CareFusion 303, Inc. - [2024] APO 50

IP AUSTRALIA
AUSTRALIAN PATENT OFFICE
CareFusion 303, Inc. [2024] APO 50
Patent Application: 2019218793

Title:Pharmacy predictive analytics

Patent Applicant:                   CareFusion 303, Inc.
Delegate:  Andrew Burgess
Decision Date:  6 December 2024
Hearing Date:  Written submissions filed on 13 August 2024

Catchwords: PATENTS – Examiner objection – section 45 and 49 – manner of manufacture – predication of medical prescription – use of locator to update location – administrative and logistics scheme – invention not to a manner of manufacture – no patentable subject matter disclosed – application refused

Representation: Patent attorney for the applicant: FB Rice Pty Ltd

IP AUSTRALIA
AUSTRALIAN PATENT OFFICE
Patent Application: 2019218793

Title:Pharmacy predictive analytics

Patent Applicant: CareFusion 303, Inc
Date of Decision: 6 December 2024
DECISION
The invention defined in each of claims 1-17 as proposed to be amended is not a manner of manufacture. Furthermore, after consideration of the material disclosed in the specification as a whole, I am of the opinion that no allowable amendment can overcome this finding. In light of this, I have not decided with respect to inventive step.
I refuse the application.
REASONS FOR DECISION
Background

Patent application 2019218793 (the application) was filed by CareFusion 303, Inc (the Applicant) on 07 February 2019 under the provisions of the Patent Cooperation Treaty. The application claims priority from US15/891809 which was filed on 08 February 2018, and entered national phase in Australia on 29 July 2020.
On 02 February 2022, the Applicant requested expedited examination. A first examination report was issued on 27 January 2023, objecting on the grounds of lack of manner of manufacture and lack of inventive step. The Applicant filed amendments (the first amendment) and responding comments on 27 September 2023. A second examination report issued on 25 October 2023, maintaining objections of lack of manner of manufacture and inventive step, and in addition objecting that the first amendment was not allowable. The Applicant filed further amendments (the second amendment) and responding comments on 08 December 2023. A third examination report was issued on 12 January 2024, maintaining objections of lack of manner of manufacture and inventive step. The Applicant filed further amendments (the third amendment) and responding comments on 23 January 2024. On 29 January 2024, the Applicant called the examiner to see if the third amendment would be successful, but the examiner advised that there would not be time to consider the response in full within the remaining time. On the same day, the Applicant requested to be heard in relation to the outstanding objections from the third examination report.
The Applicant filed their written submissions (Applicant’s submissions or AS) on 13 August 2024.
Applicable Law and the Standard of Proof
The examination of the present application is governed by the Patents Act 1990 (the Act) as amended by the Intellectual Property Laws Amendment (Raising the Bar) Act 2012 (the Raising the Bar Act). The standard of proof that applies to the examination of the present application is therefore the balance of probabilities.
I must accept the patent request and complete specification under Section 49 if I am satisfied, on the balance of probabilities, that it complies with the requirements set forth in that section, which includes, inter alia, the requirements of Section 18(1)(a) and (b). If I am not so satisfied, I may refuse the application. However, I will only refuse the application if I am also satisfied that providing the Applicant with an opportunity to amend will serve no useful purpose; for example, if I consider that any potential negative findings are not rectifiable by an allowable amendment.
The amendments
As noted above, there have been three sets of amendments filed during the examination period, with the examiner objecting that the first amendment was not allowable, but this was not maintained in the third examination report.
In general, in the remainder of this decision I will be referring to the specification and claims as proposed to be amended by the third amendment. That is, for the purposes of this decision, the specification comprises pages 1-21 of the description as filed on 23 January 2024, pages 22-26 of the claims as filed on 23 January 2024, and pages 1/5 to 5/5 of the drawings as PCT pamphlet as originally filed.
The invention as described
The specification is directed to the field of medication inventory management, particularly in the context of health care facilities. While it is not exclusively directed to hospitals, as I will expand on below, the invention appears to be premised around the idea that the care facility will comprise both central medication storage or pharmacies, and local storage cabinets.
According to the specification, the existing medication storage systems for health care facilities have certain problems, in particular related to inventory management. They utilise “patient care area based cabinets” (for brevity, area cabinets) which are located close to the point of need (not specifically described, but I assume this refers to wards of the hospital, specialist care areas, etc.). The specification refers to one prior medication management system as the “all medications model”[1], which involves stocking 90-95% of the “typical” prescribing needs in the area cabinets, which is said to result in up to 20% of the stored medications in each cabinet being “not typically prescribed” in that given area, resulting in up to 10% of stored medications ultimately expiring unused. That is, the specification seems to be suggesting that in the prior art, all area cabinets are identically stocked, regardless of what might be needed in some areas but not others. Relatedly, because the area cabinet is partially filled with medications which will only rarely be prescribed in the given care area, the cabinet has less room for those prescriptions which are needed in that care area. If a patient requires a medication that is not stored in the area cabinet, it must be ordered in from a centralised pharmacy, which creates delays, costs, and reduced patient outcomes.
[1] Specification at [0015].
At its broadest level, the invention relates to stocking each area cabinet with a mixture of medications based around what is predicted to be the likely prescriptions in that area. The invention also replaces the area cabinets with “automated dispensing machines” (for brevity, ADM). A concise summary of the invention is provided as:
“In a second embodiment, a computer-implemented method includes retrieving a personal information from a patient upon admission of the patient to a healthcare facility, wherein the personal information includes a symptom. The computer-implemented method includes retrieving a diagnostic based on the symptom and determining an anticipated medication prescription for the patient based on the personal information for the patient, on the diagnostic, and on a medication prescribing pattern stored in a memory. The computer-implemented method also includes prompting a delivery and storing of a first dose and subsequent supply of a medication from the anticipated medication prescription in an automated dispensing machine.”[2]
[2] Specification at [0004]
The first embodiment and further embodiments of the invention are broadly similar, but the computer implemented method uses additional or differently stratified data in order to determine an anticipated medication prescription.
The preferred embodiment of the invention may be described by reference to Figure 1:
The ADM 110 comprises a cabinet having several computer lockable storage drawers 115-1 etc., which include containers of medications. The containers are tagged and tracked (for example by RFID tags[3]), and the drawers are locked/unlocked in response to signals from processor 12.
[3] Specification at [0017]
The medications stored in the ADM are determined by the centralized pharmacy server 130. This contains memory 40 comprising certain sets of data:
·Physician data 43 includes a list of physicians and their associated history of medical prescriptions. The physician data may be further stratified by symptoms, diagnosis, care area, and “geographical area”[4].
·Patient data 45 includes a range of information about patients, such as demographic data (age, ethnicity) and diagnostic information[5]. It is not entirely clear to me from the specification, but patient data may also include prior prescription information.
·Medication data 47 includes inventory of all medications in the system, and frequency of prescribing of those medications, and a list of patients associated with each medication.
