Method and systems for product inventory are described. In one embodiment, an inventory surface unit retains a plurality of products in an unordered state. An inventory identification unit acquires information for an orientation, and location of the plurality of products on the inventory surface unit. The inventory identification unit is disposed above the inventory surface unit. An inventory pick unit is adapted to pick a product among the plurality of products from the inventory surface unit based on the orientation and location acquired by the inventory identification unit. The inventory pick unit is disposed proximal the inventory surface unit, and the inventory pick unit is communicatively connected to the inventory identification unit. Additional methods and systems are disclosed.
A method for predicting errors in prescription claim data is performed by a claim analysis device. The method includes extracting historical claim features from successfully processed historical claims received from the data warehouse system. The method includes extracting pending claim features from a pending claim. The method includes applying a binarization process on the extracted historical claim features to obtain a binarized training feature set. The method includes applying the binarization process on the extracted pending claim features to obtain a binarized pending feature set. The method includes calculating an aggregate distance between the binarized pending feature set and the binarized training feature set. The method includes identifying the historical claim associated with the least aggregate distance as a predictive historical claim. The method includes transmitting an alert upon determining that a billing attribute of the predictive historical claim fails to match a corresponding billing attribute of the pending claim.
G16H 20/10 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
G06F 16/28 - Databases characterised by their database models, e.g. relational or object models
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
A pharmaceutical order filling system receives pharmaceutical orders and uses a packing device to package pharmaceutical orders. The packing device is configured with at least one cutter that generates tailings and dust. A tailing collection device is provided that collects the tailings and dust generated by the packing device into and through an intake tube and into a collection assembly. The collection assembly includes a hood with at least one air filter, a frame, and a bin removably received within the frame. The frame supports the hood and aligns the bin to be in fluid communication with the hood. A gas motive device is positioned intermediate the ends of an intake tub before the hood and is configured to suction the tailings and/or dust.
G16H 20/13 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients delivered from dispensers
B65B 1/02 - Machines characterised by the incorporation of means for making the containers or receptacles
4.
DYNAMIC USER INTERFACE FOR AUTOMATED GENERATION OF CUSTOM PHYSICAL LABELS
A computer system includes memory hardware configured to store instructions and a database, and processor hardware configured to execute the instructions. The instructions include receiving input from a user. The instructions include querying the database to: obtain a label text associated with a specified national drug code (NDC), obtain a field associated with the label text, and obtain a set of field options associated with the field. The instructions include building a data structure including the label text, the field, and the set of field options. The instructions include converting the data structure to a dynamic web interface for displaying the label text, the field, and the set of field options. The instructions include receiving a user selection of a field option of the set of field options, updating the field to reflect the user selection, and generating a label by printing the label text including the updated field.
G16H 20/10 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
A computer-implemented method includes defining model attributes including a training iteration value that defines a set of training iterations to be used in machine learning to associate portions of feedback data with a set of topic groups based on similarities in concepts conveyed in the feedback data. The method includes removing at least some of the confidential information from the feedback data. The method includes receiving a topic model number selection that indicates a subset of the set of topic groups. The method includes using machine learning to train a machine model based on the model attributes and the topic model number selection. The method includes generating a display showing at least one of a topic cluster graph or a word cloud based on the machine model.
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
The medication dispensing assembly includes a housing having an interior. A medication bottle is disposed in the interior with its cap assembly facing vertically downwardly. The cap assembly includes outer, middle, and inner pieces. The outer and inner pieces are fixed with one another, and the middle piece is fixed with the bottle. A drive unit is disposed in the interior of the housing and is configured to rotate the bottle and the middle piece of the cap assembly about a vertical axis. The three pieces of the cap assembly have respective medication openings, and rotating the bottle causes individual pills to travel first from the bottle into the inner piece, then into the middle piece, then around the vertical axis, and then outside of the cap assembly through the medication opening of the outer piece.
A61J 7/00 - Devices for administering medicines orally, e.g. spoons; Pill counting devices; Arrangements for time indication or reminder for taking medicine
A61J 1/03 - Containers specially adapted for medical or pharmaceutical purposes for pills or tablets
A monitoring system for mapping and monitoring inter-application communications in a computing ecosystem is described. The monitoring system provides consolidated visibility to computing ecosystems by providing end-to-end mapping and monitoring of inter-application communications and events, changes, incidents, and status information of applications, services, and systems. As described, the monitoring system is configured to (a) identify communication paths linking the host devices, (b) generate an ecosystem map based on the communication paths, (c) transmit a monitoring signal to the network, (d) receive a monitoring response from the host devices in response to the monitoring signal including at least a first status, (e) process the monitoring response with the ecosystem map to generate an active ecosystem map, and (f) display the active ecosystem map including the host devices and at least one status associated with the host devices. As such, the monitoring system provides consolidated visibility to the ecosystem.
H04L 43/04 - Processing captured monitoring data, e.g. for logfile generation
G16H 20/10 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
H04L 43/08 - Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
8.
SHUTTLE FOR MOVING PACKAGES THROUGH A FILLING SYSTEM
The shuttle system is configured to convey a container through a filling center. The shuttle system includes a shuttle and a base plate that is operably attached with the shuttle. A plurality of support members extends vertically upwardly from the base plate and surround a container receiving space. The support members are configured to directly contact side surfaces of the container and to support the container as the shuttle moves through the filling center without locking the container to the shuttle.
B65B 43/54 - Means for supporting containers or receptacles during the filling operation
A61J 7/00 - Devices for administering medicines orally, e.g. spoons; Pill counting devices; Arrangements for time indication or reminder for taking medicine
9.
SYSTEM AND METHOD FOR SECURE DELIVERY OF A MEDICATION PACKAGE
A method for controlling secure delivery of a medication package includes receiving a medication delivery request to deliver a medication package to a first delivery location. The method also includes identifying one or more authenticated delivery locations corresponding to a recipient and determining whether the one or more authenticated delivery locations includes the first delivery location and, in response to a determination that the one or more authenticated delivery locations includes the first delivery location, instructing an unmanned aerial vehicle to transport the medication package from a starting location to the first delivery location. The method also includes, in response to the unmanned aerial vehicle communicating authentication data, determining whether the authentication data corresponds to the recipient. The method also includes, in response to a determination that the authentication data corresponds to the recipient, instructing the unmanned aerial vehicle to release the medication package to the recipient.
