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 .
DETAILED ACTION
Status of the Application
Claims 25-44 are currently pending in this case and have been examined and addressed below. This communication is a Final Rejection in response to the Amendment to the Claims and Remarks filed on 06/01/2026.
Claims 25-26, 28-30, 32, 34, 36-37, and 43-44 are currently amended.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
Claims 25-44 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
The term “long-term” in claim 25 is a relative term which renders the claim indefinite. The term “long-term” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. For purposes of examination, Examiner will interpret long-term as it refers to long-term management of patients to be management of patients that is more than one single interaction.
As per Claims 26-44, the claims depend on Claim 25 and do not remedy the indefiniteness issues of Claim 25. As dependent claims inherit the deficiencies of the claims they depend on, they are also rejected.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 25-44 are rejected because the claimed invention is directed to an abstract idea without significantly more.
Step 1
Claims 25-42 fall within the statutory category of a process. Claim 43 falls within the statutory category of an apparatus or system. Claim 44 falls within the statutory category of an article of manufacture as a computer-readable medium.
Step 2A, Prong One
As per Claim 25, the limitations selecting a type of long-term patient management; for each of a plurality of the procedures in the computerized structured guideline: matching entries in the retrospective longitudinal patient-record data to the procedure; determining according to the corresponding compliance-score calculation type, a numeric procedure compliance score based on a level of execution of the procedure and a temporal pattern of execution of the procedure, wherein the numeric procedure compliance score represents full compliance, partial compliance, or non-compliance with the procedure; wherein, for at least one procedure having a time constraint or a cyclical constraint, the numeric procedure compliance score is determined based on an execution time of the procedure or an inter-execution gap between repeated executions of the procedure; calculating a guideline adherence score by aggregating the numeric procedure compliance scores according to weights assigned to one or more stages, procedures, or components/actions of the computerized structured guideline; and generating a digital quality assessment output assessing the quality of long-term management of the patients based on the guideline adherence score, under its broadest reasonable interpretation, covers performance of the limitation in the mind. The steps of a type of long-term patient management, matching entries in the patient record to the procedure, determining a numeric procedure compliance score, determining the numeric procedure compliance score based on execution time or gap between repeated executions of the procedure, calculating a guidance adherence score by aggregating compliance scores, and generating a digital quality assessment output are concepts performed including observation, evaluation, judgement and opinion in the human mind. If a claim limitation, under its broadest reasonable interpretation, covers the performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claims recite an abstract idea.
Step 2A, Prong Two
The judicial exception is not integrated into a practical application because the additional elements and combination of additional elements do not impose meaningful limits on the judicial exception. In particular, Claim 25 recites the additional element – one or more processors. The processor in these steps is recited at a high-level of generality, such that it amounts to no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claims also recites the additional elements of retrieving, from a patient-record database, retrospective longitudinal patient-record data for a plurality of patients managed at the health care facility during a selected assessment time period and retrieving, from a knowledge base, a corresponding computerized structured guideline comprising a formal machine-interpretable representation of a plurality of procedures for the selected type of long-term patient management, wherein the computerized structured guideline defines, for respective procedures of the plurality of procedures, a type or characteristic of the procedure, including a constraint category, and a corresponding compliance-score calculation type, which amounts to insignificant extra-solution activity, as in MPEP 2106.05(g), because the steps of retrieving a longitudinal patient-record data and retrieving a structured guideline are mere data gathering in conjunction with the abstract idea where the limitation amounts to necessary data gathering and outputting, (i.e., all uses of the recited judicial exception require such data gathering or data output). See Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015) (presenting offers and gathering statistics amounted to mere data gathering). The claims describe the computerized structured guidelines which is retrieved from memory as defining a type or characteristic of the procedure, including a constraint category and a corresponding compliance score calculation type. This is merely descriptive of the data which is retrieved from memory. Because the additional elements do not impose meaningful limitations on the judicial exception, the claim is directed to an abstract idea.