[4] Specification at [0018]
[5] Ibid
For brevity, I will refer to physician data, patient data, and medication data collectively as “historical data”.
The core of the current invention relates to the predictive algorithm 49. This predictive algorithm is also variously referred to or exemplified as an intelligence engine, or neural network[6]. While the specification dedicates several pages to describing the general concept of a computer capable of running software[7], the predictive algorithm itself is simply described by way of a general reference to neural networks, possible training inputs, and desired outputs[8]. The predictive algorithm is provided with the historical data summarised above, and determines (by any means) certain “prescription patterns”[9]. In the preferred form shown in Figure 1, the predictive algorithm is associated with the centralised pharmacy server, and appears largely independent of the ADM.
[6] Specification at [0019]
[7] Specification at pages 16-20, concisely summarised by the final sentence of [0049]: that the invention is “not limited to any specific combination of hardware circuitry or software.”
[8] Specification at [0019]
[9] Ibid
The specification does not define exactly what is meant by prescription patterns. The input data for the predictive algorithm is already stratified in various ways: by care area, by patient diagnosis, by prescribing physician, etc,. This suggests that, at its broadest, the “prescription patterns” determined by the algorithm may simply be “the most common in each care area” or “the most common prescription for each symptom”. In a more complex form, the prescription pattern appears to be essentially a weighting derived by the neural network, that may be used to predict a prescription based on a number of input parameters (e.g. location, physician, and symptom). The specification notes that the patterns may change over seasons, or in response to events (such as disease outbreaks).
These prescription patterns determined by the predictive algorithm are then stored in a “computerised physician order entry database” (CPOE), which contains records of prescription patterns aggregated over a period of several years[10]. At this point, the foreshadowed conceptual imprecision arises. The specification states that the CPOE may (also? alternatively?) contain prescription data associated with physicians/symptoms/care facility, which may be used to train the predictive algorithm[11]. While this prescription data stored on the CPOE is described differently (in that it is only minimally described), it appears to be essentially the same as what I refer to as the historical data stored in the pharmacy server 130.
[10] Specification at [0020]-[0021]
[11] Specification at [0024]
The invention has three broad modes of operation. In the first, it may be used to determine the initial stocking 200 for the ADM, which is described by reference to Figures 2 and 3.
The CPOE 170, centralised pharmacy server 130, ADM 110, and individual drawers 115 are the same as discussed above. The goal of this mode of operation is to provide the highest probability that any medication prescribed for a patient in the area of the cabinet will be available in the ADM[12]. The specification states that, as part of determining the stocking of the ADM, the predictive algorithm 49 uses information from the CPOE 170 to determine both the optimal contents and location 210 for the ADM[13]. The ADM may be re-stocked 300 on a routine basis[14]. During stocking, the system determines what medications should be added to or removed from the ADM[15]. Stocking / re-stocking may take account of the current location of the ADM, and the distribution of patients and/or location of individual patients[16].
[12] [0026]
[13] [0024]
[14] [0027]
[15] [0026]
[16] [0024]-[0025]
A second mode of operation the invention is demonstrated by reference to Figure 4.
In this method 400, when a patient is admitted to the health care facility, their diagnostic information is recorded by the system at step 402[17]. Diagnostic information is not expressly defined by the application, but would plainly include symptoms, and/or medical diagnosis of the patient at the time of admission. Step 402 may also record demographic information. While the specification specifically does not state it, it appears that the information collected at step 402 may be the same as (or at least very similar to) the information previously described as “patient data”. The distinction, if there is any, seems to be that the information taken at step 402 relates to a specific patient, while “patient data” may refer to an aggregate of data across all patients.
[17] [0029]
At step 404[18], the system retrieves physician information. Similar to the above, this appears to be the same/similar to the physician data previously described.
[18] [0030]
At step 406[19], an “anticipated medication prescription” is determined. In describing this step, the specification specifically does not make reference to the predictive algorithm, but instead simply uses a “medication prescribing pattern” that is stored “in memory” (which need not be in any specific location or device[20]) and the information collected in the previous steps. Step 406 may also factor in the location of the patient and the ADM. The specification states that the medication prescribing pattern may include a prescribing pattern of multiple physicians, and also that step 406 includes a history of medication prescriptions of the physicians (this blurs the distinction between prescription patterns and physician data). The specification further states that (emphasis added):
“In some embodiments, step 406 further includes unlocking a storage drawer in an automated dispensing machine for providing to a healthcare professional access to the medication, or for preplacement of the anticipated medication prescription. In some embodiments, step 406 includes locking the storage drawer until a professional healthcare provider places an order including the anticipated medication prescription.”[21]
[19] [0031]
[20] [0028]
[21] Specification at [0032]
Note that the phrase “places an order” is slightly ambiguous as to whether the order relates to a medication from within the ADM or from the central pharmacy, but since step 406 involves locking the drawer of the ADM until the order is placed (i.e., unlocking the drawer at that time), it seems that in the above quote “order” means ordering from the ADM, not from the centralised pharmacy. With that in mind, I take it what was meant was that the health care worker orders a medication from the ADM (for example, via the attached user interface), at which point the ADM unlocks the specified drawer.
Confusingly, while it is described as the last step in the process, step 408 does not relate to any of the foregoing steps. Rather, step 408 is related to the initial setup and stocking of the ADM. While it is described much more generally, step 408 appears broadly similar to the re-stocking method 300 described above.
A third mode of operation is discussed in reference to Figure 5.
Method 500 of the invention begins with the admission of a patent to the healthcare facility at step 502. Relevant patient data is recorded[22], which again, appears essentially the same as the patient data described previously. This is followed by steps 504 and 506, examining and diagnosing of the patient, and analysing said diagnosis. In the absence of any further details regarding this step, I presume these steps are performed by a physician or other qualified medical practitioner, in the traditional manner.
[22] [0035]
At step 508[23], two things happen in parallel or almost simultaneously. A physician prescribes a medication to the patient 508b [24], presumably in the ordinary way. Independently, a prediction is made at 508a “using analytics method as disclosed herein”. I assume that is a reference to method 400, or something similar. Step 508a is described as being deployed such that a medication may be placed in a location near the patient “prior to, or simultaneously with” step 508b.
[23] [0038]
[24] [0039]
The specification states that at step 510 and 512 that:
“Step 510 includes storing the medication. In some embodiments, step 510 includes locking a storage drawer in the automated dispensing machine by actuating an electronic latch for a lid in the storage drawer.
Step 512 includes delivering, by a nurse or other healthcare professional, the selected prescription medication to a patient. In some embodiments, step 512 includes unlocking a storage drawer in the automated dispensing machine by actuating an electronic latch for a lid in the storage drawer.”[25]
[25] [0040]-[0041]
I find it notable that steps 510 and 512 refer to “the medication” and “the selected prescription medication”, which implicitly assumes that the predicted prescription of 508a matches the prescription made by the physician 508b. There is no description of what happens if the predicted medication does not match the real prescription, or even of any step for checking to see if this is the case. Figure 5 implies that the physician prescription 508b somehow flows to or interacts with step 510, but the specification does not explain what this interaction entails.