Methods and systems for selecting a machine learning algorithm are described. In one embodiment, one or more factors to be used by a machine learning algorithm in predicting a value of a required pharmacy element of a prescription are identified, the machine learning algorithm is trained to predict the value of the required pharmacy element using a first subset of previously received prescriptions, a success rates for the machine learning algorithm at predicting respective known values of respective known required pharmacy elements for each of a second subset of the previously received prescriptions are determined, and the machine learning algorithm predicts the value of the required pharmacy element of the prescription for a first predetermined period.
G16H 20/10 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
11.
METHODS AND APPARATUS FOR AUTOMATED COUNTING OF SOLIDS
A shim for a solid counting device is provided. The shim includes: a first end, including a first width and a projection extending in a lateral direction; a second end, including a second width greater than the first width; and an elongated body extending in a longitudinal dimension from the first end to the second end. The first width, the second width, and the projection configured to prevent more than one of a plurality of solids simultaneously traveling into an exit channel of the solid counting device.
A cryptographic protection system includes memory hardware configured to store instructions and processing hardware configured to execute the instructions stored by the memory hardware. The instructions include receiving a data package via a networked communications channel. The instructions include, in response to the data package satisfying first criteria, transforming the data package into a transformed package according to transformation rules. The transforming includes identifying a plurality of data elements in the data package as specified by the transformation rules and inserting each of the plurality of data elements into the transformed package. The instructions include executing a cryptographic hash on the transformed package to generate a cryptographic digest. The instructions include obtaining a cryptographic signature based on the cryptographic digest. The instructions include storing the cryptographic signature into a data store.
H04L 9/32 - Arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system
A computerized method of automated device efficacy determination for multiple monitor devices includes receiving streaming data including multiple health data values sensed by multiple monitor devices, each value indicative of health status of one or more members, and identifying first and second health data values from first and second target ones of the multiple monitor devices. The method includes determining first and second measured health status values of first and second ones of the members according to the identified first and second health data values, and aggregating the determined first measured health status value of the first member with the determined second measured health status value of the first member or the measured health status value of the second member. The method includes comparing the aggregated measured health status values to a target device efficacy threshold to determine an outcome-based device efficacy of the first and second target monitor devices.
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
G16H 40/40 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management of medical equipment or devices, e.g. scheduling maintenance or upgrades
G16H 40/67 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for remote operation
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
A61B 5/021 - Measuring pressure in heart or blood vessels
G06Q 50/28 - Logistics, e.g. warehousing, loading, distribution or shipping
G16H 20/10 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
G16Y 20/40 - Information sensed or collected by the things relating to personal data, e.g. biometric data, records or preferences
Method starts with a processor receiving configuration settings including an identified task, a relationship data, and a criticality value. Processor initializes a communication session with an agent client device. The communication session is between a virtual caller associated with the system and the agent client device. Processor then processes an audio signal of the communication session to generate an agent utterance and generates a transcribed agent utterance based on the agent utterance using a speech-to-text processor. Processor generates a virtual caller utterance using a task-specific virtual caller neural network associated with the identified task. The virtual caller utterance can be generated based on the transcribed agent utterance. Processor then causes the virtual caller utterance to be played back in the communication session to the agent client device. Other embodiments are disclosed herein.
H04M 11/10 - Telephonic communication systems specially adapted for combination with other electrical systems with dictation recording and playback systems
The medication container includes a receptacle and a cap. The cap includes a gate that can be selectively opened to enable access to medications in the receptacle and closed to restrict access to medications in the receptacle. The gate has a locking mechanism that only unlocks to allow the gate to open from the closed position in response to an application of a downward force on a portion of the gate to resiliently deflect a portion of the gate. The cap further includes electronic components that are configured to monitor movement of medications through the cap and into and out of the receptacle, the electronic components including a memory that is configured to store data pertaining to such passages of medications.
A method may include filling an order of a plurality of orders with a dosing filler system. The method may include receiving pharmaceutical orders including order for drugs used in multi-drug regimens using an order processing device. Each of the multi-drug regimen may have a plurality of scheduled dosing events. The method may include transporting containers to a dosing device, using the dosing device to dispense drugs for scheduled dosing events into the containers based on the received pharmaceutical orders, transporting the containers with the dispensed drugs to the container sealing device, using the container sealing device to seal the plurality of the containers with the dispensed drugs, transporting the dosage unit containers to the container identifier assembly, and using the container identifier assembly to identify the dosage unit containers based on the received pharmaceutical order.
G16H 20/13 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients delivered from dispensers
B65G 1/137 - Storage devices mechanical with arrangements or automatic control means for selecting which articles are to be removed
17.
METHODS AND SYSTEMS FOR FILLING CLIMATE CONTROLLED MEDICATIONS
A temperature-controlled medication packaging system includes a storage with a temperature-controlled interior containing at least one medication. The packaging system further includes at least one shipping container and at least one coolant that is sized to fit within the at least one shipping container. A first robot is adapted to retrieve the at least one medication from the storage and transport the at least one medication to a second robot. The second robot is adapted to receive the at least one medication from the first robot and to bring the at least one medication and the at least one shipping container and the at least one coolant together for packaging.
G06Q 10/0832 - Special goods or special handling procedures, e.g. handling of hazardous or fragile goods
G16H 20/13 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients delivered from dispensers
A medication dispensing system includes an automated dispensing device that includes cells with electronically activated locks. The device is configured to detect when medication counts in the cells fall below predetermined thresholds. The system further includes a plurality of first electronic devices that are associated with some of the cells and that have imagers. In response to any of the medication counts in the cells being below the predetermined threshold, the automated dispensing device is configured to automatically send a replenishment needed notification to the first electronic device associated with the cell. That first electronic device is configured to transmit a picture of a medication to a second electronic device. In response to a positive verification by a user of the second electronic device that the medication in the picture is the correct medication, the second electronic device is configured to transmit an unlock signal to the automated dispensing device.
A61J 7/00 - Devices for administering medicines orally, e.g. spoons; Pill counting devices; Arrangements for time indication or reminder for taking medicine
G16H 20/13 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients delivered from dispensers
G16H 40/63 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for local operation
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
G16H 70/40 - ICT specially adapted for the handling or processing of medical references relating to drugs, e.g. their side effects or intended usage
G06K 7/14 - Methods or arrangements for sensing record carriers by corpuscular radiation using light without selection of wavelength, e.g. sensing reflected white light
A61J 1/03 - Containers specially adapted for medical or pharmaceutical purposes for pills or tablets
G06F 3/0482 - Interaction with lists of selectable items, e.g. menus
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
H04N 7/18 - Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
19.
