DETAILED ACTION
This communication is a Final Office Action rejection on the merits. Claims 1-7, 9-16, and 18-20 are currently pending and have been addressed below.
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 .
Information Disclosure Statement (IDS)
The information disclosure statement(s) filed on 09/25/2025 comply with the provisions 37 CFR 1.97, 1.98, and MPEP 609 and is considered by the Examiner.
Response to Arguments
Applicant's arguments filed on 02/20/2026 (related to the 103 Rejection) have been fully considered but are moot in view of new grounds of rejection. Applicant's amendments necessitated the new ground(s) of rejection presented in this Office action. Rejection based on a newly cited reference(s) follows.
Applicant's arguments filed on 02/20/2026 (related to the 101 Rejection) have been fully considered but they are not persuasive.
Applicant states, on pages 12-13, that software architecture required by the claims is not a mental process as is alleged regarding the previously-pending claims. For example, a human mind cannot instantiate a gateway layer, orchestrate microservices, or execute a transformation microservice. The non-physicality of these elements does not undermine their eligibility: "much of the advancement made in computer technology consists of improvements to software that. .. may not be defined by particular physical features but rather by logical structures and processes ... Software can make non-abstract improvements to computer technology" (Enfish, LLC v. Microsoft Corp, 822 F.3d 1327 (Fed. Cir. 2016), as quoted in USPTO December 5, 2025 Memorandum, p.1).
The specification identifies a technical problem: "with the disparate platforms and programs employed by existing practices, unintegrated and not standardized, [a practice] aggregator. .. expends substantial energy and resources bringing consistency ... to the group of practices" (present application, [0006]). As detailed above, the claims reflect a solution which "define[s] a system architecture that allows for onboarding of any information of interest" such that "[i]ndividual practices are ... not required to adopt specific new or different platforms and/or applications for the benefit of group management" (present application, [0013]).
As reflected in the claims, this solution takes the form of a specific technical architecture. The claimed gateway layer, service orchestration layer, and plurality of microservices-including a transformation microservice-are not generic computer components recited at a high level of generality. Rather, their particular arrangement improves the functioning of the distributed computer system by enabling seamless integration of disparate practice data sources without requiring changes to the underlying practice or corporate software systems. As recent guidance from the USPTO has emphasized, "When evaluating a claim as a whole, examiners should not dismiss additional elements as mere 'generic computer components' without considering whether such elements confer a technological improvement to a technical problem, especially as to improvements to computer components of the computer system" (USPTO December 5, 2025 Memorandum, p. 4).
Examiner respectfully disagrees with Applicant. Claim 1 is considered to be an abstract idea because the claim limitations are directed to “certain methods of organizing human activity” which include “managing personal behavior.” In this case, the claim recites providing a report to a user, wherein the report facilitates decision making at all levels of the organization (MPEP 2106.04(a)(2), managing personal behavior). If a claim limitation, under its broadest reasonable interpretation, covers managing personal behavior, then it falls within the “certain methods of organizing human activity” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
The main functions of the additional elements recited in claim 1 are merely used to: collect data (e.g. first practice data, second practice data, and corporate data), analyze the data (e.g. transform the first practice data & second practice data, and determine a performance measure of the first practice & second practice), and display certain results of the collection and analysis (e.g. display the first practice performance measure & second practice performance measure). Those are functions that the courts have described as merely indicating a field of use or technological environment in which to apply a judicial exception (see MPEP 2106.05(h)). Further, the function of “transforming, based on the corporate specifications, the first practice data and the second practice data” is merely used to map current and future business systems and/or perform aggregations (Paragraphs 0090 & 0112). “Transforming data” is not considered an eligible transformation (MPEP 2106.05(c)).
Also, the additional element of a service orchestration layer configured to orchestrate a plurality of microservices is merely used to integrate disparate software systems (Paragraph 0067). In some embodiments, this is a microservices-based architecture including certain levels of synchronized and asynchronized data exchanges. In some implementations, each service exists independently with its own backend transactional database. Multiple services have the capability to be orchestrated in conjunction via a service orchestration layer and can also exchange data via data and event stream. In some instances, data generated at individual transactional databases gets piped into the data warehouse (e.g., element 329) directly or via staging data (e.g., element 328) with or without transformation, as needed. The gateway layer serves external applications and is used for cross-cutting concerns like logging, session management, security, load balancing, etc. (Paragraph 0079). The microservices are considered “field of use” since they’re just used to exchange and transform information for an analysis, but the technology is not improved (MPEP 2106.05h). Further, the claim and specification do not include any specific details of how the computer perform logging, session management, security, load balancing, and/or transformations. Therefore, the claim recites only the idea of a solution or outcome (see MPEP 2106.05(f)).
Lastly, the claim fails to recite any improvements to another technology or technical field, improvements to the functioning of the computer itself, use of a particular machine, effecting a transformation or reduction of a particular article to a different state or thing, adding unconventional steps that confine the claim to a particular useful application, and/or meaningful limitations beyond generally linking the use of an abstract idea to a particular environment. See 84 Fed. Reg. 55. Viewed individually or as a whole, these additional claim element(s) do not provide meaningful limitation(s) to transform the abstract idea into a patent eligible application of the abstract idea such that the claim(s) amounts to significantly more than the abstract idea itself.
Independent claims 10 recites similar features and therefore is rejected for the same reasons as independent claim 1. Claims 2-7, 9, 11-16, and 18-20 are rejected for having the same deficiencies as those set forth with respect to the claims that they depend from, independent claims 1 and 10.
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 1-7, 9-16, and 18-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., an abstract idea) without reciting significantly more.
Independent Claim 1
Step One - First, pursuant to step 1 in the January 2019 Revised Patent Subject Matter Eligibility Guidance (“2019 PEG”) on 84 Fed. Reg. 53, the claim 1 is directed to an apparatus which is a statutory category.
Step 2A, Prong One - Claim 1 recites: A distributed system comprising: a first practice comprising one or more first practice management data sources and relating to a first practice being evaluated; a second practice comprising one or more second practice management data sources and relating to a second practice being evaluated; and a corporate comprising one or more corporate data sources and relating to an aggregator of the first practice and the second practice; and to: extract; first practice data comprising a first format from the one or more first practice management data sources; and second practice data comprising a second format, different from the first format, from the one or more second practice management data sources; extract, corporate data comprising a third format, different from the first format and the second format, from the one or more corporate data sources, wherein the corporate data includes corporate specifications; transform, (i) based on the corporate specifications: the extracted first practice management data to a standardized format to obtain transformed first practice management data; and the extracted second practice management data to the standardized format to obtain transformed second practice management data; determine a first performance measure of the first practice being evaluated based on the transformed first practice management data and a second performance measure of the second practice being evaluated based on the transformed second practice management data; automatically generate (i) a report including the first performance measure and the second performance measure and (ii) metadata associated with the report; store the report and the metadata; transmit, the report based on a role of a user of the corporate; and display the report. These claim elements are considered to be abstract ideas because the claim limitations are directed to “certain methods of organizing human activity” which include “managing personal behavior.” In this case, the claim recites providing a report to a user, wherein the report facilitates decision making at all levels of the organization (MPEP 2106.04(a)(2), managing personal behavior). If a claim limitation, under its broadest reasonable interpretation, covers managing personal behavior, then it falls within the “certain methods of organizing human activity” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
Step 2A Prong 2 - The judicial exception is not integrated into a practical application. Claim 1 includes additional elements: a distributed computer system; a first practice computer system; a second practice computer system; a corporate computer system; one or more non-transitory computer-readable storage media storing processor-executable instructions configured to instantiate a software architecture comprising: a gateway layer configured to: interface with software applications of the first practice computer system, the second practice computer system, and the corporate computer system; and perform logging, session management, security, and load balancing for the distributed computer system; and a service orchestration layer in communication with the gateway layer and configured to orchestrate a plurality of microservices, wherein the distributed computer system is configured to execute the instructions of the one or more non-transitory computer-readable storage media in order to; one or more databases; a transformation microservice; and a user interface of the corporate computer system.
