DETAILED ACTION
Status of Claims
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This action is in reply to a request for continued examination (“RCE”) filed 11 May 2026, on an application filed 16 December 2107, which claims domestic priority to a provisional application filed 16 December 2016.
Claims 1, 10, 11 and 18 have been amended.
Claims 1-22 are currently pending and have been examined.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 11 May 2026 has been entered.
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 1-22 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Step 1
Claims 1-22 are within the four statutory categories. Claims 1-10 are drawn to a readmissions monitoring method, which is within the four statutory categories (i.e. process). Claims 11-22 are drawn to a readmissions monitoring system, which is within the four statutory categories (i.e. machine).
Prong 1 of Step 2A
Claim 1 recites: A readmissions monitoring method, comprising:
establishing a sensor network across two or more facilities including at least a residence of one or more patients that perform sensor measurements associated with the one or more patients, wherein the sensor network includes at least one wearable sensor worn by each of the one or more patients and one or more environmental sensors integrated with the two or more facilities, and wherein the sensor measurements determine at least movement, blood pressure, heart rate, and temperature and environmental data for the one or more patients;
aggregating the sensor measurements from the sensor network of the two or more facilities utilizing one or more transceivers of a readmission platform including one or more servers;
determining readmission risk indicators utilizing the readmission platform, wherein the readmission risk indicators are determined by the readmission platform based on a combination of real-time biometric data from the sensor measurements and historical readmission data across the two or more facilities for the one or more patients;
automatically performing readmissions risk analysis, by the readmission platform,
utilizing the readmission risk indicators associated with the one or more patients, the readmission risk analysis is performed by determining
1) real-time continuous biometric data of the one or more patients measured by the sensor measurements and
2) the historical readmission data and applying dynamic weighting to the readmission risk indicators based on identity of which one of the two or more facilities collected the sensor measurements,
wherein the dynamic weighting for each of the two or more facilities is based on historical readmission data associated with that facility to generate a customized readmission risk; and
communicating the readmission risk analysis for the one or more patients to one or more providers associated with the one or more patients from the readmission platform through one or more networks.
Claim 11 recites similar material to claim 1, and additionally A readmissions monitoring system, comprising: a processing system in communication with the sensor network.
Claim 18 recites similar material to claim 1, and additionally A readmissions monitoring system, comprising: a readmission platform including a processor for executing a set of instructions; a memory for storing the set of instructions; and a transceiver.
The underlined limitations as shown above, given the broadest reasonable interpretation, cover the abstract idea of a certain method of organizing human activity because they recite managing personal behavior or relationships or interactions between people (i.e. social activities, teaching, and following rules or instructions -- in this case the system obtains patient data, aggregates it, analyzes and communicates a readmission risk), e.g. see MPEP 2106.04(a)(2). Any limitations not identified above as part of the abstract idea are deemed “additional elements,” and will be discussed in further detail below.
Dependent claims 2-10, 12-17 and 19-22 include other limitations, for example the processing of claims 3, 4, 6, 7, 11, 14, 16, 17 and 19, the data collection and communication of claims 2, 5, 8-10, 13, 15 and 20-22, and the generic facility description of claim 12, but these only serve to further narrow the abstract idea, and a claim may not preempt abstract ideas, even if the judicial exception is narrow, e.g. see MPEP 2106.04. Hence dependent claims 2-10, 12-17 and 19-22 are nonetheless directed towards fundamentally the same abstract idea as independent claims 1, 11, and 18.
Prong 2 of Step 2A
Claims 1, 11 and 18 are not integrated into a practical application because the additional elements (i.e. any limitations that are not identified as part of the abstract idea) amount to no more than limitations which:
amount to mere instructions to apply an exception – for example, the recitation of the structural components of the computer/server, the platform and the sensor network, which amounts to merely invoking a hardware as a tool to perform the abstract idea, e.g. see paragraph 67 of the present published Specification, see MPEP 2106.05(f); and/or
generally link the abstract idea to a particular technological environment or field of use – for example, the claim language directed to collecting data using sensors in a sensor network of facilities or the specific types of healthcare data collected, which amounts to limiting the abstract idea to the field of healthcare, see MPEP 2106.05(h); and/or
adding insignificant extrasolution activity to the abstract idea, for example mere data gathering, selecting a particular data source or type of data to be manipulated, and/or insignificant application (e.g. see MPEP 2106.05(g)).