METHOD AND SYSTEM FOR PROGRAMMATICALLY TESTING USER INTERFACE PATHS
A computer system for testing a user interface includes a memory circuit and a processor circuit configured to execute instructions including obtaining a state of the user interface. The instructions include setting a current position to a specified location within the user interface. The instructions include executing user interface tests to generate multiple paths. The instructions include determining a shortest path toward a goal location by identifying a path having a minimum distance that satisfies criteria. A distance for the path is based on two-dimensional distances between pairs of consecutive positions that include the current position as well as positions, along the particular path, of user interface elements requiring interaction to satisfy the criteria. The instructions including generating a preferred path based on preferred path information indicative of a specified path toward the goal location, comparing the determined shortest path to the generated preferred path, and outputting an analysis result.
The medication container includes a receptacle that has an inner space for holding medications. The cap assembly is coupled with the receptacle for retaining the medications in the inner space. The cap assembly includes at least one passage that can be selectively opened and closed and includes at least one medication sensor that is configured to detect any medications travelling through the passage and out of the receptacle in a contactless manner. A microprocessor is in electrical communication with the at least one medication sensor and with a memory. The microprocessor is configured to record data to the memory in response to the at least one medication sensor detecting a medication travelling through the passage. A wireless module is in electrical communication with the microprocessor for uploading the data to an external device.
B65D 83/04 - Containers or packages with special means for dispensing contents for dispensing annular, disc-shaped, or spherical or like small articles, e.g. tablets or pills
A61J 1/03 - Containers specially adapted for medical or pharmaceutical purposes for pills or tablets
A hopper of a pharmaceutical counter comprises a housing defining an interior sized to hold a plurality of pharmaceuticals. The housing defines an outlet in communication with the interior that is sized and shaped to permit the plurality of pharmaceuticals to move therethrough. The hopper also includes a baffle supported by the housing and disposed in the interior. The baffle is disposed between upper and lower ends of the interior. The baffle is arranged to support a portion of the plurality of pharmaceuticals above the baffle when the plurality of pharmaceuticals is held in the interior of the housing. This relieves the head pressure of the pharmaceuticals at the outlet.
Methods and systems for medication delivery using unmanned aerial vehicles (UAVs) are provided. The methods and systems: determine a target destination for a regional payload consisting of one prescription drug item, by a server communicatively coupled to: (i) a distance UAV comprising a fixed-wing aircraft configured to travel point-to-point to a regional hub, and (ii) a plurality of local UAVs comprising rotary wing, multi-rotor aircrafts residing at the regional hub; transmit instructions to the distance UAV to fly to the regional hub with a distance payload including a plurality of regional payloads; transmit instructions to a local UAV, to: obtain the regional payload consisting of the one prescription drug item; transport the regional payload to the target destination; perform lateral movement and hover operations to access a delivery site of the target destination; and deliver the one prescription drug item by releasing the regional payload at the delivery site.
Systems and methods are provided for receiving a data set that includes demographic data and population data; training, based on the data set, a neural network to establish a relationship between different physical layouts of messages and responses to the different physical layouts of the messages; applying the trained neural network to a user profile to predict a physical layout of a message; generating instructions for an electronic device based on the predicted physical layout of the message, the instructions comprising the message; and transmitting the instructions to the electronic device to create a physical label having a layout corresponding to the predicted physical layout of the message.
A method for providing secure single sign on includes receiving a first data object from an application hosting server, the first data object indicating at least a service provider name and identifying a configuration file corresponding to the service provider name, wherein the configuration file includes at least trusted identity information. The method also includes determining, using the configuration file corresponding to the service provider name, whether the first data object is valid and, in response to a determination that the first data object is valid, generating a response message.
H04L 41/22 - Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks comprising specially adapted graphical user interfaces [GUI]
H04L 41/0869 - Validating the configuration within one network element
25.
SYSTEM AND METHOD FOR THERMAL CONTROL DURING DELIVERY OF A MEDICATION PACKAGE
A method for controlling an autonomous unmanned aerial vehicle for delivery of a medication package includes determining a thermal control period for the medication package. The method also includes identifying a delivery location corresponding to the medication package. The method also includes identifying at least one environmental characteristic of an environment that includes a delivery three-dimensional flight path between a starting location and the delivery location, wherein the at least one environmental characteristic indicates an actual weather value at the delivery location. The method also includes determining whether to deliver the medication package based on the thermal control period and the at least one environmental characteristic, using the unmanned aerial vehicle.
A package delivery system for delivering a plurality of packages with one or more unmanned aerial vehicles (UAVs) includes a package receptacle to receive and store the plurality of packages. A charging station charges a plurality of UAV batteries which power the one or more UAVs. A UAV landing pad permits the one or more UAVs to land thereon. A loader loads a package of the plurality of packages and/or a UAV battery of the plurality of UAV batteries onto the UAVs when the UAVs are on the UAV landing pad. A transporter moves the packages and/or the UAV batteries s toward the loader.
B64C 39/02 - Aircraft not otherwise provided for characterised by special use
B60L 50/60 - Electric propulsion with power supplied within the vehicle using propulsion power supplied by batteries or fuel cells using power supplied by batteries
A system and method for controlling an autonomous unmanned aerial vehicle for retrieval and delivery of a medical package includes determining a thermal control period for the medical package. The disclosure also includes identifying a relevant retrieval location corresponding to the medical package. The disclosure also includes identifying at least one environmental characteristic of an environment that includes a delivery three-dimensional flight path between the relevant retrieval location and a delivery location, wherein the at least one environmental characteristic indicates an actual weather value at the relevant retrieval location. The disclosure also includes determining whether to retrieve the medical package based on the thermal control period and the at least one environmental characteristic, using the unmanned aerial vehicle.
A governmental regulatory computing device, a user computing device, a participant computing device, and an analysis computing device communicate via a network. The analysis computing device determines a risk associated with at least one of a drug and a drug manufacturer based on data from the governmental regulatory computing device and a predicted demand from the participant computing device. The user computing device: requests and receives the risk from the analysis computing device; generates a report regarding the at least one of the drug and the drug manufacturer and include the risk in the report: and displays the report including the risk and the at least one of the drug and the drug manufacturer on a display. The analysis computing device, based on the risk associated with at least one of the drug and the drug manufacturer, selectively automatically orders a quantity of the drug from the drug manufacturer.
G16H 20/10 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
29.
PHARMACEUTICAL ORDER PROCESSING SYSTEMS AND METHODS
A pharmaceutical order processing system for processing a plurality of pharmaceutical containers includes a container repository, a container selector, an order consolidator transporter and an order consolidator. The container repository supports the pharmaceutical containers. The container selector has a picker to pick the pharmaceutical containers from the pharmaceutical container repository. The container selector includes a carriage supporting the picker and movable relative to the container repository to move the picker around the container repository. The order consolidator receives the pharmaceutical containers and places the pharmaceutical containers in a shipping package. The order consolidator transporter receives the pharmaceutical containers after they have been picked by the picker and transports the pharmaceutical containers toward the order consolidator.