The distributed computer system is merely used to perform various management functions (Paragraph 0033). The first practice, second practice, and corporate computer systems are merely used to store practice management data or corporate application data (Paragraph 0074). The service orchestration layer configured to orchestrate a plurality of microservices is merely used to integrate disparate software systems (Paragraph 0067). In some embodiments, this is a microservices-based architecture including certain levels of synchronized and asynchronized data exchanges. In some implementations, each service exists independently with its own backend transactional database. Multiple services have the capability to be orchestrated in conjunction via a service orchestration layer and can also exchange data via data and event stream. In some instances, data generated at individual transactional databases gets piped into the data warehouse (e.g., element 329) directly or via staging data (e.g., element 328) with or without transformation, as needed. The gateway layer serves external applications and is used for cross-cutting concerns like logging, session management, security, load balancing, etc. (Paragraph 0079). The database is merely used to collect data in a metadata configuration as an aspect of data analysis (Paragraph 0013). The transformation microservice is merely used to map current and future business systems, understand the current general ledger, and/or perform aggregations (Paragraphs 0090 & 0112). The user interface is merely used to provide information relating to the management of the practice to one or more user types (Paragraph 0075). Merely stating that the step is performed by a computer component results in “apply it” on a computer (MPEP 2106.05f). These elements of “distributed computer system,” “first practice computer system,” “second practice computer system,” “corporate computer system,” “service orchestration layer,” “gateway layer,” “database,” “transformation microservice,” and “user interface” are recited at a high level of generality such that it amounts no more than mere instructions to apply the exception using a generic computer element. Also, the computer systems and gateway layer are considered “field of use” since they are just used to extract information and place it in a database for an analysis, but the technology is not improved (MPEP 2106.05h). Accordingly, alone and in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Therefore, the claim is directed to an abstract idea.
Step 2B - The claim does not include additional elements that are sufficient to amount significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the claims describe how to generally “apply” the concept of determining a performance measure of the practices being evaluated based on the transformed data. The specification shows that the distributed computer system is merely used to perform various management functions (Paragraph 0033). The first practice, second practice, and corporate computer systems are merely used to store practice management data or corporate application data (Paragraph 0074). The service orchestration layer configured to orchestrate a plurality of microservices is merely used to integrate disparate software systems (Paragraph 0067). In some embodiments, this is a microservices-based architecture including certain levels of synchronized and asynchronized data exchanges. In some implementations, each service exists independently with its own backend transactional database. Multiple services have the capability to be orchestrated in conjunction via a service orchestration layer and can also exchange data via data and event stream. In some instances, data generated at individual transactional databases gets piped into the data warehouse (e.g., element 329) directly or via staging data (e.g., element 328) with or without transformation, as needed. The gateway layer serves external applications and is used for cross-cutting concerns like logging, session management, security, load balancing, etc. (Paragraph 0079). The database is merely used to collect data in a metadata configuration as an aspect of data analysis (Paragraph 0013). The transformation microservice is merely used to map current and future business systems, understand the current general ledger, and/or perform aggregations (Paragraphs 0090 & 0112). The user interface is merely used to provide information relating to the management of the practice to one or more user types (Paragraph 0075). Also, the functions of “extracting data” and “storing data” are conventional still, “receiving or transmitting data over a network” and “storing information in a memory” (MPEP 2106.05d). Further, the function of “transforming, based on the corporate specifications, the first practice data and the second practice data” is merely used to map current and future business systems (Paragraph 0090). “Transforming data” is not considered an eligible transformation (MPEP 2106.05(c)). Thus, nothing in the claim adds significantly more to the abstract idea. The claim is ineligible.
Independent claim 10 is directed to a method at step 1, which is a statutory category. Claim 10 recites similar limitations as claim 1 and is rejected for the same reasons at step 2a, prong one; step 2a, prong 2; and step 2b. Therefore, the claim is ineligible.
Dependent claims 2-4, 6, 11-13, 15, and 19-20 are not directed to any additional claim elements. Rather, these claims offer further descriptive limitations of the abstract idea mentioned above - such as: wherein the corporate specifications comprise one or more of a group including target data, benchmark data, headquarter data, and reference data; wherein the one or more first practice management data sources relating to the practice being evaluated comprise one or more of a group including financial information, human resource information, patient information, medical information, operation information, client communications, review analysis, and inventory information; wherein extracting the first practice data comprises mapping the first practice data into at least one normalized data set; wherein the first performance measure of the first practice being evaluated comprises at least one of a group including root cause, plan information, and progress toward a target; and wherein the corporate data sources comprise applications relating to at least one of a group including a human resources information system, a payroll service, an accounts receivable service, an accounts payable service, a budgeting service, an attendance tracking service, a scheduling service, a talent acquisition service, a customer relationship management platform, an enterprise resource planning platform, a customer review platform, and an employee engagement review platform. These processes are similar to the abstract idea noted in the independent claim because they further the limitations of the independent claim which are directed to “certain methods of organizing human activity” which include “managing personal behavior.” In addition, there are no additional elements to consider at Step 2A Prong 2 and Step 2B. Therefore, the claims still recite an abstract idea that can be grouped into “mental processes.”
Dependent claims 5 and 14 are directed to an additional element such as: a general ledger. The general ledger is merely used to map practice management data into different categories. Merely stating that the step is performed by a computer component results in “apply it” on a computer (MPEP 2106.05f) being applicable at both Step 2A, Prong 2 and Step 2B. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Thus, nothing in the claim adds significantly more to the abstract idea. The claim is ineligible.
Dependent claims 7, 9, 16, and 18 are directed to additional functions of the distributed computer system such as to: generate a report including the first performance measure, wherein the report comprises at least one of a group including a chart, a plot, and a table. Merely stating that the step is performed by a computer component results in “apply it” on a computer (MPEP 2106.05f) being applicable at both Step 2A, Prong 2 and Step 2B. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Thus, nothing in the claim adds significantly more to the abstract idea. The claim is ineligible.
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.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-7, 9-16, and 18 are under 35 U.S.C. 103 as being unpatentable over Snow et al. (US 2017/0169173 A1), in view of LaBorde (US 2015/0169827 A1).
Regarding claim 1 (Currently Amended), Snow et al. discloses a distributed computer system comprising (Paragraph 0015, The present invention provides methods and systems for monitoring and managing healthcare performance):
a first practice computer system comprising one or more first practice management data sources and relating to a first practice being evaluated (Paragraph 0039, Healthcare data can be collected from sources such as healthcare insurance administrations, payer-provider reimbursement contracting, physician healthcare services or providers, and physician billing and reimbursements);
a second practice computer system comprising one or more second practice management data sources and relating to a second practice being evaluated (Paragraph 0039, Healthcare data can be collected from sources such as healthcare insurance administrations, payer-provider reimbursement contracting, physician healthcare services or providers, and physician billing and reimbursements);
a corporate computer system comprising one or more corporate data sources and relating to an aggregator of the first practice and the second practice (Figure 2, item 104, Data Processing Server; Paragraph 0039, The healthcare data can be transformed from raw data into meaningful and useful information for health service managers and administrators who run medical practices and health care facilities);
and one or more non-transitory computer-readable storage media storing processor-executable instructions configured to instantiate a software architecture comprising (Paragraph 0132, In software implementations, computer software (e.g., programs or other instructions) and/or data is stored on a machine readable medium as part of a computer program product, and is loaded into a computer system or other device or machine via a removable storage drive, hard drive, or communications interface. Computer programs (also called computer control logic or computer readable program code) are stored in a main and/or secondary memory, and executed by one or more processors (controllers, or the like) to cause the one or more processors to perform the functions of the invention as described herein):
a gateway layer configured to: interface with software applications of the first practice computer system, the second practice computer system, and the corporate computer system (see Figure 1 and related text in Paragraph 0045, Network 108 may be any suitable type of network allowing transport of data communications across thereof. The network 108 may couple devices so that communications may be exchanged, such as between servers and client devices or other types of devices, including between wireless devices coupled via a wireless network, for example; Paragraph 0047, Analytic models engine 204 is configurable to run and execute analytical software and logic using data from the data sources 102 and healthcare manager devices 106. The analytical software and logic may include data mining, machine learning, and “big math” instructions or code to identify cost efficiency and where improvements may be made in quality of care and savings);