Step 2B
Claim 25 does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements when considered both individually and as an ordered combination do not amount to significantly more than the abstract idea. As discussed above with the respect to integration of the abstract idea into a practical application, the additional element of a processor to perform the method of the invention amounts to no more than mere instructions to apply the exception using a generic computing component. The system including the "processor” are recited at a high level of generality and are recited as generic computer components by describing the processor as part of a general-purpose computer (Specification, Page 25, Lines 3-5), which do not add meaningful limitations to the abstract idea beyond mere instructions to apply an exception. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claims also include the additional elements of retrieving, from a patient-record database, retrospective longitudinal patient-record data for a plurality of patients managed at the health care facility during a selected assessment time period and retrieving, from a knowledge base, a corresponding computerized structured guideline comprising a formal machine-interpretable representation of a plurality of procedures for the selected type of long-term patient management, wherein the computerized structured guideline defines, for respective procedures of the plurality of procedures, a type or characteristic of the procedure, including a constraint category, and a corresponding compliance-score calculation type, which are both elements that are well-understood, routine and conventional computer functions in the field of data management because they are claimed at a high level of generality and include receiving or transmitting data as well as storing and retrieving information from memory, which have been found to be well-understood, routine and conventional computer functions by the Court (MPEP 2106.05(d)(II)(i) Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014) ("Unlike the claims in Ultramercial, the claims at issue here specify how interactions with the Internet are manipulated to yield a desired result‐‐a result that overrides the routine and conventional sequence of events ordinarily triggered by the click of a hyperlink." (emphasis added) and (iv) Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of the computer or improves another technology. The claims do not amount to significantly more than the underlying abstract idea.
Dependent Claims
Dependent Claims 26-44 add further limitations which are also directed to an abstract idea. Claims 26-28, 31-36, and 41 further specify or limit the elements of the independent claim and are therefore directed to the same abstract idea. Claim 29 includes applying temporal fuzzy logic membership function that maps execution time or inter-execution gap to a partial compliance value between full and zero compliance. As per MPEP 2106.05(f), applying a mathematical algorithm to the abstract idea amounts to mere instructions to apply the exception which does not integrate the abstract idea into a practical application or provide significantly more than the abstract idea. Claim 30 includes multiplying respective numeric procedure compliance scores by respective procedure weights, which recites mathematical equations/calculations which falls into the abstract grouping of Mental Processes. Claims 37 and 38 include displaying guideline adherence score, procedure compliance score, component/action sub-score, or stage sub-score on a graphical user interface and displaying parameters which amounts to mere data outputting. This amounts to insignificant extra-solution activity as mere data outputting which is well-understood, routine, and conventional similar to presenting offers, as per MPEP 2106.05(d)(II). The graphical user interface is recited at a high-level of generality such that it amounts to mere instructions to apply the exception. Claims 39 and 40 include allowing a user to select presenting information to a user which is an interaction between people and therefore falls into the abstract grouping of certain methods of organizing human activity. Claim 42 includes providing a recommendation to a health care provider which is activity routinely performed in the care of a patient by a healthcare provider and therefore this is managing personal behavior which amounts to certain methods of organizing human activity. Claim 43 includes a system comprising a patient-record database storing records data, a knowledge base storing structured guidelines, and processors to execute the abstract idea of the invention. The database and knowledge base are recited at a high-level of generality and used for their ordinary purpose of storing data which amounts to mere instructions to apply the exception, as per MPEP 2106.05(f)(2). The processor is recited at a high-level of generality as a general purpose computer which executes the abstract idea, such that it amounts to mere instructions to apply the exception. Claim 44 includes a non-transitory computer-readable medium storing processor executable instructions on a computing device which execute the abstract idea of the invention. The computer-readable medium is recited at a high-level of generality as a general purpose computer component which executes the abstract idea, such that it amounts to mere instructions to apply the exception. Because the additional elements do not impose meaningful limitations on the judicial exception and the additional elements are well-understood, routine and conventional functionalities in the art, the claims are directed to an abstract idea and are not patent eligible.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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 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 25-28 and 30-44 are rejected under 35 U.S.C. 103 as being unpatentable over Gaines et al. (US 2013/0275149 A1), hereinafter Gaines, in view of White et al. (US 2020/0342969 A1), hereinafter White, in view of Gandy et al. (US 2018/0113985 A1), hereinafter Gandy.