I also note that, while the operation of the lockable drawers in 406, 510, and 512 are described as sequentially after the determining of a predicted prescription, it is not responsive to or triggered by the other steps in either process per se. The drawer is simply unlocked to provide access when access is required, which is after a medication is predicted/identified.
The invention as claimed
The proposed amendment to the claims includes 17 claims, of which claims 1, 9, and 14 are independent. A full list of the claims is included as an annex to this decision, but for present purposes it will suffice to consider claim 1 (reference integers added):
“1. A system, comprising:
a)   an automated dispensing machine of a healthcare facility;
b)   a locator device attached to the automated dispensing machine;
c)   a memory storing instructions; and
d)   a processor configured to execute the instructions to:
i.determine, from the locator device, an updated location of the automated dispensing machine;
ii.determine a new patient has been added to a patient roster of patients in the updated location of the automated dispensing machine;
iii.in response to determining the updated location and the new patient being added to the patient roster of patients in the updated location:
A.    retrieve a patient location of the new patient in the updated location of the automated dispensing machine;
B.     retrieve a diagnostic information for the new patient;
C.     retrieve historical medication prescribing patterns associated with an area corresponding to the updated location of the automated dispensing machine, at least one of the medication prescribing patterns being from a physician in charge of the patient;
D.    provide the updated location, the patient location retrieved by the processor, the diagnostic information for the new patient, and the historical medication prescribing patterns to a neural network;
E.     determine, from the neural network, an anticipated medication prescription for the patient based on providing to the neural network the updated location of the automated dispensing machine, the patient location retrieved by the processor, the diagnostic information, the historical medication prescribing patterns, and based on a medication being available through an approved formulary;
F.   prompt a delivery and storing of at least one dose of the determined anticipated medication prescription in the automated dispensing machine; and
G.    unlock a storage drawer in an automated dispensing machine for placement of the anticipated medication prescription.

For ease of reference, I will refer to a-d as “features”, i to iii as “instructions”, and A-G as “steps”.
Manner of Manufacture
Case law and legal principles
Subsection 18(1) of the Patents Act states, in part, that:
“Subject to subsection (2), an invention is a patentable invention for the purposes of a standard patent if the invention, so far as claimed in any claim:
(a)is a manner of manufacture within the meaning of section 6 of the Statute of Monopolies”
The concept of manner of manufacture has developed over time and is not readily reduced to a simple formula. The classic definition of manner of manufacture is set out in National Research Development Corporation v Commissioner of Patents[26] at [14]:
“The inquiry which the definition demands is an inquiry into the scope of the permissible subject matter of letters patent and grants of privilege protected by the section ... The right question is: ‘Is this a proper subject of letters patent according to the principles which have been developed for the application of s 6 of the Statute of Monopolies?’”
[26] [1959] HCA 67; 102 CLR 252 (NRDC)
More recently, there have been a number of Full Court decisions which considered some of the more specific considerations relevant to computer implemented inventions, relevantly including Research Affiliates LLC v Commissioner of Patents[27], Commissioner of Patents v RPL Central Pty Ltd[28], and Encompass Corporation Pty Ltd v Infotrack Pty Ltd[29]. In Research Affiliates, it was stated that (italics in original):
[27] [2014] FCAFC 150; 227 FCR 378 (Research Affiliates)
[28] [2015] FCAFC 177; 238 FCR 27 (RPL)
[29] [2019] FCAFC 161; 372 ALR 646 (Encompass)
“When the authorities in Australia prior to and including Grant are considered, a consistent approach emerges as to the relevance of:
·a distinction between a claim to a business scheme and claims to methods which in practice result in a new machine or process or an old machine giving a new and improved result – that is, a distinction between mere intellectual information and a method that affects the operation of an apparatus in a physical form ([Grant v Commissioner of Patents[30]] at [18]);
·the fact that the claimed steps are foreign to the normal use of computers, such as the production of an improved curve image ([International Business Machines Corporation v Commissioner of Patents[31]] at 225-226);
·the particular mode or manner of achieving an end result which is an artificially created state of affairs, such as the storage of data as to Chinese characters and retrieval of graphic representations to enable word processing (CCOM Pty Limited v Jiejing Pty Limited[32] at 295);
·whether part of the invention is an inventive method which includes the application and operation in a physical device (Grant at [30]);
·the distinction drawn in [Welcome Real-Time SA v Catuity Inc[33]], as explained in Grant (at [24]), between ‘a technological innovation which is patentable and a business innovation which is not’. In Catuity, Heerey J. did not accept that a physically observable effect was necessarily required (at [128]) but the Full Court in Grant expressed the opinion that a physical effect in the sense of a concrete effect or phenomenon, or manifestation or transformation is required (at [32]).
·the fact that a physical effect is required does not make it sufficient to confer patentability;
·the fact that a method may be called a business method does not prevent it being properly the subject of letters patent (Grant at [26] citing Catuity at [125]-[126]);
·the fact that for claimed computer programs, the courts look to the application of the program to produce a practical and useful result, so that more than ‘intellectual information’ is involved (Grant at [29]). A method that is in the nature of directions for use does not constitute an invention or a manner of manufacture in the absence of some previously unrecognised property of an aspect of the method (Grant at [29]).”[34]
[30] [2006] FCAFC 120; 154 FCR 62 (Grant)
[31] [1991] FCA 811; 33 FCR 218; 105 ALR 388 (IBM)
[32] (1994) 51 FCR 260 (CCOM)
[33] (2001) 113 FCR 110 (Catuity)
[34] Research Affiliates at [94].
This was expanded upon in RPL, which provides (emphasis added):
“A claimed invention must be examined to ascertain whether it is in substance a scheme or plan or whether it can broadly be described as an improvement in computer technology. The basis for the analysis starts with the fact that a business method, or mere scheme, is not, per se, patentable. The fact that it is a scheme or business method does not exclude it from properly being the subject of letters patent, but it must be more than that. There must be more than an abstract idea; it must involve the creation of an artificial state of affairs where the computer is integral to the invention, rather than a mere tool in which the invention is performed. Where the claimed invention is to a computerised business method, the invention must lie in that computerisation. It is not a patentable invention simply to ‘put’ a business method ‘into’ a computer to implement the business method using the computer for its well- known and understood functions.
Is the mere implementation of an abstract idea in a well-known machine sufficient to render patentable subject matter? Is the artificial effect that arises, because information is stored in RAM and there is communication over the Internet or Wi-Fi, sufficient? Does any physical effect give rise to a manner of manufacture? Are the mere presence of an artificial effect and economic utility, without more, sufficient to determine manner of manufacture?
It is not a question of stating precise guidelines but of deciding, in each case, whether the claimed invention, as a matter of substance not form, is properly the subject of a patent.
