CTNF 18/694,777 CTNF 98282 DETAILED ACTION Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. Specification 07-29 AIA The disclosure is objected to because of the following informalities: Para. 0094, lines 1 and 4, the phrase “local system 102” should read “local system 104 ” for the proper reference number , Appropriate correction is required. Claim Objections 07-29-01 AIA Claim s 2-3, 9, 12, 15, 22-23, 25, 29, and 34-36 are objected to because of the following informalities: Regarding claim 2 , the phrase “the initial risk predication“ in line 14 should read “the initial risk prediction ” for proper grammar, Regarding claim 3 , the phrase “the initial risk predication” in line 3 should read “the initial risk prediction ” for proper grammar, Regarding claim 9 , the phrase “wherein the plurality of identifier elements encapsulates a plurality of identifiers associated a plurality of types of the plurality of medical devices” in lines 2-4 should read “wherein the plurality of identifier elements encapsulates a plurality of identifiers associated with a plurality of types of the plurality of medical devices” for proper grammar, Regarding claim 12 , the phrase “the glove of a caregiver” in line 11 should read “the glove of the caregiver” for proper antecedent basis, Regarding claim 15 , the phrase “determined, based on the at least one of: a scrubbing event in which the needless connector is scrubbed with a disinfectant, a flushing event in which the needleless connector is flushed with a solution, a connection event in which the needleless connector is connected to a medical device, a disconnection event in which the needleless connector is disconnected from the medical device” in lines 11-14 should read “determined, based on the at least one of: the scrubbing event in which the needleless connector is scrubbed with the disinfectant, the flushing event in which the needleless connected is flushed with the solution, the connection event in which the needleless connector is connected to the medical device, the disconnection event in which the needleless connector is disconnected from the medical device” for proper antecedent basis, Regarding claim 22 , the phrase “the initial risk predication“ in line 13 should read “the initial risk prediction ” for proper grammar, Regarding claim 23 , the phrase “the initial risk predication” in line 2 should read “the initial risk prediction ” for proper grammar, Regarding claim 25 , the phase “wherein the at least one processor is obtains” in line 1 should read “wherein the at least one processor obtains” to remove the term “is” for proper grammar, Regarding claim 29 , the phrase “wherein the plurality of identifier elements encapsulates a plurality of identifiers associated a plurality of types of the plurality of medical devices” in lines 2-4 should read “wherein the plurality of identifier elements encapsulates a plurality of identifiers associated with a plurality of types of the plurality of medical devices” for proper grammar, Regarding claim 34 , the phrase “one or more image capture devices configured to capturing” in line 3 should read “one or more image capture devices configure to capture ” for proper grammar, Regarding claim 35 , the phrase “the at least one processor,,” in line 5 should read “the at least one processor,” to remove an extra comma, Regarding claim 35 , the phrase “determined, with the at least one processor, based on the at least one of: a scrubbing event in which the needless connector is scrubbed with a disinfectant, a flushing event in which the needleless connector is flushed with a solution, a connection event in which the needleless connector is connected to a medical device, a disconnection event in which the needleless connector is disconnected from the medical device” in lines 11-14 should read “determined, with the at least one processor, based on the at least one of: the scrubbing event in which the needleless connector is scrubbed with the disinfectant, the flushing event in which the needleless connected is flushed with the solution, the connection event in which the needleless connector is connected to the medical device, the disconnection event in which the needleless connector is disconnected from the medical device” for proper antecedent basis, Regarding claim 36 , the phrase “the needleless connector defining the fluid flow path of the needless connector” in lines 2-3 should read “the needleless connector defining the fluid flow path of the needless connector ” for clarity , Appropriate correction is required. Claim Rejections - 35 USC § 112 07-30-02 AIA 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. The following is a quotation of 35 U.S.C. 112 (pre-AIA), second paragraph: The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention. 07-34-01 Claims 6, 17, 23, 26, 29-30, 34, 37, and 39 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. 07-34-08 Regarding claim 6 , the phrase "(e.g., CRBSI, phlebitis, etc.)” in line 16 renders the claim indefinite because it is unclear whether the limitation(s) following the phrase are part of the claimed invention. See MPEP § 2173.05(d). Regarding claim 17 , the phrase “wherein at least one of the force sensors” in lines 3-4 renders the claim indefinite because it is unclear. Claim 17 is dependent upon claim 15 which recites in line 2 “a force sensor”. Thus, it is unclear how claim 17 is referencing at least one of the force sensors when claim 15 introduces only a singular force sensor. Examiner is interpreting this as the singular force sensor of claim 15. Regarding claim 23 , the phrase “at least one of the following: the initial risk predication, the recommendation, and the updated risk prediction, the cost prediction, or any combination thereof” in lines 2-4 renders the claim indefinite because it is unclear. It is unclear whether the processor provides at least one of the combined data of the initial risk prediction, the recommendation, and the updated risk prediction or the cost prediction or any combination thereof, or if the processor provides at least one of the initial risk prediction, the recommendation, the updated risk prediction, the cost prediction, or any combination thereof. Examiner is interpreting this limitation as the latter. 07-34-08 Regarding claim 26 , the phrase "(e.g., CRBSI, phlebitis, etc.)” in line 16 renders the claim indefinite because it is unclear whether the limitation(s) following the phrase are part of the claimed invention. See MPEP § 2173.05(d). Regarding claim 29 , the phrase “determining, with the at least one processor, based on the plurality of images, a plurality of identifier elements within the environment over the period of time, wherein the plurality of identifier elements is associated with a plurality of medical devices, and wherein the plurality of identifier elements encapsulates a plurality of identifiers associated a plurality of types of the plurality of medical devices” in lines 7-11 renders the claim indefinite because it is unclear. It is unclear whether these are a different plurality of identifier elements associated with a different plurality of medical devices and a different plurality of identifiers associated with a different plurality of types of the plurality of medical devices or the same limitations aforementioned in lines 2-4 of claim 29. Examiner is interpreting them as the same. Examiner suggests amending to recite “determining, with the at least one processor, based on the plurality of images, the plurality of identifier elements within the environment over the period of time, wherein the plurality of identifier elements is associated with the plurality of medical devices, and wherein the plurality of identifier elements encapsulates the plurality of identifiers associated with the plurality of types of the plurality of medical devices”. Regarding claim 34 , the phrase “a state of a package containing a medical device over the period of time” in lines 6-7 renders the claim indefinite because it is unclear. It is unclear whether this is a different package containing a different medical device or the aforementioned package and medical device in line 2 of claim 34. Examiner is interpreting them as the same. Examiner suggests amending to recite “a state of the package containing the medical device over the period of time”. Regarding claim 37 , the phrase “wherein at least one of the force sensors” in lines 2-3 renders the claim indefinite because it is unclear. Claim 37 is dependent upon claim 35 which recites in line 2 “a force sensor”. Thus, it is unclear how claim 37 is referencing at least one of the force sensors when claim 35 introduces only a singular force sensor. Examiner is interpreting this as the singular force sensor of claim 35. Regarding claim 39 , the phrase “receiving, with the at least one processor, from the acoustic sensor, a signal including a sound signature” in lines 4-5 renders the claim indefinite because it is unclear. It is unclear whether this is a different signal including a different sound signature or the aforementioned signal in line 3 of claim 39. Examiner is interpreting it as the same. Examiner suggest amending to recite “receiving, with the at least one processor, from the acoustic sensor, the signal including the sound signature”. Regarding claim 30 , this claim is rejected due to being dependent upon a rejected base claim. Claim Rejections - 35 USC § 101 07-04-01 AIA 07-04 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, 5, 21 and 25 are rejected under 35 U.S.C. 101. Step 1: Claim 1 is directed to a system, claim 5 is dependent upon claim 1, claim 21 is directed to a method, and claim 25 is dependent upon claim 21; wherein, a system and method are both eligible at step 1. Step 2A Prong One: With respect to step 2A, the following elements of claims 1, 5, 21 and 25 are considered to be abstract: Claim 1, lines 3-4 recite “ obtain vascular access management (VAM) data associated with a vascular access treatment associated with a patient” , which appears to be a mental process. A clinician could visually obtain data about a treatment associated with a patient. Claim 1, lines 5-6 recite “determine an insight associated with the vascular access treatment associated with the patient” , which appears to be a mental process. A clinician could mentally make a judgement associated with the treatment. Claim 1, line 7 recites “ provide the insight associated with the vascular access treatment”, which appears to be a mental process. A clinician could verbally provide said judgement associated with the treatment. Claim 5, line 3 recites “ collecting, from a plurality of different data sources, source data” , which appears to be a mental process. A clinician can visually collect data from a plurality of data sources. Claim 5, line 4 recites “ associating the source data with at least one clinical protocol” , which appears to be a mental process. A clinician could make mental associations of said source data with at least one clinical protocol. Claim 5, lines 5-6 recite “ aggregating the source data associated with the at least one clinical protocol as the VAM data associated with the vascular access treatment associated with the patient” , which appears to be a mental process. A clinician can mentally group the data associated with the at least one clinical protocol and mentally label it as said VAM data. Claim 21, lines 2-3 recite “ obtaining, with at least one processor, vascular access management (VAM) data associated with a vascular access treatment associated with a patient ”, which appears to be a mental process. A clinician could visually obtain data about a treatment associated with a patient. Claim 21, lines 4-5 recite “ determining, with the at least one processor, an insight associated with the vascular access treatment associated with the patient”, which appears to be a mental process. A clinician could mentally make a judgement associated with the treatment. Claim 21, lines 6-7 recite “ providing, with the at least one processor, the insight associated with the vascular access treatment”, which appears to be a mental process. A clinician could verbally provide said judgement associated with the treatment. Claim 25, line 3 recites “ collecting, from a plurality of different data sources, source data” , which appears to be a mental process. A clinician can visually collect data from a plurality of data sources. Claim 25, line 4 recites “ associating the source data with at least one clinical protocol” , which appears to be a mental process. A clinician could make mental associations of said source data with at least one clinical protocol. Claim 25, lines 5-6 recite “ aggregating the source data associated with the at least one clinical protocol as the VAM data associated with the vascular access treatment associated with the patient” , which appears to be a mental process. A clinician can mentally group the data associated with the at least one clinical protocol and mentally label it as said VAM data. Step 2A Prong Two: The following are additional elements that do not amount to a practical application at step 2A: Claim 1 recites “a system comprising: at least one processor programmed and/or configured to”. These limitations are essentially stating that the system comprises a computer and said limitation are merely being performed on a computer. The system and computer are recited at a high level of generality. The computer is used to generally apply the abstract idea without placing any limits on how the system functions. See MPEP 2106.05(f). Claim 5 recites “the system of claim 1, wherein the at least one processor is programmed and/or configured to obtain the VAM data by”. These limitations are essentially stating that the system comprises a computer and said limitation are merely being performed on a computer. The system and computer are recited at a high level of generality. The computer is used to generally apply the abstract idea without placing any limits on how the system functions. See MPEP 2106.05(f). Claim 21 recites “with the at least one processor”. This limitation is essentially stating that the method comprises a computer and is merely being performed on a computer. The computer is used generally to apply the abstract idea without placing any limits on how the method functions. See MPEP 2106.05(f). Claim 25 recites “the method of claim 21, wherein the at least one processor is obtains the VAM data by”. These limitations are essentially stating that the method comprises a computer and said limitation are merely being performed on a computer. The method and computer are recited at a high level of generality. The computer is used to generally apply the abstract idea without placing any limits on how the method functions. See MPEP 2106.05(f). Step 2B: In re-evaluating the additional element sunder step 2B, the limitations of claims 1, 5, 21, and 25, when considered individually and as an ordered combination do not amount to significantly more than the abstract idea for the reasons set forth above. Claims 2-4 and 6-20 dependent upon claim 1 and claims 22-24 and 26-40 dependent upon claim 21 introduce limitations that integrate the mental processes into practical applications for example claims 2 and 22 introduce limitations for determining risk predictions, recommended process or products, and cost predictions for a patient during vascular access treatment. Thus, claims 2-4, 6-20, 22-24, and 26-40 are not currently rejected under 101. Claim Rejections - 35 USC § 102 07-06 AIA 15-10-15 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. 