As per Claim 25, Gaines discloses a computerized method, executed by one or more processors ([0012] method executed by a processor or computer system), for assessing quality of long-term management of patients at a health care facility (Abstract evaluate quality of care of patients), the method comprising:
retrieving, from a patient-record database, retrospective longitudinal patient-record data for a plurality of patients managed at the health care facility during a selected assessment time period ([0017] data sources include data storage in the form of electronic medical systems/EMRs; see Fig. 12, Receive EMRs; [0027] EMRs collected over a period of time, i.e. longitudinal record, from multiple entities; [0047] EMRS are received from data sources);
selecting a type of long-term patient management and retrieving from a knowledge base, a corresponding computerized structured guideline (see Fig. 3 where protocols are displayed for the selected sepsis management, where sepsis comprises plurality of events, [0018] protocols include treatment guidelines for various conditions, [0023-0024] map a protocol for sepsis (selected condition) which includes plurality of steps, [0030] process map for a protocol is selected); and
generating, by the one or more processors, a digital quality-assessment output (see Fig. 8-11/[0038] where the display generates a digital output of the quality-assessment, reports generated for metrics for the protocol which include the compliance for the sepsis protocol) assessing the quality of long-term management of the patients based on the guideline adherence score (Abstract/[0011] metrics are determined to evaluate quality of care and compliance with the protocols for treating conditions, [0023] monitor quality of care provided to patients for a protocol for treating a medical condition, [0034] where the metric is a compliance rate which indicates the adherence to compliance with the protocol, [0045] metrics determined to measure the quality of care associated with a protocol).
However, Gaines may not explicitly disclose the following which is taught by White: patient management is a type of long-term patient management ([0041] the patient management for which compliance is calculated is from triggering event such as an injury until resolution; Examiner interprets this to be management over a period of time which reads on long-term management);
computerized structured guideline comprising a formal machine-interpretable representation of a plurality of procedures for the selected type of long-term patient management ([0045-0046] EBM guidelines are used for developing patient management and include guidelines for each diagnosis or injury which requires long-term management which are codified, i.e. in machine-interpretable representations; [0048] guidelines are mapped to the billing codes);
wherein the computerized structured guideline defines, for respective procedures of the plurality of procedures, a type or characteristic of the procedure, including a constraint category, and a corresponding compliance-score calculation type ([0038] the treatment table, i.e. guideline definitions for all the procedures, includes types of treatments that relate to each diagnosis, [0039] compliance score table includes threshold at which remedial action is triggered for a particular injury/disease (Examiner interprets this to be a constraint to the guidelines), and patient table includes the compliance score calculation based on diagnosis and treatments, i.e. calculation type);
for each of a plurality of the procedures in the computerized structured guideline: matching entries in the retrospective longitudinal patient- record data to the procedure ([0025] map the evidence-based guidelines to the medical billing records, i.e. patient-record data to the procedure); and
determining, according to the corresponding compliance-score calculation type, a numeric procedure compliance score based on a level of execution of the procedure and a temporal pattern of execution of the procedure ([0040] EBM guideline tables include the parameters of treatment such as time of treatment, frequency of services to be provided based on injury, this information is used to calculate compliance score; [0059-0051] compliance score based on execution of the treatment plan/selected procedure, where the score can be numeric based on a 1 to 100 range or a one to ten range, etc.), wherein the numeric procedure compliance score represents full compliance, partial compliance, or non-compliance with the procedure ([0036] compliance score on a range of zero to one with zero being non-compliant and one being full compliance, Examiner notes that all values in between would therefore be a partial compliance in the ratio of the numerical value);
wherein, for at least one procedure having a time constraint or a cyclical constraint, the numeric procedure compliance score is determined based on an execution time of the procedure or an inter-execution gap between repeated executions of the procedure ([0040] EBM guideline tables include the parameters of treatment such as time of treatment, frequency of services to be provided based on injury, this information is used to calculate compliance score).