To reiterate some of the matters discussed in Research Affiliates:
·It is necessary to ascertain whether the contribution to the claimed invention is technical in nature. In Aerotel Ltd v Telco Holdings Ltd; Macrossan’s Application [2007], the subject matter was an interactive system whereby questions were asked, the answers incorporated in a draft and, depending on some particular answers, further questions were asked. It was held that, apart from the fact of running a computer program, there was nothing technical about the contribution and the method was for the business of advising upon and creating appropriate company documents.
·One consideration is whether the invention solves a “technical” problem within the computer or outside the computer, or whether it results in an improvement in the functioning of the computer, irrespective of the data being processed.
·Does the claimed method merely require generic computer implementation?
·Is the computer merely the intermediary, configured to carry out the method using a computer readable medium containing program code for performing the method, but adding nothing to the substance of the idea? In Alice Corporation, the method was for exchanging financial obligations in which the computer was used to create records, track multiple transactions and issue simultaneous instructions. The majority in the Supreme Court of the United States concluded that the use of the computer added nothing to the substance of the abstract idea of reducing settlement risk in exchanging financial obligations.”[35].
[35] RPL at [96]-[99].
Encompass summarised the process followed by RPL and Research Affiliates as (emphasis added):
“In each case, the Full Court was seeking to describe the conceptual distinction between a manner of manufacture and an unpatentable abstraction. In each case, the Full Court was explaining that a claimed method that is unpatentable does not change its legal character merely because the method is implemented by the instrumentality of a computer.”[36]
[36] Encompass at [91].
Similarly, in Commissioner of Patents v Rokt Pte Ltd[37] it was stated at [74] that:
“Secondly, as we have noted, the task of construing the specification involves arriving at a characterisation of the invention claimed in order to determine whether or not it is in substance for a manner of manufacture. That involves the application of the common law principles developed to separate patentable inventions from schemes or methods of business. The latter can, in the context of computer implementation, appear to be dressed in the clothes of invention. In each of Research Affiliates, RPL Central and Encompass, the Full Court found the computer implemented inventions not to be patentable; each was a case of the Emperor’s new clothes.”
[37] [2020] FCAFC 86; 277 FCR 267 (Rokt) at [74].
The Applicant’s submissions make significant repeated reference to Moshinsky J’s decision in UbiPark Pty Ltd v TMA Capital Australia Pty Ltd (No 2)[38]. The invention in UbiPark relates to an app for controlling access to a car park, and relevantly involved Bluetooth beacons arranged at entry and exit lanes of the car park and barriers at the entry and exit lanes, which was found to comprise patentable subject matter. As I will expand on below, the Applicant argues the current invention is analogous to UbiPark, but for now I will just note that in terms of the principles to be applied, Moshinsky J referred to and accepted the same authorities I refer to above[39].
[38] [2023] FCA 885 (UbiPark)
[39] Ibid at 197-198
Finally, the overarching theme was most succinctly put by Gageler and Nettle JJ in the Myriad case at [144]:
“Whatever words have been used, the matter must be looked at as one of substance and effect must be given to the true nature of the claim.”
Summary of Examiners Objection
Throughout all examination reports, the examiner has maintained that the claimed invention does not comprise a patentable manner of manufacture. The core of the examiner’s objection from the first report was that:
“The problem solved by the invention, i.e. the prediction of a patient's medication prescription, is not a technical problem. The technical features of the claimed invention, considered in combination, were generic in the art at the priority date. The claimed invention does not result in an improvement in the functioning of the computer, irrespective of the data processed. Rather, the contribution is in the particular data processed in association with the rules related to medication prediction. As such, the substance of the claimed invention amounts to an abstract scheme for predicting a patient's medication based on various collected data associated with the patient.
Therefore the claimed invention, as a matter of substance, does not define subject matter suitable for a patent.”[40]
[40] First examination report
As set out above, the Applicant responded with multiple rounds of submissions and amendments, but it is apparent from the third examination report that the Applicant’s efforts only marginally altered the examiners characterisation of the invention:
“Claims 1-17 do not define a manner of manufacture within the meaning of Section 18(1)(a) of the Patents Act 1990, as discussed in the previous examination reports for this case. In particular, the substance of the claimed invention amounts to a scheme for predicting a patient's medication based on various collected location-specific and diagnosis-specific data associated with the patient.”[41]
[41] Third examination report
Summary of the Applicant’s submission
I will expand below, but I consider the following passage of the Applicant’s submissions captures the core of the Applicant’s arguments:
“The examiner sets out in the first examination report several factors which the examiner asserts may be considered when determining the substance of the invention, including:
·How does the claimed invention work?
·What problem does it address?
·What is the result of performing the claimed invention?
·What was the state of the art as at the priority date?
·What does the claimed invention add to the state of the art?
·What are the advantages of the claimed invention?
Based on this framework, combined with a proper understanding of the problem solved by the invention, it becomes apparent that the invention addresses the problem of determining an updated location of a dispensing machine and appropriately updating the contents of the machine following relocation of the machine, with minimal user interaction. The invention uses technically implanted sensing of the physical location of the machine to trigger appropriate medication delivery to the machine to update and also to influence the physical behaviour of the machine in unlocking the drawer. As explained above with regard to inventive step, this physical configuration and system behaviour is clearly non-standard in the art of medication delivery systems at the priority date, which does not contemplate updating a mobile dispensing machine. The invention provides the advantage of ensuring that the machine remains adequately stocked, while minimising the need for a user to interact with the machine/system.”[42]
[42] AS at 32-33.
It is clear the initial point of divergence between the examiner and Applicant lies in the correct characterisation of the problem being addressed by the invention.
Does the invention solve a technical problem?
The examiner’s objection
As will be seen, the principal disagreement relates to the problem(s) addressed by the invention. The examiner objection relevantly argued that:
“The problem solved by the invention, i.e. the prediction of a patient's medication prescription, is not a technical problem. The technical features of the claimed invention, considered in combination, were generic in the art at the priority date.[43]
and (in response to certain interlocutory arguments presented by the applicant)
“You argue that ‘the predictions are made without any knowledge of the new patient’s history, including without knowledge of the patient’s own physician’s prescribing history which is a significant technical contribution to dispensing systems’. However I do not see that there is a technical contribution here. These features simply define the particular data which is used to make the prediction, without providing any technical contribution in actually making the prediction. The use of a generic neural network simply provides a ‘black box’ type solution, and therefore your invention simply recites a conceptual solution to the prediction problem. The substance of the invention lies in the data which is used to make the prediction, rather than in the prediction methodology itself.”[44]
and
“Para [0025] of the Specification discloses that ‘in some embodiments system 200 is configured to update the contents of automated dispensing machine 110 according to an updated location 210 of automated dispensing machine 110 (e.g., by a wireless locator or GPS attached to automated dispensing machine 110, or simply by updating information logged in the system and transmitted through network 150)’ while para [0017] discloses ‘locking and unlocking an electronic latch closing a lid in storage drawer 115’. These passages indicate that the technical implementation of these steps (determine location, lock/unlock the storage drawer) is entirely left to the person skilled in the art, hence cannot be considered to form the substance of the invention. Therefore, neither the problem (determining a medication inventory which assures that medications stored in the cabinets are the most commonly prescribed medication types), nor the solution (prediction of medications of a per-patient basis) is considered to be technical.”[45]
[43] First examination report
[44] Second examination report
[45] Third examination report
The Applicant’s submissions
The Applicant has submitted that (italics in original, bold emphasis added):
“The examiner’s conclusion with regard to the substance of the invention appears to be predicated on the problem identified by the examiner (determining a medication inventory which assures that medications stored in the cabinets are the most commonly prescribed medication type) and solution (prediction of medications of a per-patient basis), which the examiner argues are non-technical. However, as set out [in submissions regarding inventive step], we submit that this identification of the problem to be solved is not appropriate in view of the invention currently defined in the claims. Rather, the problem should be considered how to identify when a medication dispensing machine has been moved and to appropriately update the contents of the machine when the machine is moved. In this regard, the solution is provided by the claimed interrelationship between the physical aspects of the system and the medication prediction aspects.”[46]
[46] AS at 31
The relevant portion of the Applicant’s submissions on inventive step are (emphasis added):
“Paragraph [0002], referenced by the examiner, broadly sets out a background to the invention. However, the problems described in this single paragraph cannot be read as limiting on problems that may be addressed by the various embodiments of the invention that are subsequently described.