07-07-aia AIA 07-07 The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action: A person shall be entitled to a patent unless – 07-08-aia AIA (a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention. 07-12-aia AIA (a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention. 07-15 AIA Claim (s) 1, 4, 6, 15-19, 21, 24, 26, and 35-39 are rejected under 35 U.S.C. 102( a)(1 ) as being anticipated by Isaacson (W.O Patent Pub. No. 2020163304 A1) . Regarding claim 1 , Isaacson discloses (Claim 1) a system (100 in Fig. 1) comprising: at least one processor programmed and/or configured to (see para. 0077-0079 – within system 100 for managing IV treatments, subsystems in the form of medication source systems 102 each include controllers 204 having processors for carrying out programs and each subsystem 102 having smart devices 104 with processors for carrying out programs, examiner is interpreting the processor as a combination of the processors within the subsystem 102): obtain vascular access management (VAM) data associated with a vascular access treatment associated with a patient (examiner notes the medication source system 102 is configured to obtain several data sources associated with its IV treatment not all which will be cited herein, see Fig. 9 and para. 00132 and 00136-00137 – the processor of medication source system 102 performs step 902 for obtaining medication data, wherein medication data may be an identifier of a type of medication, etc. associated with the IV treatment of system 100, see para. 00107 – the processor of medication source system 102 obtains sensor signals from its smart devices 104 associated with scrubbing events, flushing events, or connection events which are associated with the IV treatment); determine an insight associated with the vascular access treatment associated with the patient (examiner notes the medication source system 102 is configured to obtain several data sources associated with its IV treatment and determine insights not all of which will be cited herein, see Fig. 9 and para. 00139 – processor of medication source system 102 performs step 904 for determining an insight in the form of determining compatibility of medications for the IV treatment of system 100, see para. 00107 – the processor of medication source system 102 determines insights on the scrubbing event, flushing event, or connection event from the force signal from force sensor 502); and provide the insight associated with the vascular access treatment (examiner notes the medication source system 102 is configured to provide insights determined from several obtained data source not all of which will be cited herein, see Fig. 9 and para. 00142 – processor of medication source system 102 performs step 906 for providing an indication of compatibility from step 904, see Fig. 6A-6B and para. 0081 – the processor of medication source system 102 provides said determined insights via smart devices 104 as patient-side feedback). Regarding claim 4 , Isaacson discloses (Claim 4) the system (100) of claim 1, wherein the at least one processor provides the insight by automatically controlling, based on the insight, at least one medical device (206a-n in Fig. 2A) to adjust a flow of a fluid to the patient during the vascular access treatment (see para. 0143 – when the processor of the medication source system 102 provides the insight in the form of indicating compatibility, said processor automatically controls each medication source device 206a to inhibit or prevent delivery by stopping the pump if the indication is incompatible). Regarding claim 6 , Isaacson discloses (Claim 6) the system (100) of claim 1, wherein the VAM data includes one or more of the following parameters: a medication associated with a patient (see para. 00132). Regarding claim 15 , Isaacson discloses (Claim 15) the system (100) of claim 1, further comprising: a needleless connector (214 in Fig. 2A-2C and 5A-5C) including a fluid flow path (see para. 00106); and a force sensor (502 in Fig. 5A-5C) connected to the needleless connector (214, see para. 00106); wherein the at least one processor is further programmed and/or configured to: receive, from the force sensor (502), a force signal (see para. 00107 – force sensor 502 generates a force signal which may be communicated to the medication source system 102 and said processor); and determine, based on the force signal, at least one of: a scrubbing event in which the needleless connector (214) is scrubbed with a disinfectant, a flushing event in which the needleless connector (214) is flushed with a solution, a connection event in which the needleless connector (214) is connected to a medical device, or any combination thereof (see para. 00107); and determine, based on the at least one of: a scrubbing event in which the needleless connector (214) is scrubbed with a disinfectant, a flushing event in which the needleless connector (214) is flushed with a solution, a connection event in which the needleless connector (214) is connected to a medical device, or any combination thereof, at least a portion of the VAM data associated with the vascular access treatment associated with the patient (see para. 00107 – the processor of medication source system 102 determines insights on the scrubbing event, flushing event, or connection event from the force signal from force sensor 502 which are at least a portion of data associated with the IV treatment). Regarding claim 16 , Isaacson discloses (Claim 16) the system (100) of claim 15, wherein the force sensor (502 in Fig. 5A-5C) is positioned between an outer surface of an inner wall (510 in Fig. 5A-5B) of the needleless connector (214) defining the fluid flow path of the needleless connector (214) and an inner surface of an outer wall (512 in Fig. 5A-5B) of the needleless connector (214) surrounding the inner wall (510) of the needleless connector (214, see Fig. 5A-5B and para. 00108-00109). Regarding claim 17 , Isaacson discloses (Claim 17) the system (100) of claim 15, wherein a first end (404 in Fig. 4A) of the needleless connector (214) includes a septum (408 in Fig. 4A and 5A) including a surface facing in a first direction, wherein at least one of the force sensors (502 in Fig. 5A) is configured to detect a force in a second direction perpendicular to the surface of the septum (408) facing in the first direction (see para. 00109), and wherein the at least one processor is further programmed and/or configured to: determine, based on the force signal indicating periodic forces in the second direction perpendicular to the surface of the septum (408) facing in the first direction, the flushing event, wherein the flushing event includes a pulsatile flushing event (see para. 00109). Regarding claim 18 , Isaacson discloses (Claim 18) the system (100) of claim 1, further comprising: a needleless connector (214 in Fig. 4-5C) including a fluid flow path (see para. 00106), a force sensor (502 in Fig. 5A-5B) configured to measure a force signal (see para. 00106), and a visual indicator (252 in Fig. 4B-4C, see para. 0091), wherein the at least one processor is further programmed and/or configured to: receive, from the force sensor (502), a force signal (see para. 00107 – force sensor 502 generates a force signal which may be communicated to the medication source system 102 and said processor); determine, based on the force signal, at least one of: a scrubbing event in which the needleless connector (214) is scrubbed with a disinfectant, a flushing event in which the needleless connector (214) is flushed with a solution, a connection event in which the needleless connector (214) is connected to a medical device, or any combination thereof (see para. 00107); and control the visual indicator (252) to provide a visual indication associated with the at least one of: the scrubbing event in which the needleless connector (214) is scrubbed with the disinfectant, the flushing event in which the needleless connector (214) is flushed with the solution, the connection event in which the needleless connector (214) is connected to the medical device, or any combination thereof (see para. 00115). Regarding claim 19 , Isaacson discloses (Claim 19) the system (100) of claim 1, further comprising: a needleless connector (214 in Fig. 2A-C) including a fluid flow path (see Fig. 2C and para. 00117); an acoustic sensor connected to the needleless connector (214, see para. 00117), wherein the at least one processor is further programmed and/or configured to: receive, from the acoustic sensor, a signal including a sound signature (see para. 00117 and 00150 – the processor of smart devices 104 receives an acoustic signal in the form of an acoustic signature from the acoustic sensor); determine, based on the signal, an event associated with the needleless connector (214, see para. 00117 and 00119 – the sound signal can be used to determine location of a needle tip); and determine, based on the determined event associated with the needleless connector (214), at least a portion of the VAM data associated with the vascular access treatment associated with the patient (see para. 00117 and 00119 – the location of the needle tip is used to determine if the catheter is properly placed). Regarding claim 21 , Isaacson discloses (Claim 21) a method comprising: obtaining, with at least one processor (see para. 0077-0079 – within system 100 for managing IV treatments, subsystems in the form of medication source systems 102 each include controllers 204 having processors for carrying out methods and each subsystem 102 having smart devices 104 with processors for carrying out methods, examiner is interpreting the processor as a combination of the processors within the subsystem 10), vascular access management (VAM) data associated with a vascular access treatment associated with a patient (examiner notes the medication source system 102 is configured to obtain several data sources associated with its IV treatment not all which will be cited herein, see Fig. 9 and para. 00132 and 00136-00137 – the processor of medication source system 102 performs step 902 for obtaining medication data, wherein medication data may be an identifier of a type of medication, etc. associated with the IV treatment of system 100, see para. 00107 – the processor of medication source system 102 obtains sensor signals from its smart devices 104 associated with scrubbing events, flushing events, or connection events which are associated with the IV treatment); determining, with the at least one processor, an insight associated with the vascular access treatment associated with the patient (examiner notes the medication source system 102 is configured to obtain several data sources associated with its IV treatment and determine insights not all of which will be cited herein, see Fig. 9 and para. 00139 – processor of medication source system 102 performs step 904 for determining an insight in the form of determining compatibility of medications for the IV treatment of system 100, see para. 00107 – the processor of medication source system 102 determines insights on the scrubbing event, flushing event, or connection event from the force signal from force sensor 502); and providing, with the at least one processor, the insight associated with the vascular access treatment (examiner notes the medication source system 102 is configured to provide insights determined from several obtained data source not all of which will be cited herein, see Fig. 9 and para. 00142 – processor of medication source system 102 performs step 906 for providing an indication of compatibility from step 904, see Fig. 6A-6B and para. 0081 – the processor of medication source system 102 provides said determined insights via smart devices 104 as patient-side feedback). Regarding claim 24 , Isaacson discloses (Claim 24) the method of claim 21, wherein the at least one processor provides the insight by automatically controlling, based on the insight, at least one medical device (206a-n in Fig. 2A) to adjust a flow of a fluid to the patient during the vascular access treatment (see para. 0143 – when the processor of the medication source system 102 provides the insight in the form of indicating compatibility, said processor automatically controls each medication source device 206a to inhibit or prevent delivery by stopping the pump if the indication is incompatible). Regarding claim 26 , Isaacson discloses (Claim 26) the method of claim 21, wherein the VAM data includes one or more of the following parameters: a medication associated with a patient (see para. 00132). Regarding claim 35 , Isaacson discloses (Claim 35) the method of claim 21, further comprising: measuring, with a force sensor (502 in Fig. 5A-5C) connected to a needleless connector (214 in Fig. 2A-2C and 5A-5C) including a fluid flow path, a force signal (see para. 00106); receiving, with at least one processor, from the force sensor (502), the force signal (see para. 00107 – force sensor 502 generates a force signal which may be communicated to the medication source system 102 and said processor); and determining, with the at least one processor, based on the force signal, at least one of: a scrubbing event in which the needleless connector (214) is scrubbed with a disinfectant, a flushing event in which the needleless connector (214) is flushed with a solution, a connection event in which the needleless connector (214) is connected to a medical device, or any combination thereof (see para. 00107); and determining, with the at least one processor, based on the at least one of: a scrubbing event in which the needleless connector (214) is scrubbed with a disinfectant, a flushing event in which the needleless connector (214) is flushed with a solution, a connection event in which the needleless connector (214) is connected to a medical device, or any combination thereof, at least a portion of the VAM data associated with the vascular access treatment associated with the patient (see para. 00107 – the processor of medication source system 102 determines insights on the scrubbing event, flushing event, or connection event from the force signal from force sensor 502 which are at least a portion of data associated with the IV treatment). Regarding claim 36 , Isaacson discloses (Claim 36) the method of claim 35, wherein the force sensor (502 in Fig. 5A-5C) is positioned between an outer surface of an inner wall (510 in Fig. 5A-5B) of the needleless connector (214) defining the fluid flow path of the needleless connector (214) and an inner surface of an outer wall (512 in Fig. 5A-5B) of the needleless connector (214) surrounding the inner wall (510) of the needleless connector (214, see Fig. 5A-5B and para. 00108-00109). Regarding claim 37 , Isaacson discloses (Claim 37) the method of claim 35, wherein a first end (404 in Fig. 4A) of the needleless connector (214) includes a septum (408 in Fig. 4A and 5A) including a surface facing in a first direction, wherein at least one of the force sensors (502 in Fig. 5A) is configured to detect a force in a second direction perpendicular to the surface of the septum (408) facing in the first direction (see para. 00109), and wherein the method further comprises: determining, with the at least one processor, based on the force signal indicating periodic forces in the second direction perpendicular to the surface of the septum (408) facing in the first direction, the flushing event, wherein the flushing event includes a pulsatile flushing event (see para. 00109). Regarding claim 38 , Isaacson discloses (Claim 38) the method of claim 21, further comprising: measuring, with a force sensor (502 in Fig. 5A-5C) of a needleless connector (214 in Fig. 4A-5C) including a fluid flow path (see para. 00106), the force sensor (502), and a visual indicator (252 in Fig. 4B-4C, see para. 0091), a force signal (see para. 00106); receiving, with the at least one processor, from the force sensor (502), a force signal (see para. 00107 – force sensor 502 generates a force signal which may be communicated to the medication source system 102 and said processor); determining, with the at least one processor, based on the force signal, at least one of: a scrubbing event in which the needleless connector (214) is scrubbed with a disinfectant, a flushing event in which the needleless connector (214) is flushed with a solution, a connection event in which the needleless connector (214) is connected to a medical device, or any combination thereof (see para. 00107); and controlling, with the at least one processor, the visual indicator (252) to provide a visual indication associated with the at least one of: the scrubbing event in which the needleless connector (214) is scrubbed with the disinfectant, the flushing event in which the needleless connector (214) is flushed with the solution, the connection event in which the needleless connector (214) is connected to the medical device, or any combination thereof (see para. 00115). Regarding claim 39 , Isaacson discloses (Claim 39) the method of claim 21, further comprising: measuring, with an acoustic sensor connected to a needleless connector (214 in Fig. 2A-C) including a fluid flow path (see Fig. 2C and para. 00117), a signal including a sound signature (see para. 00117 and 00150 – the processor of smart devices 104 receives an acoustic signal in the form of an acoustic signature from the acoustic sensor); determining, with the at least one processor, based on the signal, an event associated with the needleless connector (214, see para. 00117 and 00119 – the sound signal can be used to determine location of a needle tip); and determining, with the at least one processor, based on the determined event associated with the needleless connector (214), at least a portion of the VAM data associated with the vascular access treatment associated with the patient (see para. 00117 and 00119 – the location of the needle tip is used to determine if the catheter is properly placed) . Claim Rejections - 35 USC § 103 07-06 AIA 15-10-15 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. 07-20-aia AIA 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. 07-23-aia AIA 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. 07-21-aia AIA Claim (s) 2-3 and 22-23 are rejected under 35 U.S.C. 103 as being unpatentable over Isaacson in view of Chen et al. (U.S Patent Pub. No. 20220020463 A1, “Chen”) in view of Hasegawa et al. (J.P Patent Pub. No. 2012128670 A, “Hasegawa”) . Regarding claim 2 , Isaacson discloses the system of claim 1, as discussed above. However, Isaacson fails to disclose (Claim 2) wherein the at least one processor is programmed and/or configured to determine the insight associated with the vascular access treatment associated with the patient by: determining, based on the VAM data, an initial risk prediction for the vascular access treatment associated with the patient, wherein the initial risk prediction includes a probability that the patient experiences at least one complication in response to the vascular access treatment; determining, based on the VAM data and the initial risk prediction, a recommendation associated with the vascular access treatment associated with the patient, wherein the recommendation includes at least one of a recommended process and a recommend product to be used for the vascular access treatment; determining, based on the VAM data and the recommendation, an updated risk prediction for the vascular access treatment associated with the patient; determining, based on the VAM data, the initial risk predication, the recommendation, and the updated risk prediction, a cost prediction associated with the vascular access treatment associated with the patient, wherein the cost prediction includes a predicted savings in terms of a reduced cost of complication from adoption of the at least one of the recommended process and the recommend product. Chen discloses a method and system for optimizing pharmacotherapy using risk analysis (see Abstract), wherein Chen teaches (Claim 2) wherein the at least one processor is programmed and/or configured to determine the insight associated with the treatment associated with the patient by (see para. 0010 – computer may execute the method for optimizing pharmacotherapy and determines efficacy insights associated with the therapy): determining, based on the data, an initial risk prediction for the treatment associated with the patient (see 108 in Fig. 1 and para. 0031-0032 – method involves determining an initial risk score of the therapy based on population data), wherein the initial risk prediction includes a probability that the patient experiences at least one complication in response to the treatment (see para. 0031); determining, based on the data and the initial risk prediction, a recommendation associated with the treatment associated with the patient (see 110 in Fig. 1 and para. 0033 – method involves updating an efficacy-risk map which recommends ways to optimize the patient’s therapy and is based upon the data and initial risk score), wherein the recommendation includes at least one of a recommended process and a recommend product to be used for the vascular access treatment (see para. 0023, 0330-0034 – the therapy recommendation includes a recommended drug product); determining, based on the data and the recommendation, an updated risk prediction for the treatment associated with the patient (see para. 0031-0032 – as the therapy is underway, the method involves updating the risk score for the treatment based on the data and the efficacy-risk map). Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the processor of the system taught by Isaacson to incorporate the programming of an initial risk prediction, recommendation, and updated risk prediction as taught by Chen. Chen teaches programming for developing risk scores as part of optimizing a therapy and reducing risk for a patient (see para. 0010 and 0033). Hasegawa discloses a health business support system (see Fig. 1) having a CPU (104) for executing various programs of the system (see para. 0022-0023) including predicting cost reduction due to adoption of recommended medical interventions (see para. 0012). Hasegawa teaches a CPU (104) executing a medical cost model (1400 in Fig. 14) which indicates the average medical cost for an individual based upon a severity (602) of the illness and physiological values of the patient such as fasting blood glucose (504, see para. 0100-0101), an inspection value improvement model (1900 in Fig. 19) which provides a plurality of instruction services for improving the severity of the illness (see para. 0168 and 0181), and a predicted medical cost reduction effect calculation unit (131) which uses the medical cost model (1400) and value improvement model (1900) to calculate the predicted medical cost reduction amount by the instruction services (see para. 0035). Thus, Hasegawa teaches (Claim 2) determining, based on data, initial illness severity prediction, recommended instruction services, and updated illness severity prediction, a cost prediction associated with the treatment (see para. 0035), wherein the cost prediction includes a predicted savings in terms of a reduced cost of complication from adoption of the at least one of the recommended process and the recommend product (see para. 0035 and para. 0174). Since Chen in modified Isaacson discloses a risk analysis method for a treatment which comprises determining an initial risk prediction, a therapy recommendation, and updated risk prediction, and Hasegawa discloses a predicted medical cost reduction model that uses initial illness severity, therapy recommendations, and updated risk predictions to calculate a predicted savings in term of reduced cost from using the recommending therapy, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the processor of the system taught by modified Isaacson to incorporate the programming of a cost prediction as taught by Hasegawa. Hasegawa teaches a system that aids in prevention of serious diseases with an aim of reducing medical expenses by providing a model for predicting medical cost reduction effect corresponding to specific health guidance (see para. 0001 and 0011). Regarding claim 3 , modified Isaacson discloses the system of claim 2, as discussed above. In modified Isaacson, Chen discloses (Claim 3) wherein the at least one processor provides the insight by providing, to a user device, at least one of the following: the recommendation (see para. 0035 – the processor provides the insight regarding the recommendation about the therapy to a user device). Regarding claim 22 , Isaacson discloses the method of claim 21, as discussed above. However, Isaacson fails to disclose (Claim 22) wherein the insight associated with the vascular access treatment associated with the patient is determined by: determining, based on the VAM data, an initial risk prediction for the vascular access treatment associated with the patient, wherein the initial risk prediction includes a probability that the patient experiences at least one complication in response to the vascular access treatment; determining, based on the VAM data and the initial risk prediction, a recommendation associated with the vascular access treatment associated with the patient, wherein the recommendation includes at least one of a recommended process and a recommend product to be used for the vascular access treatment; determining, based on the VAM data and the recommendation, an updated risk prediction for the vascular access treatment associated with the patient; determining, based on the VAM data, the initial risk predication, the recommendation, and the updated risk prediction, a cost prediction associated with the vascular access treatment associated with the patient, wherein the cost prediction includes a predicted savings in terms of a reduced cost of complication from adoption of the at least one of the recommended process and the recommend product. Chen discloses a method and system for optimizing pharmacotherapy using risk analysis (see Abstract), wherein Chen teaches (Claim 22) wherein the at least one processor is programmed and/or configured to determine the insight associated with the treatment associated with the patient by (see para. 0010 – computer may execute the method for optimizing pharmacotherapy and determines efficacy insights associated with the therapy): determining, based on the data, an initial risk prediction for the treatment associated with the patient (see 108 in Fig. 1 and para. 0031-0032 – method involves determining an initial risk score of the therapy based on population data), wherein the initial risk prediction includes a probability that the patient experiences at least one complication in response to the treatment (see para. 0031); determining, based on the data and the initial risk prediction, a recommendation associated with the treatment associated with the patient (see 110 in Fig. 1 and para. 0033 – method involves updating an efficacy-risk map which recommends ways to optimize the patient’s therapy and is based upon the data and initial risk score), wherein the recommendation includes at least one of a recommended process and a recommend product to be used for the vascular access treatment (see para. 0023, 0330-0034 – the therapy recommendation includes a recommended drug product); determining, based on the data and the recommendation, an updated risk prediction for the treatment associated with the patient (see para. 0031-0032 – as the therapy is underway, the method involves updating the risk score for the treatment based on the data and the efficacy-risk map). Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the processor of the method taught by Isaacson to incorporate the programming of an initial risk prediction, recommendation, and updated risk prediction as taught by Chen. Chen teaches programming for developing risk scores as part of optimizing a therapy and reducing risk for a patient (see para. 0010 and 0033). Hasegawa discloses a health business support system (see Fig. 1) having a CPU (104) for executing various programs of the system (see para. 0022-0023) including predicting cost reduction due to adoption of recommended medical interventions (see para. 0012). Hasegawa teaches a CPU (104) executing a medical cost model (1400 in Fig. 14) which indicates the average medical cost for an individual based upon a severity (602) of the illness and physiological values of the patient such as fasting blood glucose (504, see para. 0100-0101), an inspection value improvement model (1900 in Fig. 19) which provides a plurality of instruction services for improving the severity of the illness (see para. 0168 and 0181), and a predicted medical cost reduction effect calculation unit (131) which uses the medical cost model (1400) and value improvement model (1900) to calculate the predicted medical cost reduction amount by the instruction services (see para. 0035). Thus, Hasegawa teaches (Claim 22) determining, based on data, initial illness severity prediction, recommended instruction services, and updated illness severity prediction, a cost prediction associated with the treatment (see para. 0035), wherein the cost prediction includes a predicted savings in terms of a reduced cost of complication from adoption of the at least one of the recommended process and the recommend product (see para. 0035 and para. 0174). Since Chen in modified Isaacson discloses a risk analysis method for a treatment which comprises determining an initial risk prediction, a therapy recommendation, and updated risk prediction, and Hasegawa discloses a predicted medical cost reduction model that uses initial illness severity, therapy recommendations, and updated risk predictions to calculate a predicted savings in term of reduced cost from using the recommending therapy, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the processor of the method taught by modified Isaacson to incorporate the programming of a cost prediction as taught by Hasegawa. Hasegawa teaches a system that aids in prevention of serious diseases with an aim of reducing medical expenses by providing a model for predicting medical cost reduction effect corresponding to specific health guidance (see para. 0001 and 0011). Regarding claim 23 , modified Isaacson discloses the method of claim 22, as discussed above. In modified Isaacson, Chen discloses (Claim 23) wherein the at least one processor provides the insight by providing, to a user device, at least one of the following: the recommendation (see para. 0035 – the processor provides the insight regarding the recommendation about the therapy to a user device) . 