Therefore, it would have been obvious to a person of ordinary skill in the art before the filing of the present application to combine the known concept of computerized structured guidelines including constraints used to calculate a compliance score from White with the known treatment protocol guidelines from Gaines in order to improve medical management strategies to improve health care outcomes in the setting of complex data and rules (White [0002]).
However, Gaines and White may not explicitly disclose the following which is taught by Gandy: calculating a guideline adherence score by aggregating the numeric procedure compliance scores according to weights assigned to one or more stages, procedures, or components/actions of the computerized structured guideline ([0028] PALM score is the a compliance score for a medical treatment plan made up of several components based on compliance with different components or actions such as medications, labs, etc., [0052] overall PALM score is the sum of the components of the score, where each component is has a different weighting factor).
Therefore, it would have been obvious to a person of ordinary skill in the art before the filing of the present application to combine the known concept of aggregating component compliance scores to determine a total compliance score from Gandy with the known treatment protocol guidelines and compliance score from Gaines and White in order to improve a patient’s non-adherence to medical treatment plans by providing detailed feedback to the patient regarding their adherence (Gandy [0004]).
As per Claim 26, Gaines, White, and Gandy discloses the method of Claim 25. Gaines also teaches the constraint category comprises one or more of a binary constraint, a cyclical constraint, a time constraint, an entry-condition constraint, an order constraint, a multiple-condition constraint, or a combination thereof ([0040] EBM guideline tables include the parameters of treatment such as time of treatment, frequency of services to be provided based on injury, this information is used to calculate compliance score).
Therefore, it would have been obvious to a person of ordinary skill in the art before the filing of the present application to combine the known concept of computerized structured guidelines including constraints used to calculate a compliance score from White with the known treatment protocol guidelines from Gaines in order to improve medical management strategies to improve health care outcomes in the setting of complex data and rules (White [0002]).
As per Claim 27, Gaines, White, and Gandy discloses the method of Claim 26. Gaines also teaches the characteristics of a procedure comprise: binary constraint, cyclical (periodic) constraint, time constraint, entry- condition constraint, order constraint, multiple constraints, or any combinations thereof ([0026] steps of the protocol include attributes which include event time such as how often an event is required to occur, such as every four hours, can also include an event type such as a physician order, also can include a time attribute/constraint, [0052] procedure includes events such as a binary constraint including checking for respiratory distress, or a cyclical constraint including performing a lactic acid test every four hours, and time constraints based on what time particular events occur in the workflow of the guideline/protocol).
As per Claim 28, Gaines, White, and Gandy discloses the method of Claim 25. Gaines also teaches the corresponding compliance score calculation type comprises one or more of : binary calculation, proportional calculation, temporal fuzzy logic calculation, or any combinations thereof ([0034] compliance metric is calculated as a percentage, i.e. proportional calculation, Examiner notes that only one of the above options is required by the claim).
As per Claim 30, Gaines, White, and Gandy discloses the method of Claim 25. Gaines may not explicitly disclose the following which is taught by Gandy: the weights comprise different procedure weights assigned to one or more procedures of the computerized structured guideline, and wherein calculating the guideline adherence score comprises multiplying respective numeric procedure compliance scores by respective procedure weights ([0028] PALM score is the a compliance score for a medical treatment plan made up of several components based on compliance with different components or actions such as medications, labs, etc., [0052] overall PALM score is the sum of the components of the score, where each component is has a different weighting factor, i.e. weight multiplied by the component score).
