DETAILED ACTION
Status
This Final Office Action is in response to the communication filed on 17 November 2025. No claims have been cancelled, claims 1, 3, 8, and 11-12 have been amended, and no new claims have been added. Therefore, claims 1-13 are pending and presented for examination.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
A summary of the Examiner’s Response to Applicant’s amendment:
The Examiner notes that a large section of text has been added to independent claim 1 without edit markings (see the Claim Objection below). Since the Examiner has noticed this amending, although un-marked, it is being regarded as effective for amending. However, no other editing without edit markings has been noticed by the Examiner, so any other un-marked editing is being considered as ineffective as an amendment.
Applicant’s amendment overcomes the claim 9 rejection(s) under 35 USC § 112; therefore, the Examiner withdraws the rejection(s).
Applicant’s amendment does not overcome the claim 11 rejection(s) under 35 USC § 112; therefore, the Examiner maintains the rejection(s).
Applicant’s amendment appears to overcome the § 101 rejection of claim 11 regarding non-statutory subject matter; therefore, the Examiner withdraws the rejection(s).
Examiner’s Note
The Examiner notes that recitations to Applicant's specification, as below, are in reference to the Pre-Grant Publication of Applicant’s specification.
The Examiner notes that the light of the specification indicates that “processing unit” as at claim 12 (and the respective dependent claims) is a hardware processor such as a central processing unit (CPU), graphics processing unit (GPU), or the like – see Applicant ¶ 0036).
The Examiner notes that claim 3 indicates that the prediction function for an expected length of stay of the inpatient (i.e., a patient already occupying a bed per claim 1) may be based on “independent variables compris[ing] one or more of … or measurement value describing a patient's condition of the inpatient”. This is understood and interpreted as being a measurement value describing the inpatient condition. Although this certainly appears to be “independent”, the Examiner notes that this indicates that a patient occupying a bed is expected to somehow have an altered or different length of stay merely based on a waiting patient’s condition measurement value. This appears to indicate, for example, that a patient will be removed from the hospital because a waiting patient needs the bed. Although this could indeed be correct, the Examiner wanted to check that there is not some language or translation issue that is changing or influencing the claim phrasing.
The Examiner notes that claim 12 indicates “using big data” at the preamble, but there is no described definition, nor apparently a term of art definition, of what is or is not “big data”. Since there is no actual limitation to use “big data” or indication of what is or is not “big data”, and the claimed system is comprised of various “processing unit[s]” that the description indicates may be merely a general purpose computer, there is no apparent limiting structure indicated by “big data” and the preamble of claim 12 is therefore interpreted as intended and may be granted little if any patentable weight.
The Examiner notes that the indications at claim 3 of “diagnosis code, surgery code, treatment code, or measurement value describing a patient's condition of the waiting patient” are not described in the specification, and therefore are being interpreted as any indication of a diagnosis, surgery, care level, treatment, etc.
The Examiner notes that claim 1 recites “if a searched list of hospital beds does not include an empty hospital bed, pre- assigning a hospital bed … wherein the pre- assigning comprises”. MPEP § 2111.04(II) indicates that “The broadest reasonable interpretation of a method (or process) claim having contingent limitations requires only those steps that must be performed and does not include steps that are not required to be performed because the condition(s) precedent are not met.” Since the condition precedent (i.e., that the list of hospital beds does not include an empty hospital bed) need not be met, the ensuing steps of calculating a daily discharge probability based on a pre-modeled function and recording or changing states in/at the FSM are contingent and not required by the method.
Similarly, claims 8, 9, and 10 also indicates contingent limitations (i.e., “if the urgency … satisfies a priority condition”, and “if the … waiting time is equal to or shorter than the maximum tolerable waiting time” at claim 8, “if the comparison results in that the maximum tolerable waiting time is longer than the expected waiting time” at claim 9, “when the recipient FSM has the first-2 state”, “when the urgency of admission of the requester FSM is higher than that of the recipient FSM as a result of the comparison”, and “when the urgency of admission of the requester FSM is equal to or lower than that of the recipient FSM” at claim 10), which also then are analyzed as the broadest reasonable interpretation indicating the ensuing steps are not required to be performed.
The Examiner suggests, should Applicant want to require the ensuing steps, that the claim be amended to positively recite that there is no empty or available bed (perhaps via a determination of that lack of a bed) and require the ensuing steps.