07-21-aia AIA Claim (s) 5 and 25 are rejected under 35 U.S.C. 103 as being unpatentable over Isaacson in view of Blomquist (U.S Patent Pub. No. 20080033402 A1) . Regarding claim 5 , Isaacson discloses the system of claim 1, as discussed above. While Isaacson discloses obtaining the VAM data, for example, by collecting identifiers or sensor signals (see para. 00132 and 00107), Isaacson fails to disclose (Claim 5) wherein the at least one processor is programmed and/or configured to obtain the VAM data by: collecting, from a plurality of different data sources, source data; associating the source data with at least one clinical protocol; and aggregating the source data associated with the at least one clinical protocol as the VAM data associated with the vascular access treatment associated with the patient. Blomquist discloses an infusion pump network (200 in Fig. 2) having a plurality of computing systems (104 in Fig. 2) associated with a plurality of infusion pumps (102 in Fig. 2) wherein the computing systems (104) comprises processors interpreted together as the at least one processor for obtaining data (see para. 0053-0054 and 0060). Blomquist teaches (Claim 5) wherein the at least one processor is programmed and/or configured to obtain the data by: collecting, from a plurality of different data sources, source data (see para. 0096 – in order to assign a pump protocol to the correct pump 102, the computing systems 104 are assigned an identification code that corresponds to an identification code for the correct protocol stored in a database (504 in Fig. 5) in the server (206 in Fig. 5, see para. 0091 and 0096, thus the processor is programmed to obtain from each infusion pump 102 its identification code); associating the source data with at least one clinical protocol (see para. 0096 – each identification code is associated with its complementary code in the database 504 and thus its correct pump protocol); and aggregating the source data associated with the at least one clinical protocol as the VAM data associated with the treatment associated with the patient (see para. 0096 – the identification code with its associated pump protocol are grouped by the processor to access the data associated with the pump treatment, see para. 0056 and 0095– the data associated with the pump treatment within the pump protocol includes operational characteristics of the infusion pump during a specific therapy for a specific patient and specific drug). Since Isaacson discloses a system having a plurality of infusion pumps with corresponding controllers all in a network (106, see Fig. 1), and Blomquist discloses a similar system having a plurality of infusion pumps with corresponding controllers all in a network (see Fig. 1), it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the processor of the system taught by Isaacson to incorporate the programming of collecting the data, associating the data with at least one clinical protocol, and aggregating said data and protocol as the VAM data as taught by Blomquist. Blomquist teaches that when multiple infusion pumps are in communication under a common network, each infusion pump is provided an identification code to ensure that the infusion pumps access the correct library and/or protocol (see para. 0096). Regarding claim 25 , Isaacson discloses the method of claim 21, as discussed above. While Isaacson discloses obtaining the VAM data, for example, by collecting identifiers or sensor signals (see para. 00132 and 00107), Isaacson fails to disclose (Claim 25) wherein the at least one processor is obtains the VAM data by: collecting, from a plurality of different data sources, source data; associating the source data with at least one clinical protocol; and aggregating the source data associated with the at least one clinical protocol as the VAM data associated with the vascular access treatment associated with the patient. Blomquist discloses an infusion pump network (200 in Fig. 2) having a plurality of computing systems (104 in Fig. 2) associated with a plurality of infusion pumps (102 in Fig. 2) wherein the computing systems (104) comprises processors interpreted together as the at least one processor for obtaining data (see para. 0053-0054 and 0060). Blomquist teaches (Claim 25) wherein the at least one processor is obtains the VAM data by: collecting, from a plurality of different data sources, source data (see para. 0096 – in order to assign a pump protocol to the correct pump 102, the computing systems 104 are assigned an identification code that corresponds to an identification code for the correct protocol stored in a database (504 in Fig. 5) in the server (206 in Fig. 5, see para. 0091 and 0096, thus the processor is programmed to obtain from each infusion pump 102 its identification code); associating the source data with at least one clinical protocol (see para. 0096 – each identification code is associated with its complementary code in the database 504 and thus its correct pump protocol); and aggregating the source data associated with the at least one clinical protocol as the VAM data associated with the treatment associated with the patient (see para. 0096 – the identification code with its associated pump protocol are grouped by the processor to access the data associated with the pump treatment, see para. 0056 and 0095– the data associated with the pump treatment within the pump protocol includes operational characteristics of the infusion pump during a specific therapy for a specific patient and specific drug). Since Isaacson discloses a system having a plurality of infusion pumps with corresponding controllers all in a network (106, see Fig. 1), and Blomquist discloses a similar system having a plurality of infusion pumps with corresponding controllers all in a network (see Fig. 1), it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the processor of the system taught by Isaacson to incorporate the programming method of collecting the data, associating the data with at least one clinical protocol, and aggregating said data and protocol as the VAM data as taught by Blomquist. Blomquist teaches that when multiple infusion pumps are in communication under a common network, each infusion pump is provided an identification code to ensure that the infusion pumps access the correct library and/or protocol (see para. 0096) . 07-21-aia AIA Claim (s) 7 and 27 are rejected under 35 U.S.C. 103 as being unpatentable over Isaacson in view of Nesterenko et al. (U.S Patent Pub. No. 20210059784 A1, “Nesterenko”) . Regarding claim 7 , Isaacson discloses the system of claim 1, as discussed above. While Isaacson discloses a singular local system (102, 104 in Fig. 1 and 2A), wherein the local system (102, 104) includes a central computing system (204 in Fig. 2A), a sensor system (254 in Fig. 2C) including at least one sensor (see para. 0091), and a user device (208 in Fig. 2A, see para. 0087-0091 - the local system 102 includes controller 204, sensors 254 in their corresponding smart devices 104, and user input devices 208); and a management system (108 in Fig. 1) configured as a central unit or command center for remotely monitoring line maintenance activities at the local system (102, 104, see para. 0084), however Isaacson fails to disclose (Claim 7) a plurality of local systems each including a central computing system, sensor system, and user device, and the management system configured to remotely monitor line maintenance activities at each local system. Nesterenko discloses a system for managing a plurality of medical devices used in a medical environment (see Abstract and para. 0004-0005), wherein Nesterenko teaches (Claim 7) a plurality of local systems (104 in Fig. 1 and 3-4) each comprising a central computing system (302 in Fig. 3), a sensor system (323 in Fig. 3), and a user device (310 in Fig. 3, see Fig. 3-4 and para. 0034 and 0039); and a management system (108 in Fig. 1-2) configured as a central unit or command center for remotely monitoring line maintenance activities of each local system (104) in the plurality of local systems (104, see para. 0027, 0053, 0056-0057). Since Isaacson discloses an environment such as that seen in an emergency room with a user connected to a plurality of lumens or fluid lines at the same time and the need for the environment to provide organizational software for tracking the fluid lines infusion, maintenance, removal, and the like (see para. 0002), and Nesterenko discloses an environment such as that seen in a medical environment having to track and identify medical devices being used by a plurality of patients and clinicians (see para. 0004-0005), it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system having a singular local system taught by Isaacson to be a system having a plurality of local systems as taught by Nesterenko and according to known methods to yield predictable results. Isaacson’s local system being implemented in emergency room environments would be in the proximity of other similar local system’s given the nature of an emergency room. Thus, one of ordinary skill in the art would have recognized that it would have been obvious to modify Isaacson’s system comprising a singular local system to be a plurality of local systems as taught by Nesterenko. Regarding claim 27 , Isaacson discloses the method of claim 21, as discussed above. While Isaacson discloses the method of remotely monitoring, with a management system (108 in Fig. 1) configured as a central unit or command center, line maintenance activities of a singular local system (102, 104 in Fig. 1 and 2A, see para. 0084), wherein the local system (102, 104) includes a central computing system (204 in Fig. 2A), a sensor system (254 in Fig. 2C) including at least one sensor (see para. 0091), and a user device (208 in Fig. 2A, see para. 0087-0091 - the local system 102 includes controller 204, sensors 254 in their corresponding smart devices 104, and user input devices 208); however Isaacson fails to disclose (Claim 27) a plurality of local systems each including a central computing system, sensor system, and user device, and the management system configured to remotely monitor line maintenance activities at each local system. Nesterenko discloses a system and method for managing a plurality of medical devices used in a medical environment (see Abstract and para. 0004-0005), wherein Nesterenko teaches (Claim 27) remotely monitoring, with a management system (108 in Fig. 1-2) configured as a central unit or command center, line maintenance activities at a plurality of local systems (104 in Fig. 1 and 3-4, see para. 0027, 0053, 0056-0057), wherein each local system (104 in Fig. 1 and 3-4) includes a central computing system (302 in Fig. 3), a sensor system (323 in Fig. 3), and a user device (310 in Fig. 3, see Fig. 3-4 and para. 0034 and 0039); and Since Isaacson discloses an environment such as that seen in an emergency room with a user connected to a plurality of lumens or fluid lines at the same time and the need for the environment to provide organizational software for tracking the fluid lines infusion, maintenance, removal, and the like (see para. 0002), and Nesterenko discloses an environment such as that seen in a medical environment having to track and identify medical devices being used by a plurality of patients and clinicians (see para. 0004-0005), it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method and its system having a singular local system taught by Isaacson to be a method and system having a plurality of local systems as taught by Nesterenko and according to known methods to yield predictable results. Isaacson’s local system being implemented in emergency room environments would be in the proximity of other similar local system’s given the nature of an emergency room. Thus, one of ordinary skill in the art would have recognized that it would have been obvious to modify Isaacson’s system comprising a singular local system to be a plurality of local systems as taught by Nesterenko . 07-21-aia AIA Claim (s) 8-10 and 28-30 are rejected under 35 U.S.C. 103 as being unpatentable over Isaacson in view of Philippe et al. (U.S Patent Pub. No. 20130076898 A1, “Philippe”) . Regarding claim 8 , Isaacson discloses the system of claim 1, as discussed above. However, Isaacson fails to disclose (Claim 8) one or more image capture devices configured to capture, over a period of time, a plurality of images of an environment surrounding the one or more image capture devices; and wherein the at least one processor is further programmed and/or configured to: determine, based on the plurality of images, a plurality of locations of a plurality of medical devices within the environment over the period of time and a plurality of types of the plurality of medical devices; and determine, based on the plurality of locations of the plurality of medical devices within the environment over the period of time and the plurality of types of the plurality of medical devices, at least a portion of the VAM data associated with the vascular access treatment associated with the patient. Phillipe discloses a medical product tracking system and method (See Abstract), wherein Phillipe teaches (Claim 8) one or more image capture devices (22 in Fig. 1) configured to capture, over a period of time, a plurality of images of an environment surrounding the one or more image capture devices (22, see para. 0043, 0048, and 0050 – camera 22 takes a plurality of images over a period of time of its surrounding environment); wherein the at least one processor is further programmed and/or configured to (see para. 0048 – imagining unit 20 comprises a processor for executing a program analyzing the images from camera 22 and making determinations): determine, based on the plurality of images, a plurality of locations of a plurality of medical devices within the environment over the period of time and a plurality of types of the plurality of medical devices (see Fig. 3 and para. 0050); and determine, based on the plurality of locations of the plurality of medical devices within the environment over the period of time and the plurality of types of the plurality of medical devices, at least a portion of the data associated therewith (see para. 0050 – processor determines based on the locations of plurality of medical devices and their types whether a particular medical product is present in the system). Since Isaacson discloses that the system comprises a processor for obtaining identifier information for medication data for processing (see para. 00132), and Phillipe discloses an imagining system and processor for obtaining identifier information of medical devices within the system to determine the type of medical devices therein (see para. 0050), it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system and its processor taught by Isaacson to incorporate a camera and programming method for image analysis to determine the locations of medical devices and the types of medical devices as taught by Philippe such that the system of Isaacson would incorporate a camera for taking images of the medication source systems (102) to determine the presence and types of medical devices therein and thus the associated data. Philippe teaches that the use of a computerized imaging system is beneficial as it provides a “hands-off” system for use by health care personnel which reduces health-care personnel responsibilities and avoids contamination by maintaining a sterile environment with less touching of medical devices (see para. 0036). Regarding claim 9 , Isaacson discloses the system of claim 1, as discussed above. Isaacson further discloses the