Therefore, it would have been obvious to a person of ordinary skill in the art before the filing of the present application to combine the known concept of aggregating component compliance scores to determine a total compliance score from Gandy with the known treatment protocol guidelines and compliance score from Gaines and White in order to improve a patient’s non-adherence to medical treatment plans by providing detailed feedback to the patient regarding their adherence (Gandy [0004]).
As per Claim 31, Gaines, White, and Gandy discloses the method of Claim 25. Gaines also teaches at least some of the procedures are comprised of one or more discrete components/actions ([0041-0042] protocol specifies guidelines for a medical condition and includes a workflow with a series of events/steps).
As per Claim 32, Gaines, White, and Gandy discloses the method of Claim 31. Gandy also teaches at least one procedure comprises a plurality of discrete components/actions and wherein the weights comprise different component/action weights assigned to at least two of the discrete components/actions ([0028] PALM score is the a compliance score for a medical treatment plan made up of several components based on compliance with different components or actions such as medications, labs, etc., [0052] overall PALM score is the sum of the components of the score, where each component is has a different weighting factor).
Therefore, it would have been obvious to a person of ordinary skill in the art before the filing of the present application to combine the known concept of aggregating component compliance scores to determine a total compliance score from Gandy with the known treatment protocol guidelines and compliance score from Gaines and White in order to improve a patient’s non-adherence to medical treatment plans by providing detailed feedback to the patient regarding their adherence (Gandy [0004]).
As per Claim 33, Gaines, White, and Gandy discloses the method of Claim 25. Gaines also teaches the guidelines are comprised of stages, each stage comprises one or more procedures ([0041-0042] protocol specifies guidelines for a medical condition and includes a workflow with a series of events/steps and each of these steps includes attributes associated with each event/step).
As per Claim 34, Gaines, White, and Gandy discloses the method of Claim 31. Gandy also teaches at least one of the computerized structured guidelines comprises a plurality of stages, each stage comprising one or more procedures, and wherein the weights comprise different stage weights assigned to at least two stages ([0028] PALM score is the a compliance score for a medical treatment plan made up of several components based on compliance with different components or actions such as medications, labs, etc., [0052] overall PALM score is the sum of the components of the score, where each component is has a different weighting factor).
Therefore, it would have been obvious to a person of ordinary skill in the art before the filing of the present application to combine the known concept of aggregating component compliance scores to determine a total compliance score from Gandy with the known treatment protocol guidelines and compliance score from Gaines and White in order to improve a patient’s non-adherence to medical treatment plans by providing detailed feedback to the patient regarding their adherence (Gandy [0004]).
As per Claim 35, Gaines, White, and Gandy discloses the method of Claim 25. Gaines also teaches the guideline(s) are predetermined, based on the type of management ([0041] protocols which specify the treatment guidelines for the condition are received form a data source such as a health organization, i.e. predetermined).
As per Claim 36, Gaines, White, and Gandy discloses the method of Claim 25. Gaines may not disclose the following which is taught by White: the computerized structured guideline comprises procedural knowledge, declarative knowledge, and quality-assessment knowledge stored in the knowledge base ([0038] data store for computerized structured guideline includes tables including treatment table, i.e. procedural knowledge, provider table, claim event table, injured worker table, etc., which are declarative information; [0039] compliance score table and threshold table include quality-assessment knowledge information).
Therefore, it would have been obvious to a person of ordinary skill in the art before the filing of the present application to combine the known concept of computerized structured guidelines based on particular knowledge from White with the known treatment protocol guidelines from Gaines in order to improve medical management strategies to improve health care outcomes in the setting of complex data and rules (White [0002]).
As per Claim 37, Gaines, White, and Gandy discloses the method of Claim 25. Gaines also teaches displaying on a graphical user interface, to a user one or more of the guideline adherence score, a procedure compliance score, a component/action sub-score, or a stage sub-score (see Fig. 8 which displays compliance metrics, [0036-0037] determining compliance with protocol and provide analytic views, where the analytic views are displayed such that they can be selected to identify problems).