Claim Objections
Claim 1 is objected to because of the following informalities: the phrase “wherein the pre-assigning comprises: calculating a daily discharge probability of the inpatient based on an expected length of stay of the inpatient by applying inpatient information of the inpatient to a pre-modeled prediction function, wherein the prediction function is generated based on training data of previously hospitalized and discharged patients, the prediction function being generated by selecting one or more variables from a plurality of variables associated with discharge of patients and formalizing a correlation between the selected one or more variables and an actual length of stay in the past, “ has been added to independent claim 1 without edit markings.
The Examiner notes that this is being considered as an “informality” since it was noticed by the Examiner. The Examiner further notes that no other editing without edit markings has been noticed by the Examiner, so any other un-marked editing is being considered as ineffective for amending.
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
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.
Claim 11 is 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 pre-AIA the applicant regards as the invention.
Claim 11 recites “A non-transitory computer-readable medium storing program instructions that, when executed by a processor, cause the processor to perform the smart hospital bed operating method according to claim 1”.
MPEP § 608.01(n)(III) indicates the “TEST FOR PROPER DEPENDENCY” as “a claim in dependent form shall contain:
(i) a reference to a claim previously set forth, and
(ii) then specify a further limitation of the subject matter claimed.
A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers”.
Claim 11 refers to claim 1 and specifies a further limitation in reciting the recording medium and/or the act of actually recording the program; however, it is indefinite whether claim 11 requires the actual performance of the method steps or activities as at claim 1. MPEP § 2173.05(p) indicates that “A single claim which claims both an apparatus and the method steps of using the apparatus is indefinite under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph”, where the medium indicated is apparently a form of apparatus, and parent/recited claim 1 indicates the method.
Therefore, it is indefinite whether claim 11 is a dependent claim or is an independent claim – i.e., whether the performance of the method steps is required, or just the program is required.
For purposes of Examination, the Examiner is interpreting claim 11 as depending from claim 1, and only requiring a computer-readable recording media with a program to perform the method steps of claim 1.
As a suggested remedy for this rejection, the Examiner suggests deleting the reference to claim 1, and then including a listing of the steps that would be performed when the program instructions are executed by the processor.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-14 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Please see the following Subject Matter Eligibility (“SME”) analysis:
For analysis under SME Step 1, the claims herein are directed to a method (claims 1-11 and system (claims 12-15), and computer-readable recording medium (claim 11 – possibly, see the 112 rejection above), which would be classified, or could be amended to be classified, under one of the listed statutory classifications (SME Step 1=Yes).
For analysis under revised SME Step 2A, Prong 1, independent claim 1 recites a smart hospital bed operating method performed by a computing device comprising a processor, the method comprising: receiving a hospital bed assignment query including a hospitalization indication condition for a waiting patient; searching for a hospital bed that matches the hospitalization indication condition; and if a searched list of hospital beds does not include an empty hospital bed, pre-assigning a hospital bed occupied by an inpatient to the waiting patient based on a hospital bed assignment plan table including the expected discharge date of the inpatient wherein the pre-assigning comprises: calculating a daily discharge probability of the inpatient based on an expected length of stay of the inpatient by applying inpatient information of the inpatient to a pre-modeled prediction function, wherein the prediction function is generated based on training data of previously hospitalized and discharged patients, the prediction function being generated by selecting one or more variables from a plurality of variables associated with discharge of patients and formalizing a correlation between the selected one or more variables and an actual length of stay in the past, wherein the daily discharge probability is a probability that the inpatient will actually be discharged on a corresponding day, creating a finite state machine (FSM) corresponding to the hospitalization indication of the waiting patient, wherein the FSM has condition attributes that describe the hospitalization indication conditions and state attributes that describe the states of the FSM, wherein the state of the FSM includes a first state, a first-2 state, and a second state, wherein the first state indicates searching for hospital beds, the first-2 state indicates tentative assignment, and the second state indicates that assignment is completed, placing the FSM on the hospital bed assignment plan table according to a code of conduct predefined for each state of the FSM, and wherein a plurality of FSMs may be preferentially assigned or concede their already assigned hospital beds based on their state attributes and the condition attributes of waiting patients.
Independent claim 12 is analyzed similarly to claim 1 since directed to a hospital bed operating system … comprising: a hospital bed management processing unit …; a hospital bed assignment processing unit …; and a hospital bed schedule prediction processing unit configured to perform the same or similar activities as at claim 1 above.
Claim 11 is analyzed similarly to claim 1 (when or if regarded as an independent claim) since directed to a non-transitory computer-readable medium storing program instructions that, when executed by a processor, cause the processor to perform the same or similar activities as at claim 1 above.