Additionally, dependent claims 2-10, 12-17 and 19-22 include other limitations, but these limitations also amount to no more than generally linking the abstract idea to a particular technological environment or field of use (e.g. the use of the sensor network of claim 2, and the generic facility description of claim 12), adding insignificant extrasolution activity to the abstract idea (transmission of alerts/data of claims 8, 13 and 21), and/or do not include any additional elements beyond those already recited in independent claims 1, 11 and 18, and hence also do not integrate the aforementioned abstract idea into a practical application.
Step 2B
Claims 1, 11 and 18 do not include additional elements that are sufficient to amount to “significantly more” than the judicial exception because the additional elements (i.e. the non-underlined limitations above – in this case, the dispensing device and the one or more processors), as stated above, are directed towards no more than limitations that amount to mere instructions to apply the exception, generally link the abstract idea to a particular technological environment or field of use, and/or add insignificant extra-solution activity to the abstract idea, wherein the insignificant extra-solution activity comprises limitations which:
amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields, as demonstrated by:
The Specification expressly disclosing that the additional elements are well-understood, routine, and conventional in nature:
paragraph 67 of the present published Specification discloses that the additional elements (i.e. the functional components of the computer/server, the sensors and transceiver) comprise a plurality of different types of generic computing systems that are configured to perform generic computer functions (i.e. receive and process data) that are well-understood, routine, and conventional activities previously known to the pertinent industry (i.e. healthcare);
Relevant court decisions: The following are examples of court decisions demonstrating well-understood, routine and conventional activities, e.g. see 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));
ii. Performing repetitive calculations, Flook, 437 U.S. at 594, 198 USPQ2d at 199 (recomputing or readjusting alarm limit values); Bancorp Services v. Sun Life, 687 F.3d 1266, 1278, 103 USPQ2d 1425, 1433 (Fed. Cir. 2012) ("The computer required by some of Bancorp’s claims is employed only for its most basic function, the performance of repetitive calculations, and as such does not impose meaningful limits on the scope of those claims.");
iii. Electronic recordkeeping, Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 225, 110 USPQ2d 1984 (2014) (creating and maintaining "shadow accounts"); Ultramercial, 772 F.3d at 716, 112 USPQ2d at 1755 (updating an activity log);
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;
Dependent claims 2-10, 12-17 and 19-22 include other limitations, but none of these limitations are deemed significantly more than the abstract idea because, as stated above, the aforementioned dependent claims do not recite any additional elements not already recited in independent claims 1, 11 and 18, and/or the additional elements recited in the aforementioned dependent claims similarly amount to generally linking the abstract idea to a particular technological environment or field of use (e.g. the use of the sensor network of claim 2, and the generic facility description of claim 12), adding insignificant extrasolution activity to the abstract idea (transmission of alerts/data of claims 8, 13 and 21), and hence do not amount to “significantly more” than the abstract idea.
Thus, taken alone, the additional elements do not amount to significantly more than the abstract idea identified above. Furthermore, looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually, and there is no indication that the combination of elements improves the functioning of a computer or improves any other technology, and their collective functions merely provide conventional computer implementation.
Therefore, whether taken individually or as an ordered combination, claims 1-22 are nonetheless rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
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 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 of this title, 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.
Claim(s) 1, 2 and 4-22 are rejected under 35 U.S.C. 103 as being obvious over Nunez et al. (U.S. PG-Pub 2017/0109494 1), hereinafter Nunez, further in view of Tran (U.S. PG-Pub 2008/0004904 A1), in view of Tolvanen et al. (U.S. PG-Pub 2015/0199744 A1), hereinafter Tolvanen.