limitations of (Claim 9) further comprising: a plurality of identifier elements associated with a plurality of medical devices (see para. 00132), wherein the plurality of identifier elements encapsulates a plurality of identifiers associated a plurality of types of the plurality of medical devices (see para. 00132). However, Isaacson fails to disclose (Claim 9) one or more image capture devices configured to capture, over a period of time, a plurality of images of an environment surrounding the one or more image capture devices, wherein the at least one processor is further programmed and/or configured to: determine, based on the plurality of images, the plurality of identifier elements within the environment over the period of time; determine, based on the plurality of identifier elements determined in the plurality of images, the plurality of types of the plurality of medical devices and a plurality of locations of the plurality of medical devices within the environment over the period of time; and determine, based on the plurality of types of the plurality of medical devices and the plurality of locations of the plurality of medical devices within the environment over the period of time, at least a portion of the VAM data associated with the vascular access treatment associated with the patient. Phillipe discloses a medical product tracking system and method (See Abstract), wherein Phillipe teaches (Claim 9) further comprising: a plurality of identifier elements associated with a plurality of medical devices (see para. 0030-0033), wherein the plurality of identifier elements encapsulates a plurality of identifiers associated a plurality of types of the plurality of medical devices (see para. 0030-0033 and 0050); and one or more image capture devices (22 in Fig. 1) configured to capture, over a period of time, a plurality of images of an environment surrounding the one or more image capture devices (22, see para. 0043, 0048, and 0050 – camera 22 takes a plurality of images over a period of time of its surrounding environment), wherein the at least one processor is further programmed and/or configured to (see para. 0048 – imagining unit 20 comprises a processor for executing a program analyzing the images from camera 22 and making determinations): determine, based on the plurality of images, the plurality of identifier elements within the environment over the period of time (see para. 0050 and 0053); determine, based on the plurality of identifier elements determined in the plurality of images, the plurality of types of the plurality of medical devices and a plurality of locations of the plurality of medical devices within the environment over the period of time (see para. 0050 and 0053); and determine, based on the plurality of types of the plurality of medical devices and the plurality of locations of the plurality of medical devices within the environment over the period of time, at least a portion of the data associated therewith (see para. 0050 and 0053 – processor determines based on the locations of plurality of medical devices and their types whether a particular medical product is present in the system). Since Isaacson discloses that the system comprises a processor for obtaining identifier information for medication data for processing (see para. 00132), and Phillipe discloses an imagining system and processor for obtaining identifier information of medical devices within the system to determine the type of medical devices therein (see para. 0050), it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system and its processor taught by Isaacson to incorporate a camera and programming method for image analysis to determine the locations of medical devices and the types of medical devices based upon identifier elements as taught by Philippe such that the system of Isaacson would incorporate a camera for taking images of the medication source systems (102) to determine the presence and types of medical devices based upon identifier elements therein and thus the associated data. Philippe teaches that the use of a computerized imaging system is beneficial as it provides a “hands-off” system for use by health care personnel which reduces health-care personnel responsibilities and avoids contamination by maintaining a sterile environment with less touching of medical devices (see para. 0036). Regarding claim 10 , modified Isaacson discloses the system of claim 9, as discussed above. In modified Isaacson, Phillipe discloses (Claim 10) wherein the plurality of identifier elements includes at least one identifier element including at least one of the following types of identifier elements: a colored pattern, a reflective pattern, a fluorescent pattern, a predetermined shape and color, a LED pattern, a barcode, or any combination thereof (see para. 0032-0033). Regarding claim 28 , Isaacson discloses the method of claim 21, as discussed above. However, Isaacson fails to disclose (Claim 28) further comprising: capturing, with one or more image capture devices, over a period of time, a plurality of images of an environment surrounding the one or more image capture devices; and determining, with the at least one processor, based on the plurality of images, a plurality of locations of a plurality of medical devices within the environment over the period of time and a plurality of types of the plurality of medical devices; and determining, with the at least one processor, based on the plurality of locations of the plurality of medical devices within the environment over the period of time and the plurality of types of the plurality of medical devices, at least a portion of the VAM data associated with the vascular access treatment associated with the patient. Phillipe discloses a medical product tracking system and method (See Abstract), wherein Phillipe teaches (Claim 28) further comprising: capturing, with one or more image capture devices (22 in Fig. 1), over a period of time, a plurality of images of an environment surrounding the one or more image capture devices (22, see para. 0043, 0048, and 0050 – camera 22 takes a plurality of images over a period of time of its surrounding environment); determining, with the at least one processor (see para. 0048 – imagining unit 20 comprises a processor for executing a program analyzing the images from camera 22 and making determinations), based on the plurality of images, a plurality of locations of a plurality of medical devices within the environment over the period of time and a plurality of types of the plurality of medical devices (see Fig. 3 and para. 0050); and determining, with the at least one processor, based on the plurality of locations of the plurality of medical devices within the environment over the period of time and the plurality of types of the plurality of medical devices, at least a portion of the data associated therewith (see para. 0050 – processor determines based on the locations of plurality of medical devices and their types whether a particular medical product is present in the system). Since Isaacson discloses that the system comprises a processor for obtaining identifier information for medication data for processing (see para. 00132), and Phillipe discloses an imagining system and processor for obtaining identifier information of medical devices within the system to determine the type of medical devices therein (see para. 0050), it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method and its processor taught by Isaacson to incorporate a camera and programming method for image analysis to determine the locations of medical devices and the types of medical devices as taught by Philippe such that the system of Isaacson would incorporate a camera for taking images of the medication source systems (102) to determine the presence and types of medical devices therein and thus the associated data. Philippe teaches that the use of a computerized imaging system is beneficial as it provides a “hands-off” system for use by health care personnel which reduces health-care personnel responsibilities and avoids contamination by maintaining a sterile environment with less touching of medical devices (see para. 0036). Regarding claim 29 , Isaacson discloses the method of claim 21, as discussed above. Isaacson further discloses the limitations of (Claim 29) further comprising: a plurality of identifier elements associated with a plurality of medical devices (see para. 00132), wherein the plurality of identifier elements encapsulates a plurality of identifiers associated a plurality of types of the plurality of medical devices (see para. 00132). However, Isaacson fails to disclose (Claim 29) capturing, with one or more image capture devices, over a period of time, a plurality of images of an environment surrounding the one or more image capture devices, determining, with the at least one processor, based on the plurality of images, a plurality of identifier elements within the environment over the period of time, wherein the plurality of identifier elements is associated with a plurality of medical devices, and wherein the plurality of identifier elements encapsulates a plurality of identifiers associated a plurality of types of the plurality of the plurality of medical devices; and determining, with the at least one processor, based on the plurality of identifier elements determined in the plurality of images, the plurality of types of the plurality of medical devices and a plurality of locations of the plurality of medical devices within the environment over the period of time. Phillipe discloses a medical product tracking system and method (See Abstract), wherein Phillipe teaches (Claim 29) further comprising: a plurality of identifier elements associated with a plurality of medical devices (see para. 0030-0033), wherein the plurality of identifier elements encapsulates a plurality of identifiers associated a plurality of types of the plurality of medical devices (see para. 0030-0033 and 0050); and capturing, with one or more image capture devices (22 in Fig. 1), over a period of time, a plurality of images of an environment surrounding the one or more image capture devices (22, see para. 0043, 0048, and 0050 – camera 22 takes a plurality of images over a period of time of its surrounding environment), determining, with the at least on processor (see para. 0048 – imagining unit 20 comprises a processor for executing a program analyzing the images from camera 22 and making determinations), based on the plurality of images, a plurality of identifier elements within the environment over the period of time (see para. 0050 and 0053), wherein the plurality of identifier elements is associated with a plurality of medical devices (see para. 0030-0033), and wherein the plurality of identifier elements encapsulates a plurality of identifiers associated a plurality of types of the plurality of medical devices (see para. 0030-0033 and 0050); and determining, with the at least one processor, based on the plurality of identifier elements determined in the plurality of images, the plurality of types of the plurality of medical devices and a plurality of locations of the plurality of medical devices within the environment over the period of time (see para. 0050 and 0053). Since Isaacson discloses that the system comprises a processor for obtaining identifier information for medication data for processing (see para. 00132), and Phillipe discloses an imagining system and processor for obtaining identifier information of medical devices within the system to determine the type of medical devices therein (see para. 0050), it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method and its processor taught by Isaacson to incorporate a camera and programming method for image analysis to determine the locations of medical devices and the types of medical devices based upon identifier elements as taught by Philippe such that the method of Isaacson would incorporate a camera for taking images of the medication source systems (102) to determine the presence and types of medical devices based upon identifier elements therein. Philippe teaches that the use of a computerized imaging system is beneficial as it provides a “hands-off” system for use by health care personnel which reduces health-care personnel responsibilities and avoids contamination by maintaining a sterile environment with less touching of medical devices (see para. 0036). Regarding claim 30 , modified Isaacson discloses the method of claim 29, as discussed above. In modified Isaacson, Phillipe discloses (Claim 30) wherein the plurality of identifier elements includes at least one identifier element including at least one of the following types of identifier elements: a colored pattern, a reflective pattern, a fluorescent pattern, a predetermined shape and color, a LED pattern, a barcode, or any combination thereof (see para. 0032-0033) . 07-21-aia AIA Claim (s) 11 and 31 are rejected under 35 U.S.C. 103 as being unpatentable over Isaacson in view of Sathe (U.S Patent Pub. No. 20160089530 A1) . Regarding claim 11 , Isaacson discloses the system of claim 1, as discussed above. However, Isaacson fails to disclose (Claim 11) further comprising: one or more image capture devices configured to capture, over a period of time, a plurality of images of an environment surrounding the one or more image capture devices; wherein the at least one processor is further programmed and/or configured to: determine, based on the plurality of images, a plurality of locations of a plurality of medical devices within the environment over the period of time and a plurality of types of the plurality of medical devices; determine, based on the plurality of locations of the plurality of medical devices within the environment over the period of time, a plurality of distances between the plurality of medical devices over the period of time; determine, based on the plurality of distances between the plurality of medical devices over the period of time and the plurality of types of the plurality of medical devices, at least one event of the following events: (i) a connection of a first medical device of the plurality of medical devices to a second medical device of the plurality of medical devices and (ii) a disconnection of the first medical device of the plurality of medical devices from the second medical device of the plurality of medical devices; and determine, based on the at least one determined event, at least a portion of the VAM data associated with the vascular access treatment associated with the patient. Sathe discloses a medical device cap system and method for tracking connection information about the system (See Abstract), Sathe teaches (Claim 11) further comprising: one or more image capture devices (180 in Fig. 3) configured to capture, over a period of time, a plurality of images of an environment surrounding the one or more image capture devices (see Fig. 3 and para. 0037 – barcode scanner 180 captures a plurality of images of a medical device cap 40 and connected medical device over a period of time of use of the cap 40); wherein the at least one processor is further programmed and/or configured to (see para. 0036 – cap 40 and scanner 180 have processing capabilities as they record, transmit, and determine compliance information from the barcode label 56 of cap 40): determine, based on the plurality of images, a plurality of locations of a plurality of medical devices within the environment over