While the problem identified by the examiner (i.e. determining medication for a current, singular, location of a cabinet) is arguably a problem addressed in D1, this is not the problem solved by the invention as defined in the currently pending claims.
We submit that the problem solved by the invention as presently claimed is how to identify when a medication dispensing machine has been moved and to appropriately update the contents of the machine when the machine is moved. As will be described further, this solution is exemplified, in part, by the claimed features of a locator device and determining an updated location from the locator device.”[47]
[47] AS at 12-14
Also relevantly, in terms of the construction of “updated location”, the Applicant submits that (emphasis added):
“Moreover, the claims state explicitly ‘… receive an updated location…’. That is, the claims are clearly directed to a dispensing machine that moves, not a machine that is stationary. There would be no need to receive an ‘updated’ location for a machine that is stationary. Further, the claims require that the retrieval of data and provision of data to the neural network occurs ‘… in response to determining the updated location and the new patient being added to the patient roster of patients in the updated location.’ Thus, the claims should be construed to exclude a stationary machine, at least in that, when the claims take place, the machine has clearly been moved and the resultant updates to the machine location have a flow-on effect to the updating of the machine inventory.”[48]
[48] AS at 36. For completeness, I note the claims do not explicitly state “… receive an updated location…”, rather they define that the system “determine” or “provide” the updated location. The distinction does not materially alter either the Applicant’s argument or my analysis.
Considerations
With respect to the Applicant, it is not clear to me how they arrived at their suggested problem, nor the proposed construction of “updated location”.
In terms of construction, as a starting point, the Macquarie Dictionary defines “update” as “to bring up to date”, “the act of updating”, or “an updated version; revision”[49]. While this has connotations of change, to me it is more significant that it has connotations of currency – the updated version is the version (in the current matter, the location) which is most up to date, and the act of updating is the process of replacing the old with the new. It is not clear to me that the plain meaning of “updated location” only relates to a change in location, so much as to the current location. To provide a mundane example, if I were to open a map application on my phone, it would continuously “update” my location even if I simply sit unmoving at my desk. My location has updated in the sense that a previous determination of my location at a certain point in time has been replaced with a new determination of my location at a more up to date point in time. The fact I did not move does not mean the new location is not an updated location.
[49] Macquarie Dictionary (online at 28 November 2024) ‘update’ < type="1">
As quoted above, the Applicant contests that in the current invention, a different construction is required, as there would be no reason to update the location if the location has not changed. The Applicant’s reasoning appears to stem from instruction i) and iii) of claim 1 (“determine… an updated location” and “in response to determining the updated location”), and the disclosure in the following passage of the description:
“In addition, in some embodiments system 200 is configured to update the contents of automated dispensing machine 110 according to an updated location 210 of automated dispensing machine 110 (e.g., by a wireless locator or GPS attached to automated dispensing machine 110, or simply by updating information logged in the system and transmitted through network 150).”[50]
[50] Specification at [0025]
However, this passage is almost immediately followed by
“As a part of the setup or initiation of automated dispensing machine 110 within location 210[,] System 200 may provide a pharmacist a list, based on the data, of which medications can be removed from the automated dispensing machine, and which medications should be added to cabinet stock, in order to provide the highest probability that any medication prescribed for a patient in the area of the cabinet will be available in the cabinet instead of being delivered from pharmacy 110.”[51]
and (in the context of method/system 300, emphasis added)
“Predictive algorithm 49 analyzes prescription data from CPOE database stratified by hospital care area 170 to determine contents of automated dispensing machine 110 that may be removed and replaced with more frequently used medications. In some embodiments, system 300 updates and adjusts the contents of automated dispensing machine 110 on a routine basis. Thus, system 300 may substantially reduce extra costs currently experienced for medication management in healthcare facilities.”[52]
[51] Specification at [0026]
[52] Specification at [0027]
To my mind, there is a distinction between, on the one hand, determining that an ADM has moved and consequently triggering a stocking or re-stocking of the ADM (which appears to be what the Applicant is advancing), and on the other hand, updating the contents of the ADM (i.e., stocking or re-stocking on an apparently routine basis) which involves as one of its steps updating the location. In the first case, the process begins with the detection of a change in location, and nothing happens unless the location changes. This seems inconsistent with the desired goal of maintaining an optimal stock of medications in the ADM. In the second case, which appears closer to what has been described by the specification, the “updated location” is simply the current location, as that is what is required to determine the current hospital care area (and by association, the relevant patients and/or historical data and/or prescription patterns). Whether or not the updated location is different from a prior location does not appear to factor into the process. To elaborate on that point, what I mean is that the specification does not disclose or suggest, for example, a method involving deciding to skip re-training the neural network in the event that the ADM has not moved.
Relatedly, instruction iii) of claim 1 is phrased as being “in response to determining the updated location”, not responding to a change in location. That is, the steps A-G of instruction iii) are in response to the determination instruction being completed. That is, it merely indicates that the steps that follow (A-G) are sequential to determining the location of the ADM.
In summary, I do not agree with the Applicant’s construction of excluding stationary ADMs, or equivalently limiting the scope to moving or moveable ADM(s). For the avoidance of doubt, a moving or moveable ADM would be included, but the claim is not limited to that.
With this construction in mind, it appears to me that, while a system according to the claim might be capable of solving the problem the Applicant suggests (how to identify when an ADM has moved), that is not what the claim defines, nor the problem which the claimed invention is directed towards. This is consistent with the invention described in methods 300-500, which are equally silent regarding the movement of the ADM.