As per claims 1, 11 and 18, Nunez discloses a readmission monitoring system and method (Nunez, Figs. 1 and 11.), comprising:
establishing a sensor network for two or more facilities including a residence of one or more patients that perform sensor measurements associated with the one or more patients, wherein the sensor network includes at least one ... sensor used by each of the one or more patients and one or more … sensors integrated with the two or more facilities, and wherein the sensor measurements determine at least ... blood pressure, heart rate ... (Patient is provided with a patient station facility including patient monitoring equipment, including cardiac or respiratory monitors, that are used to perform sensor measurements, see Nunez paragraphs 25-27 and 43. System also stores collected laboratory measurements of the patient, which would comprise a sensor network of patient data, see Fig. 1. Facilities include hospitals, outpatient clinics and also patient’s homes, at least, see paragraph 21.);
aggregating the sensor measurements from the sensor network of the two or more facilities utilizing one or more transceivers of a readmission platform including one or more servers (Measured data of a plurality of patients are aggregated, see Figs. 3-6, and 66, at least. All information is accessible by the control system #40 of Fig. 1 for comparison of data, see paragraph 33 and is stored in patient information database #62 and readmission risk database #60, see paragraph 27 “for a previous or current patient”. Note servers of Fig. 2. System is provided over multiple facilities, including primary and alternate facilities, see paragraph 21. Paragraph 23, at least, discloses transceivers.);
determining readmission risk indicators utilizing the readmission platform, wherein the readmission risk indicators are determined by the readmission platform based on a combination of real-time biometric data from the sensor measurements and historical readmission data across the two or more facilities for the one or more patients (Nunez discloses determining readmission risk indicators, aka parameters, based on readmission data associated with at least historical readmission data for a facility/region for a time period – see paragraphs 21, 25 and 47-53. The variables used are some measured by sensors, both directly at patient and through laboratory collection processes. Nunez discloses use of historical readmission data using a database of readmission data from 70 acute care hospitals, see paragraph 48. Data collected in real-time would comprise real-time biometric data, whether it is used immediately or stored and used later.);
automatically performing readmissions risk analysis, by the readmission platform, utilizing the readmission risk indicators associated with the one or more patients, the readmission risk analysis is performed by determining 1) real-time continuous biometric data of the one or more patients measured by the sensor measurements and 2) the historical readmission data (Nunez uses the database of risk parameters [risk indicators] and collected patient data to determine a patient’s readmission risk given their current condition, see paragraphs 19, 27, 30, 31, 56, 70 and 71; sensor measurements are utilized, see perform sensor measurements, see paragraphs 25-27 and 43. Data collected in real-time would comprise real-time biometric data, whether it is used immediately or stored and used later. It is old and well known for medical monitoring equipment to collect real-time continuous biometric data.);
and applying dynamic weighting to the readmission risk indicators … wherein the dynamic weighting for each of the two or more facilities is based on historical readmission data associated with that facility to generate a customized readmission risk (Nunez discloses determining readmission risk indicators, aka parameters, based on readmission data associated with at least historical readmission data for a facility/region for a time period – see paragraphs 21, 25 and 47-53. Nunez discloses various weighted parameters, such as age, gender and lab tests, see paragraph 50; also see the weighting of parameters of paragraph 53.);
communicating the readmission risk analysis for the one or more patients to one or more providers associated with the one or more patients from the readmission platform through one or more networks (System communicate the determined readmission risk for the patient by attaching to all test orders prescribed for the patient’s care, which would be utilized by a provider when providing care, in order to lessen risk of readmission; system is also operative to change the patient’s care based on the determined readmission risk score in order to lessen risk of readmission, see paragraphs 19 and 70. Readmission risk database including determined readmission risk score is accessed by provider at paragraph 28.);
11. devices for sensing information including at least biometrics of the patients (Patient is provided with a patient station facility including patient monitoring equipment, including cardiac or respiratory monitors, that are used to perform sensor measurements, see paragraphs 25-27. System determines a patient odds ratio and readmission risk score using the patient specific data and readmission risk parameters, see paragraphs 56 and 71.);
18. processor for executing a set of instructions; memory for storing the set of instructions (Nunez, Figs. 1, 2 and 11.); and
Display the readmission risk score for the one or more patients (Nunez, paragraph 71.).
Nunez fails to explicitly disclose:
wearable sensors;
environmental sensors;
sensor measurements determining movement and temperature and environmental data; and
determining a condition of a patient based on sensor measurements; and
weighting variables based on the source of data.
However, Tran teaches that it was old and well known in the art of healthcare communications at the time of the invention/filing to provide wearable sensors, environmental sensors;
sensor measurements determining movement and temperature and environmental data; determining a condition of a patient based on sensor measurements (Tran provides a monitoring system that includes wearable and environmental sensors that measure movement, temperature and environmental data, using measurements to determine the patient’s current condition, as well as risk of future conditions, see paragraphs 54, 57, 182, 222, 267, 379, 444.) in order “to bring together multiple devices into interoperable (inter-connected) systems to improve patient care and avoid unnecessary accidents” (Tran, paragraph 3).