the period of time and a plurality of types of the plurality of medical devices (see para. 0036-0039 – the processor determines based on the scanner 180’s images, a location of the cap 40 relative to the location of the medical device component for connection over a period of time, see para. 0055 – the processor may further determine type of medical cap information from the images such as the engagement mechanism); determine, based on the plurality of locations of the plurality of medical devices within the environment over the period of time, a plurality of distances between the plurality of medical devices over the period of time (see para. 0037 – the processor determines whether the medical device cap 40 is connected or disconnected to the corresponding medical device component using the plurality of images from scanner 180 and thus determines a plurality of distances, i.e. connected or disconnected, between the cap 40 and corresponding medical device component based upon the corresponding location of said devices); determine, based on the plurality of distances between the plurality of medical devices over the period of time and the plurality of types of the plurality of medical devices, at least one event of the following events: (i) a connection of a first medical device (40) of the plurality of medical devices to a second medical device of the plurality of medical devices and (ii) a disconnection of the first medical device (40) of the plurality of medical devices from the second medical device of the plurality of medical devices (see Fig. 3 and para. 0037); and determine, based on the at least one determined event, at least a portion of the data associated with the treatment associated with the patient (see para. 0037 and 0040 – the connection or disconnection event determines duration of cap use, frequency of cap use, and tracking of the cap which are associated with the IV treatment). Since Isaacson discloses an IV treatment having needleless connectors (214), and Sathe discloses an IV treatment having an IV access port (see Fig. 3) and a medical device cap (40), wherein the locations and connection/disconnection between the port and cap can be tracked using a barcode scanner, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system and its processor taught by Isaacson to incorporate a medical device cap, barcode scanner, and programming method for image analysis to determine the locations of medical devices, distances therebetween, and connection or disconnection events as taught by Sathe such that the system of Isaacson would incorporate a barcode scanner for taking images of the medication source systems (102) to determine the locations of the medical device caps relative to the needleless connectors (214), distances therebetween, and connection or disconnection events therebetween. Sathe discloses that use of a trackable medical device cap results in better compliance and leads to reduced incidents of catheter related blood stream infections related to medical device component contamination (see para. 0039). Regarding claim 31 , Isaacson discloses the method of claim 21, as discussed above. However, Isaacson fails to disclose (Claim 21) further comprising: capturing, with one or more image capture devices, over a period of time, a plurality of images of an environment surrounding the one or more image capture devices; determining, with at least one processor, based on the plurality of images, a plurality of locations of a plurality of medical devices within the environment over the period of time and a plurality of types of the plurality of medical devices; determining, with at least one processor, based on the plurality of locations of the plurality of medical devices within the environment over the period of time, a plurality of distances between the plurality of medical devices over the period of time; determining, with at least one processor, based on the plurality of distances between the plurality of medical devices over the period of time and the plurality of types of the plurality of medical devices, at least one event of the following events: (i) a connection of a first medical device of the plurality of medical devices to a second medical device of the plurality of medical devices and (ii) a disconnection of the first medical device of the plurality of medical devices from the second medical device of the plurality of medical devices; and determining, with at least one processor, based on the at least one determined event, at least a portion of the VAM data associated with the vascular access treatment associated with the patient. Sathe discloses a medical device cap system and method for tracking connection information about the system (See Abstract), Sathe teaches (Claim 21) further comprising: capturing, with one or more image capture devices (180 in Fig. 3), over a period of time, a plurality of images of an environment surrounding the one or more image capture devices (see Fig. 3 and para. 0037 – barcode scanner 180 captures a plurality of images of a medical device cap 40 and connected medical device over a period of time of use of the cap 40); determining, with at least one processor (see para. 0036 – cap 40 and scanner 180 have processing capabilities as they record, transmit, and determine compliance information from the barcode label 56 of cap 40), based on the plurality of images, a plurality of locations of a plurality of medical devices within the environment over the period of time and a plurality of types of the plurality of medical devices (see para. 0036-0039 – the processor determines based on the scanner 180’s images, a location of the cap 40 relative to the location of the medical device component for connection over a period of time, see para. 0055 – the processor may further determine type of medical cap information from the images such as the engagement mechanism); determining, with at least one processor, based on the plurality of locations of the plurality of medical devices within the environment over the period of time, a plurality of distances between the plurality of medical devices over the period of time (see para. 0037 – the processor determines whether the medical device cap 40 is connected or disconnected to the corresponding medical device component using the plurality of images from scanner 180 and thus determines a plurality of distances, i.e. connected or disconnected, between the cap 40 and corresponding medical device component based upon the corresponding location of said devices); determining, with at least one processor, based on the plurality of distances between the plurality of medical devices over the period of time and the plurality of types of the plurality of medical devices, at least one event of the following events: (i) a connection of a first medical device (40) of the plurality of medical devices to a second medical device of the plurality of medical devices and (ii) a disconnection of the first medical device (40) of the plurality of medical devices from the second medical device of the plurality of medical devices (see Fig. 3 and para. 0037); and determining, with at least one processor, based on the at least one determined event, at least a portion of the data associated with the treatment associated with the patient (see para. 0037 and 0040 – the connection or disconnection event determines duration of cap use, frequency of cap use, and tracking of the cap which are associated with the IV treatment). Since Isaacson discloses an IV treatment having needleless connectors (214), and Sathe discloses an IV treatment having an IV access port (see Fig. 3) and a medical device cap (40), wherein the locations and connection/disconnection between the port and cap can be tracked using a barcode scanner, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method and its processor taught by Isaacson to incorporate a medical device cap, barcode scanner, and programming method for image analysis to determine the locations of medical devices, distances therebetween, and connection or disconnection events as taught by Sathe such that the method of Isaacson would incorporate a barcode scanner for taking images of the medication source systems (102) to determine the locations of the medical device caps relative to the needleless connectors (214), distances therebetween, and connection or disconnection events therebetween. Sathe discloses that use of a trackable medical device cap results in better compliance and leads to reduced incidents of catheter related blood stream infections related to medical device component contamination (see para. 0039) 07-21-aia AIA Claim (s) 12, 14, 32, and 34 are rejected under 35 U.S.C. 103 as being unpatentable over Isaacson in view of Amanatullah et al. (U.S Patent Pub. No. 20200253683 A1, “Amanatullah”) . Regarding claim 12 , Isaacson discloses the system of claim 1, as discussed above. However, Isaacson fails to disclose (Claim 12) further comprising: a first identifier element associated with a medical device, wherein the first identifier element encapsulates a first identifier associated with the medical device; a second identifier element associated with a glove of a caregiver, wherein the second identifier element encapsulates a second identifier associated with the glove of the caregiver; one or more image capture devices configured to capture, over a period of time, a plurality of images of an environment surrounding the one or more image capture devices; and wherein the at least one processor is further programmed and/or configured to: determine, based on the plurality of images, the first identifier element associated with the medical device and the second identifier element associated with the glove of a caregiver; determine, based on the first identifier element in the plurality of images, the medical device and a location of the medical device within the environment over the period of time; determine, based on the second identifier element in the plurality of images, the glove of the caregiver and a location of the glove of the caregiver within the environment over the period of time; determine, based on the location of the medical device within the environment over the period of time and the location of the glove of the caregiver within the environment over the period of time and the location, at least one event associated with the medical device; and determine, based on the at least one determined event, at least a portion of the VAM data associated with the vascular access treatment associated with the patient. Amanatullah discloses a method for tracking objects within a surgical space (see Abstract), wherein Amanatullah teaches (Claim 12) further comprising: a first identifier element associated with a medical device (see para. 0027 – a QR code or barcode may be applied to a first medical device such as a surgical instrument), wherein the first identifier element encapsulates a first identifier associated with the medical device (see para. 0027 – the QR code or barcode would encapsulate a first identifier associated with said surgical instrument); a second identifier element associated with a glove of a caregiver (see para. a second QR code or barcode may be applied to the surgical gloves of the surgeon), wherein the second identifier element encapsulates a second identifier associated with the glove of the caregiver (see para. 0027 – the second QR code or barcode would encapsulate a second identifier associated with said surgical gloves); one or more image capture devices configured to capture, over a period of time, a plurality of images of an environment surrounding the one or more image capture devices (see para. 0024-0027 – the system may comprise cameras that can detect QR codes or barcodes in images captured over a period of time of the surgical environment); and wherein the at least one processor is further programmed and/or configured to (see para. 0011): determine, based on the plurality of images, the first identifier element associated with the medical device and the second identifier element associated with the glove of a caregiver (see para. 0009 and 0027 – computing system detects objects and surgical staff within the surgical space using the images from the camera and the QR codes or barcodes on said objects and staff); determine, based on the first identifier element in the plurality of images, the medical device and a location of the medical device within the environment over the period of time (see para. 0009 and 0027); determine, based on the second identifier element in the plurality of images, the glove of the caregiver and a location of the glove of the caregiver within the environment over the period of time (see para. 0009 and 0027); determine, based on the location of the medical device within the environment over the period of time and the location of the glove of the caregiver within the environment over the period of time and the location, at least one event associated with the medical device (see para. 0009 and 0027 – the location of the surgical instruments and glove of the caregiver can be used to determine injury risks within the surgical environment); and determine, based on the at least one determined event, at least a portion of the data associated with the treatment associated with the patient (see para. 0009 and 0013– said injury risks are used to determine prompts for safer handling). Since Isaacson discloses an IV treatment system comprising needle tips for insertion into vascular for infusion (see para. 0116), and Amanatullah discloses a surgical environment tracking system comprising a camera and computing system for determining distances between medical devices and surgeon staff to prevent injury, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system and its processor taught by Isaacson to incorporate a first identifier element on a medical device, a second identifier element on the glove of the caregiver, and programming method for image analysis to determine the locations of the medical device and the glove of the caregiver and an event associated with the medical device as taught by Amanatullah such that the needle or needless connector of Isaacson would comprise a first identifier element, the glove of the physician would comprise a second identifier element, and a camera and processor would together capture images and analyze them to determine injury risk due to the sharp needle. Amanatullah teaches a computer system that can calculate near-instantaneous probability of injury to surgical staff by a sharp or acute object based on its current packaging state, retention, and orientation, as extracted from a current image of the surgical space and initiate prompts to ensure safe handling of the said objects which makes for a more safe surgical environment (see para. 0013). Regarding claim 14, Isaacson discloses the system of claim 1, as discussed above. However, Isaacson fails to disclose (Claim 14) a package containing a medical device; one or more image capture devices configured to capture, over a period of time, a plurality of images of an environment surrounding the one or more image capture devices; and wherein the at least one processor is further programmed and/or configured to: determine, based on the plurality of images, a state of the package over the period of time; determine, based on the state of the package over the period of time, whether the medical device is removed from the package; and determine, based