B65B 5/08 - Packaging groups of articles, the articles being individually gripped or guided for transfer to the containers or receptacles
G05B 15/02 - Systems controlled by a computer electric
B65G 1/137 - Storage devices mechanical with arrangements or automatic control means for selecting which articles are to be removed
B65B 61/20 - Auxiliary devices, not otherwise provided for, for operating on sheets, blanks, webs, binding material, containers or packages for adding cards, coupons or other inserts to package contents
B65B 5/06 - Packaging groups of articles, the groups being treated as single articles
30.
WEARABLE DEVICES AND SYSTEMS FOR PRESCRIPTION ADHERENCE
A wearable computing device for monitoring and facilitating prescription adherence by a patient is provided. The wearable computing device is in communication with an inventory management server. The wearable computing device includes a processor and a memory. The processor is configured to receive a set of prescription plan data including at least a prescription identifier and a prescription rate associated with the prescription identifier. The processor is further configured to determine an inventory level associated with the prescription identifier. The processor is also configured to determine, based at least on the prescription rate, a time value representing a period of time in which a patient is prescribed to take a pharmaceutical associated with the prescription identifier. The processor is additionally configured to present a prescription inventory indicator representing the inventory level. The processor is also configured to present a timer indicator representing the time value.
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
A61J 7/04 - Arrangements for time indication or reminder for taking medicine, e.g. programmed dispensers
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
Methods and systems for performing dose regimen modification are provided. The methods and systems perform operations comprising: receiving prescription related data for treating a patient with an expected level of efficacy, the prescription related data comprising medication regimen information including dose and interval; determining, using a model, a first amount of drug waste based on the prescription related data; comparing the first amount of drug waste to a threshold value; and in response to determining that the first amount of drug waste transgresses the threshold value, identifying an alternate medication regimen that is associated with a treatment having a given level of efficacy corresponding to the expected level of efficacy, the alternate medication regimen being associated with a second amount of drug waste that is lower than the first amount of drug waste; and triggering a notification associated with the alternate medication regimen.
G16H 20/10 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
32.
ADAPTIVE MODEL TRANSFORMATION IN MULTI-TENANT ENVIRONMENT
A method includes receiving a query directed to a first data model that specifies base data fields. The method includes determining extension bindings for the first data model. A binding specifies an extension to the first data model and specifies one of the base data fields as a node at which the specified extension is added. The extension specifies a non-empty set of data fields. The method includes retrieving base data values according to the base data fields and extension data values according to, for a first binding, the set of data fields. The method includes generating a data object from the base and extension data values according to a second data model. The second data model is based on the first data model extended by adding the data fields from the extension specified by the first binding to the first data model at the specified node.
The cleaner assembly is configured for cleaning an automated dispensing device is described herein. The cleaner assembly includes a pallet; a plurality of side walls enclosing an inner chamber; a blower configured to propel contaminants into said inner chamber; and at least one roller operably supported by and projecting above at least one of said side walls, said at least one roller being configured to scrape contaminants off of a base plate of the automated dispensing device and towards said blower.
B65B 5/10 - Filling containers or receptacles progressively or in stages by introducing successive articles, or layers of articles
A61J 7/00 - Devices for administering medicines orally, e.g. spoons; Pill counting devices; Arrangements for time indication or reminder for taking medicine
B65G 45/22 - Cleaning devices comprising fluid applying means
A61J 1/03 - Containers specially adapted for medical or pharmaceutical purposes for pills or tablets
34.
METHODS AND SYSTEMS FOR PREDICTING PRESCRIPTION DIRECTIONS USING MACHINE LEARNING ALGORITHM
Methods and systems for predicting prescription drug directions are described. In one embodiment, a drug direction prediction subsystem receives and pre-processes values of a plurality of required pharmacy elements for a corresponding prescription of a plurality of prescriptions, generates respective weights for the values of the plurality of required pharmacy elements of the prescription based on one or more of the values of the plurality required pharmacy elements of the prescription, creates a machine learning model to be used by the applicable one of the plurality of machine learning algorithms in predicting drug directions of the prescription, the machine learning model using the values of the plurality of required pharmacy elements of the prescription and the respective weights, and predicts a plurality of drug directions of a new prescription by executing the machine learning model using weighted values of the plurality of required pharmacy elements of the new prescription.
G16H 20/10 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
A computer system includes memory storing a database including a label text table for storing multiple label texts each associated with a national drug code (NDC), a fields table, and a field options table. A processor is configured to execute instructions including receiving drug input from a user indicative of a specified NDC, querying the database to obtain a label text associated with the specified NDC, at least one field associated with the obtained label text, and multiple field options associated with the obtained field, building a data structure, converting the data structure to a user interface for displaying the obtained label text, the obtained field, and the multiple obtained field options, receiving a user selection of one of the multiple obtained field options, and printing the label text including the updated field to a label and/or saving the label text including the updated field to a record database.
G16H 20/10 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
Systems and methods herein describe receiving a transport request from a first device, transmitting the transport request to a second device, causing the second device to display a first instruction, determining that a current location of a securable container associated with the second device matches the first location, based on the determination, generating a first access code operable to access the securable container, and transmitting the first access code to a third device, receiving an indication that the securable container has been opened using the first access code, based on the indication, causing the second device to display a second instruction, determining that a subsequent location of the securable container matches the second location, based on the determination, generating a second access code and transmitting the second access code to the first device; and receiving a subsequent indication that the securable container has been opened using the second access code.
A container forming apparatus includes a plurality of forming members that have outer forming surfaces, which are shaped to form pockets in a sheet of material. A plurality of actuators are in mechanical connection with the forming members. The actuators are able to extend and retract the forming members. A controller is in electrical communication with the plurality of actuators. The controller is able to simultaneously extend any one or any combination of the forming members to create a plurality of pockets in a determined pattern in the sheet of material to produce a customized blister pack.
A61J 1/03 - Containers specially adapted for medical or pharmaceutical purposes for pills or tablets
B65D 75/36 - Articles or materials enclosed between two opposed sheets or blanks having their margins united, e.g. by pressure-sensitive adhesive, crimping, heat-sealing, or welding one or both sheets or blanks being recessed to accommodate contents one sheet or blank being recessed and the other formed of relatively stiff flat sheet material, e.g. blister packages
B65D 75/32 - Articles or materials enclosed between two opposed sheets or blanks having their margins united, e.g. by pressure-sensitive adhesive, crimping, heat-sealing, or welding one or both sheets or blanks being recessed to accommodate contents
B65B 5/02 - Machines characterised by incorporation of means for making the containers or receptacles
B65B 9/04 - Enclosing successive articles, or quantities of material, between opposed webs one or both webs being formed with pockets for the reception of the articles, or of the quantities of material
38.