As per Claim 38, Gaines, White, and Gandy discloses the method of Claim 37. Gaines also teaches displaying to a user one or more quality assessment related parameters of all patients, a selected group of one or more patients, one or more quality assessment related parameters over a selected time period, one or more quality assessment related parameters of selected health care providers, one or more quality assessment related parameters of selected wards of the health care facility, or any combinations thereof ([0036] the analytic views which provide the scores and reports are provided by caregivers, particular departments, particular shifts (time periods), [0037] analytic views are provided as a display with drill down capabilities to display metrics by department, shift, individuals, etc.).
As per Claim 39, Gaines, White, and Gandy discloses the method of Claim 25. Gaines also teaches allowing a user to select presenting to a user one or more of: guideline adherence score of all patients, guideline adherence score of a selected group of one or more patients, guideline adherence score over selected time frames, guideline adherence score of selected health care providers, guideline adherence score of selected wards of the health care facility, or any combination thereof ([0036] the analytic views which provide the scores and reports are provided by caregivers, particular departments, particular shifts (time periods), [0037] analytic views are provided as a display with drill down capabilities to display metrics by department, shift, individuals, etc. where the user selects the metrics to view by clicking on an event on the display).
As per Claim 40, Gaines, White, and Gandy discloses the method of Claim 25. Gaines also teaches allowing a user to select presenting to a user one or more of: one or more procedure compliance score(s) of all patients, one or more procedure compliance score(s) of a selected group of one or more patients, one or more procedure compliance score(s) over selected time frame(s), one or more procedure compliance score(s) of selected health care providers, one or more procedure compliance score(s) of selected wards of the health care facility, or any combination thereof ([0036] the analytic views which provide the scores and reports are provided by caregivers, particular departments, particular shifts (time periods), [0037] analytic views are provided as a display with drill down capabilities to display metrics by department, shift, individuals, etc. where the user selects the metrics to view by clicking on an event on the display).
As per Claim 41, Gaines, White, and Gandy discloses the method of Claim 25. Gaines also teaches the quality assessment is retrospective ([0027] EMR data is used to determine metrics and the EMR data is collected over a period of time, i.e. not real-time data, [0053-0054] population EMR data is used to map to the process map and determine metrics).
As per Claim 42, Gaines, White, and Gandy discloses the method of Claim 25. Gaines also teaches providing a recommendation to a health care provider, based on one or more procedure compliance score(s) and/or the guideline adherence score ([0037] remedies are determined such as additional training or new internal shift change procedures, based on the compliance and variance from protocol).
As per Claim 43, Gaines discloses a system for assessing quality of long-term management of patients at a health care facility, the system comprising:
a patient-record database storing retrospective longitudinal patient-record data for a plurality of patients ([0017] data sources include data storage in the form of electronic medical systems/EMRs; see Fig. 12, Receive EMRs; [0027] EMRs collected over a period of time, i.e. longitudinal record, from multiple entities; [0047] EMRS are received from data sources);
a knowledge base storing a plurality of computerized structured guidelines (see Fig. 3 where protocols are displayed for the selected sepsis management, where sepsis comprises plurality of events, [0018] protocols include treatment guidelines for various conditions, [0023-0024] map a protocol for sepsis (selected condition) which includes plurality of steps, [0030] process map for a protocol is selected), and
one or more processors in communication with the patient-record database and the knowledge base ([0057-0058] CQA system which executes the invention is a computer platform including processors), the one or more processors configured to perform the method of claim 25 (taught by Gaines, White, and Gandy as described above).