on a determination that the medical device is removed from the package, at least a portion of the VAM data associated with the vascular access treatment associated with the patient. Amanatullah discloses a method for tracking objects within a surgical space (see Abstract), wherein Amanatullah teaches (Claim 14) a package containing a medical device (see para. 0046 and 0065 – the surgical system may comprise a medical device such as a needle that is housed in a needle tray packaging); one or more image capture devices configured to capture, over a period of time, a plurality of images of an environment surrounding the one or more image capture devices (see para. 0020 and 0022 – the surgical system comprises a camera for capturing images of the space around said camera over time); and wherein the at least one processor is further programmed and/or configured to (see para. 0125): determine, based on the plurality of images, a state of the package over the period of time (see para. 0047 and 0066); determine, based on the state of the package over the period of time, whether the medical device is removed from the package (see para. 0047 and 0066); and determine, based on a determination that the medical device is removed from the package, at least a portion of the data associated with the treatment associated with the patient (see para. 0047 and 0066 – the computer system can determine based on the state of the packaging of the medical device a contamination risk and injury risk within the surgical space). Since Isaacson discloses an IV treatment system comprising needle tips for insertion into vascular for infusion (see para. 0116), and Amanatullah discloses a surgical environment tracking system comprising a camera and computing system for determining packaging states of medical devices such as needles, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system and its processor taught by Isaacson to incorporate a package containing the medical device, a camera, and programming method for image analysis to determine the packaging state of the medical device as taught by Amanatullah such that the needle of Isaacson would comprise a package and a camera and processor would together capture images and analyze them to determine injury risk or contamination risk due to the needle being removed from its packaging. Amanatullah teaches a computer system that can calculate near-instantaneous probability of injury to surgical staff by a sharp or acute object or contamination risk within the surgical space based on the medical device’s current packaging state, retention, and orientation, as extracted from a current image of the surgical space and initiate prompts to ensure safe and sterile handling of the said objects which makes for a more safe surgical environment (see para. 0012-0013). Regarding claim 32 , Isaacson discloses the method of claim 21, as discussed above. However, Isaacson fails to disclose (Claim 32) further comprising: capturing, with one or more image capture devices, over a period of time, a plurality of images of an environment surrounding the one or more image capture devices; determining, with the at least one processor, based on the plurality of images, a first identifier element associated with a medical device and a second identifier element associated with a glove of a caregiver, wherein the first identifier element encapsulates a first identifier associated with the medical device, and wherein the second identifier element encapsulates a second identifier associated with the glove of the caregiver; determining, with the at least one processor, based on the first identifier element in the plurality of images, the medical device and a location of the medical device within the environment over the period of time; determining, with the at least one processor, based on the second identifier element in the plurality of images, the glove of the caregiver and a location of the glove of the caregiver within the environment over the period of time; determining, with the at least one processor, based on the location of the medical device within the environment over the period of time and the location of the glove of the caregiver within the environment over the period of time, at least one event associated with the medical device; and determining, with the at least one processor, based on the at least one determined event, at least a portion of the VAM data associated with the vascular access treatment associated with the patient. Amanatullah discloses a method for tracking objects within a surgical space (see Abstract), wherein Amanatullah teaches (Claim 32) further comprising: capturing, with one or more image capture devices, over a period of time, a plurality of images of an environment surrounding the one or more image capture devices (see para. 0024-0027 – the system may comprise cameras that can detect QR codes or barcodes in images captured over a period of time of the surgical environment); determining, with the at least one processor (see para. 0011), based on the plurality of images, a first identifier element associated with a medical device and a second identifier element associated with a glove of a caregiver (see para. 0009 and 0027 – a QR code or barcode may be applied to a first medical device such as a surgical instrument, a second QR code or barcode may be applied to the surgical gloves of the surgeon, the computing system detects objects and surgical staff within the surgical space using the images from the camera and the QR codes or barcodes on said objects and staff); determining, with the at least one processor, based on the first identifier element in the plurality of images, the medical device and a location of the medical device within the environment over the period of time (see para. 0009 and 0027); determining, with the at least one processor, based on the second identifier element in the plurality of images, the glove of the caregiver and a location of the glove of the caregiver within the environment over the period of time (see para. 0009 and 0027); determining, with the at least one processor, based on the location of the medical device within the environment over the period of time and the location of the glove of the caregiver within the environment over the period of time, at least one event associated with the medical device (see para. 0009 and 0027 – the location of the surgical instruments and glove of the caregiver can be used to determine injury risks within the surgical environment); and determining, with the at least one processor, based on the at least one determined event, at least a portion of the data associated with the treatment associated with the patient (see para. 0009 and 0013– said injury risks are used to determine prompts for safer handling). Since Isaacson discloses an IV treatment system comprising needle tips for insertion into vascular for infusion (see para. 0116), and Amanatullah discloses a surgical environment tracking system comprising a camera and computing system for determining distances between medical devices and surgeon staff to prevent injury, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method and its processor taught by Isaacson to incorporate a first identifier element on a medical device, a second identifier element on the glove of the caregiver, and programming method for image analysis to determine the locations of the medical device and the glove of the caregiver and an event associated with the medical device as taught by Amanatullah such that the needle or needless connector of Isaacson would comprise a first identifier element, the glove of the physician would comprise a second identifier element, and a camera and processor would together capture images and analyze them to determine injury risk due to the sharp needle. Amanatullah teaches a computer system that can calculate near-instantaneous probability of injury to surgical staff by a sharp or acute object based on its current packaging state, retention, and orientation, as extracted from a current image of the surgical space and initiate prompts to ensure safe handling of the said objects which makes for a more safe surgical environment (see para. 0013). Regarding claim 34, Isaacson discloses the method of claim 21, as discussed above. However, Isaacson fails to disclose (Claim 34) a package containing a medical device; one or more image capture devices configured to capturing, with one or more image capture devices, over a period of time, a plurality of images of an environment surrounding the one or more image capture devices; and determining, with the at least one processor, based on the plurality of images, a state of the package over the period of time; determining, with the at least one processor, based on the state of the package over the period of time, whether the medical device is removed from the package; and determining, with the at least one processor, based on a determination that the medical device is removed from the package, at least a portion of the VAM data associated with the vascular access treatment associated with the patient. Amanatullah discloses a method for tracking objects within a surgical space (see Abstract), wherein Amanatullah teaches (Claim 34) a package containing a medical device (see para. 0046 and 0065 – the surgical system may comprise a medical device such as a needle that is housed in a needle tray packaging); one or more image capture devices configured to capturing, with one or more image capture devices, over a period of time, a plurality of images of an environment surrounding the one or more image capture devices (see para. 0020 and 0022 – the surgical system comprises a camera for capturing images of the space around said camera over time); and determining, with the at least one processor (see para. 0125), based on the plurality of images, a state of the package over the period of time (see para. 0047 and 0066); determining, with the at least one processor, based on the state of the package over the period of time, whether the medical device is removed from the package (see para. 0047 and 0066); and determining, with the at least one processor, based on a determination that the medical device is removed from the package, at least a portion of the data associated with the treatment associated with the patient (see para. 0047 and 0066 – the computer system can determine based on the state of the packaging of the medical device a contamination risk and injury risk within the surgical space). Since Isaacson discloses an IV treatment system comprising needle tips for insertion into vascular for infusion (see para. 0116), and Amanatullah discloses a surgical environment tracking system comprising a camera and computing system for determining packaging states of medical devices such as needles, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method and its processor taught by Isaacson to incorporate a package containing the medical device, a camera, and programming method for image analysis to determine the packaging state of the medical device as taught by Amanatullah such that the needle of Isaacson would comprise a package and a camera and processor would together capture images and analyze them to determine injury risk or contamination risk due to the needle being removed from its packaging. Amanatullah teaches a computer system that can calculate near-instantaneous probability of injury to surgical staff by a sharp or acute object or contamination risk within the surgical space based on the medical device’s current packaging state, retention, and orientation, as extracted from a current image of the surgical space and initiate prompts to ensure safe and sterile handling of the said objects which makes for a more safe surgical environment (see para. 0012-0013) . 07-21-aia AIA Claim (s) 13 and 33 are rejected under 35 U.S.C. 103 as being unpatentable over Isaacson in view of Burkholz et al. (U.S Patent Pub. NO. 20150209510 A1, “Burkholz”) . Regarding claim 13 , Isaacson discloses the system of claim 1, as discussed above. While Isaacson discloses that each medication source system (102) may comprise one or more manual fluid delivery system such as one or more syringes (see para. 0077), Isaacson fails to disclose (Claim 13) further comprising: one or more image capture devices configured to capture, over a period of time, a plurality of images of an environment surrounding the one or more image capture devices; and wherein the at least one processor is further programmed and/or configured to: determine, based on the plurality of images, a location of a plunger of a syringe relative to a barrel of the syringe in the environment over the period of time; determine, based on the location of the plunger of the syringe relative to the barrel of the syringe over the period of time, at least one fluid delivery from the syringe; and determine, based on the at least one determined fluid delivery, at least a portion of the VAM data associated with the vascular access treatment associated with the patient. Burkholz discloses a system and method for obtaining fluid delivery information from a syringe using image analysis (see Abstract), wherein Burkholz teaches (Claim 13) further comprising: one or more image capture devices (12 in Fig. 1) configured to capture, over a period of time, a plurality of images of an environment surrounding the one or more image capture devices (12, see Fig. 1, para. 0047, 0054, and 0061 – digital camera 12 is configured to capture a plurality of images of a pre-filled syringe 28 over a course of time of its delivery operation); and wherein the at least one processor is further programmed and/or configured to (see para. 0052): determine, based on the plurality of images, a location of a plunger (32 in Fig. 1) of a syringe (18 in Fig. 1) relative to a barrel of the syringe (18) in the environment over the period of time (see para. 0058-0059); determine, based on the location of the plunger (32) of the syringe (18) relative to the barrel of the syringe (18) over the period of time, at least one fluid delivery from the syringe (18, see para. 0058-0059); and determine, based on the at least one determined fluid delivery, at least a portion of the VAM data associated with the vascular access treatment associated with the patient (see para. 0058-0059 and 0061 – the plunger location information and determined fluid delivery may be used to determine at least the time of injection). Since Isaacson discloses an IV treatment system comprising one or more syringes for delivery of the drug, and Burkholz discloses an image-based tracking system for tracking fluid delivery from a syringe using a camera, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system and its processor taught by Isaacson to incorporate an identifier on the plunger of the syringe, camera, and programming method for image analysis to determine the location of the plunger in the syringe and at least one fluid delivery from said syringe as taught by Burkholz. Burkholz teaches that the image-based tracking system for drug delivery from a syringe reduces the risk of medication infusion and delivery error and improves clinical workflow for identifying, confirming, and documenting fluid delivery of medication to patients in real-time and at the clinical point of use (see para. 0010). Regarding claim 33 , Isaacson discloses the method of claim 21, as discussed above. While Isaacson discloses that each medication source