…, wherein the distributed computer system is configured to execute the instructions of the one or more non-transitory computer-readable storage media in order to (Figure 2, item 104, Data Processing Server; Paragraph 0132, In software implementations, computer software (e.g., programs or other instructions) and/or data is stored on a machine readable medium as part of a computer program product, and is loaded into a computer system or other device or machine via a removable storage drive, hard drive, or communications interface. Computer programs (also called computer control logic or computer readable program code) are stored in a main and/or secondary memory, and executed by one or more processors (controllers, or the like) to cause the one or more processors to perform the functions of the invention as described herein):
extract, (i) to the one or more databases, (ii) through the gateway layer, and …; first practice data comprising a first format from the one or more first practice management data sources; and second practice data comprising a second format, different from the first format, from the one or more second practice management data sources (Figure 1, item 108, Network; Paragraph 0039, Healthcare data can be collected from sources such as healthcare insurance administrations, payer-provider reimbursement contracting, physician healthcare services or providers, and physician billing and reimbursements; Paragraph 0042, The data from data sources 102 may be in any and in disparate kinds of data formats. Receiving data from data sources 102 may include establishing connections or linking the data processing server 104 with a given account, server, directory, system, interface, etc.; Paragraph 0045, Network 108 may be any suitable type of network allowing transport of data communications across thereof. The network 108 may couple devices so that communications may be exchanged, such as between servers and client devices or other types of devices, including between wireless devices coupled via a wireless network, for example; Paragraph 0047, Analytic models engine 204 is configurable to run and execute analytical software and logic using data from the data sources 102 and healthcare manager devices 106. The analytical software and logic may include data mining, machine learning, and “big math” instructions or code to identify cost efficiency and where improvements may be made in quality of care and savings);
extract, to the one or more databases, corporate data comprising a third format, different from the first format and the second format, from the one or more corporate data sources, wherein the corporate data includes corporate specifications (Figure 2, item 104, Data Processing Server; Paragraph 0041, In at least one embodiment, data derived from external data (external parties) may be combined with data from sources internal to an organization such as financial and operations data (internal data) to provide a wide overview of care provided by a plurality of healthcare service networks. Healthcare services include, but are not limited to, services provided by primary care physicians and specialists, acute care such as radiology, out-patient, and inpatient, and post-acute care such as skilled nursing, rehabilitation, and home health; Paragraph 0042, The data from data sources 102 may be in any and in disparate kinds of data formats. Receiving data from data sources 102 may include establishing connections or linking the data processing server 104 with a given account, server, directory, system, interface, etc.; As stated in Paragraphs 0024 & 0124 of Applicant’s specification, corporate specifications may comprise headquarter data. Examiner interprets “information from sources internal to an organization such as type of services provided” as “corporate data”);
transform, (i) based on the corporate specifications, …: the extracted first practice management data to a standardized format to obtain transformed first practice management data; and the extracted second practice management data to a standardized format to obtain transformed second practice management data (Figure 2, item 104, Data Processing Server; Paragraph 0039, Healthcare data can be collected from sources such as healthcare insurance administrations, payer-provider reimbursement contracting, physician healthcare services or providers, and physician billing and reimbursements. The healthcare data can be transformed from raw data into meaningful and useful information for health service managers and administrators who run medical practices and health care facilities; Paragraph 0041, In at least one embodiment, data derived from external data (external parties) may be combined with data from sources internal to an organization such as financial and operations data (internal data) to provide a wide overview of care provided by a plurality of healthcare service networks. Healthcare services include, but are not limited to, services provided by primary care physicians and specialists, acute care such as radiology, out-patient, and inpatient, and post-acute care such as skilled nursing, rehabilitation, and home health; Paragraph 0042, The data from data sources 102 may be in any and in disparate kinds of data formats. Receiving data from data sources 102 may include establishing connections or linking the data processing server 104 with a given account, server, directory, system, interface, etc.);
determine a first performance measure of the first practice being evaluated based on the transformed first practice management data and a second performance measure of the second practice being evaluated based on the transformed second practice management data (Paragraph 0039, The healthcare data can be transformed from raw data into meaningful and useful information for health service managers and administrators who run medical practices and health care facilities; Paragraph 0042, The data from data sources 102 may be in any and in disparate kinds of data formats. Receiving data from data sources 102 may include establishing connections or linking the data processing server 104 with a given account, server, directory, system, interface, etc.); Paragraph 0047, Data may be executed according to cost and quality distribution model instructions to determine how individual physician practices are currently performing and how their performance could be improved in certain areas. A comparison of episodes can be generated as analytic data output from analytic models engine 204 for the purposes of managing care and resources; Paragraph 0056, Prescriptive opportunities may be generated using historical performance data based on data (e.g., current contract rates or prices) retrieved from data aggregator 210 and performance monitor 202. Trends emerging from this data can be used to aid in avoiding mistakes or notice gaps in care that may have gone otherwise unnoticed. Opportunities can be extrapolated from peer performance, physician performance, patient risk, and a number of other factors);
automatically generate, …, (i) a report including the first performance measure and the second performance measure and (ii) metadata associated with the report (Paragraph 0047, Data may be executed according to cost and quality distribution model instructions to determine how individual physician practices are currently performing and how their performance could be improved in certain areas. A comparison of episodes can be generated as analytic data output from analytic models engine 204 for the purposes of managing care and resources; Paragraph 0054, Performance monitor 202 is operable to generate a variety of reports and charts of, for example, contract financial performance, clinical performance, and operational performance. Performance charts can be generated to identify performance vs. goals and identify areas where action should be taken. A summary view of how the organization is performing across all of its risk-based contracts can be tracked by the performance monitor 202. The performance monitor 202 may show complex actuarial forecasts in such a way that the operator can quickly understand whether a particular risk based contract is going to achieve savings or if they will miss them and by how much);
store the report and the metadata in the one or more databases (Paragraph 0042, Data processing server 104 is operable to periodically retrieve or poll data sources 102 to collect data for generating predictive and prescriptive opportunities, and provide advanced analytics for enterprise planning and execution (along with surveillance of current operations) by healthcare manager devices 106; Paragraph 0043, A plurality of data processing server 104 may comprise, a cloud computing resource, a grid computing resource, and/or any other distributed computing arrangement; Paragraph 0054, Performance monitor 202 is operable to generate a variety of reports and charts of, for example, contract financial performance, clinical performance, and operational performance. Performance charts can be generated to identify performance vs. goals and identify areas where action should be taken);
transmit, … and via the gateway layer, the report to the corporate computer system based on a role of a user of the corporate computer system (Figure 1, item 108, Network; Paragraph 0054, Performance monitor 202 is operable to generate a variety of reports and charts of, for example, contract financial performance, clinical performance, and operational performance. Performance charts can be generated to identify performance vs. goals and identify areas where action should be taken. A summary view of how the organization is performing across all of its risk-based contracts can be tracked by the performance monitor 202. The performance monitor 202 may show complex actuarial forecasts in such a way that the operator can quickly understand whether a particular risk based contract is going to achieve savings or if they will miss them and by how much; Paragraph 0055, The analytics data may be transmitted to healthcare manager devices 106 and presented in charts, graphs, visual animations, videos, renderings, spreadsheets or any other file layout or format);
and display, in a user interface of the corporate computer system, the report (Figure 2, item 104, Data Processing Server; Paragraph 0053, Analytic output data generated from analytic models engine 204 may be used by performance monitor 202 to generate data for display of comparisons, distributions, risk, expected costs, and an optimal intersection between cost and quality to healthcare manager devices 106. Analytic models engine 204 further includes advisor logic (not illustrated) that may be presented in a user interface as digital consultants; Paragraph 0054, Performance monitor 202 is operable to generate a variety of reports and charts of, for example, contract financial performance, clinical performance, and operational performance. Performance charts can be generated to identify performance vs. goals and identify areas where action should be taken. A summary view of how the organization is performing across all of its risk-based contracts can be tracked by the performance monitor 202. The performance monitor 202 may show complex actuarial forecasts in such a way that the operator can quickly understand whether a particular risk based contract is going to achieve savings or if they will miss them and by how much).
Although Snow et al. further discloses wherein the system may be implemented via software as a service (Paragraph 0042, SaaS), Snow et al. does not specifically disclose a service orchestration layer in communication with the gateway layer and configured to orchestrate a plurality of microservices (e.g., perform logging, session management, security, load balancing, and data transformation services).