SYSTEM AND METHOD FOR AUTOMATIC DETECTION FOR MULTIPLE FAILED ORDERS AT A BACK END PHARMACY
A method for predicting pharmacy order failures includes receiving sensor data from one or more sensors associated with pharmacy order fulfilment, and identifying at least one pharmacy order package associated with the sensor data. The method also includes updating data associated with the at least one pharmacy order package based on at least some of the sensor data, and providing, to a predictive model, the updated data, The predictive model may be configured to predict one or more failures in a pharmacy order associated with the at least one pharmacy order package. The method also includes, in response to receiving at least one prediction output from the predictive model indicating at least one failure prediction, initiating at least one corrective action.
G06Q 10/08 - Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
B65G 1/137 - Storage devices mechanical with arrangements or automatic control means for selecting which articles are to be removed
G06Q 30/06 - Buying, selling or leasing transactions
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
G16H 20/10 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
A temperature-controlled medication packaging system includes a storage with a temperature-controlled interior containing at least one medication. The packaging system further includes at least one shipping container and at least one coolant that is sized to fit within the at least one shipping container. A first robot is adapted to retrieve the at least one medication from the storage and transport the at least one medication to a second robot. The second robot is adapted to receive the at least one medication from the first robot and to bring the at least one medication and the at least one shipping container and the at least one coolant together for packaging.
G06Q 10/0832 - Special goods or special handling procedures, e.g. handling of hazardous or fragile goods
G16H 20/13 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients delivered from dispensers
A method for testing a user interface (UI) includes obtaining a first state of the UI and setting a current position to specified location coordinates. The method includes determining whether the first state satisfies criteria for a goal and, if so, updating a collection of completed tests with a test distance and test data. The method includes, in response to the first state not satisfying the criteria: determining a set of potential user actions to be performed in the first state based on interactive elements of the UI; selecting and executing an action; and updating the test distance based on the current position and location coordinates of the element associated with the action. The method includes determining a shortest path to the goal in the UI based on the collection of completed tests. The method includes, based on the determined shortest path, automatically visually transforming a state of the UI.
A pharmaceutical extractor and associated components and methods for removing pharmaceuticals from a plurality of containers. The extractor includes a plurality of holders. Each holder is configured to hold at least one container of the plurality of containers. Each holder is repeatedly cycled through a series of container operation locations of the pharmaceutical extractor. In the series of container operation locations, the holders receive containers, the containers are cut to form pharmaceutical outlets in the containers, pharmaceuticals are moved out of the pharmaceutical outlets, and empty containers are dropped by the holders.
A mail-order drug delivery system includes an order processing device configured to determine a first shipping mode and a corresponding first shipping carrier, generate an expected shipping duration associated with delivery of a drug, determine an origin forecasted temperature, determine a destination forecasted temperature, associate a shipping container with the drug to contain the drug, access temperature model data associated with the shipping container; and determine a predicted temperature of the drug at the shipping destination. The determination is based on forecasted temperatures, the expected shipping duration, the temperature model data, a next pickup time, a storage location of the drug, and a time difference between packing and the next pickup time. The system includes a packing device configured to receive the drug from a transport mechanism and selectively package the drug within the shipping container in response to the predicted temperature meeting a temperature-related storage requirement of the drug.
The medication container includes a receptacle that has an inner space for holding medications. The cap assembly is coupled with the receptacle for retaining the medications in the inner space. The cap assembly includes at least one passage that can be selectively opened and closed and includes at least one medication sensor that is configured to detect any medications travelling through the passage and out of the receptacle in a contactless manner. A microprocessor is in electrical communication with the at least one medication sensor and with a memory. The microprocessor is configured to record data to the memory in response to the at least one medication sensor detecting a medication travelling through the passage. A wireless module is in electrical communication with the microprocessor for uploading the data to an external device.
B65D 83/00 - Containers or packages with special means for dispensing contents
A61J 1/03 - Containers specially adapted for medical or pharmaceutical purposes for pills or tablets
B65D 83/04 - Containers or packages with special means for dispensing contents for dispensing annular, disc-shaped, or spherical or like small articles, e.g. tablets or pills
A pharmaceutical order processing system for processing a plurality of pharmaceutical containers includes a container repository, a container selector, an order consolidator transporter and an order consolidator. The container repository supports the pharmaceutical containers. The container selector has a picker to pick the pharmaceutical containers from the pharmaceutical container repository. The container selector includes a carriage supporting the picker and movable relative to the container repository to move the picker around the container repository. The order consolidator receives the pharmaceutical containers and places the pharmaceutical containers in a shipping package. The order consolidator transporter receives the pharmaceutical containers after they have been picked by the picker and transports the pharmaceutical containers toward the order consolidator.
B65B 5/06 - Packaging groups of articles, the groups being treated as single articles
B65B 5/08 - Packaging groups of articles, the articles being individually gripped or guided for transfer to the containers or receptacles
B65G 1/137 - Storage devices mechanical with arrangements or automatic control means for selecting which articles are to be removed
G05B 15/02 - Systems controlled by a computer electric
B65B 61/20 - Auxiliary devices, not otherwise provided for, for operating on sheets, blanks, webs, binding material, containers or packages for adding cards, coupons or other inserts to package contents
45.
SYSTEM AND METHOD FOR AUGMENTED REALITY DETECTION OF LOOSE PHARMACY ITEMS
A method includes capturing, by an image-capturing device, a one or more images of at least a portion of a pharmacy workstation. The method also includes identifying, by a processor in communication with the image capturing device, objects of interest in a first image of the one or more images and classifying, by the processor, the detected objects of interest using a convolutional neural network associated with the processor. The method also includes identifying, by the processor, a boundary defining an opening of a container in a second image of the one or more images. The method also includes updating, by the processor, an objects in container list based on a determination that at least one of the classified objects passed the boundary.
G16H 20/10 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
G06T 19/00 - Manipulating 3D models or images for computer graphics
Methods and systems for prescription drug shipping selection are provided. The methods and systems include operations comprising: obtaining, by a server, activity data from a plurality of devices associated with a location, the activity data representing different types of activities that take place at the location over a threshold period of time; aggregating, by the server, the activity data to generate a location-based presence model for the location, the location-based presence model indicating likelihoods that a person is present at the location at a plurality of different time windows; and identifying, by the server, based on the location-based presence model, a time window for delivery of a perishable item to the location.