system (102) may comprise one or more manual fluid delivery system such as one or more syringes (see para. 0077), Isaacson fails to disclose (Claim 33) further comprising: capturing, with one or more image capture devices, over a period of time, a plurality of images of an environment surrounding the one or more image capture devices; and determining, with the at least one processor, based on the plurality of images, a location of a plunger of a syringe relative to a barrel of the syringe in the environment over the period of time; determining, with the at least one processor, based on the location of the plunger of the syringe relative to the barrel of the syringe over the period of time, at least one fluid delivery from the syringe; and determining, with the at least one processor, based on the at least one determined fluid delivery, at least a portion of the VAM data associated with the vascular access treatment associated with the patient. Burkholz discloses a system and method for obtaining fluid delivery information from a syringe using image analysis (see Abstract), wherein Burkholz teaches (Claim 33) further comprising: capturing, with one or more image capture devices (12 in Fig. 1) over a period of time, a plurality of images of an environment surrounding the one or more image capture devices (12, see Fig. 1, para. 0047, 0054, and 0061 – digital camera 12 is configured to capture a plurality of images of a pre-filled syringe 28 over a course of time of its delivery operation); determining, with the at least one processor (see para. 0052), based on the plurality of images, a location of a plunger (32 in Fig. 1) of a syringe (18 in Fig. 1) relative to a barrel of the syringe (18) in the environment over the period of time (see para. 0058-0059); determining, with the at least one processor, based on the location of the plunger (32) of the syringe (18) relative to the barrel of the syringe (18) over the period of time, at least one fluid delivery from the syringe (18, see para. 0058-0059); and determining, with the at least one processor, based on the at least one determined fluid delivery, at least a portion of the VAM data associated with the vascular access treatment associated with the patient (see para. 0058-0059 and 0061 – the plunger location information and determined fluid delivery may be used to determine at least the time of injection). Since Isaacson discloses an IV treatment system comprising one or more syringes for delivery of the drug, and Burkholz discloses an image-based tracking system for tracking fluid delivery from a syringe using a camera, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method and its processor taught by Isaacson to incorporate an identifier on the plunger of the syringe, camera, and programming method for image analysis to determine the location of the plunger in the syringe and at least one fluid delivery from said syringe as taught by Burkholz. Burkholz teaches that the image-based tracking system for drug delivery from a syringe reduces the risk of medication infusion and delivery error and improves clinical workflow for identifying, confirming, and documenting fluid delivery of medication to patients in real-time and at the clinical point of use (see para. 0010) . 07-21-aia AIA Claim (s) 20 and 40 are rejected under 35 U.S.C. 103 as being unpatentable over Isaacson in view of Brand et al. (W.O Patent Pub. No. 2020163297 A1, “Brand”) . Regarding claim 20 , Isaacson discloses the system of claim 1, as discussed above. Isaacson further discloses the limitations of (Claim 20) a needleless connector (214 in Fig. 4A-5C) including a fluid flow path and a septum (408 in Fig. 4A, see para. 0090). However, Isaacson fails to disclose (Claim 20) an optical sensor connected to the needleless connector, wherein the optical sensor is configured to detect a movement of the septum, wherein the at least one processor is further programmed and/or configured to: receive, from the optical sensor, a signal associated with the movement of the septum; determine, based on the signal, an event associated with the needleless connector; and determine, based on the determined event associated with the needleless connector, at least a portion of the VAM data associated with the vascular access treatment associated with the patient. Brand discloses a similar IV treatment system (100 in Fig. 1) comprising a plurality of medication source systems (102 in Fig. 1) each having smart devices (104 in Fig. 1) and needleless connectors (214 in Fig. 2A), wherein Brand teaches (Claim 20) a needleless connector (214 in Fig. 4A-5C) including a fluid flow path and a septum (408 in Fig. 4A, see para. 00155); an optical sensor connected to the needleless connector (see para. 00234 - sensor 254 connected to connector 214 may be an optical sensor), wherein the optical sensor is configured to detect a movement of the septum (408, see para. 00234), wherein the at least one processor is further programmed and/or configured to (see para. 00145-00146 – within system 100 for managing IV treatments, subsystems in the form of medication source systems 102 each include controllers 204 having processors for carrying out programs and each subsystem 102 having smart devices 104 with processors for carrying out programs, examiner is interpreting the processor as a combination of the processors within the subsystem 102): receive, from the optical sensor, a signal associated with the movement of the septum (408, see para. 00234); determine, based on the signal, an event associated with the needleless connector (214, see para. 0053 and 00234 – processor determines an event occurred with the needless connector 214); and determine, based on the determined event associated with the needleless connector (214), at least a portion of the VAM data associated with the vascular access treatment associated with the patient (see para. 00234 – processor further determines based on the occurred event whether the needleless connector 214 was connected or disconnected from the medical device which is data associated with the IV treatment). Since Isaacson discloses an IV system comprising needless connectors having sensors in communication with processors for determining data related to the IV treatment, and Brand discloses a very similar IV system comprising needleless connectors having sensors in communication with processors for determining data related to the IV treatment, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the needless connector and the system’s processor taught by Isaacson to incorporate an optical sensor and programming for determining movement of the optical sensor for further determining treatment data as taught by Brand. Brand teaches an optical sensor within the needleless connector can detect movement of the septum which is used to determine if the connector was connected or disconnected from a medical device and provides insight into the IV treatment (see para. 00234). Regarding claim 40 , Isaacson discloses the method of claim 21, as discussed above. Isaacson further discloses the limitations of (Claim 40) a needleless connector (214 in Fig. 4A-5C) including a fluid flow path and a septum (408 in Fig. 4A, see para. 0090). However, Isaacson fails to disclose (Claim 40) measuring, with an optical sensor connected to the needleless connector, a movement of the septum; receiving, with the at least one processor, from the optical sensor, a signal associated with the movement of the septum; determining, with the at least one processor, based on the signal, an event associated with the needleless connector; and determining, with the at least one processor, based on the determined event associated with the needleless connector, at least a portion of the VAM data associated with the vascular access treatment associated with the patient. Brand discloses a similar IV treatment system (100 in Fig. 1) comprising a plurality of medication source systems (102 in Fig. 1) each having smart devices (104 in Fig. 1) and needleless connectors (214 in Fig. 2A), wherein Brand teaches (Claim 40) measuring, with an optical sensor connected to a needleless connector (214 in Fig. 4A-5C) including a fluid flow path and a septum (408 in Fig. 4A, see para. 00155 and 00234), a movement of the septum (408, see para. 00234) receiving, with the at least one processor (see para. 00145-00146 – within system 100 for managing IV treatments, subsystems in the form of medication source systems 102 each include controllers 204 having processors for carrying out programs and each subsystem 102 having smart devices 104 with processors for carrying out programs, examiner is interpreting the processor as a combination of the processors within the subsystem 102), from the optical sensor, a signal associated with the movement of the septum (408, see para. 00234); determining, with the at least one processor, based on the signal, an event associated with the needleless connector (214, see para. 0053 and 00234 – processor determines an event occurred with the needless connector 214); and determining, with the at least one processor, based on the determined event associated with the needleless connector (214), at least a portion of the VAM data associated with the vascular access treatment associated with the patient (see para. 00234 – processor further determines based on the occurred event whether the needleless connector 214 was connected or disconnected from the medical device which is data associated with the IV treatment). Since Isaacson discloses an IV system comprising needless connectors having sensors in communication with processors for determining data related to the IV treatment, and Brand discloses a very similar IV system comprising needleless connectors having sensors in communication with processors for determining data related to the IV treatment, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the needless connector and the method’s processor taught by Isaacson to incorporate an optical sensor and programming for determining movement of the optical sensor for further determining treatment data as taught by Brand. Brand teaches an optical sensor within the needleless connector can detect movement of the septum which is used to determine if the connector was connected or disconnected from a medical device and provides insight into the IV treatment (see para. 00234). Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to KAYLA MARIE TURKOWSKI whose telephone number is (703)756-4680. The examiner can normally be reached Mon – Thurs, 7:00 AM – 4 :00 PM EST . Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Bhisma Mehta can be reached at 571-272-3383. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /KAYLA M. TURKOWSKI/Examiner, Art Unit 3783 /COURTNEY FREDRICKSON/Primary Examiner, Art Unit 3783 Application/Control Number: 18/694,777 Page 2 Art Unit: 3783 Application/Control Number: 18/694,777 Page 3 Art Unit: 3783 Application/Control Number: 18/694,777 Page 4 Art Unit: 3783 Application/Control Number: 18/694,777 Page 5 Art Unit: 3783 Application/Control Number: 18/694,777 Page 6 Art Unit: 3783 Application/Control Number: 18/694,777 Page 7 Art Unit: 3783 Application/Control Number: 18/694,777 Page 8 Art Unit: 3783 Application/Control Number: 18/694,777 Page 9 Art Unit: 3783 Application/Control Number: 18/694,777 Page 10 Art Unit: 3783 Application/Control Number: 18/694,777 Page 11 Art Unit: 3783 Application/Control Number: 18/694,777 Page 12 Art Unit: 3783 Application/Control Number: 18/694,777 Page 13 Art Unit: 3783 Application/Control Number: 18/694,777 Page 14 Art Unit: 3783 Application/Control Number: 18/694,777 Page 15 Art Unit: 3783 Application/Control Number: 18/694,777 Page 16 Art Unit: 3783 Application/Control Number: 18/694,777 Page 17 Art Unit: 3783 Application/Control Number: 18/694,777 Page 18 Art Unit: 3783 Application/Control Number: 18/694,777 Page 19 Art Unit: 3783 Application/Control Number: 18/694,777 Page 20 Art Unit: 3783 Application/Control Number: 18/694,777 Page 21 Art Unit: 3783 Application/Control Number: 18/694,777 Page 22 Art Unit: 3783 Application/Control Number: 18/694,777 Page 23 Art Unit: 3783 Application/Control Number: 18/694,777 Page 24 Art Unit: 3783 Application/Control Number: 18/694,777 Page 25 Art Unit: 3783 Application/Control Number: 18/694,777 Page 26 Art Unit: 3783 Application/Control Number: 18/694,777 Page 27 Art Unit: 3783 Application/Control Number: 18/694,777 Page 28 Art Unit: 3783 Application/Control Number: 18/694,777 Page 29 Art Unit: 3783 Application/Control Number: 18/694,777 Page 30 Art Unit: 3783 Application/Control Number: 18/694,777 Page 31 Art Unit: 3783 Application/Control Number: 18/694,777 Page 32 Art Unit: 3783 Application/Control Number: 18/694,777 Page 33 Art Unit: 3783 Application/Control Number: 18/694,777 Page 34 Art Unit: 3783 Application/Control Number: 18/694,777 Page 35 Art Unit: 3783 Application/Control Number: 18/694,777 Page 36 Art Unit: 3783 Application/Control Number: 18/694,777 Page 37 Art Unit: 3783 Application/Control Number: 18/694,777 Page 38 Art Unit: 3783 Application/Control Number: 18/694,777 Page 39 Art Unit: 3783 Application/Control Number: 18/694,777 Page 40 Art Unit: 3783 Application/Control Number: 18/694,777 Page 41 Art Unit: 3783 Application/Control Number: 18/694,777 Page 42 Art Unit: 3783 Application/Control Number: 18/694,777 Page 43 Art Unit: 3783 Application/Control Number: 18/694,777 Page 44 Art Unit: 3783 Application/Control Number: 18/694,777 Page 45 Art Unit: 3783 Application/Control Number: 18/694,777 Page 46 Art Unit: 3783 Application/Control Number: 18/694,777 Page 47 Art Unit: 3783 Application/Control Number: 18/694,777 Page 48 Art Unit: 3783 Application/Control Number: 18/694,777 Page 49 Art Unit: 3783 Application/Control Number: 18/694,777 Page 50 Art Unit: 3783 Application/Control Number: 18/694,777 Page 51 Art Unit: 3783 Application/Control Number: 18/694,777 Page 52 Art Unit: 3783 Application/Control Number: 18/694,777 Page 53 Art Unit: 3783 Application/Control Number: 18/694,777 Page 54 Art Unit: 3783 Application/Control Number: 18/694,777 Page 55 Art Unit: 3783 Application/Control Number: 18/694,777 Page 56 Art Unit: 3783 Application/Control Number: 18/694,777 Page 57 Art Unit: 3783 Application/Control Number: 18/694,777 Page 58 Art Unit: 3783 Application/Control Number: 18/694,777 Page 59 Art Unit: 3783 Application/Control Number: 18/694,777 Page 60 Art Unit: 3783 Application/Control Number: 18/694,777 Page 61 Art Unit: 3783 Application/Control Number: 18/694,777 Page 62 Art Unit: 3783 Application/Control Number: 18/694,777 Page 63 Art Unit: 3783 Application/Control Number: 18/694,777 Page 64 Art Unit: 3783 Application/Control Number: 18/694,777 Page 65 Art Unit: 3783 Application/Control Number: 18/694,777 Page 66 Art Unit: 3783 Application/Control Number: 18/694,777 Page 67 Art Unit: 3783 Application/Control Number: 18/694,777 Page 68 Art Unit: 3783 Application/Control Number: 18/694,777 Page 69 Art Unit: 3783 Application/Control Number: 18/694,777 Page 70 Art Unit: 3783 Application/Control Number: 18/694,777 Page 71 Art Unit: 3783 Application/Control Number: 18/694,777 Page 72 Art Unit: 3783 Application/Control Number: 18/694,777 Page 73 Art Unit: 3783 Application/Control Number: 18/694,777 Page 74 Art Unit: 3783 Application/Control Number: 18/694,777 Page 75 Art Unit: 3783 Application/Control Number: 18/694,777 Page 76 Art Unit: 3783
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