se, Pait more explicitly defines rules for governing how patient-related data is shared and formatted (Pait: ¶¶ 23, 29 – Third party servers may be set up as devices in a cloud.; ¶¶ 40-45 – “[0040] In block 308, the patient data provider server 110 filters the patient data objects based at least in part on the access privileges of the requesting third party organization. For example, the third party organization may provide a list of the patients for which the third party organization is authorized to access patient information. Alternatively, or in addition, the patient data objects may be associated with an identifier of a third party organization, such as third party payer identifier. Thus, in one or more implementations the patient data provider server 110 may filter the patient data objects based at least in part on an identifier of the third party organization and a third party payer identifier associated with the patient data objects. [0041] In one or more implementations, if the third party organization is not authorized to view the patient data objects that include patient-identifiable data, such as patient names, etc., the patient data provider server 110 may filter the patient data objects by removing any patient-identifiable data from the patient data objects. For example, the patient data provider server 110 may anonymize the patient data objects by replacing patient-identifiable data with patient-unidentifiable data and/or by removing any patient-identifiable data from the patient data objects. [0042] In block 310, the patient data provider server 110 may map, transform, and/or normalize the filtered patient data objects based at least in part on the requesting third party organization. For example, the requesting third party organization may provide the patient data provider server 110 with one or more data mapping rules, data transformation rules, and/or data normalization rules, and the patient data provider server 110 may utilize any received rules to map, transform, and/or normalize the patient data objects. For example, a data mapping rule may be used to map the data fields of the patient data object to data fields utilized by the third party organization, a data transformation rule may be used to transform the patient data object into a data format used by the third party organization, and a data normalization rule may be used to normalize the data values of the patient data objects. For example, a data normalization rule may be used to convert any values of "M" for a gender data field to "male". [0043] In block 312, the patient data provider server 110 determines whether any data functions exist for the third party organization and/or individual users of the third party organization. For example, a third party organization may provide data functions that the third party organization would like applied to the transformed patient data objects. If, in block 312, the patient data provider server 110 determines that at least one data function exists for the requesting third party organization, the patient data provider server 110 moves to block 314. In block 314, the patient data provider server 110 applies the at least one data function to the transformed patient data objects. In one or more implementations, the patient data provider server 110 may provide a graphical user interface to the third party organizations, e.g. via one or more the third party user devices 102, 104, 106, that allows the third party organizations to create and/or manage data mapping rules, data transformation rules, data normalization rules, and/or data functions. [0044] In one or more implementations, data functions may be used to process the patient data objects to provide the third party organizations with additional insight into the patients and/or the healthcare facilities 120A-C. For example, a data function applied to the patient data objects may be used to identify potential outbreaks, and/or specific patients, to better perform programs for outpatient/home infection prevention, which may prevent the spread of illnesses to other family members that are covered by the third party organization. Similarly, a data function may be used to identify patients that missed a clinic infusion visit, multi-drug resistant organisms (MRDO), e.g. integrated culture data, resistant patterns, pathogens specific to identify patients of interest, and caterers/devices pulled from cabinets to identify those at high risk for infection.”).
Also, extracting additional QC data from the additional test result data may be interpreted as processing multiple requests, including for different parties and in different situations. As explained above, Pait evaluates specific rules as they relate to who can access which specific types of data and such rules may be defined by users via a GUI (Pait: ¶ 43).
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
because “the sample-to-answer system is able to communicate with any hospital LIS because it is driven by multiple standard messaging protocols such as HL7 and ASTM. In this way, if the hospital's LIS system is updated the LIS interchange can be remotely updated (an update on the clinical instrument is not required)” (Brown: ¶ 309) and since “[m]onitoring and reporting quality control is both a requirement and a best practice to ensure the accuracy of patient testing results and compliance with lab standards” (Brown: ¶ 346) and “for HIPPA compliance” (Brown: ¶ 349). Again, extracting additional QC data from the additional test result data may be interpreted as processing multiple requests, including for different parties and in different situations. 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 extract additional QC data from the additional test result data so that multiple data requests that are subject to varying rules may be more efficiently processed.
[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 patient data 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 cloud-based QC data flow system coupled to the LIS via the local network, the cloud-based 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 QC data management platform coupled to the QC data flow system via an external network, the 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 (¶ 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 patient data from the test result data using a set of one or more rules, wherein a first rule identifies a format of the test result data, and the second rule is selected based on the identified format and applied to extract the QC data and remove the patient data;
wherein the patient data remains in the local network.