The dependent claims (claims 2-11 and 13-14) appear to be encompassed by the abstract idea of the independent claims since they merely indicate calculating length of stay (using a pre-modeled prediction function), creating a table including the length of stay, and assigning the bed based on the table (claim 2), using dependent and independent variables (gender, diagnosis, surgery, or treatment code, a measurement value) (claim 3), determining independent variable coefficients by an optimization algorithm (claim 4), the assignment plan table having empty and fill cells, and using an FSM, setting a state based on the patient history, and placing the FSM according to a predefined code of conduct (claim 5), the state being an initial search state, the code of conduct being to place the FSM in the earliest empty cell, and updating to an assigned state (claim 6), sending a reservation indicating a completed assignment (claim 7), if urgency is indicated, comparing expected wait times to a maximum tolerable wait time (claim 8), reassigning tentatively-assigned beds based on the urgency comparison (claims 9-10), a computer-readable recording media recording a program for the activities (claim 11), a database storing bed resource, inpatient, and waiting patient information (claim 13), and/or an interface to provide the assignment plan table (claim 14).
The underlined portions of the claims are an indication of elements additional to the abstract idea (to be considered below).
The claim elements may be summarized as the idea of assigning hospital beds to patients, perhaps including by calculating an expected bed availability; however, the Examiner notes that although this summary of the claims is provided, the analysis regarding subject matter eligibility considers the entirety of the claim elements, both individually and as a whole (or ordered combination). This idea is within the following grouping(s) of subject matter:
Certain methods of organizing human activity (e.g. … business relations; and/or managing personal behavior or relationships between people such as social activities, teaching, and following rules or instructions) as based on the queries, searching, and pre-assigning of beds based on a table;
Mathematical concepts (e.g., relationships, formulas, equations, and/or calculations) based at least on using a pre-modeled function to calculate a discharge probability, using a finite state machine, using an optimization algorithm to determine independent variable coefficients, etc. (at some dependent claims); and
Therefore, the claims are found to be directed to an abstract idea.
For analysis under revised SME Step 2A, Prong 2, the above judicial exception is not integrated into a practical application because the additional elements do not impose a meaningful limit on the judicial exception when evaluated individually and as a combination. The additional elements are the method being performed by a computing device comprising a processor (at claim 1), the system comprising processing units (at claim 12) and a non-transitory computer-readable medium storing program instructions that, when executed by a processor, cause the processor to perform method steps (at claim 11). The Examiner notes that the database and plan table as indicated at the claims may be at least the analog of hard-copy versions of the database and table. The FSM recited is really just listing the status of the search for a bed (i.e., searching, tentative assignment, completed assignment), but is recited as a machine, and is therefore analyzed as such. These additional elements do not reflect an improvement in the functioning of a computer or an improvement to other technology or technical field, effect a particular treatment or prophylaxis for a disease or medical condition (there is no medical disease or condition, much less a treatment or prophylaxis for one), implement the judicial exception with, or by using in conjunction with, a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing (there is no transformation/reduction of a physical article), and/or apply or use the judicial exception in some other meaningful way beyond generically linking use of the judicial exception to a particular technological environment.
The claims appear to merely apply the judicial exception, include instructions to implement an abstract idea on a computer, or merely use a computer as a tool to perform the abstract idea. The additional elements appear to merely add insignificant extra-solution activity to the judicial exception and/or generally link the use of the judicial exception to a particular technological environment or field of use.
For analysis under SME Step 2B, the claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements, as indicated above, are merely “[a]dding the words ‘apply it’ (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, e.g., a limitation indicating that a particular function such as creating and maintaining electronic records is performed by a computer, as discussed in Alice Corp.” that MPEP § 2106.05(I)(A) indicates to be insignificant activity.
There is no indication the Examiner can find in the record regarding any specialized computer hardware or other “inventive” components, but rather, the claims merely indicate computer components which appear to be generic components and therefore do not satisfy an inventive concept that would constitute “significantly more” with respect to eligibility. Applicant ¶¶ 0174-0176 indicate the computer and media as merely being general-purpose devices “such as a desktop computer, laptop computer, notebook, smart phone, or the like, or any device that may be integrated”.
The individual elements therefore do not appear to offer any significance beyond the application of the abstract idea itself, and there does not appear to be any additional benefit or significance indicated by the ordered combination, i.e., there does not appear to be any synergy or special import to the claim as a whole other than the application of the idea itself.