For completeness, even if my construction of “updated location” is incorrect and the claimed invention is limited to a moving ADM, that does not mean that there is any technical problem associated with determining such movement. As I will expand on below, the invention updates the location with standard and well known techniques (claim 1 refers to a “locator device” which would appear to encompass essentially any known or conventional techniques). That strongly implies that there is no technical problem associated with determining movement of the ADM, or at the very least, it is not a problem which the current invention solves (as I will expand on below).
As may have been foreshadowed by my summary of the disclosure above, my reading of the specification leads me to agree with the examiner: the problem which the claimed invention is directed towards is how to predict a medication prescription. The invention described by the specification more generally is directed to a related problem, of how to stock an ADM such that there is a high probability that required medications will be available to fulfil any given prescription likely to be associated with the ADM. Both problems are broadly inventory management or logistical problems. To me, these are not technical problems per se, but more analogous to the types of business methods or mere schemes which, as noted in RPL, are not patentable per se. In looking to see if there is anything more than that, I will turn to the solution.
Is the solution technical?
The examiner’s objection
The examiner’s comments on the solution were reasonably closely tied to his comments on the problem being solved, but relevantly included:
“Rather, the contribution is in the particular data processed in association with the rules related to medication prediction. As such, the substance of the claimed invention amounts to an abstract scheme for predicting a patient's medication based on various collected data associated with the patient.”[53]
and
“You argue that ‘the predictions are made without any knowledge of the new patient’s history, including without knowledge of the patient’s own physician’s prescribing history which is a significant technical contribution to dispensing systems’. However I do not see that there is a technical contribution here. These features simply define the particular data which is used to make the prediction, without providing any technical contribution in actually making the prediction. The use of a generic neural network simply provides a ‘black box’ type solution, and therefore your invention simply recites a conceptual solution to the prediction problem. The substance of the invention lies in the data which is used to make the prediction, rather than in the prediction methodology itself.”[54]
and
“Para [0025] of the Specification discloses that ‘in some embodiments system 200 is configured to update the contents of automated dispensing machine 110 according to an updated location 210 of automated dispensing machine 110 (e.g., by a wireless locator or GPS attached to automated dispensing machine 110, or simply by updating information logged in the system and transmitted through network 150)’ while para [0017] discloses ‘locking and unlocking an electronic latch closing a lid in storage drawer 115’. These passages indicate that the technical implementation of these steps (determine location, lock/unlock the storage drawer) is entirely left to the person skilled in the art, hence cannot be considered to form the substance of the invention. Therefore, neither the problem (determining a medication inventory which assures that medications stored in the cabinets are the most commonly prescribed medication types), nor the solution (prediction of medications of a per-patient basis) is considered to be technical.”[55]
[53] First examination report.
[54] Second examination Report.
[55] Third examination report.
The Applicant’s submissions
Regarding the technical nature of the solution, the Applicant argues:
“The invention uses technically implanted sensing of the physical location of the machine to trigger appropriate medication delivery to the machine to update and also to influence the physical behaviour of the machine in unlocking the drawer.”[56]
[56] AS at 33.
In response to the examiner’s comments in the third report quoted above, the Applicant stated: (emphasis added):
“We submit that this exclusion of individual aspects of the claim from the substance of the invention is inappropriate. Identification of the substance of the invention does not involve disregarding material aspects of the claim language. These claim elements, and their interactions, must therefore be considered as part of the claim as a whole. It impermissible to disaggregate the integers of the method in order to point to only the predictive aspect as the ‘substance of the invention’. The invention as claimed is not merely the prediction of an anticipated medication prescription, but the system within which that prediction is achieved, including the physical aspects of the movable machine, locator device and lockable drawer.”[57]
[57] AS at 34.
Expanding on this point, the Applicant also submitted that (emphasis added):
“The present claims defined that, when the location is updated (as determined by the locator device, such as a GPS), the historical patterns (of physicians) associated with the updated location are automatically retrieved by the system and provided to the neural network for use in making the resultant predictions. In this regard, we again submit that there is an interrelationship between physical aspects of the system (i.e., the claimed locator device and dispensing machine) and the prediction elements (i.e., prompting a delivery and storing of the medication predicted by the neural network) as the retrieval of the patient location, diagnostic information, historical medication prescribing patterns, input to the neural network, and prompting a delivery, are all ‘in response to determining the updated location and the new patient being added to the patient roster of patients in the updated location...’, that is, in response to the physical movement of the machine.”
The Applicant submits that this interrelationship between the physical aspects of the locator and the prediction elements is analogous to UbiPark:
“That is, in UbiPark the technical solution was based on using the strength of an entry signal to infer the location of a user’s vehicle. This location data was then used to influence the behaviour of the system, particularly when to transmit entry/exit request data to the system for raising of the barrier, without the need for the user to interact with their phone. Similarly, in the present claims, the data from the locator device is used to determine the location of the dispensing machine. This location data is used to influence the behaviour of the system, particularly when to trigger retrieval of data (as well as what data to retrieve). The location information is used in the system as both a trigger for the subsequent information retrieval, and as a filter for the retrieved data. That is, the movement of the machine, rendered trackable by the locator device, influences the behaviour of the system and the data provided to the neural network for determining of a medication prediction and subsequent unlocking of the drawer so that the predicated medications can be placed in the machine.”
Considerations
The Applicant’s comments about the technical solution are understandably closely linked with their submissions on the alleged technical problem of determining when the ADM has moved. To the extent that the Applicant relies upon the characterisation of the problem as a need to determine the ADM has moved, and the solution of this problem as being technical, I disagree for the reasons set out above.
Regardless, even if I was persuaded the problem to be solved relates to a need to determine when the ADM has moved, the claimed solution of a locator device is generic to the point of being a tautology – any and all solutions for determining the location of the machine would fall within the ambit of “locator device”. To the extent there is any technical problem or technical solution associated with determining an updated location, it is not a problem addressed by the specification. Instead, as I set out above, the problem the invention is directed towards is how to predict a medication prescription, and how to predict what medications to stock an ADM with.
With that in mind, the solution offered by the specification relates to the use of a predictive algorithm, which is trained on a set of historical data about past prescriptions. The historical data is provided as stratified in various ways (or, equivalently, the historical data comprises a set of differently stratified datasets), from which the predictive algorithm can determine patterns. The ADM can then use these patterns to determine what medications should be stocked into inventory. Relevant to the present claims, one form involves historical data stratified by patient care area, which the predictive algorithm can use to determine patterns of prescription for each patient care area, which the ADM may then use, in conjunction with the current location of the ADM, to determine what medications should be stocked.
As summarised above, the Applicant argues that the interrelationship between the locator for determining the location and the predictive algorithm is particularly significant. While they phrased the function of the locator as determining that the ADM has moved, which I disagree with for the reasons above, their reasoning would seem to be similar for simply determining the current location of the ADM. The system uses the current location to select and retrieve relevant data (patient roster, historical medication prescribing patterns) to provide to the predictive algorithm (or “neural network” in the language of claim 1).