However, Gaines may not explicitly disclose the following which is taught by White: each computerized structured guideline comprising a formal machine-interpretable representation of a plurality of procedures ([0045-0046] EBM guidelines are used for developing patient management and include guidelines for each diagnosis or injury which requires long-term management which are codified, i.e. in machine-interpretable representations; [0048] guidelines are mapped to the billing codes)
and defining, for respective procedures, a type or characteristic of the procedure, including a constraint category, a corresponding compliance-score calculation type ([0038] the treatment table, i.e. guideline definitions for all the procedures, includes types of treatments that relate to each diagnosis, [0039] compliance score table includes threshold at which remedial action is triggered for a particular injury/disease (Examiner interprets this to be a constraint to the guidelines), and patient table includes the compliance score calculation based on diagnosis and treatments, i.e. calculation type).
Therefore, it would have been obvious to a person of ordinary skill in the art before the filing of the present application to combine the known concept of computerized structured guidelines including constraints used to calculate a compliance score from White with the known treatment protocol guidelines from Gaines in order to improve medical management strategies to improve health care outcomes in the setting of complex data and rules (White [0002]).
However, Gaines and White may not explicitly disclose the following which is taught by Gandy: weights assigned to one or more stages, procedures, or components/actions of the computerized structured guideline ([0028] PALM score is the a compliance score for a medical treatment plan made up of several components based on compliance with different components or actions such as medications, labs, etc., [0052] overall PALM score is the sum of the components of the score, where each component is has a different weighting factor).
Therefore, it would have been obvious to a person of ordinary skill in the art before the filing of the present application to combine the known concept of aggregating component compliance scores to determine a total compliance score from Gandy with the known treatment protocol guidelines and compliance score from Gaines and White in order to improve a patient’s non-adherence to medical treatment plans by providing detailed feedback to the patient regarding their adherence (Gandy [0004]).
As per Claim 44, Gaines discloses a non-transitory computer-readable medium storing processor executable instructions that, when executed by one or more processors, cause the one or more processors ([0057-0058] CQA system which executes the invention includes a computer readable medium which provides instructions to the processors) to perform operations comprising the method of claim 25 (taught by Gaines, White, and Gandy as described above).
Claim 29 is rejected under 35 U.S.C. 103 as being unpatentable over Gaines (US 2013/0275149 A1), in view of White (US 2020/0342969 A1), in view of Gandy (US 2018/0113985 A1), in view of Sazonov (US 2015/0351981 A1), hereinafter Sazonov.
As per Claim 29, Gaines, White, and Gandy discloses the method of Claim 25. Gaines, White, and Gandy do not explicitly disclose the following which is taught by Sazonov: applying fuzzy temporal logic calculation using a fuzzy logic membership function that maps an execution time or an inter-execution gap to a partial compliance value between full compliance and zero compliance ([0047] use of fuzzy logic rules to determine compliance with clinical guidelines such as number or duration of events performed; see Claim 6 where duration of action is compared with guideline to generate feedback which indicates level of compliance; [0040] based on the number or duration of the activity performed, generate a level of compliance with a guideline by comparing number of times/duration of time to the guideline).
Therefore, it would have been obvious to a person of ordinary skill in the art before the filing of the present application to combine the known concept of the use of fuzzy logic to determine compliance scores for clinical guidelines from Sazonov with the known treatment protocol guidelines from Gaines, White, and Gandy in order to ensure that patient care events meet the guidelines such as proper pressure relief actions being undertaken to provide care for the patient (Sazonov [0049]).
Response to Arguments
Applicant’s arguments, see Page 8, “Response to Claim Objections”, filed 06/01/2026 with respect to claim 25 have been fully considered and they are persuasive. Therefore, the Objection of 03/04/2026 has been withdrawn.
Applicant’s arguments, see Pages 9-11, “35 U.S.C. §101 Rejections ”, filed 06/01/2026 with respect to claims 25-44 have been fully considered but they are not persuasive.