Brown discloses:
filtering the test result data to extract the QC 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, and the second rule is selected based on the identified format and applied to extract the QC data and remove the patient data (Brown: ¶¶ 309-310 – “[0309] The hospital's LIS sends the PTO to an LIS interchange which converts the PTO request from an HL7 or ASTM format to a CSV format and the PTO is now referred to as a test order or an interchange order or formatted test order and the like. HL7 and ASTM are a set of standards used in the transfer of information between clinical instruments and Laboratory Information Systems. In this way, the sample-to-answer system is able to communicate with any hospital LIS because it is driven by multiple standard messaging protocols such as HL7 and ASTM. In this way, if the hospital's LIS system is updated the LIS interchange can be remotely updated (an update on the clinical instrument is not required). [0310] The sample-to-answer system further supports a “flat file format” i.e. non-standard file support for laboratories without automated interfaces (HL7 or ASTM). As such, tests can be imported and/or exported manually in a text format, CSV, TXT or XML formats. Automatic results can be released in XML format to a shared network location.“ Knowing how to properly format imported and exported data implies the existence of relevant instructions to process the correct format accordingly.; ¶ 349 – “Further, patient data is automatically removed in all exported run data (troubleshooting logs and raw data calculations such as nA signal from targets, non-detected targets, controls etc) for HIPPA compliance.” Knowing that patient data needs to be removed from exported information implies that there are instructions to identify and remove patient data from data exports.);
wherein the patient data remains in the local network (Brown: ¶ 346 – “Monitoring and reporting quality control is both a requirement and a best practice to ensure the accuracy of patient testing results and compliance with lab standards. With on-board QC tracking capabilities, the sample-to-answer system provides safeguards to ensure labs not only run controls when required but can easily track and report compliance. Indeed, the base station itself retains onboard QC test records to help ensure the lab runs controls when required.”; ¶ 349 – “Further, patient data is automatically removed in all exported run data (troubleshooting logs and raw data calculations such as nA signal from targets, non-detected targets, controls etc) for HIPPA compliance.”).
Even if Brown’s implied instructions are not seen as rules per se, Pait more explicitly defines rules for governing how patient-related data is shared and formatted (Pait: ¶¶ 23, 29 – Third party servers may be set up as devices in a cloud.; ¶¶ 40-45 – “[0040] In block 308, the patient data provider server 110 filters the patient data objects based at least in part on the access privileges of the requesting third party organization. For example, the third party organization may provide a list of the patients for which the third party organization is authorized to access patient information. Alternatively, or in addition, the patient data objects may be associated with an identifier of a third party organization, such as third party payer identifier. Thus, in one or more implementations the patient data provider server 110 may filter the patient data objects based at least in part on an identifier of the third party organization and a third party payer identifier associated with the patient data objects. [0041] In one or more implementations, if the third party organization is not authorized to view the patient data objects that include patient-identifiable data, such as patient names, etc., the patient data provider server 110 may filter the patient data objects by removing any patient-identifiable data from the patient data objects. For example, the patient data provider server 110 may anonymize the patient data objects by replacing patient-identifiable data with patient-unidentifiable data and/or by removing any patient-identifiable data from the patient data objects. [0042] In block 310, the patient data provider server 110 may map, transform, and/or normalize the filtered patient data objects based at least in part on the requesting third party organization. For example, the requesting third party organization may provide the patient data provider server 110 with one or more data mapping rules, data transformation rules, and/or data normalization rules, and the patient data provider server 110 may utilize any received rules to map, transform, and/or normalize the patient data objects. For example, a data mapping rule may be used to map the data fields of the patient data object to data fields utilized by the third party organization, a data transformation rule may be used to transform the patient data object into a data format used by the third party organization, and a data normalization rule may be used to normalize the data values of the patient data objects. For example, a data normalization rule may be used to convert any values of "M" for a gender data field to "male". [0043] In block 312, the patient data provider server 110 determines whether any data functions exist for the third party organization and/or individual users of the third party organization. For example, a third party organization may provide data functions that the third party organization would like applied to the transformed patient data objects. If, in block 312, the patient data provider server 110 determines that at least one data function exists for the requesting third party organization, the patient data provider server 110 moves to block 314. In block 314, the patient data provider server 110 applies the at least one data function to the transformed patient data objects. In one or more implementations, the patient data provider server 110 may provide a graphical user interface to the third party organizations, e.g. via one or more the third party user devices 102, 104, 106, that allows the third party organizations to create and/or manage data mapping rules, data transformation rules, data normalization rules, and/or data functions. [0044] In one or more implementations, data functions may be used to process the patient data objects to provide the third party organizations with additional insight into the patients and/or the healthcare facilities 120A-C. For example, a data function applied to the patient data objects may be used to identify potential outbreaks, and/or specific patients, to better perform programs for outpatient/home infection prevention, which may prevent the spread of illnesses to other family members that are covered by the third party organization. Similarly, a data function may be used to identify patients that missed a clinic infusion visit, multi-drug resistant organisms (MRDO), e.g. integrated culture data, resistant patterns, pathogens specific to identify patients of interest, and caterers/devices pulled from cabinets to identify those at high risk for infection.”).
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 patient data from the test result data using a set of one or more rules, wherein a first rule identifies a format of the test result data, and the second rule is selected based on the identified format and applied to extract the QC data and remove the patient data;
wherein the patient data remains in the local network
because “the sample-to-answer system is able to communicate with any hospital LIS because it is driven by multiple standard messaging protocols such as HL7 and ASTM. In this way, if the hospital's LIS system is updated the LIS interchange can be remotely updated (an update on the clinical instrument is not required)” (Brown: ¶ 309) and since “[m]onitoring and reporting quality control is both a requirement and a best practice to ensure the accuracy of patient testing results and compliance with lab standards” (Brown: ¶ 346) and “for HIPPA compliance” (Brown: ¶ 349).
[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, 4, 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 Brown et al. (US 2019/0062809) in view of Pait et al. (US 2015/0006201), 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 Brown et al. (US 2019/0062809) in view of Pait et al. (US 2015/0006201), 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
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to 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