Therefore, it would have been obvious to one of ordinary skill in the art of healthcare communications at the time of the invention/filing to modify the system for calculating a readmission risk score of Nunez to include providing wearable sensors, environmental sensors;
sensor measurements determining movement and temperature and environmental data; determining a condition of a patient based on sensor measurements, as taught by Tran, in order to create a system for calculating a readmission risk score that can monitor a patient and “bring together multiple devices into interoperable (inter-connected) systems to improve patient care and avoid unnecessary accidents” (Tran, paragraph 3).
Tolvanen teaches that it was old and well known in the art of healthcare communications at the time of the invention/filing to provide weighting variables based on the source of data (Tolvanen, paragraph 147.) in order that “data fields provided by the more trustworthy data source may be associated with the higher weight, identified in the optimum cluster, and more likely to be used in the data record” (Tolvanen, paragraph 147.).
Therefore, it would have been obvious to one of ordinary skill in the art of healthcare communications at the time of the invention/filing to modify the system for calculating a readmission risk score of Nunez/Tran to include weighting variables based on the source of data, as taught by Tolvanen, in order to create a system for calculating a readmission risk score that can monitor a patient wherein “data fields provided by the more trustworthy data source may be associated with the higher weight, identified in the optimum cluster, and more likely to be used in the data record” (Tolvanen, paragraph 147.).
Nunez, Tran and Tolvanen are all directed to the processing of patient data in order to provide improved patient healthcare outcomes. Moreover, merely adding a well-known element into a well-known system, to produce a predictable result to one of ordinary skill in the art, does not render the invention patentably distinct over such combination (see MPEP 2141).
A recitation directed to the manner in which a claimed apparatus is intended to be used does not distinguish the claimed apparatus from the prior art, if the prior art has the capability to so perform, see MPEP 2114 (II) and Ex parte Masham, 2 USPQ2d 1647 (Bd. Pat. App. & Inter. 1987). “Language that suggest or makes optional but does not require steps to be performed or does not limit a claim to a particular structure does not limit the scope of a claim or claim limitation”, see MPEP 2111.04.
The following limitations are interpreted as an intended use of the claimed invention:
1,18. … to generate a customized readmission risk; and
18. ... for receiving and aggregating historic readmission data as well as sensor measurements from the one or more sensors.
The prior art is capable of performing the intended use recitation, therefore the prior art meets the limitations.
As per claims 2, 5-10, 12, 13, 15-17 and 20-22, Nunez/Tran/Tolvanen discloses claims 1, 11 and 18, discussed above. Nunez also discloses:
2. performing sensor measurements utilizing the sensor network across the two or more facilities based on a location of the for the one or more patients (Patient is provided with a patient station facility including patient monitoring equipment, including cardiac or respiratory monitors, that are used to perform sensor measurements, see Nunez paragraphs 25-27. Facilities include hospitals, outpatient clinics and also patient’s homes, at least, see paragraph 21. It is the Office’s position that data collected from a facility would be data measured based on a location of the patient.);
5. wherein the readmission risk analysis is communicated in response to exceeding one or more thresholds (System continually updates the calculated risk score based on new information and provides that score continually, see Nunez paragraphs 27. All data contained within the readmission risk database, including readmission risk score, is configured to be communicable to various hospital systems, see paragraph 27. System sends alerts based on score exceeding thresholds, see paragraphs 31 and 40.).