However, LaBorde discloses and perform logging, session management, security, and load balancing for the distributed computer system; and a service orchestration layer in communication with the gateway layer and configured to orchestrate a plurality of microservices, wherein the distributed computer system is configured to execute the instructions of the one or more non-transitory computer-readable storage media in order to: extract, (i) to one or more databases, (ii) through the gateway layer, and (iii) using microservices of the plurality of microservices as orchestrated by the service orchestration layer (Paragraph 0014, The instructions configure the controller to verify the resource request. Particularly, the controller confirms that the certification authority is one of a number of predetermined trusted certification authorities. Once confirmed, a secure communication session between the patient list manager device and the patient list manager client device is established; Paragraph 0020, The patient list manager modules and applications running on server and client devices can be configured as a suite of microservices and applications, each with the responsibility for one or multiple related tasks or functions. The patient list manager device can be deployed utilizing one or a plurality of the following strategies: i) running multiple instances of an the patient list manager devices with a load balancer to distribute inbound requests equitably, ii) running the patient list manager and its modules as independent microservices, each focused on a particular use case or task or each focused on all tasks related to a particular resource or entity, iii) sharing or partitioning data across a set of patient list manager database servers separating or organizing the data based on a characteristic, property or attribute of the data and utilizing a component to route requests to the correct server; Paragraph 0083, The memory 1026, 1046 can be one or a combination of a variety of types of memory such as random access memory (RAM), read only memory (ROM), flash memory, dynamic RAM (DRAM) or the like. Alternatively, as shown in FIG. 1C, the patient list database 102 can be a portion of the patient list device 104. The memory 1026, 1046 includes instructions for the controllers 1024, 1044 to execute processes for providing the patient list manager; Paragraph 0085, It should be noted that in FIGS. 1B-1C, one server was shown merely for ease of illustration. However, as shown in FIG. 1E, the system for providing the patient list manager can include a plurality of servers and databases 170 connected to the network 105 via a load balancer 165; Paragraph 0125, Access to various reporting functionality is managed on a need to have basis; only users with a business or clinical need for certain reporting functions are given such access and the local administrator for the subscription manages this; Paragraph 0152, The data statistics can be updated automatically in the dashboard in real time. The information is as up to date as the information last entered into the patient list manager database. No manual data collection, manipulation or calculations are necessary which eliminates a significant amount of the cost and time lag generating this information typically entails); …
transform, (i) based on the corporate specifications and (ii) using a transformation microservice of the plurality of microservices: the extracted first practice management data to a standardized format to obtain transformed first practice management data; and the extracted second practice management data to the standardized format to obtain transformed second practice management data (Paragraph 0020, The patient list manager modules and applications running on server and client devices can be configured as a suite of microservices and applications, each with the responsibility for one or multiple related tasks or functions. The patient list manager device can be deployed utilizing one or a plurality of the following strategies: i) running multiple instances of an the patient list manager devices with a load balancer to distribute inbound requests equitably, ii) running the patient list manager and its modules as independent microservices, each focused on a particular use case or task or each focused on all tasks related to a particular resource or entity, iii) sharing or partitioning data across a set of patient list manager database servers separating or organizing the data based on a characteristic, property or attribute of the data and utilizing a component to route requests to the correct server; see Figure 1A and related text in Paragraph 0081, The patient list manager is a solution that creates value for physicians and other providers that provide services across the multiple often times un-affiliated facilities 108, 110, 114 in addition to possibly seeing patients in their offices (not shown). The patient list manager helps address the issues resulting from gaps in cross-facility data access and the current inability of physicians and other providers to visualize cross-facility data in one interface from the physician or other providers prospective; Paragraph 0135, In instances when diagnostic imaging studies are successfully delivered on physical media to a point of care, there are also challenges with viewing the images. The file formats are often a specialized type that require specific viewing software not widely available on most computers. For this reason, the images on the physical media are typically packaged with an imaging viewer software. However, there is a highly fragmented market of software vendors that provide these viewers and with significant frequency the physicians or other providers are unfamiliar with the nuances of operating the specific vendor's software and, as a result, viewing the films becomes a time sink, injecting further inefficiencies into an already complicated process. This can be disruptive patient flow bottleneck in a busy clinic. Moreover, some of the imaging viewer software requires local installation and administrative rights to the operating system on the local computer, which is not something the physicians or other providers have in some care settings; Paragraph 0137, user at the client device 3308 has appropriate credentials for accessing the imaging module. Accessing the imaging module can be accessing a website hosted by a server or executing a client specific application stored at the client device. The client device 3308 includes images files 3306 formatted with the DICOM (Digital Imaging and Communications in Medicine) standard from physical media at any point of care. The client device 3308 can securely upload the encrypted imaging files to a memory space (cloud) provided by the PACS servers 3304 wherein the uploaded encrypted images and imaging header information are stored. The imaging module can index the uploaded images and tag them to the corresponding patients in the patient list database 3302; Examiner interprets “formatting the image to a standard format” as the “transformation”);
determine a first performance measure of the first practice being evaluated based on the transformed first practice management data and a second performance measure of the second practice being evaluated based on the transformed second practice management data (Paragraph 0152, Ultimately the data statistics and metrics reported can be used to improve patient outcomes and physician and other provider practice financial performance. Reports might include simple statistics for a subscriber specified date range such as clinical visit type volumes, surgical case types volumes and these respective volumes across facilities, by individual facility, by provider, by service line, etc. More complicated statistics requiring mathematical or algorithmic operations on data captured that are determined to be important can also be generated and output to the dashboard such as wound infection rates, readmission rates, etc. Any statistics and metrics that can be generated leveraging the structured point of care data captured can be output and made visible to subscribers with appropriate credentials in the dashboard in real time. If historical reports with particular statistics and metrics covering certain time periods or comparing certain time periods are desired, these can be generated and viewed in the graphical user interface or populated into a PDF which can be printed if a hard copy is desired. The statistics and metrics help increase the visibility of work flows, outcomes and volumes enabling subscribers to objectively understand and better manage (in real time or near real time) i) what is going on in their practice from a clinical and business operations standpoint, ii) practice and practice member productivity and performance versus targets; and iii) decision making around changes that might be made or implemented in the practice based on data driven impact assessment and key metric tracking and review);
automatically generate, using the microservices of the plurality of microservices, (i) a report including the first performance measure and the second performance measure and (ii) metadata associated with the report (Paragraph 0020, The patient list manager modules and applications running on server and client devices can be configured as a suite of microservices and applications, each with the responsibility for one or multiple related tasks or functions. The patient list manager device can be deployed utilizing one or a plurality of the following strategies: i) running multiple instances of an the patient list manager devices with a load balancer to distribute inbound requests equitably, ii) running the patient list manager and its modules as independent microservices, each focused on a particular use case or task or each focused on all tasks related to a particular resource or entity, iii) sharing or partitioning data across a set of patient list manager database servers separating or organizing the data based on a characteristic, property or attribute of the data and utilizing a component to route requests to the correct server; Paragraph 0152, The data statistics can be updated automatically in the dashboard in real time. The information is as up to date as the information last entered into the patient list manager database. No manual data collection, manipulation or calculations are necessary which eliminates a significant amount of the cost and time lag generating this information typically entails. These metrics can be securely accessed and used by physicians and other clinical providers, managers, executives and other subscribers for business intelligence and clinical intelligence. The data helps these subscribers more efficiently manage the activities and performance of individual, group or hospital owned physician practice and to readily assess their activities across multiple facilities on potentially disparate systems in one interface. Ultimately the data statistics and metrics reported can be used to improve patient outcomes and physician and other provider practice financial performance. Reports might include simple statistics for a subscriber specified date range such as clinical visit type volumes, surgical case types volumes and these respective volumes across facilities, by individual facility, by provider, by service line, etc.);
store the report and the metadata in the one or more databases (Paragraph 0076, In overview, the present disclosure concerns a system for providing a patient data management and reporting platform (referred to here as a patient list manager). In the system, one or more client devices and servers provide secure storage and access of patient data across different facilities; Paragraph 0152, If historical reports with particular statistics and metrics covering certain time periods or comparing certain time periods are desired, these can be generated and viewed in the graphical user interface or populated into a PDF which can be printed if a hard copy is desired. The statistics and metrics help increase the visibility of work flows, outcomes and volumes enabling subscribers to objectively understand and better manage (in real time or near real time) i) what is going on in their practice from a clinical and business operations standpoint, ii) practice and practice member productivity and performance versus targets; and iii) decision making around changes that might be made or implemented in the practice based on data driven impact assessment and key metric tracking and review);
transmit, using microservices of the plurality of microservices and via the gateway layer, the report to the corporate computer system based on a role of a user of the corporate computer system; and display, in a user interface of the corporate computer system, the report (Paragraph 0020, The patient list manager modules and applications running on server and client devices can be configured as a suite of microservices and applications, each with the responsibility for one or multiple related tasks or functions. The patient list manager device can be deployed utilizing one or a plurality of the following strategies: i) running multiple instances of an the patient list manager devices with a load balancer to distribute inbound requests equitably, ii) running the patient list manager and its modules as independent microservices, each focused on a particular use case or task or each focused on all tasks related to a particular resource or entity, iii) sharing or partitioning data across a set of patient list manager database servers separating or organizing the data based on a characteristic, property or attribute of the data and utilizing a component to route requests to the correct server; Paragraph 0125, Access to various reporting functionality is managed on a need to have basis; only users with a business or clinical need for certain reporting functions are given such access and the local administrator for the subscription manages this; Paragraph 0152, The data statistics can be updated automatically in the dashboard in real time. The information is as up to date as the information last entered into the patient list manager database. No manual data collection, manipulation or calculations are necessary which eliminates a significant amount of the cost and time lag generating this information typically entails. These metrics can be securely accessed and used by physicians and other clinical providers, managers, executives and other subscribers for business intelligence and clinical intelligence. The data helps these subscribers more efficiently manage the activities and performance of individual, group or hospital owned physician practice and to readily assess their activities across multiple facilities on potentially disparate systems in one interface. Ultimately the data statistics and metrics reported can be used to improve patient outcomes and physician and other provider practice financial performance. Reports might include simple statistics for a subscriber specified date range such as clinical visit type volumes, surgical case types volumes and these respective volumes across facilities, by individual facility, by provider, by service line, etc. More complicated statistics requiring mathematical or algorithmic operations on data captured that are determined to be important can also be generated and output to the dashboard such as wound infection rates, readmission rates, etc. Any statistics and metrics that can be generated leveraging the structured point of care data captured can be output and made visible to subscribers with appropriate credentials in the dashboard in real time. If historical reports with particular statistics and metrics covering certain time periods or comparing certain time periods are desired, these can be generated and viewed in the graphical user interface or populated into a PDF which can be printed if a hard copy is desired. The statistics and metrics help increase the visibility of work flows, outcomes and volumes enabling subscribers to objectively understand and better manage (in real time or near real time) i) what is going on in their practice from a clinical and business operations standpoint, ii) practice and practice member productivity and performance versus targets; and iii) decision making around changes that might be made or implemented in the practice based on data driven impact assessment and key metric tracking and review).