The dependent claims, as indicated above, appear encompassed by the abstract idea since they merely limit the idea itself; therefore the dependent claims do not add significantly more than the idea.
Therefore, SME Step 2B=No, any additional elements, whether taken individually or as an ordered whole in combination, do not amount to significantly more than the abstract idea, including analysis of the dependent claims.
Please see the Subject Matter Eligibility (SME) guidance and instruction materials at https://www.uspto.gov/patent/laws-and-regulations/examination-policy/subject-matter-eligibility, which includes the latest guidance, memoranda, and update(s) for further information.
NOTICE
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-3 and 5-14 are rejected under 35 U.S.C. 103 as being unpatentable over Mancine et al. (U.S. Patent Application Publication No. 2017/0149701, hereinafter Mancine) in view of Shanbhag (U.S. Patent Application Publication No. 2016/0180029) in further view of Ellis et al. (U.S. Patent Application Publication No. 2006/0247948, hereinafter Ellis)
Claim 1: Mancine discloses a smart hospital bed operating method performed by a computing device comprising a processor (see Mancine at least at, e.g., ¶ 0010, “a non-transitory computer-readable medium may store program instructions, which are executed by at least one processor device and cause a central communication server to perform operations for centralized event monitoring and notification communications”; citation hereafter by number only) , the method comprising:
receiving a hospital bed assignment query including a hospitalization indication condition for a waiting patient (0085, “Patient placement interface 800 may include a number of different data fields to generate a transfer request. The data fields may include patient information 802, bed request information 804, …. Bed request information 804 may include the bed request time, the requester, the request status, the origination, and the level of care”);
searching for a hospital bed that matches the hospitalization indication condition (0073, “After one or more beds are found to have the critical preferences in steps 508-510, steps 514-518 may provide an iterative approach to optimize the bed assignment accordingly to the non-critical inputs”); and
if a searched list of hospital beds does not include an empty hospital bed, pre- assigning a hospital bed occupied by an inpatient to the waiting patient based on a hospital bed assignment plan table including the expected discharge date of the inpatient (0071, “The availability of the bed may be determined by whether the bed is either unoccupied or occupied by a patient with a pending or confirmed discharge”, 0075, “network server 160 may be configured to receive assignment and/or discharge data from database 180 for each department and/or hospital, and process the received data to assign the patient bed based on real-time department and/or hospital loads, to assign the hospital unit best positioned to receive and/or discharge the patient at the corresponding date and/or time”), wherein the pre-assigning comprises:
calculating a daily discharge probability of the inpatient based on an expected length of stay of the inpatient by applying inpatient information of the inpatient to a pre-modeled prediction function (0069, “Occupied beds as well as beds assigned to patients pending discharge may therefore be stored as unavailable locations. In some embodiments, unavailable locations may include an indication that they are expected to become available within a predetermined time period. The predetermined time period, for example, can be associated with the metrics calculated by the system associated with the store patient condition, patient progress through an itinerary generated in association with the patient condition, and stored metrics associated with a predetermined patient discharge process, and the patient's current status in the discharge process”), … the prediction function being generated by selecting one or more variables from a plurality of variables associated with discharge of patients and formalizing a correlation between the selected one or more variables and an actual length of stay (0069, “Occupied beds as well as beds assigned to patients pending discharge may therefore be stored as unavailable locations. In some embodiments, unavailable locations may include an indication that they are expected to become available within a predetermined time period. The predetermined time period, for example, can be associated with the metrics calculated by the system associated with the store patient condition, patient progress through an itinerary generated in association with the patient condition, and stored metrics associated with a predetermined patient discharge process, and the patient's current status in the discharge process”),
creating a finite state machine (FSM) corresponding to the hospitalization indication of the waiting patient (0006, “monitoring a plurality of parameters, schedules, milestones, and events associated with a patient visit, from the patient intake process through to patient discharge and beyond. In some embodiments, event information is received from a network device. Event information can include, for example, a status of one or more hospital beds monitored for occupancy, cleanliness, and maintenance”, 0069, “information may include detailed information of each unit of the hospital including, for example, the number and locations of occupied and unoccupied beds of each unit, and the status of the patients of each occupied bed. Specifically, the network server 160 may receive personal attributes of each of the patients (e.g. gender, age, and personality) along with the expected discharge of each of the patients…. Occupied beds as well as beds assigned to patients pending discharge may therefore be stored as unavailable locations. In some embodiments, unavailable locations may include an indication that they are expected to become available within a predetermined time period. The predetermined time period, for example, can be associated with the metrics calculated by the system associated with the store patient condition, patient progress through an itinerary generated in association with the patient condition, and stored metrics associated with a predetermined patient discharge process, and the patient's current status in the discharge process. In some embodiments, the predetermined time period may be associated with one or more scheduled events for cleaning or maintaining the unavailable location, and an expected completion time for the scheduled events”),
wherein the FSM has condition attributes that describe the hospitalization indication conditions and state attributes that describe the states of the FSM (0006, 0069 as above),
Mancine, however, does not appear to explicitly disclose wherein the prediction function is generated based on training data of previously hospitalized and discharged patients … in the past, wherein the daily discharge probability is a probability that the inpatient will actually be discharged on a corresponding day, wherein the state of the FSM includes a first state, a first-2 state, and a second state, wherein the first state indicates searching for hospital beds, the first-2 state indicates tentative assignment, and the second state indicates that assignment is completed, placing the FSM on the hospital bed assignment plan table according to a code of conduct predefined for each state of the FSM, and wherein a plurality of FSMs may be preferentially assigned or concede their already assigned hospital beds based on their state attributes and the condition attributes of waiting patients.