6. updating the readmissions risk analysis in response to additional historical readmission data or sensor measurements associated with the one or more patients (System is operative to continually update the readmission risk with new data received in real time, see Nunez paragraphs 27 and 71.);
7,16,22. wherein the readmission risk analysis is expressed as a score (Nunez, paragraphs 19, 27, 30, 31, 56, 70 and 71.);
8. sending one or more alerts based on updates or changes to the readmissions risk analysis determined from the sensor measurements for the one or more patients (System continually updates the calculated risk score based on new information and provides that score continually, see Nunez paragraphs 27. All data contained within the readmission risk database, including readmission risk score, is configured to be communicable to various hospital systems, see paragraph 27. System sends alerts based on score, see paragraphs 31 and 40.);
9,15,20. the readmissions risk includes a plurality of data points including medical records, procedure data, the historic readmission data, hospital or facility data, patient data, post care data, and acute care data for a time period (See data sources of Fig. 1 and corresponding text, and paragraphs 47-53.);
10. indicating which of the plurality of data points most significantly affect readmissions risks for each of the one or more patients individually when communicating the readmission risk analysis (Nunez discloses a ranking of the most reliable indicators of readmission data points, see the c-statistic of various parameters of Fig. 8; this is an indication of which of the plurality of data points most significantly affect readmissions risks for a plurality of patients. A secondary embodiment of Nunez discloses communicating the readmission risk analysis, as shown above, see paragraphs 27, 70 and 71. Nunez outputs a report based on each of the one or more patients individually, see Fig. 11 #1130.);
12. wherein the two or more facilities include at least a care facility and a home (Patient is provided with a patient station facility, within a clinic or hospital, including patient monitoring equipment, including cardiac or respiratory monitors, that are used to perform sensor measurements, see Nunez paragraphs 25-27. Facilities include hospitals, outpatient clinics and also patient’s homes, at least, see paragraph 30.);
13,21. sends one or more communications including at least the analysis in response to exceeding one or more thresholds and to a patient provider (Nunez, paragraph 71, device is reconfigured based on communicated risk score. All data contained within the readmission risk database, including readmission risk score, is configured to be communicable to various hospital systems, see paragraph 27. System communicate the determined readmission risk for the patient by attaching to all test orders prescribed for the patient’s care, which would be utilized by a provider when providing care, in order to lessen risk of readmission, see paragraph 70. System sends alerts based on score exceeding thresholds, see paragraphs 31 and 40.); and
17. wherein the processing system further updates the analysis in response to updated information, and sends one or more alerts to one or more specified users in response to the analysis exceeding one or more thresholds (System continually updates the calculated risk score based on new information and provides that score continually, see Nunez paragraph 27. All data contained within the readmission risk database, including readmission risk score, is configured to be communicable to various hospital systems, see paragraph 27. System sends alerts based on score exceeding thresholds, see paragraphs 31 and 40.).
As per claims 4, 14 and 19, Nunez/Tran/Tolvanen discloses claims 1, 11 and 18, discussed above. Nunez also discloses:
4, 14. wherein the readmission risk indicators are … to generate a readmission risk ratio associated with the readmission risk analysis (Nunez discloses the weighing of factors used for determining historical readmission data in order to make a readmission risk score, see paragraphs 53-56); and
19. weight … the biometrics and the historic readmission data to generate a readmission risk ratio associated with the readmission risk (Nunez discloses the weighing of factors used for determining historical readmission data, see paragraphs 53-56.).
Nunez fails to explicitly disclose averaging of factors.
However, Tran teaches that it was old and well known in the art of healthcare communications at the time of the invention/filing to disclose averaging of patient factors (Tran, paragraphs 244, 246, 251, 384 and 385.) in order to utilize appropriate patient results in a system to monitor a patient for health changes.
Therefore, it would have been obvious to one of ordinary skill in the art of healthcare communications at the time of the invention/filing to modify the system for calculating a readmission risk score of Nunez/Tran/Tolvanen to include averaging patient factors, as taught by Tran, in order to create a system for calculating a readmission risk score that will utilize appropriate patient results in a system to monitor a patient for health changes. Moreover, merely adding a well-known element into a well-known system, to produce a predictable result to one of ordinary skill in the art, does not render the invention patentably distinct over such combination (see MPEP 2141).
Claim 3 is rejected under 35 U.S.C. 103 as being obvious over Nunez/Tran/Tolvanen, further in view of Lindenauer, et al. ("The Performance of US Hospitals as Reflected in Risk-Standardized 30-Day Mortality and Readmission Rates for Medicare Beneficiaries with Pneumonia." July/August 2010), hereinafter Performance.
As per claim 3, Nunez/Tran/Tolvanen discloses claims 1, 11 and 18, discussed above. Nunez also discloses weighing the historical readmission data for the two or more facilities ... to generate the historical readmission data (Nunez discloses the weighing of factors used for determining historical readmission data, see paragraphs 53-56.).
Nunez fails to explicitly disclose consideration of data locally, regionally, and nationally in determining readmission risk.
However, Performance teaches that it was old and well known in the art of healthcare communications at the time of the invention/filing to provide consideration of data locally, regionally, and nationally in determining readmission risk (Performance, pages 12-16 considers readmission risk data locally, regionally and nationally and compares them appropriately.) in order to study the effects of “Risk-standardized 30-day mortality and, to a lesser extent, readmission rates for patients with pneumonia [which] vary substantially across hospitals and regions and may present opportunities for quality improvement, especially at low performing institutions and areas” (Performance, Conclusions, page E12.).