Methods and systems for prescription drug shipping selection are provided. The methods and systems include operations comprising: obtaining, by a server, activity data from a plurality of devices associated with a location, the activity data representing different types of activities that take place at the location over a threshold period of time; aggregating, by the server, the activity data to generate a location-based presence model for the location, the location-based presence model indicating likelihoods that a person is present at the location at a plurality of different time windows; and identifying, by the server, based on the location-based presence model, a time window for delivery of a perishable item to the location.
A method includes receiving a data access request at a computing system. The data access request is for completion of a first data processing task using the computing system. The method also includes accessing a plurality of first document types associated with a plurality of data processing tasks that include the first data processing task. The plurality of first document types indicates which of various subsets of data are required to complete the plurality of data processing tasks. The method also includes accessing a plurality of second document types that indicate assignments of the plurality of data processing tasks to a plurality of system requestors that includes the first system requestor, and executing the first data processing task based on the plurality of first document types and the plurality of second document types.
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
A computer system includes memory hardware configured to store a dynamic mock engine module for service simulation in a user interface application development system, and multiple mock configurations. Processor hardware is configured to execute instructions including receiving an endpoint name associated with an endpoint of a user interface, receiving an input request, and selecting at least one of the mock configurations that corresponds to the received endpoint name. For each of the selected mock configurations corresponding to the endpoint, the instructions include determining a number of field values in the mock request of the selected mock configuration that match a field value of the input request. The instructions include determining which one of the selected mock configurations has a greatest match with the received input request, and transmitting the output response of the mock configuration having the greatest match to a computing device of the user interface application development system.
A system includes one or more processors coupled to a camera and a display. The processor(s) identify a unique identifier on a label of a prescription pill bottle or container using images generated by the camera, and request additional data from a pharmacy benefit manager using the identifier. The system includes an augmented reality subsystem that directs the display to present the additional data from the benefit manager in an augmented reality foreground image displayed over the camera images, directs the display to present interactive portion(s) in the augmented reality foreground image, and, responsive to detecting a user selection, implements an action that includes transmitting a request to refill a prescription drug, calling a doctor, and/or directing the display to present drug interaction information.
G06V 20/20 - Scenes; Scene-specific elements in augmented reality scenes
G06T 19/00 - Manipulating 3D models or images for computer graphics
G16H 80/00 - ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring
G06K 7/14 - Methods or arrangements for sensing record carriers by corpuscular radiation using light without selection of wavelength, e.g. sensing reflected white light
51.
SYSTEMS AND METHODS FOR PROVIDING STABLE DEPLOYMENTS TO MAINFRAME ENVIRONMENTS
A quality assurance system includes a mainframe deployment device in communication with a mainframe device with a codebase. The mainframe deployment device initializes a branch repository corresponding to a code region of the codebase, identifies, for a code element of the code region, a timestamp indicating a creation time and a user identifier indicating an owner, populates the branch repository with the code element based on the code region and the timestamp, applies a code security scan to the branch repository to identify and resolve a code security issue, and applies a code quality scan to the branch repository to identify a code quality issue in the code element, assign the code element to the user identifier based at least partially on the timestamp, and route the code element along with information regarding the code quality issue to correct the code quality issue in the code element.
A method for controlling an autonomous unmanned aerial vehicle for delivery of a medication package includes determining a thermal control period for the medication package. The method also includes identifying a delivery location corresponding to the medication package. The method also includes identifying at least one environmental characteristic of an environment that includes a delivery three-dimensional flight path between a starting location and the delivery location, wherein the at least one environmental characteristic indicates an actual weather value at the delivery location. The method also includes determining whether to deliver the medication package based on the thermal control period and the at least one environmental characteristic, using the unmanned aerial vehicle.
Methods and systems for item delivery using multiple unmanned aerial vehicles are provided. The methods and systems include operations comprising: obtaining, by a distance unmanned aerial vehicle (UAV), a package that includes a plurality of items, each item being associated with a target delivery destination; delivering, by the distance UAV, the package to a regional hub that includes a local UAV, the distance UAV being configured to travel a longer distance and carry more weight than the local UAV; retrieving, by the local UAV, a given item of the plurality of items from the package; determining, by the local UAV, the target delivery destination associated with the given item; and delivering, by the local UAV, the given item to the target delivery destination.
B64C 39/02 - Aircraft not otherwise provided for characterised by special use
G01W 1/06 - Instruments for indicating weather conditions by measuring two or more variables, e.g. humidity, pressure, temperature, cloud cover or wind speed giving a combined indication of weather conditions
A package delivery system for delivering a plurality of packages with one or more unmanned aerial vehicles (UAVs) includes a package receptacle to receive and store the plurality of packages. A charging station charges a plurality of UAV batteries which power the one or more UAVs. A UAV landing pad permits the one or more UAVs to land thereon. A loader loads a package of the plurality of packages and/or a UAV battery of the plurality of UAV batteries onto the UAVs when the UAVs are on the UAV landing pad. A transporter moves the packages and/or the UAV batteries s toward the loader.
B60L 50/60 - Electric propulsion with power supplied within the vehicle using propulsion power supplied by batteries or fuel cells using power supplied by batteries
B60L 53/50 - Charging stations characterised by energy-storage or power-generation means
B60L 53/80 - Exchanging energy storage elements, e.g. removable batteries
B64D 9/00 - Equipment for handling freight; Equipment for facilitating passenger embarkation or the like
Systems and methods herein describe receiving a transport request from a first device, transmitting the transport request to a second device, causing the second device to display a first instruction, determining that a current location of a securable container associated with the second device matches the first location, based on the determination, generating a first access code operable to access the securable container, and transmitting the first access code to a third device, receiving an indication that the securable container has been opened using the first access code, based on the indication, causing the second device to display a second instruction, determining that a subsequent location of the securable container matches the second location, based on the determination, generating a second access code and transmitting the second access code to the first device; and receiving a subsequent indication that the securable container has been opened using the second access code.
A system and method for controlling an autonomous unmanned aerial vehicle for retrieval and delivery of a medical package includes determining a thermal control period for the medical package. The disclosure also includes identifying a relevant retrieval location corresponding to the medical package. The disclosure also includes identifying at least one environmental characteristic of an environment that includes a delivery three-dimensional flight path between the relevant retrieval location and a delivery location, wherein the at least one environmental characteristic indicates an actual weather value at the relevant retrieval location. The disclosure also includes determining whether to retrieve the medical package based on the thermal control period and the at least one environmental characteristic, using the unmanned aerial vehicle.