Where Mancine does not appear to go into detail about how the discharge of a patient is predicted, Shanbhag teaches that “the current health condition of the patient may be compared with health conditions of multiple patients in the past who were having the same medical condition. The health conditions of these patients may be part of historical information 212 that may be stored. The historical information 212 includes criticality assessment parameters of the multiple patients and their treatment schedule and discharge information in the hospital may be stored in the memory 102. Based on the mapping the discharge date of the patient is identified. In this example for the patient who has undergone a heart surgery may require certain days of observation in the hospital and hence the patients having similar medical condition and their length of stay in the hospital enables to predict the discharge date. However the discharge date can vary based on any change in medical condition of the patient. The change may be severe or better based on which the initial discharge date may be postponed or preponed. Hence the discharge date is predicted based on real time medical condition of the patient. In an embodiment the medical condition of the patient may be analyzed at predefined instances such as after every predefined time interval” (Shanbhag at 0022). Therefore, the Examiner understands and finds that to predict a day for probability of discharge based on past patients is applying a known technique to a known device, method, or product ready for improvement to yield predictable results so as to more accurately predict discharge probability.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine or modify the bed assignments of Mancine with the discharge prediction of Shanbhag in order to predict a day for probability of discharge based on past patients so as to more accurately predict discharge probability.
The rationale for combining in this manner is that to predict a day for probability of discharge based on past patients is applying a known technique to a known device, method, or product ready for improvement to yield predictable results so as to more accurately predict discharge probability as explained above.
Mancine in view of Shanbhag, however, does not appear to explicitly disclose wherein the state of the FSM includes a first state, a first-2 state, and a second state, wherein the first state indicates searching for hospital beds, the first-2 state indicates tentative assignment, and the second state indicates that assignment is completed, placing the FSM on the hospital bed assignment plan table according to a code of conduct predefined for each state of the FSM, and wherein a plurality of FSMs may be preferentially assigned or concede their already assigned hospital beds based on their state attributes and the condition attributes of waiting patients. The light of Applicant’s specification and also the claims indicate that the FSM is really merely a listing of the status of the patient’s bed assignment, where Ellis teaches “an electronically generated bed board comprising a plurality of graphical representations of bed cells each having associated therewith a set of bed attributes and a plurality of graphical representations of patient cards each having associated therewith a set of patient attributes” (Ellis at 0006) where “the electronically generated bed board 10 may be used in a manner similar to a "on the wall" bed board having bed slots and patient cards. The holding area 18 may be a temporary "parking" area for patient cards 12. A patient card 12 can be dragged from a bed cell 14 and dropped into the holding area 18, or vice versa. Note that the cards 12 in the holding area 18 represent patients, and not beds. Beds are not moved into the holding area 18, only patient cards 12 and reservation cars 16 are moved into the holding area 18. After a patient card 12 is removed from a bed cell 14, the bed status (and the appearance of bed cell) temporarily changes to reflect that there is no longer a patient in the bed. When a patient card 12 is dragged from the holding area 18 and dropped into a bed cell 14, that action temporarily associates that patient with that bed. In this manner, the user may try a variety of different patient/room assignments until some optimized or otherwise desirable configuration is achieved. During this "modeling" stage, the various associations are temporarily saved. The assignment becomes final when the user clicks on a save button, or takes other appropriate actions to indicate that the current configuration of the bed board 10 is the configuration to be saved. That allows the user to model (try) different assignment scenarios before saving a final one” (Ellis at 0028). At Ellis, then, the “searching” state as claimed is indicated by the patient cards being considered for assignment, the “tentative” state as claimed is indicated by the temporary assignments, and the “completed” state is indicated by the saved final configuration, where the holding and transferring of patients (see Ellis at 0006, 0022-0023, 0026, Fig. 7) indicates that bed assignment states may be overridden or conceded. Therefore, the Examiner understands and finds that to use a FSM listing assignment status is applying a known technique to a known device, method, or product ready for improvement to yield predictable results so as to optimize bed assignments.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine or modify the bed assignments of Mancine in view of Shanbhag with the status indications of Ellis in order to use a FSM listing assignment status so as to optimize bed assignments.