Applicant argues that the claims (claim 25 as exemplary) is not directed to a mental process because the claim does not reasonably cover unaided mental activity. Applicant further argues that retrieving retrospective longitudinal patient-record data from a patient-record database, retrieving a formal machine-interpretable structured guideline from a knowledge base, matching patient-record entries to procedures of the structured guideline, applying compliance-score calculation types corresponding to constraint categories, determining temporal compliance, and producing a quality-assessment output are rooted in computerized processing rather than mental judgment alone. Examiner respectfully disagrees. Examiner does agree that retrieving patient-record data from a database and structured guideline from a knowledge base are not activities which are performed using human mental activity. These are additional elements which are not part of the abstract idea and are analyzed as such in the rejection above. These additional elements are mere data gathering which is insignificant extra-solution activity which is well-understood, routine, and conventional similar to retrieving data from memory, as in MPEP 2106.05(d)(II). The steps of matching patient-record entries to procedures of the structured guidelines, applying compliance-score calculation types corresponding to constraint categories, determining temporal compliance, and producing a quality-assessment output, although they are performed using a processor, can be performed using human mental evaluation, judgment, observation, and opinion. The formal machine-interpretable data structured guideline is described as being machine-interpretable, but this does not preclude the guideline from being able to be processed by the human mind. There are many data structures which can be interpreted by machines which humans can analyze. Therefore, these steps of data analysis fall into the abstract grouping of mental processes.
Applicant argues that the claim integrates the abstract idea into a practical application because the computerized structured guideline controls how the processor calculates numeric compliance scores. Further, Applicant argues that the claim processor applies machine-interpretable guideline knowledge to longitudinal patient-record data to determine procedure-level compliance scores and a guideline adherence score. Examiner is not persuaded that this provides a technical improvement which would integrate the abstract idea into a technical improvement. The use of guidelines, even those which include procedural knowledge, declarative knowledge, and quality-assessment knowledge, to apply to the patient record data to perform analysis and determine a compliance score still amounts to data analysis which can be performed using human mental processing with or without the aid of pencil and paper. These elements are still considered to be part of the abstract idea and not additional elements and therefore do not integrate the abstract idea into a practical application.
Applicant argues that claim 26 amounts to significantly more than the abstract idea because the claim requires a specific arrangement of patient-record data retrieval, knowledge-base data retrieval of formal structured guideline, constraint-category-specific compliance scoring, temporal scoring based on execution times or inter-execution gaps, weighted aggregation across guideline elements, and generation of an electronic quality-assessment output. Examiner respectfully disagrees that this amounts to significantly more than the abstract idea. Applicant has not provided what improvement is achieved by any specific arrangement of elements in the claims. Examiner notes that the compliance scoring, temporal scoring, weighted aggregation across guideline elements, and generation of quality-assessment output is directed to the abstract idea itself and any improvement which results from the specific analysis steps is an improvement to the abstract idea itself and does not amount to significantly more than the abstract idea. Therefore, that leaves analysis of whether the arrangement of retrieving patient-record data and retrieval of formal structured guidelines as additional elements to determine if they are well-understood, routine, and conventional. The retrieval of data from memory or a knowledge base is found to be well-understood, routine, and conventional by the courts as evidenced by MPEP 2106.05(d)(II) storing and retrieving information in memory. Therefore, the claims do not amount to significantly more than the abstract idea.
Applicant’s arguments, see Pages 12-14, “35 U.S.C. §102 Rejections ”, filed 06/01/2026 with respect to claims 25-28, 31, 33, 35, and 37-44 have been fully considered and they are persuasive. Therefore, the 102 rejection of 03/04/2026 has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made over 35 U.S.C. §103 in view of Gaines, White, and Gandy.
Applicant’s arguments, see Pages 14-19, “35 U.S.C. §103 Rejections ”, filed 06/01/2026 with respect to claims 29-30, 32, 34, 36 have been fully considered and they are persuasive. Therefore, the 103 rejection of 03/04/2026 has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made over 35 U.S.C. §103 in view of White and Gandy.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/EVANGELINE BARR/Primary Examiner, Art Unit 3682
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