In this sense, there is an interaction between the physical element of the locator, and the predictive algorithm. While the absence of any such interaction would fairly decisively render the invention an abstract scheme without physical effect, the existence of such an interaction is not, of itself, determinative that there is “more than that” in the RPL sense. The Applicant’s argument appears to be that because the prediction method uses the location of the ADM as one input, the physical sensor/locator is an essential characterising attribute of the invention. However, to me, this is no different from the fact that the operational steps of the method require a physical computer. While that does render the claim something other than purely abstract information, in this case, it does not materially alter the substance of the invention. The situation would be different if there was some technical problem related to locating the automated dispensing machine, but as I have set out above, I cannot see any such problem being addressed by this application. This is reinforced by the specification itself, which teaches that the locator may be replaced “simply by updating information logged in the system and transmitted through network”[58]. That is, while the claim defines the use of a locator, the specification makes reasonably clear that it is not material to the invention how the location is updated, merely that the updated location is provided. As such, the “physical aspect” of the sensor is not material, the substance is merely that the updated location information is provided.
[58] Specification at [0025]
Turning to the step of unlocking the drawer, this relates to step G, which, in its proper context, comprises:
“d) a processor configured to execute the instructions to:
…
iii) in response to determining the updated location and the new patient being added to the patient roster of patients in the updated location:
…
G) unlock a storage drawer in an automated dispensing machine for placement of the anticipated medication prescription.
As a couple of observations on the construction of this step: Firstly, note that the step of unlocking is notionally responsive to determining the updated location and new patient data, but does not depend on what the new location is. Secondly, the claim does not seem to require any specific drawer to be unlocked, merely that it is one of the drawers of the ADM.
This apparent lack of interaction between the location data (or any other data) and the operation of the lockable drawer is consistent with the invention described, as I discussed above. In at least the preferred forms of the invention described by the specification, the drawer is simply unlocked to provide access when access is required, which is when a nurse or other healthcare professional collects, places, or orders the medication in the drawer, optionally via the attached user interface. While the claim does not appear to be limited to unlocking/locking responsive to an authorised user interacting with the user interface, it does appear to be included. This severs any meaningful interaction between this step and any of the other steps of the method 400. The unlocking is (or at the very least, includes) simply unlocking a drawer at the instruction of a user. In this sense, the Applicant’s analogy to UbiPark is quite inapt, as UbiPark was primarily directed to controlling access to a secure location to only authorised individuals.
The overall effect is that in regards to the lockable drawer, my main takeaway is that the invention includes an electronically controllable lock, which may be unlocked or locked when needed, for example by a user manipulating the user interface in order to perform step G, but given the general lack of attention paid to this concept, and its lack of interaction with other steps of the process, the operation of the lock is in the nature of Rokt’s “clothing” of the invention, rather than forming part of the substance of the invention itself.
Consistent with the problem I identified above, I consider the solution provided by the specification relates to the use of location information and historical data to inform or train a neural network or similar predictive algorithm, which discovers patterns of prescriptions which the system may use to predict likely prescriptions for a given location and stock the ADM accordingly, and/or predict likely prescriptions for a particular patent. The solution is essentially an administrative scheme for inventory management. While this may make use of physical elements such as a locator and lockable drawers, this does not alter the substance any more than the fact the medication inventory itself is physical.
Does the invention involve an improvement in computer technology?
The examiner’s objection
The examiner relevantly stated that:
“Regarding the provision of ‘an artificial state of affairs and a useful result’, your invention does not involve any more than standard implementation of know computer technology components. I do not agree that the invention produces the requisite effect required by the case law.”[59]
[59] Third examination report
The Applicant’s submissions
The Applicant submits that:
“The examiner alleges that the claimed invention does not involve any more than standard implementation of known computer technology components. However, again, the examiner fails to consider the combination of elements as defined in the claim. The examiner has not shown that the claimed determination of machine location, and the use of this location data as an input to triggering and filtering data retrieval was standard use of computers at the priority date. That is, although the computer technology components may be known, their utilisation in the presently claimed invention involves ingenuity.”[60]
[60] AS at 40.
Considerations

The Applicant’s argument seems to be that because it has not been demonstrated that using location information to filter data was standard use, it follows that such a use cannot be “standard implementation of known computer technology”. The Applicant is making the mistake of confusing an invention utilising a computer to do something new with an invention which allows a computer to do something which it previously could not do. The latter may be a new patentable improvement in computer technology, while the former is merely new and possibly inventive[61].
[61] See also BaVelPay S.L.U (B-67506527) [2022] APO 78 at [48].
Looking to the specification, the application has gone to great lengths to make it unmistakeably clear that there is nothing special or unusual about the computer equipment employed. Most of pages 16 to 20 (out of a total of 21 pages of description) are dedicated to setting out that essentially any known computer hardware and software systems may be employed. I see nothing in the present application which would allow the system to do anything which was not previously possible or overcomes some previous limitation in computer technology.
It is clear that the invention does not relate to some improvement to computer technology.
Conclusion of Manner of Manufacture
Having considered all of the above, I consider that the substance of the present invention lies in a method of predicting medications that are likely to be prescribed at a location, and stocking an ADM at that location such that there is a high probability that required medications will be available to fulfil any given prescription likely to be associated with the ADM. The method involves using location information and historical information of prior prescriptions as inputs to a predictive algorithm, which determines patterns of prescription, which in turn may be used to predict what medications should be stocked and/or what medication is likely to be required for a new patient.
To me, the overall character of the substance of the invention is an administrative or logistical scheme, of the type which has never been patentable. It follows that the invention of claim 1 is not a manner of manufacture.
In addition, I have considered each of the claims 2-17. To quickly paraphrase, independent claim 9 relates to a computer implemented method which essentially accords with the instructions executed by the processor of claim 1 (i.e., feature d of claim 1 and associated instructions/steps), and independent claim 14 essentially comprises the same instructions stored in a non-transitory computer readable medium. These all clearly relate to the same substantive invention as claim 1, and do not involve a manner of manufacture for the same reason.
Looking to the dependent claims, claims 2, 5, 6, 7, 8, and 10 all relate to the feature of storing the prescription patterns in memory, and further specifying what the prescription patterns comprise (e.g. claim 6 defines the patterns comprise a history of medication prescriptions of the physician for patients with a similar diagnosis), claims 3, 4, and 11 are directed to determining a routine stocking of the anticipated medication and determining whether the anticipated medication is currently stored, claims 12 and 15 define diagnostic information as comprising laboratory results, and claims 13 and 16 define the additional step of determining that the prescription pattern has changed. These may all be categorised as defining further details of the information used by the administrative scheme, or further details of the administrative scheme itself (e.g. stored in memory or routine stocking). Claim 17 defines that the locator is a GPS, but for similar reasons as discussed regarding a locator, I do not accept that the use of a GPS in its normal routine way transforms the substance of the otherwise unpatentable scheme into a technical method of locating the ADM.
I do not believe any of the claims define any features which would materially alter my characterisation of the substance of the invention. It follows that none of claims 1-17 define a patentable manner of manufacture.
Can an allowable amendment resolve the objection?