The rationale for combining in this manner is that to use a FSM listing assignment status is applying a known technique to a known device, method, or product ready for improvement to yield predictable results so as to optimize bed assignments as explained above.
Claim 2: Mancine in view of Shanbhag in further view of Ellis discloses the method of claim 1 wherein the pre-assigning of the hospital bed occupied by the inpatient to the waiting patient comprises calculating the expected length of stay of the inpatient by applying inpatient information of the inpatient to a pre-modeled prediction function (Mancine at 0075, “network server 160 may be configured to receive assignment and/or discharge data from database 180 for each department and/or hospital, and process the received data to assign the patient bed based on real-time department and/or hospital loads, to assign the hospital unit best positioned to receive and/or discharge the patient at the corresponding date and/or time”),
creating a hospital bed assignment plan table including the calculated expected length of stay (Mancine at 0075, “network server 160 may be configured to receive assignment and/or discharge data from database 180 for each department and/or hospital, and process the received data to assign the patient bed based on real-time department and/or hospital loads, to assign the hospital unit best positioned to receive and/or discharge the patient at the corresponding date and/or time” – real-time load updating indicating the database/table is continuously being created as an updated version), and
assigning the hospital bed to the waiting patient based on the hospital bed assignment plan table (Mancine at 0075, as above),
wherein the hospital bed assignment plan table consists of inpatient hospital beds, inpatients occupying the inpatient hospital beds, and days (Mancine at 0075, as above; 0073 as indicating a single bed, multiple beds, or no beds meeting the search query input or criteria).
Claim 3: Mancine in view of Shanbhag in further view of Ellis discloses the method of claim 2, wherein the expected length of stay of the inpatient is calculated by the prediction function consisting of a dependent variable and a plurality of independent variables, and is an expected length of stay from a hospitalization indication date to an expected discharge date of the inpatient (Mancine at 0075, “network server 160 may be configured to receive assignment and/or discharge data from database 180 for each department and/or hospital, and process the received data to assign the patient bed based on real-time department and/or hospital loads, to assign the hospital unit best positioned to receive and/or discharge the patient at the corresponding date and/or time” – noting that Applicant ¶ 0054 indicates the expected length of stay as being the dependent variable), wherein the independent variables comprise one or more of gender, diagnosis code, surgery code, treatment code, or measurement value describing a patient's condition of the waiting patient (0065, “additional inputs pertaining to the patient. The inputs may include information to supplement the information received in step 502, such as personal attributes, patient preferences, and isolation information. Personal attributes may include, for example, physiological data, gender, height, weight, age, mental health, physical health, mobility, personality, level of sedation, and/or any other physical or mental characteristic. Patient preferences may include, for example, bed size, bed firmness, bed adjustability, level of care, desired interaction with other patients, desired location relative to a nurse's station or a window, and/or any other special accommodations. The isolation information may include information relating to any transmittable disease, such as transmission type (e.g., airborne, contact, etc.) and organism (e.g., MRSA)” – the indications of isolation information, mental health, physical health, mobility, personality, level of sedation, level of care, etc. being regarded as the diagnosis, surgery, or treatment code(s) per the light of the specification).
Claim 5: Mancine in view of Shanbhag in further view of Ellis discloses the method of claim 3,
wherein the hospital bed assignment plan table comprises a plurality of cells, each of which includes an empty cell associated with hospital beds and days and a fill cell associated with hospital beds, inpatients, and days (Ellis at 0006, 0022-0023, 0026, 0028, and Fig. 7 as combined above and using the rationale as at the combination above),
wherein the assigning of the hospital bed to the waiting patient based on the hospital bed assignment plan table comprises
creating a finite state machine (FSM) of the waiting patient (Ellis at 0006, 0022-0023, 0026, 0028, and Fig. 7 as combined above and using the rationale as at the combination above),
setting a state of the FSM based on the previous history of the waiting patient of the FSM, where if there is no previous history, the state is set to an initial state (Ellis at 0006, 0022-0023, 0026, 0028, and Fig. 7 as combined above and using the rationale as at the combination above), and
placing the FSM on the hospital bed assignment plan table according to a code of conduct predefined for each state of the FSM (Ellis at 0006, 0022-0023, 0026, 0028, and Fig. 7 as combined above and using the rationale as at the combination above).