It would have been obvious to one ordinary skill in the art before the effective filing date to modify the management system used to determine a performance measure of a first practice and a second practice of the invention of Snow et al. to further specify wherein the management system includes a plurality of microservices of the invention of LaBorde because doing so would allow the management system to configure applications running on server as a suite of microservices and applications, each with the responsibility for one or more multiple related tasks or functions (see LaBorde, Paragraph 0020). Further, the claimed invention is merely a combination of old elements, and in combination each element would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Regarding claim 10 (Currently Amended), Snow et al. discloses a method for managing practice data comprising (Paragraph 0015, The present invention provides methods and systems for monitoring and managing healthcare performance):
instantiating a software architecture comprising: a gateway layer configured to: interface with software applications of a distributed computer system including a first practice computer system, a second practice computer system, and a corporate computer system (Paragraph 0039, Healthcare data can be collected from sources such as healthcare insurance administrations, payer-provider reimbursement contracting, physician healthcare services or providers, and physician billing and reimbursements; see Figure 1 and related text in Paragraph 0045, Network 108 may be any suitable type of network allowing transport of data communications across thereof. The network 108 may couple devices so that communications may be exchanged, such as between servers and client devices or other types of devices, including between wireless devices coupled via a wireless network, for example; Paragraph 0047, Analytic models engine 204 is configurable to run and execute analytical software and logic using data from the data sources 102 and healthcare manager devices 106. The analytical software and logic may include data mining, machine learning, and “big math” instructions or code to identify cost efficiency and where improvements may be made in quality of care and savings; Paragraph 0132, In software implementations, computer software (e.g., programs or other instructions) and/or data is stored on a machine readable medium as part of a computer program product, and is loaded into a computer system or other device or machine via a removable storage drive, hard drive, or communications interface. Computer programs (also called computer control logic or computer readable program code) are stored in a main and/or secondary memory, and executed by one or more processors (controllers, or the like) to cause the one or more processors to perform the functions of the invention as described herein); …;
extracting, (i) to the one or more databases, (ii) through the gateway layer, and …, first practice data comprising a first format from the one or more first practice management data sources of a first practice computer system relating to a first practice being evaluated; extracting, to the one or more databases, second practice data comprising a second format different from the first format from one or more second practice management data sources of a second practice computer system relating to a second practice being evaluated (Figure 1, item 108, Network; Paragraph 0039, Healthcare data can be collected from sources such as healthcare insurance administrations, payer-provider reimbursement contracting, physician healthcare services or providers, and physician billing and reimbursements; Paragraph 0042, The data from data sources 102 may be in any and in disparate kinds of data formats. Receiving data from data sources 102 may include establishing connections or linking the data processing server 104 with a given account, server, directory, system, interface, etc.; Paragraph 0045, Network 108 may be any suitable type of network allowing transport of data communications across thereof. The network 108 may couple devices so that communications may be exchanged, such as between servers and client devices or other types of devices, including between wireless devices coupled via a wireless network, for example; Paragraph 0047, Analytic models engine 204 is configurable to run and execute analytical software and logic using data from the data sources 102 and healthcare manager devices 106. The analytical software and logic may include data mining, machine learning, and “big math” instructions or code to identify cost efficiency and where improvements may be made in quality of care and savings);
extracting, to the one or more databases, corporate data comprising a third format different from the first format and the second format, from the one or more corporate data sources of a corporate computer system relating to an aggregator of the first practice and the second practice, wherein the corporate data includes corporate specifications (Figure 2, item 104, Data Processing Server; Paragraph 0041, In at least one embodiment, data derived from external data (external parties) may be combined with data from sources internal to an organization such as financial and operations data (internal data) to provide a wide overview of care provided by a plurality of healthcare service networks. Healthcare services include, but are not limited to, services provided by primary care physicians and specialists, acute care such as radiology, out-patient, and inpatient, and post-acute care such as skilled nursing, rehabilitation, and home health; Paragraph 0042, The data from data sources 102 may be in any and in disparate kinds of data formats. Receiving data from data sources 102 may include establishing connections or linking the data processing server 104 with a given account, server, directory, system, interface, etc.; As stated in Paragraphs 0024 & 0124 of Applicant’s specification, corporate specifications may comprise headquarter data. Examiner interprets “information from sources internal to an organization such as type of services provided” as “corporate data”);
transforming, (i) based on the corporate specifications, …: the extracted first practice management data to a standardized format to obtain transformed first practice management data; and the extracted second practice management data to a standardized format to obtain transformed second practice management data (Figure 2, item 104, Data Processing Server; Paragraph 0039, Healthcare data can be collected from sources such as healthcare insurance administrations, payer-provider reimbursement contracting, physician healthcare services or providers, and physician billing and reimbursements. The healthcare data can be transformed from raw data into meaningful and useful information for health service managers and administrators who run medical practices and health care facilities; Paragraph 0041, In at least one embodiment, data derived from external data (external parties) may be combined with data from sources internal to an organization such as financial and operations data (internal data) to provide a wide overview of care provided by a plurality of healthcare service networks. Healthcare services include, but are not limited to, services provided by primary care physicians and specialists, acute care such as radiology, out-patient, and inpatient, and post-acute care such as skilled nursing, rehabilitation, and home health; Paragraph 0042, The data from data sources 102 may be in any and in disparate kinds of data formats. Receiving data from data sources 102 may include establishing connections or linking the data processing server 104 with a given account, server, directory, system, interface, etc.);
determining a first performance measure of the first practice being evaluated based on the transformed first practice management data and a second performance measure of the second practice being evaluated based on the transformed second practice management data (Paragraph 0039, The healthcare data can be transformed from raw data into meaningful and useful information for health service managers and administrators who run medical practices and health care facilities; Paragraph 0042, The data from data sources 102 may be in any and in disparate kinds of data formats. Receiving data from data sources 102 may include establishing connections or linking the data processing server 104 with a given account, server, directory, system, interface, etc.); Paragraph 0047, Data may be executed according to cost and quality distribution model instructions to determine how individual physician practices are currently performing and how their performance could be improved in certain areas. A comparison of episodes can be generated as analytic data output from analytic models engine 204 for the purposes of managing care and resources; Paragraph 0056, Prescriptive opportunities may be generated using historical performance data based on data (e.g., current contract rates or prices) retrieved from data aggregator 210 and performance monitor 202. Trends emerging from this data can be used to aid in avoiding mistakes or notice gaps in care that may have gone otherwise unnoticed. Opportunities can be extrapolated from peer performance, physician performance, patient risk, and a number of other factors);
automatically generate, …, (i) a report including the first performance measure and the second performance measure and (ii) metadata associated with the report (Paragraph 0047, Data may be executed according to cost and quality distribution model instructions to determine how individual physician practices are currently performing and how their performance could be improved in certain areas. A comparison of episodes can be generated as analytic data output from analytic models engine 204 for the purposes of managing care and resources; Paragraph 0054, Performance monitor 202 is operable to generate a variety of reports and charts of, for example, contract financial performance, clinical performance, and operational performance. Performance charts can be generated to identify performance vs. goals and identify areas where action should be taken. A summary view of how the organization is performing across all of its risk-based contracts can be tracked by the performance monitor 202. The performance monitor 202 may show complex actuarial forecasts in such a way that the operator can quickly understand whether a particular risk based contract is going to achieve savings or if they will miss them and by how much);
storing the report and the metadata in the one or more databases (Paragraph 0042, Data processing server 104 is operable to periodically retrieve or poll data sources 102 to collect data for generating predictive and prescriptive opportunities, and provide advanced analytics for enterprise planning and execution (along with surveillance of current operations) by healthcare manager devices 106; Paragraph 0043, A plurality of data processing server 104 may comprise, a cloud computing resource, a grid computing resource, and/or any other distributed computing arrangement; Paragraph 0054, Performance monitor 202 is operable to generate a variety of reports and charts of, for example, contract financial performance, clinical performance, and operational performance. Performance charts can be generated to identify performance vs. goals and identify areas where action should be taken);
transmitting, … and via the gateway layer, the report to the corporate computer system based on a role of a user of the corporate computer system (Figure 1, item 108, Network; Paragraph 0054, Performance monitor 202 is operable to generate a variety of reports and charts of, for example, contract financial performance, clinical performance, and operational performance. Performance charts can be generated to identify performance vs. goals and identify areas where action should be taken. A summary view of how the organization is performing across all of its risk-based contracts can be tracked by the performance monitor 202. The performance monitor 202 may show complex actuarial forecasts in such a way that the operator can quickly understand whether a particular risk based contract is going to achieve savings or if they will miss them and by how much; Paragraph 0055, The analytics data may be transmitted to healthcare manager devices 106 and presented in charts, graphs, visual animations, videos, renderings, spreadsheets or any other file layout or format);
and displaying, in a user interface of the corporate computer system, the report (Figure 2, item 104, Data Processing Server; Paragraph 0053, Analytic output data generated from analytic models engine 204 may be used by performance monitor 202 to generate data for display of comparisons, distributions, risk, expected costs, and an optimal intersection between cost and quality to healthcare manager devices 106. Analytic models engine 204 further includes advisor logic (not illustrated) that may be presented in a user interface as digital consultants; Paragraph 0054, Performance monitor 202 is operable to generate a variety of reports and charts of, for example, contract financial performance, clinical performance, and operational performance. Performance charts can be generated to identify performance vs. goals and identify areas where action should be taken. A summary view of how the organization is performing across all of its risk-based contracts can be tracked by the performance monitor 202. The performance monitor 202 may show complex actuarial forecasts in such a way that the operator can quickly understand whether a particular risk based contract is going to achieve savings or if they will miss them and by how much).