As can be seen above, my considerations involved both the claims and the invention described in the specification. I have found nothing in the specification which could be made the subject of a claim to overcome the finding of lack of manner of manufacture. With this in mind, I do not see any reasonable prospect of amending the claims to overcome the lack of manner of manufacture.
Inventive Step
In light of my conclusion above, the issue of inventive step is largely a moot point. The inventiveness or otherwise of the claims will not affect the outcome of my decision. Therefore, I will not decide on inventive step.
SUMMARY
The invention defined by claims 1-17 does not relate to a manner of manufacture within the meaning of subsection 18(1)(a). Furthermore, I have considered the specification in detail and consider that there is nothing which could form the basis for a patentable manner of manufacture. It follows that there would be no useful purpose in allowing any further opportunity to amend, and as such, the application should be refused.
Andrew Burgess
Delegate of the Commissioner
ANNEX
Claims
Claim 1: A system, comprising:
an automated dispensing machine of a healthcare facility;
a locator device attached to the automated dispensing machine;
a memory storing instructions; and
a processor configured to execute the instructions to:
determine, from the locator device, an updated location of the automated dispensing machine;
determine a new patient has been added to a patient roster of patients in the updated location of the automated dispensing machine;
in response to determining the updated location and the new patient being added to the patient roster of patients in the updated location:
retrieve a patient location of the new patient in the updated location of the automated dispensing machine;
retrieve a diagnostic information for the new patient;
retrieve historical medication prescribing patterns associated with an area corresponding to the updated location of the automated dispensing machine, at least one of the medication prescribing patterns being from a physician in charge of the patient;
provide the updated location, the patient location retrieved by the processor, the diagnostic information for the new patient, and the historical medication prescribing patterns to a neural network;
determine, from the neural network, an anticipated medication prescription for the patient based on providing to the neural network the updated location of the automated dispensing machine, the patient location retrieved by the processor, the diagnostic information, the historical medication prescribing patterns, and based on a medication being available through an approved formulary;
prompt a delivery and storing of at least one dose of the determined anticipated medication prescription in the automated dispensing machine; and
unlock a storage drawer in an automated dispensing machine for placement of the anticipated medication prescription.
Claim 2: The system of claim 1, wherein the medication prescribing patterns are stored in the memory.
Claim 3: The system of claim 1 or claim 2, wherein the processor is configured to determine a routine stock of the anticipated medication prescription in an automated medication cabinet.
Claim 4: The system of any one of the preceding claims, wherein the processor is further configured to execute the instructions to determine whether the anticipated medication prescription is currently stored in the dispensing machine.
Claim 5: The system of any one of the preceding claims, wherein the medication prescribing patterns are stored in the memory, and processor is further configured to determine the anticipated medication prescription based on a change of a medication prescribing pattern of the medication prescribing patterns stored in the memory.
Claim 6: The system of any one of the preceding claims, wherein the medication prescribing patterns are stored in the memory and comprise a history of medication prescriptions of the physician for patients with similar diagnosis.
Claim 7: The system of any one of the preceding claims, wherein the medication prescribing patterns are stored in the memory and comprise a trend and a change in a medication prescription pattern over a period of time.
Claim 8: The system of any one of the preceding claims, wherein the medication prescribing pattern are stored in the memory and comprise a prescription data stored for an extended period of time in the memory.
Claim 9: A computer-implemented method, comprising:
determining, from a locator device attached to an automated dispensing machine, an updated location of the dispensing machine in a healthcare facility;
determining that a new patient has been added to a patient roster of patients in the updated location;
in response to determining the updated location and the new patient being added to the patient roster of patients in the updated location:
determining a patient location of the new patient in the updated location of the automated dispensing machine;
retrieving diagnostic information associated with the new patient;
determining historical medication prescribing patterns associated with an area corresponding to the updated location of the automated dispensing machine, at least one of the medication prescribing patterns being from a physician associated with the new patient;
providing the updated location, the determined patient location, the diagnostic information for the new patient, and the historical medication prescribing patterns to a neural network;
determining, from the neural network, an anticipated medication prescription for the patient based on providing to the neural network the updated location of the automated dispensing machine, the determined patient location, the diagnostic information, the historical medication prescribing patterns, and based on a medication being available through an approved formulary;
prompting a delivery and storing of a first dose and subsequent supply of a medication from the anticipated medication prescription in the automated dispensing machine; and
unlocking a storage drawer in the automated dispensing machine for placement of the anticipated medication prescription.
Claim 10: The computer-implemented method of claim 9, wherein the medication prescribing patterns are stored in a memory of the automated dispensing machine and comprise a prescribing pattern of multiple physicians in a selected area, and wherein the computer-implemented method further comprises prompting a storage of the anticipated medication prescription in the automated dispensing machine located in the selected area.
Claim 11: The computer-implemented method of claim 9 or claim 10, wherein the medication prescribing patterns comprise a prescription pattern over a length of time for a selected area of a healthcare facility where an automated medication cabinet is located, and wherein the computer implemented method comprises prompting a routine stocking of the anticipated medication prescription in the automated medication cabinet.
Claim 12: The computer-implemented method of any one of claims 9 to 11, wherein the diagnostic information comprises at least one laboratory result from the new patient.
Claim 13: The computer-implemented method of any one of claims 9 to 12, wherein determining the anticipated medication prescription comprises determining a change of a medication prescribing pattern stored in a memory.
Claim 14: A non-transitory, computer readable medium comprising instructions which, when executed by a processor in a computer cause the computer to perform a method, the method comprising:
determining, from a locator device attached to an automated dispensing machine, an updated location of the dispensing machine in a healthcare facility;
determining that a new patient has been added to a patient roster of patients in the updated location;
in response to determining the updated location and the new patient being admitted to the healthcare facility:
determining a patient location of the new patient in the updated location;
retrieving diagnostic information associated with the new patient;
determining historical medication prescribing patterns associated with an area corresponding to the updated location of the automated dispensing machine, at least one of the medication prescribing patterns being from a physician associated with the new patient;
providing the updated location of the automated dispensing machine, the determined patient location, the diagnostic information for the new patient, and the historical medication prescribing patterns to a neural network;
determining, from the neural network, an anticipated medication prescription for the patient based on providing to the neural network the updated location of the automated dispensing machine, the determined patient location, the diagnostic information, the historical medication prescribing patterns, and based on a medication being available through an approved formulary;
prompting a delivery and storage of a first dose and subsequent supply of a medication from the anticipated medication prescription in the automated dispensing machine; and
unlocking a storage drawer in the automated dispensing machine for placement of the anticipated medication prescription.
Claim 15: The non-transitory, computer-readable medium of claim 14, wherein, in the method, retrieving the diagnostic information comprises at least one laboratory result from the new patient.
Claim 16: The non-transitory, computer-readable medium of claim 14 or claim 15 wherein, in the method, determining the anticipated medication prescription comprises determining a change of a medication prescribing pattern stored in a memory.
Claim 17: The non-transitory, computer-readable medium of any one of claims 14 to 16, wherein the locator device is a GPS device.