Claim 6: Mancine in view of Shanbhag in further view of Ellis discloses the method of claim 5,
wherein the initial state is a first-1 state which indicates searching for cells in which the FSM will be placed (Ellis at 0006, 0022-0023, 0026, 0028, and Fig. 7 as combined above and using the rationale as at the combination above),
wherein the placing of the FSM on the hospital bed assignment plan table according to the code of conduct predefined for each state of the FSM comprises
placing the FSM whose state is set to the first-1 state in the earliest empty cell among the empty cells in the hospital bed assignment plan table and updating the state of the FSM to a first-2 state, where the earliest empty cell is an empty cell associated with the inpatient hospital bed with the earliest expected admission date in the hospital bed assignment plan table (Ellis at 0006, 0022-0023, 0026, 0028, and Fig. 7 as combined above and using the rationale as at the combination above), and
updating the state of the FSM to the second state if there is no event for a first predetermined period of time (Ellis at 0006, 0022-0023, 0026, 0028, and Fig. 7 as combined above and using the rationale as at the combination above),
wherein the second state indicates that assignment is completed (Ellis at 0006, 0022-0023, 0026, 0028, and Fig. 7 as combined above and using the rationale as at the combination above).
Claim 7: Mancine in view of Shanbhag in further view of Ellis discloses the method of claim 6, wherein the placing of the FSM on the hospital bed assignment plan table according to the code of conduct predefined for each state of the FSM further comprises
sending a reservation notification message including the fact that assignment has been completed to a waiting patient of the FSM in the second state (Mancine at 0010, “monitoring and notification communications”, 0076, “Once the assignment is complete, network server 160 may automatically send a notification to user”; Ellis at 0006, 0022-0023, 0026, 0028, and Fig. 7 as combined above and using the rationale as at the combination above),
wherein the reservation notification message includes hospital bed resource information about a hospital bed associated with the cells in which the FSM is placed (Mancine at 0010, “monitoring and notification communications”, 0076, “Once the assignment is complete, network server 160 may automatically send a notification to user”; Ellis at 0006, 0022-0023, 0026, 0028, and Fig. 7 as combined above and using the rationale as at the combination above).
Claim 8: Mancine in view of Johnson discloses the method of claim 6,
wherein if the urgency of admission included in the hospitalization indication condition satisfies a priority condition, the FSM of the waiting patient who satisfies the priority condition comprises an attribute of maximum tolerable waiting time (Mancine at 0071, “The availability of the bed may be determined by whether the bed is either unoccupied or occupied by a patient with a pending or confirmed discharge”, 0075, “network server 160 may be configured to receive assignment and/or discharge data from database 180 for each department and/or hospital, and process the received data to assign the patient bed based on real-time department and/or hospital loads, to assign the hospital unit best positioned to receive and/or discharge the patient at the corresponding date and/or time”; Ellis at 0006, 0022-0023, 0026, 0028, and Fig. 7 as combined above and using the rationale as at the combination above),
wherein the inpatient hospital bed associated with empty cells in which the FSM in the first-2 state is placed is a tentatively-assigned hospital bed (Mancine at 0071, and 0075 as above; Ellis at 0006, 0022-0023, 0026, 0028, and Fig. 7 as combined above and using the rationale as at the combination above),
wherein the placing of the FSM on the hospital bed assignment plan table according to the code of conduct predefined for each state of the FSM comprises
comparing an expected waiting time for the inpatient hospital bed associated with empty cells in which the FSM in the first-2 state is placed with a preset maximum tolerable waiting time (Mancine at 0071, and 0075 as above; Ellis at 0006, 0022-0023, 0026, 0028, and Fig. 7 as combined above and using the rationale as at the combination above); and
if the comparison results in that the expected waiting time is equal to or shorter than the maximum tolerable waiting time, updating the state of the FSM to a second state (Mancine at 0071, and 0075 as above; Ellis at 0006, 0022-0023, 0026, 0028, and Fig. 7 as combined above and using the rationale as at the combination above).