Therefore, it would have been obvious to one of ordinary skill in the art of healthcare communications at the time of the invention/filing to modify the system for calculating a readmission risk score of Nunez/Tran/Tolvanen to include consideration of data locally, regionally, and nationally in determining readmission risk, as taught by Performance, in order to create a system for calculating a readmission risk score that can study the effects of “Risk-standardized 30-day mortality and, to a lesser extent, readmission rates for patients with pneumonia [which] vary substantially across hospitals and regions and may present opportunities for quality improvement, especially at low performing institutions and areas” (Performance, Conclusions, page E12.). Moreover, merely adding a well-known element into a well-known system, to produce a predictable result to one of ordinary skill in the art, does not render the invention patentably distinct over such combination (see MPEP 2141).
Both Nunez and Performances are directed to the processing of monitored patient data in order to provide improved patient healthcare outcomes.
Response to Arguments
Applicant’s arguments filed 26 May 2026 concerning the rejection of all claims under 35 U.S.C. 112 have been fully considered and are persuasive in view of the amendments to the claims. Accordingly, this rejection has been withdrawn.
Applicant’s arguments filed 26 May 2026 concerning the rejection of all claims under 35 U.S.C. 101 and 103 have been fully considered but they are not persuasive.
With regard to the rejection of the claims under 35 USC 101, Applicant argues on pages 12-16 that the claims are statutory because:
A. Step 2A, Prong 1: The claims are not directed to an abstract idea because the claims require specific hardware (sensors, transceivers, servers) and the fact that the biometric data is collected continuously collected precludes it from being a mental task. The claims require a specific technical process not performable mentally or on paper.
B. Step 2A, Prong 2: The amended claims are integrated into a practical application: The claims provide a technical solution to a technological problem: the inaccurate prediction of hospital readmissions due to fragmented, non-continuous data collection across facilities by using facility-specific dynamic weighting. Also, the sensor network addresses a specific technical challenge by bridging a data gap.
C. Step 2B: The amended claims recite significantly more than any abstract idea and the office has failed to provide evidence to the contrary showing that claimed combination is well-understood, routine and conventional (“WRC”).
The Office respectfully disagrees. Please see the statutory rejection of the claims above.
Regarding argument A., as indicated above, the claims are directed to an abstract idea without significantly more. The mere fact that the claims recite language and other activities that are not performed by a human does not mean the claims are not directed to an abstract idea without significantly more. As shown above, the claims are directed to certain methods of organizing human activity, not to a mental process; whether the process can be performed in the mind is irrelevant.
MPEP 2106. 04(a)(2)(II) states that a claimed invention is directed to certain methods of organizing human activity if the identified claim elements contain limitations that encompass fundamental economic principles or practices, commercial or legal interactions, or managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions). The Examiner submits that the identified claim elements represent a series of rules or instructions that a person or persons, with or without the aid of a computer, would follow to provide a readmission risk score. Furthermore, the Examiner submits that healthcare itself is inherently represents the organization of human activity. Applicant has not pointed to anything in the claims that fall outside of this characterization: the recited sensor network across facilities is not shown to be part of the Abstract Idea, rather it comprises generically recited additional elements. Because the claim elements fall under a series of rules or instructions that a person or persons would follow to provide a readmission risk score, the claimed invention is directed to an abstract idea.
Further, there is no reason that “dynamic weighting” cannot be performed mentally using paper.
Regarding argument B., as indicated above, the Examiner respectfully disagrees. MPEP 2106.04(d)(1) and MPEP 2106.05(a) indicates that a practical application may be present where the claimed invention provides a technical solution to a technical problem. See, e.g., DDR Holdings, LLC. v. Hotels.com, L.P., 773 F.3d 1245, 1259 (Fed. Cir. 2014) (finding that claiming a website that retained the “look and feel” of a host webpage provided a technological solution to the problem of retention of website visitors by utilizing a website descriptor that emulated the “look and feel” of the host webpage, where the problem arose out of the internet and was thus a technical problem). Here, the Applicant’s argued problem is not a technological problem caused by a computing environment. The problem of determine readmission risk was not a problem cause by the computer, is it a problem that existed and/or exists regardless of whether a computer is involved in the process. The recitation of additional elements such as a generic sensor network comprising a data gathering step does not change this analysis. At best, Applicant’s identified problem is a business problem. Because no technological problem is present, the claims do not provide a practical application.