Although Snow et al. further discloses wherein the system may be implemented via software as a service (Paragraph 0042, SaaS), Snow et al. does not specifically disclose a service orchestration layer in communication with the gateway layer and configured to orchestrate a plurality of microservices (e.g., perform logging, session management, security, load balancing, and data transformation services).
However, LaBorde discloses and perform logging, session management, security, and load balancing for the distributed computer system; and a service orchestration layer in communication with the gateway layer and configured to orchestrate a plurality of microservices (Paragraph 0014, The instructions configure the controller to verify the resource request. Particularly, the controller confirms that the certification authority is one of a number of predetermined trusted certification authorities. Once confirmed, a secure communication session between the patient list manager device and the patient list manager client device is established; Paragraph 0020, The patient list manager modules and applications running on server and client devices can be configured as a suite of microservices and applications, each with the responsibility for one or multiple related tasks or functions. The patient list manager device can be deployed utilizing one or a plurality of the following strategies: i) running multiple instances of an the patient list manager devices with a load balancer to distribute inbound requests equitably, ii) running the patient list manager and its modules as independent microservices, each focused on a particular use case or task or each focused on all tasks related to a particular resource or entity, iii) sharing or partitioning data across a set of patient list manager database servers separating or organizing the data based on a characteristic, property or attribute of the data and utilizing a component to route requests to the correct server; Paragraph 0125, Access to various reporting functionality is managed on a need to have basis; only users with a business or clinical need for certain reporting functions are given such access and the local administrator for the subscription manages this);
extracting, to one or more databases (ii) through the gateway layer, and (iii) using microservices of the plurality of microservices as orchestrated by the service orchestration layer, first practice data comprising a first format from one or more first practice management data sources of a first practice computer system relating to a first practice being evaluated; extracting, to the one or more databases, second practice data comprising a second format different from the first format from one or more second practice management data sources of a second practice computer system relating to a second practice being evaluated; extracting, to the one or more databases, corporate data comprising a third format different from the first format and the second format from one or more corporate data sources of a corporate computer system relating to an aggregator of the first practice and the second practice, wherein corporate data includes corporate specifications (Paragraph 0020, The patient list manager modules and applications running on server and client devices can be configured as a suite of microservices and applications, each with the responsibility for one or multiple related tasks or functions. The patient list manager device can be deployed utilizing one or a plurality of the following strategies: i) running multiple instances of an the patient list manager devices with a load balancer to distribute inbound requests equitably, ii) running the patient list manager and its modules as independent microservices, each focused on a particular use case or task or each focused on all tasks related to a particular resource or entity, iii) sharing or partitioning data across a set of patient list manager database servers separating or organizing the data based on a characteristic, property or attribute of the data and utilizing a component to route requests to the correct server; see Figure 1A and related text in Paragraph 0081, The patient list manager is a solution that creates value for physicians and other providers that provide services across the multiple often times un-affiliated facilities 108, 110, 114 in addition to possibly seeing patients in their offices (not shown). The patient list manager helps address the issues resulting from gaps in cross-facility data access and the current inability of physicians and other providers to visualize cross-facility data in one interface from the physician or other providers prospective; Paragraph 0135, In instances when diagnostic imaging studies are successfully delivered on physical media to a point of care, there are also challenges with viewing the images. The file formats are often a specialized type that require specific viewing software not widely available on most computers. For this reason, the images on the physical media are typically packaged with an imaging viewer software. However, there is a highly fragmented market of software vendors that provide these viewers and with significant frequency the physicians or other providers are unfamiliar with the nuances of operating the specific vendor's software and, as a result, viewing the films becomes a time sink, injecting further inefficiencies into an already complicated process. This can be disruptive patient flow bottleneck in a busy clinic. Moreover, some of the imaging viewer software requires local installation and administrative rights to the operating system on the local computer, which is not something the physicians or other providers have in some care settings; Paragraph 0137, user at the client device 3308 has appropriate credentials for accessing the imaging module. Accessing the imaging module can be accessing a website hosted by a server or executing a client specific application stored at the client device. The client device 3308 includes images files 3306 formatted with the DICOM (Digital Imaging and Communications in Medicine) standard from physical media at any point of care. The client device 3308 can securely upload the encrypted imaging files to a memory space (cloud) provided by the PACS servers 3304 wherein the uploaded encrypted images and imaging header information are stored. The imaging module can index the uploaded images and tag them to the corresponding patients in the patient list database 3302);
transforming, (i) based on the corporate specifications and (ii) using a transformation microservice of the plurality of microservices: the extracted first practice management data to a standardized format to obtain transformed first practice management data; and the extracted second practice management data to the standardized format to obtain transformed second practice management data (Paragraph 0020, The patient list manager modules and applications running on server and client devices can be configured as a suite of microservices and applications, each with the responsibility for one or multiple related tasks or functions. The patient list manager device can be deployed utilizing one or a plurality of the following strategies: i) running multiple instances of an the patient list manager devices with a load balancer to distribute inbound requests equitably, ii) running the patient list manager and its modules as independent microservices, each focused on a particular use case or task or each focused on all tasks related to a particular resource or entity, iii) sharing or partitioning data across a set of patient list manager database servers separating or organizing the data based on a characteristic, property or attribute of the data and utilizing a component to route requests to the correct server; see Figure 1A and related text in Paragraph 0081, The patient list manager is a solution that creates value for physicians and other providers that provide services across the multiple often times un-affiliated facilities 108, 110, 114 in addition to possibly seeing patients in their offices (not shown). The patient list manager helps address the issues resulting from gaps in cross-facility data access and the current inability of physicians and other providers to visualize cross-facility data in one interface from the physician or other providers prospective; Paragraph 0135, In instances when diagnostic imaging studies are successfully delivered on physical media to a point of care, there are also challenges with viewing the images. The file formats are often a specialized type that require specific viewing software not widely available on most computers. For this reason, the images on the physical media are typically packaged with an imaging viewer software. However, there is a highly fragmented market of software vendors that provide these viewers and with significant frequency the physicians or other providers are unfamiliar with the nuances of operating the specific vendor's software and, as a result, viewing the films becomes a time sink, injecting further inefficiencies into an already complicated process. This can be disruptive patient flow bottleneck in a busy clinic. Moreover, some of the imaging viewer software requires local installation and administrative rights to the operating system on the local computer, which is not something the physicians or other providers have in some care settings; Paragraph 0137, user at the client device 3308 has appropriate credentials for accessing the imaging module. Accessing the imaging module can be accessing a website hosted by a server or executing a client specific application stored at the client device. The client device 3308 includes images files 3306 formatted with the DICOM (Digital Imaging and Communications in Medicine) standard from physical media at any point of care. The client device 3308 can securely upload the encrypted imaging files to a memory space (cloud) provided by the PACS servers 3304 wherein the uploaded encrypted images and imaging header information are stored. The imaging module can index the uploaded images and tag them to the corresponding patients in the patient list database 3302; Examiner interprets “formatting the image to a standard format” as the “transformation”);
determining a first performance measure of the first practice being evaluated based on the transformed first practice management data and a second performance measure of the second practice being evaluated based on the transformed second practice management data (Paragraph 0152, Ultimately the data statistics and metrics reported can be used to improve patient outcomes and physician and other provider practice financial performance. Reports might include simple statistics for a subscriber specified date range such as clinical visit type volumes, surgical case types volumes and these respective volumes across facilities, by individual facility, by provider, by service line, etc. More complicated statistics requiring mathematical or algorithmic operations on data captured that are determined to be important can also be generated and output to the dashboard such as wound infection rates, readmission rates, etc. Any statistics and metrics that can be generated leveraging the structured point of care data captured can be output and made visible to subscribers with appropriate credentials in the dashboard in real time. If historical reports with particular statistics and metrics covering certain time periods or comparing certain time periods are desired, these can be generated and viewed in the graphical user interface or populated into a PDF which can be printed if a hard copy is desired. The statistics and metrics help increase the visibility of work flows, outcomes and volumes enabling subscribers to objectively understand and better manage (in real time or near real time) i) what is going on in their practice from a clinical and business operations standpoint, ii) practice and practice member productivity and performance versus targets; and iii) decision making around changes that might be made or implemented in the practice based on data driven impact assessment and key metric tracking and review);