Systems and methods herein describe a phantom therapy system. The phantom therapy system receives, via a network from a human machine interface pad, a set of pressure measurements, generates a set of pound-force per square inch (PSI) measurements based on the set of pressure measurements, transmits the set of PSI measurements to the set of pneumatic actuators coupled to a wearable fabric, and causes the set of pneumatic actuators to generate mechanical motion based on the set of PSI measurements.
G16H 40/63 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for local operation
G16H 20/30 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
Targeted medical intervention system comprises a processor that performs operations comprising selecting target user and generating targeted subset from population of users. To generate the targeted subset, the processor, compares each of the medical claim histories of the population of users to the target medical claim history based on similarity, frequency, and recency; generates a similarity score, a frequency score, and a recency score for each of the plurality of users; and selects the users to be included in the targeted subset based on the similarity score, the frequency score, and the recency score. The processor then monitors, for a period of time, the target medical claim history in comparison with medical claim histories to detect an anomaly in the target medical claim history; and causes an electronic communication to be displayed by a client device that comprises initiation of an intervention to be performed. Other embodiments are disclosed herein.
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G16H 40/67 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for remote operation
60.
Systems and methods for pharmaceutical container processing
A pharmaceutical extractor and associated components and methods for removing pharmaceuticals from a plurality of containers. The extractor includes a plurality of holders. Each holder is configured to hold at least one container of the plurality of containers. Each holder is repeatedly cycled through a series of container operation locations of the pharmaceutical extractor. In the series of container operation locations, the holders receive containers, the containers are cut to form pharmaceutical outlets in the containers, pharmaceuticals are moved out of the pharmaceutical outlets, and empty containers are dropped by the holders.
Systems and methods are provided for receiving a data set that includes demographic data and population data; training, based on the data set, a neural network to establish a relationship between different physical layouts of messages and responses to the different physical layouts of the messages; applying the trained neural network to a user profile to predict a physical layout of a message; generating instructions for an electronic device based on the predicted physical layout of the message, the instructions comprising the message; and transmitting the instructions to the electronic device to create a physical label having a layout corresponding to the predicted physical layout of the message.
A method for dynamically scoring aspects of a data object includes receiving a first data object indicating and determining a first sum of a product of a first value and a first weight value plus a product of a second value and a second weight value and generating a first score based on a result of the first sum. The method also includes determining a second sum of a product of a third value and a third weight value plus a product of a fourth value and a fourth weight value and generating a second score based on a result of the second sum. The method also includes determining a first data object score for the first data object based on, at least, the first score, the second score, and a fifth value.
G16H 10/00 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data
G16H 20/10 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
G16H 15/00 - ICT specially adapted for medical reports, e.g. generation or transmission thereof
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
A method includes receiving a data processing request at a computing system. The data processing request identifies data to be compared to sets of criteria according to a predefined sequence of the sets that is defined by a non-variant logic process. The method also includes determining whether the request is to be processed according to a variant logic process that defines a modified sequence of the criteria sets than the non-variant logic process. The method also includes dynamically altering the predefined sequence of the criteria sets to the modified sequence responsive to determining that the request is to be processed using the variant logic process, comparing the data identified by the request with the criteria sets according to the modified sequence, and processing the data according to the criteria sets of criteria in the modified sequence.
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
A pharmaceutical container holder for holding pharmaceutical containers includes a receiver having an interior sized and shaped to receive and hold the pharmaceutical containers as a stack of pharmaceutical containers. The receiver has a removal location from which the pharmaceutical containers are removed from the receiver. A lift raises the pharmaceutical containers disposed in the interior of the receiver upward to move the pharmaceutical containers toward the removal location. A lift controller operates the lift to move the pharmaceutical containers upward toward the removal location after an upper-most pharmaceutical container of the stack of pharmaceutical containers has been removed from the removal location to move a subsequent upper-most pharmaceutical container of the stack of pharmaceutical containers to the removal location.
Methods and systems for prescription drug shipping selection are provided. The methods and systems include operations comprising: obtaining, by a server, activity data from a plurality of devices associated with a location, the activity data representing different types of activities that take place at the location over a threshold period of time; aggregating, by the server, the activity data to generate a location-based presence model for the location, the location-based presence model indicating likelihoods that a person is present at the location at a plurality of different time windows; and identifying, by the server, based on the location-based presence model, a time window for delivery of a perishable item to the location.
A method includes receiving historical data collected from a client associated with members. The historical data includes per-member metrics for the client and demographic information for the members. The method includes identifying therapeutic classes for the client based on the per-member metrics and the demographic information. The method includes segmenting the historical data into a data set for each therapeutic class. The method includes, for each therapeutic class of the set of therapeutic classes, determining a pattern for the per-member metrics corresponding to the respective therapeutic class, generating a respective predictive model based on the pattern, and training a neural network of the respective predictive model using a two-stage training process. The predictive model is configured to generate, as output for the therapeutic class, a per-member metric prediction for an input period of future time. The method includes generating predictions for the therapeutic classes using the predictive models.
G16H 70/40 - ICT specially adapted for the handling or processing of medical references relating to drugs, e.g. their side effects or intended usage
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
68.
Adaptive model transformation in multi-tenant environment
A query processing method includes receiving a query from a requestor. The query is directed to a first data model specifying multiple base data fields. The method includes determining a set of extension bindings for the first data model based on the query. Each binding specifies an extension to the first data model from a set of model extensions and specifies one of the base data fields of the first data model as a node at which the extension is added. The method includes generating a data object from base data values and extension data values according to an extended data model. The extended data model is defined by the first data model extended by, for each binding of the set, adding data fields from the specified extension to the first data model at the specified node. The method includes returning the data object to the requestor.
A method for providing mainframe codebase maintenance and security is performed by a mainframe deployment device. The method includes importing the mainframe codebase from a mainframe device. The mainframe codebase includes at least one code region including at least one code element. The method also includes identifying the code regions and initializing a branch repository corresponding to at least one identified code region. The method includes querying the imported mainframe codebase to identify, for the code elements, a user identifier and a source region. The method includes populating the branch repositories with the code elements based on the respective source region. The method includes applying a code quality scan to the populated branch repositories to identify a code quality issue in the respective code elements. The method also includes submitting at least one code element having an identified code quality issue to a user device correct the code quality issues.