Regarding argument C., please see the new expanded statutory rejection, issued above, where the claims have been shown to be directed to an abstract idea without significantly more, and WRC is shown by citing the present specification and a series of relevant court cases.
Accordingly, the statutory rejection has been upheld.
With regard to the rejection of the claims under 35 USC 103, Applicant argues on pages 17-18 that the cited references fail to disclose a sensor network across two or more facilities.
A. The cited references fail to disclose facility-specific historical data weighting.
B. There is no motivation to combine Nunez, Tran and Tolvanen.
The Office respectfully disagrees. Please see the prior art rejection of the claims, issued above.
Regarding A., As shown above, Nunez discloses determining readmission risk indicators, aka parameters, based on readmission data associated with at least historical readmission data for a facility/region for a time period – see paragraphs 21, 25 and 47-53. Nunez discloses various weighted parameters, such as age, gender and lab tests, see paragraph 50; also see the weighting of parameters of paragraph 53.
The mere fact that Nunez uses the data from the same facility as well as other facilities does not distinguish from Applicant’s claims citing that the dynamic weighting is based on readmission data associated with that facility.
Further, Tolvanen teaches that it was old and well known in the art of healthcare communications at the time of the invention/filing to provide weighting variables based on the source of data (Tolvanen, paragraph 147.) in order that “data fields provided by the more trustworthy data source may be associated with the higher weight, identified in the optimum cluster, and more likely to be used in the data record” (Tolvanen, paragraph 147.). It is the combination of references that disclose the limitation, not each reference separately.
In response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986).
Further, any difference between the claims and the cited art amount to mere design choice, as the data would be processed the same and the invention enacted the same regardless of where the data is identified as being collected from. System is provided over multiple facilities, including primary and alternate facilities, see paragraph 21.
Regarding B., In response to applicant’s argument that there is no teaching, suggestion, or motivation to combine the references, the examiner recognizes that obviousness may be established by combining or modifying the teachings of the prior art to produce the claimed invention where there is some teaching, suggestion, or motivation to do so found either in the references themselves or in the knowledge generally available to one of ordinary skill in the art. See In re Fine, 837 F.2d 1071, 5 USPQ2d 1596 (Fed. Cir. 1988), In re Jones, 958 F.2d 347, 21 USPQ2d 1941 (Fed. Cir. 1992), and KSR International Co. v. Teleflex, Inc., 550 U.S. 398, 82 USPQ2d 1385 (2007). In this case, as shown above, the motivation arises from the references themselves.
To the extent that arguments concerning the rejection of claims are repeated in response to the rejection of other claims, the Office accordingly incorporates the responses to arguments detailed above.
The remainder of Applicant's arguments have been fully considered but are moot because they amount to a general allegation that the claims define a patentable invention without specifically pointing out how the language of the claims patentably distinguishes them from the references.
In conclusion, all of the limitations which Applicant disputes as missing in the applied references, including the features newly added by amendment, have been fully addressed by the Office as either being fully disclosed or obvious in view of the collective teachings of Nunez, Tran, Tolvanen, Pauls, An and Huynh, based on the logic and sound scientific reasoning of one ordinarily skilled in the art at the time of the invention, as detailed in the remarks and explanations given in the preceding sections of the present Office Action and in the prior Office Actions (09 February 2026, 18 June 2025, 17 December 2024, 11 June 2023, 17 November 2023, 8 March 2023, 13 October 2022, 18 March 2022, 25 October 2021 and 26 May 2021), and incorporated herein.
Conclusion
Unused but cited relevant prior art includes:
Nijesen et al. (U.S. PG-Pub 2017/0156681 A1), which discloses a system and method for assessing the risk of an exacerbation and/or hospitalization.
Any inquiry of a general nature or relating to the status of this application or concerning this communication or earlier communications from the Examiner should be directed to Mark Holcomb, whose telephone number is 571.270.1382. The Examiner can normally be reached on Monday-Friday (8-5). If attempts to reach the Examiner by telephone are unsuccessful, the Examiner’s supervisor, Kambiz Abdi, can be reached at 571.272.6702.
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/MARK HOLCOMB/
Primary Examiner, Art Unit 3685
19 May 2026
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