automatically generate, using the microservices of the plurality of microservices, (i) a report including the first performance measure and the second performance measure and (ii) metadata associated with the report (Paragraph 0020, The patient list manager modules and applications running on server and client devices can be configured as a suite of microservices and applications, each with the responsibility for one or multiple related tasks or functions. The patient list manager device can be deployed utilizing one or a plurality of the following strategies: i) running multiple instances of an the patient list manager devices with a load balancer to distribute inbound requests equitably, ii) running the patient list manager and its modules as independent microservices, each focused on a particular use case or task or each focused on all tasks related to a particular resource or entity, iii) sharing or partitioning data across a set of patient list manager database servers separating or organizing the data based on a characteristic, property or attribute of the data and utilizing a component to route requests to the correct server; Paragraph 0152, The data statistics can be updated automatically in the dashboard in real time. The information is as up to date as the information last entered into the patient list manager database. No manual data collection, manipulation or calculations are necessary which eliminates a significant amount of the cost and time lag generating this information typically entails. These metrics can be securely accessed and used by physicians and other clinical providers, managers, executives and other subscribers for business intelligence and clinical intelligence. The data helps these subscribers more efficiently manage the activities and performance of individual, group or hospital owned physician practice and to readily assess their activities across multiple facilities on potentially disparate systems in one interface. Ultimately the data statistics and metrics reported can be used to improve patient outcomes and physician and other provider practice financial performance. Reports might include simple statistics for a subscriber specified date range such as clinical visit type volumes, surgical case types volumes and these respective volumes across facilities, by individual facility, by provider, by service line, etc.);
storing the report and the metadata in the one or more databases (Paragraph 0076, In overview, the present disclosure concerns a system for providing a patient data management and reporting platform (referred to here as a patient list manager). In the system, one or more client devices and servers provide secure storage and access of patient data across different facilities; Paragraph 0152, If historical reports with particular statistics and metrics covering certain time periods or comparing certain time periods are desired, these can be generated and viewed in the graphical user interface or populated into a PDF which can be printed if a hard copy is desired. The statistics and metrics help increase the visibility of work flows, outcomes and volumes enabling subscribers to objectively understand and better manage (in real time or near real time) i) what is going on in their practice from a clinical and business operations standpoint, ii) practice and practice member productivity and performance versus targets; and iii) decision making around changes that might be made or implemented in the practice based on data driven impact assessment and key metric tracking and review);
transmitting, using microservices of the plurality of microservices and via the gateway layer, the report to the corporate computer system based on a role of a user of the corporate computer system; and display, in a user interface of the corporate computer system, the report (Paragraph 0020, The patient list manager modules and applications running on server and client devices can be configured as a suite of microservices and applications, each with the responsibility for one or multiple related tasks or functions. The patient list manager device can be deployed utilizing one or a plurality of the following strategies: i) running multiple instances of an the patient list manager devices with a load balancer to distribute inbound requests equitably, ii) running the patient list manager and its modules as independent microservices, each focused on a particular use case or task or each focused on all tasks related to a particular resource or entity, iii) sharing or partitioning data across a set of patient list manager database servers separating or organizing the data based on a characteristic, property or attribute of the data and utilizing a component to route requests to the correct server; Paragraph 0125, Access to various reporting functionality is managed on a need to have basis; only users with a business or clinical need for certain reporting functions are given such access and the local administrator for the subscription manages this; Paragraph 0152, The data statistics can be updated automatically in the dashboard in real time. The information is as up to date as the information last entered into the patient list manager database. No manual data collection, manipulation or calculations are necessary which eliminates a significant amount of the cost and time lag generating this information typically entails. These metrics can be securely accessed and used by physicians and other clinical providers, managers, executives and other subscribers for business intelligence and clinical intelligence. The data helps these subscribers more efficiently manage the activities and performance of individual, group or hospital owned physician practice and to readily assess their activities across multiple facilities on potentially disparate systems in one interface. Ultimately the data statistics and metrics reported can be used to improve patient outcomes and physician and other provider practice financial performance. Reports might include simple statistics for a subscriber specified date range such as clinical visit type volumes, surgical case types volumes and these respective volumes across facilities, by individual facility, by provider, by service line, etc. More complicated statistics requiring mathematical or algorithmic operations on data captured that are determined to be important can also be generated and output to the dashboard such as wound infection rates, readmission rates, etc. Any statistics and metrics that can be generated leveraging the structured point of care data captured can be output and made visible to subscribers with appropriate credentials in the dashboard in real time. If historical reports with particular statistics and metrics covering certain time periods or comparing certain time periods are desired, these can be generated and viewed in the graphical user interface or populated into a PDF which can be printed if a hard copy is desired. The statistics and metrics help increase the visibility of work flows, outcomes and volumes enabling subscribers to objectively understand and better manage (in real time or near real time) i) what is going on in their practice from a clinical and business operations standpoint, ii) practice and practice member productivity and performance versus targets; and iii) decision making around changes that might be made or implemented in the practice based on data driven impact assessment and key metric tracking and review).
It would have been obvious to one ordinary skill in the art before the effective filing date to modify the management system used to determine a performance measure of a first practice and a second practice of the invention of Snow et al. to further specify wherein the management system includes a plurality of microservices of the invention of LaBorde because doing so would allow the management system to configure applications running on server as a suite of microservices and applications, each with the responsibility for one or more multiple related tasks or functions (see LaBorde, Paragraph 0020). Further, the claimed invention is merely a combination of old elements, and in combination each element would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Regarding claims 2 and 11 (Original), which are dependent of claims 1 and 10, the combination of Snow et al. and LaBorde discloses all the limitations in claims 1 and 10. Snow et al. further discloses wherein the corporate specifications comprise one or more of a group including target data, benchmark data, headquarter data, and reference data (Figure 2, item 104, Data Processing Server; Paragraph 0041, In at least one embodiment, data derived from external data (external parties) may be combined with data from sources internal to an organization such as financial and operations data (internal data) to provide a wide overview of care provided by a plurality of healthcare service networks. Healthcare services include, but are not limited to, services provided by primary care physicians and specialists, acute care such as radiology, out-patient, and inpatient, and post-acute care such as skilled nursing, rehabilitation, and home health; As stated in Paragraphs 0024 & 0124 of Applicant’s specification, corporate specifications may comprise headquarter data. Examiner interprets “information from sources internal to an organization such as type of services provided” as “corporate data”).
Regarding claims 3 and 12 (Previously Presented), which are dependent of claims 1 and 10, the combination of Snow et al. and LaBorde discloses all the limitations in claims 1 and 10. Snow et al. further discloses wherein the one or more first practice management data sources relating to the first practice being evaluated comprise one or more of a group including: financial information; human resource information; patient information; medical information; operation information; client communications; review analysis; and inventory information (Paragraph 0046, Data aggregator 210 is operable to extract healthcare data such as health service transactions, patient medical data, physician data, health plan data, provider contract data, lab data, pharmacy data, market trend data, reference data, payment data, and reimbursement data from data sources 102 and/or healthcare manger devices 106 for identifying care events (e.g., treatments, visits and procedures of patients); Paragraph 0075, he healthcare data may include data such as patient conditions, paid claims, and associated treatment information; It can be noted that the claim language is written in alternative form. The limitation taught by Snow et al. is based on “financial information,” “patient information,” and “medical information”).