Claim 9: Mancine in view of Johnson discloses the method of claim 8,
wherein the placing of the FSM on the hospital bed assignment plan table according to the code of conduct predefined for each state of the FSM comprises
if the comparison results in that the maximum tolerable waiting time is longer than the expected waiting time for the tentatively-assigned hospital bed, sending a concession request signal to another FSM, and updating the state of the FSM from the first-2 state to a first-3 state, where the other FSM is a recipient FSM and includes another FSM tentatively assigned to another hospital bed with an expected discharge date that is equal to or earlier than the maximum tolerable waiting time (Mancine at 0071, and 0075 as above; Ellis at 0006, 0022-0023, 0026, 0028, and Fig. 7 as combined above and using the rationale as at the combination above), and
upon receiving a concession request acceptance signal from the recipient FSM, replacing the FSM to cells where the recipient FSM that transmitted the concession request acceptance signal is placed, and updating the replaced FSM to the second state (Mancine at 0071, and 0075 as above; Ellis at 0006, 0022-0023, 0026, 0028, and Fig. 7 as combined above and using the rationale as at the combination above).
Claim 10: Mancine in view of Johnson discloses the method of claim 9, further comprising:
when the recipient FSM has the first-2 state and
receives a concession request signal from a requester FSM, comparing the urgency of admission of the recipient FSM with the urgency of admission of the requester FSM (Mancine at 0071, and 0075 as above; Ellis at 0006, 0022-0023, 0026, 0028, and Fig. 7 as combined above and using the rationale as at the combination above);
when the urgency of admission of the requester FSM is higher than that of the recipient FSM as a result of the comparison, transmitting a concession request acceptance signal to the requester FSM (Mancine at 0071, and 0075 as above; Ellis at 0006, 0022-0023, 0026, 0028, and Fig. 7 as combined above and using the rationale as at the combination above); and
when the urgency of admission of the requester FSM is equal to or lower than that of the recipient FSM, transmitting a concession request rejection signal to the requester FSM (Mancine at 0071, and 0075 as above; Ellis at 0006, 0022-0023, 0026, 0028, and Fig. 7 as combined above and using the rationale as at the combination above).
Claims 11-14 are rejected on the same basis as claim 1 above since Mancine discloses a computer-readable recording medium recording a program for performing the smart hospital bed operating method according to claim 1 (for claim 11) and a hospital bed operating system using big data, the system comprising: a hospital bed management processing unit …; a hospital bed assignment processing unit …; and a hospital bed schedule prediction processing unit for performing the same or similar activities as at claim 1 (for claim 12), further comprising a database storing the hospital bed resource information, the inpatient information, and the waiting patient information (for claim 13) and a user interface provision unit that provides the hospital bed assignment plan table to a user (for claim 14) (Mancine at 0009, database, 0010, “a non-transitory computer-readable medium may store program instructions, which are executed by at least one processor device and cause a central communication server to perform operations for centralized event monitoring and notification communications”).
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Mancine in view of Shanbhag in further view of Ellis and in still further view of Lee et al. (U.S. Patent Application Publication No. 2013/0097053, hereinafter Lee)
Claim 4: Mancine in view of Shanbhag in further view of Ellis discloses the method of claim 3, but does not appear to explicitly disclose wherein coefficients of the independent variables in the prediction function are determined by an optimization algorithm, and the optimization algorithm includes job shop scheduling, Petri net, or CPU scheduling. Lee, however, teaches “recommending a combined service most efficient to a situation of a user considering the degree of complementarity between a plurality of services” (Lee at 0009), including where service items may be a homecare service and/or a health service (Lee at 0042), where “a correlation coefficient of an independent variable is a coefficient expressing how much a dependent variable and the independent variable are related or how much the independent variables are related, which is a value expressing a relation between the extracted independent variable and the dependent variable, i.e., a service index, or a value expressing a relation among the independent variables. Correlation coefficients of independent variables are previously stored in the psychosocial theory model database. Preferably, the correlation matrix is created by converting the correlation coefficients of the independent variables into a Petri net. The Petri net is invented by Carl Petri of Germany in 1960s, which is a method used as a useful means for modeling various situations” (Lee at 0055). Therefore, the Examiner understands and finds that to use at least a Petri net to optimize coefficients of independent variables is applying a known technique to a known device, method, or product ready for improvement to yield predictable results so as to provide the most efficient recommendations.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine or modify the bed assignments of Mancine in view of Shanbhag in further view of Ellis with the recommendations of Lee in order to use at least a Petri net to opt