Regarding claims 4 and 13 (Previously Presented), which are dependent of claims 1 and 10, the combination of Snow et al. and LaBorde discloses all the limitations in claims 1 and 10. Snow et al. further discloses wherein extracting the first practice data comprises mapping the first practice management data into at least one normalized data set (Paragraph 0042, The data from data sources 102 may be in any and in disparate kinds of data formats. Receiving data from data sources 102 may include establishing connections or linking the data processing server 104 with a given account, server, directory, system, interface, etc.; Paragraph 0060, FIG. 3 presents a component diagram of a computing system according to an embodiment of the present invention. Data aggregator 210 includes a normalization processor 304 and a de-identification module 306. De-identification module 306 is operable to retrieve healthcare data from healthcare data store 302 and remove identification information from the healthcare data to safeguard sensitive information and keep the data confidential. Normalization processor 304 may then normalized the data for differences among patients by factors such as age, race, location, weight and gender).
Regarding claims 5 and 14 (Previously Presented), which are dependent of claims 4 and 13, the combination of Snow et al. and LaBorde discloses all the limitations in claims 4 and 13. Snow et al. further discloses wherein the mapping of the first practice data into the at least one normalized data set includes using a general ledger, and the general ledger includes categories having at least one of a group including: revenue, cost of goods sold, cost of services, cost of goods service by position, operating expense, gross profit, earnings before interest, taxes, depreciation and amortization (EBITDA), net income, and ownership (Paragraph 0042, Data from the data sources 102 may include electronic medical records, paid claims data, general ledger data, beneficiary data, drug data, lab data, admission, discharge and transfer data, etc. The data from data sources 102 may be in any and in disparate kinds of data formats. Receiving data from data sources 102 may include establishing connections or linking the data processing server 104 with a given account, server, directory, system, interface, etc.; Paragraph 0047, he analytical software and logic may include data mining, machine learning, and “big math” instructions or code to identify cost efficiency and where improvements may be made in quality of care and savings. For example, data may be executed according to cost and quality distribution model instructions to determine how individual physician practices are currently performing and how their performance could be improved in certain areas; It can be noted that the claim language is written in alternative form. The limitation taught by Snow et al. is based on “cost of services”).
Regarding claims 6 and 15 (Previously Presented), which are dependent of claims 1 and 10, the combination of Snow et al. and LaBorde discloses all the limitations in claims 1 and 10. Snow et al. further discloses wherein the first performance measure of the first practice being evaluated comprises at least one of a group including root cause, plan information, and progress toward a target (Paragraph 0052, The prescriptive opportunity manager 206 may analyze the variations (especially outliers or variations outside of a specific standard deviation) from the analytic models engine 204 to determine corrective actions to minimize the variations. Corrective actions may be activities that can be pursued to achieve or improve certain variables such as savings or quality of care. Prescriptive opportunity manager 206 is able to recommend prescriptive opportunities for improving variables such as quality and cost by recommending actions such as terminating physicians, employing fewer and lesser expensive procedures, diagnostics, and medicine, and cease or avoid referring to certain physicians; It can be noted that the claim language is written in alternative form. The limitation taught by Snow et al. is based on “plan information.” Examiner interprets “corrective actions” as the “plan information”).
Regarding claims 7 and 16 (Previously Presented), which are dependent of claims 6 and 15, the combination of Snow et al. and LaBorde discloses all the limitations in claims 6 and 15. Snow et al. further discloses wherein the distributed computer system is further configured to generate a report including the first performance measure (Paragraph 0040, Historical, current and predictive views of business operations may be generated by reporting, online analytical processing, analytics, data mining, process mining, complex event processing, business performance management, benchmarking, text mining, predictive analytics and prescriptive analytics; Paragraph 0054, Performance monitor 202 is operable to generate a variety of reports and charts of, for example, contract financial performance, clinical performance, and operational performance).
Regarding claims 9 and 18 (Previously Presented), which are dependent of claims 7 and 16, the combination of Snow et al. and LaBorde discloses all the limitations in claims 7 and 16. Snow et al. further discloses wherein the report comprises at least one of a group including a chart, a plot, and a table (Paragraph 0054, Performance monitor 202 is operable to generate a variety of reports and charts of, for example, contract financial performance, clinical performance, and operational performance; It can be noted that the claim language is written in alternative form. The limitation taught by Snow et al. is based on a chart).
Claims 19 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Snow et al. (US 2017/0169173 A1), in view of LaBorde (US 2015/0169827 A1), in further view of Hampapur et al. (US 2022/0391815 A1).
Regarding claims 19 and 20 (Previously Presented), which are dependent of claims 1 and 10, the combination of Snow et al. and LaBorde discloses all the limitations in claims 1 and 10. Snow et al. further discloses wherein the corporate data sources comprise applications relating to at least one of a group including: a human resources information system; a payroll service; an accounts receivable service; an accounts payable service; a budgeting service; an attendance tracking service; a scheduling service; a talent acquisition service; a customer relationship management platform; an enterprise resource planning platform; a customer review platform; and an employee engagement review platform (Paragraph 0042, The data from data sources 102 may be in any and in disparate kinds of data formats. Receiving data from data sources 102 may include establishing connections or linking the data processing server 104 with a given account, server, directory, system, interface, etc.).
Although Snow et al. discloses to receive corporate data from multiple data sources (Paragraph 0042), the combination of Snow et al. and LaBorde does not specifically disclose wherein the corporate data sources comprise applications relating to at least one of a group including: a human resources information system; a payroll service; an accounts receivable service; an accounts payable service; a budgeting service; an attendance tracking service; a scheduling service; a talent acquisition service; a customer relationship management platform; an enterprise resource planning platform; a customer review platform; and an employee engagement review platform.
However, Hampapur et al. discloses wherein the corporate data sources comprise applications relating to at least one of a group including: a human resources information system; a payroll service; an accounts receivable service; an accounts payable service; a budgeting service; an attendance tracking service; a scheduling service; a talent acquisition service; a customer relationship management platform; an enterprise resource planning platform; a customer review platform; and an employee engagement review platform (Paragraph 0029, FIG. 2 shows an environment 200 including data sources 202, an integrated system 204, and user interfaces 206. The data sources 202 may store information from multiple sources. For example, when the enterprise 102 represents the hospital ecosystem, the data sources 202 may include data or information related to a hospital information system (HIS), an enterprise resource planning (ERP) system, a financial management system, etc.; Paragraph 0038, The data associated with the ERP system may include information associated with services or functions, such as a human resources planning, a customer relationship management, a project management, a supply chain management, finance, etc. The data associated with the financial management system may include information associated with the financial transactions, a department wise revenue, a pricing information associated with the medical procedures, pricing/spend data, a hospital financial structure and models, and a revenue generated representing financial information of the enterprise 102; It can be noted that the claim language is written in alternative form. The limitation taught by Hampapur et al. is based on at least: an enterprise resource planning platform; a human resources information system; an enterprise resource planning system).
It would have been obvious to one ordinary skill in the art before the effective filing date to modify the management system used to determine a performance measure of a first practice and a second practice based on one or more corporate data sources of the invention of Snow et al. to further specify wherein the corporate data sources comprise applications relating to at least a human resources information system of the invention of Hampapur et al. because doing so would allow the system to use an integrated system to store data from multiple sources including an enterprise resource planning system (see Hampapur et al., Paragraph 0029). Further, the claimed invention is merely a combination of old elements, and in combination each element would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure.
Park Eun Cheol et al. (KR 2021/0070572 A) – discloses a hospital management information system (MIS), or may receive various types of information and data required for cost analysis for each medical action from the hospital management information system and build and store it as a database. The database 110 may store the aggregated cost for each cost center. Here, the cost center refers to the smallest unit organization in which costs are accumulated, and may vary depending on hospitals and the like. 2 shows a plurality of cost center points, such as an outpatient clinic, a hospital room, a laboratory, an operating room, a medical department, and a medical material room (see at least Page 3).
Neelakandan et al. (US 2022/0327634 A1) – discloses methods and systems for generating relevant attribute data for benchmark comparison, based on geospatial boundaries. According to certain embodiments, based on a geospatial-based query using the coordinates of a company, a first group of companies is found within a first radius of the company. The first group of companies is further queried based on a financial metric within a range of the same metric of the company. If the query results in a statistically significant number of companies in the first group of companies, financial attributes of each of the first group of companies are aggregated to develop a benchmark (see at least Paragraph 0007).
Evans (US 2013/0054260 A1) - discloses in a general ledger system, costs and expenses are recorded by the department or area in which they are incurred. Since products and services provided are typically Supported by multiple departments or areas, the costs recorded on the general ledger for any particular department will therefore only represent a portion of the total costs for any particular product or service. This phenomenon is particularly true in health care, as a patient will likely receive services from many different departments during the patient’s treatment (see at least Paragraph 0010).
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/MARJORIE PUJOLS-CRUZ/Examiner, Art Unit 3624
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