An apparatus for liquid medication bottle-splitting is provided. The apparatus includes: a first dispensing section comprising a funnel-shaped hollow body with a wide inlet opening tapering to a narrow outlet; a second dispensing section comprising a second funnel-shaped hollow body with a second wide inlet opening tapering to a second narrow outlet; and a crossover channel connecting the first dispensing section to the second dispensing section, the crossover channel including a crossover opening extending a length of the crossover channel, and the crossover channel being angled to evenly distribute a flow of liquid medication into at least a first split portion in the first dispensing section and a second split portion in the second dispensing section; the first dispensing section adapted to dispense the first split portion, and the second dispensing section adapted to dispense the second split portion.
A method includes storing a parameter related to a user, storing descriptive data for multiple identifiers, and indexing multiple events. Each event corresponds to a physical object supplied to a user on behalf of an entity. The method includes identifying a first set of identifiers based on commonality among the descriptive data. The method includes training a machine learning model for the first set of identifiers based on event data from within a predetermined epoch. The method includes receiving an indication of a selected identifier and determining a first intake metric of the selected identifiers using the machine learning model. The method includes determining a second intake metric of the selected identifier and the parameter and transforming the user interface according to the first and second intake metrics. The first intake metric represents an amount of resources expected to be received during a second epoch subsequent to the predetermined epoch.
G06F 9/451 - Execution arrangements for user interfaces
G16H 40/67 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for remote operation
G06F 17/11 - Complex mathematical operations for solving equations
Method for generating user interface that indicates medication changes in medication starts with a processor detecting a medication change event. Processor retrieves medication information based on the medication change event including images of two medications. Processor generates color difference output using a color neural network, image of first medication and second medication. Color difference output comprises information on a difference in hue, saturation or color distribution. Processor generates medication appearance difference output using medication appearance neural network, image of first medication and second medication. Medication appearance difference output comprises information on a difference in shape, segmentation or form. Processor generates a differential record using the color difference output and medication appearance difference output. Processor causes medication change user interface to be displayed that comprises medication images and color and appearance descriptions of the medication which are displayed to emphasize differences identified in the differential record. Other embodiments are disclosed herein.
A61J 7/00 - Devices for administering medicines orally, e.g. spoons; Pill counting devices; Arrangements for time indication or reminder for taking medicine
G16H 20/10 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
G06V 10/56 - Extraction of image or video features relating to colour
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 10/22 - Image preprocessing by selection of a specific region containing or referencing a pattern; Locating or processing of specific regions to guide the detection or recognition
A medication dispensing system includes an automated dispensing device that includes cells with electronically activated locks. The device is configured to detect when medication counts in the cells fall below predetermined thresholds. The system further includes a plurality of first electronic devices that are associated with some of the cells and that have imagers. In response to any of the medication counts in the cells being below the predetermined threshold, the automated dispensing device is configured to automatically send a replenishment needed notification to the first electronic device associated with the cell. That first electronic device is configured to transmit a picture of a medication to a second electronic device. In response to a positive verification by a user of the second electronic device that the medication in the picture is the correct medication, the second electronic device is configured to transmit an unlock signal to the automated dispensing device.
G06F 7/00 - Methods or arrangements for processing data by operating upon the order or content of the data handled
G16H 20/13 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients delivered from dispensers
H04N 7/18 - Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
A61J 7/00 - Devices for administering medicines orally, e.g. spoons; Pill counting devices; Arrangements for time indication or reminder for taking medicine
G16H 40/63 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for local operation
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
G16H 70/40 - ICT specially adapted for the handling or processing of medical references relating to drugs, e.g. their side effects or intended usage
G06K 7/14 - Methods or arrangements for sensing record carriers by corpuscular radiation using light without selection of wavelength, e.g. sensing reflected white light
A61J 1/03 - Containers specially adapted for medical or pharmaceutical purposes for pills or tablets
G06F 3/0482 - Interaction with lists of selectable items, e.g. menus
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
A61J 1/14 - Containers specially adapted for medical or pharmaceutical purposes - Details; Accessories therefor
74.
Systems and methods for pharmaceutical package delivery
A pharmaceutical package for carrying a pharmaceutical container includes a first housing and a second housing in the first housing. The second housing defines a compartment sized and shaped to receive and carry the pharmaceutical container. A gas chamber is disposed between the first and second housings. The gas chamber is configured to hold a gas in an inflated state of the gas chamber. A passage extends from the first housing to the second housing and defines a passageway extending there-between to allow the pharmaceutical container to be positioned in the compartment of the second housing by moving the pharmaceutical container through the passageway. One or more supports are connected to and extending between the first housing and the second housing. The one or more supports secure and hold the second housing in the first housing.
B65D 81/20 - Containers, packaging elements, or packages, for contents presenting particular transport or storage problems, or adapted to be used for non-packaging purposes after removal of contents providing specific environment for contents, e.g. temperature above or below ambient under vacuum or superatmospheric pressure, or in a special atmosphere, e.g. of inert gas
B64F 1/32 - Ground or aircraft-carrier-deck installations for handling freight
B64C 39/02 - Aircraft not otherwise provided for characterised by special use
A47G 29/14 - Deposit receptacles for food, e.g. breakfast, milk; Similar receptacles for large parcels with appliances for preventing unauthorised removal of the deposited articles
B64U 101/60 - UAVs specially adapted for particular uses or applications for transporting goods other than weapons
A computer system includes memory hardware configured to store a predictive analyzer module, and a fallout transaction history record database including multiple historical fallout transaction records each associated with a database entity. Processor hardware is configured to execute instructions including receiving a fallout transaction request, determining a database search type according to at least one error field of the fallout transaction request, and searching, via the predictive analyzer module, to identify at least one of the multiple historical fallout transaction records associated with one or more field values of the fallout transaction request and the at least one error field. In response to identifying a matching one of the multiple historical fallout transaction records, the instructions include updating the at least one error field of the fallout transaction request, and transmitting the updated fallout transaction request to an automated request processor in response to a successful validation.
G06F 16/21 - Design, administration or maintenance of databases
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
77.
Display screen with a transitional graphical user interface
A method includes generating an intervention model by determining principal components for features of a training set, associating each feature of the training set with one of the principal components, selecting features of the training set most closely correlated with the principal components, performing a regression analysis on the selected features to determine a subset of the selected features that are most closely correlated with a model target, training a machine learning model with the subset, verifying the trained machine learning model with a verification set, and saving the verified trained machine learning model as the intervention model. The method includes determining an intervention expectation indicating a likelihood that the user will take action in response to an intervention being execute, determining a likelihood of a gap in care for the user, selecting and scheduling an intervention for execution based on the care gap likelihood and the intervention expectation.
G16H 80/00 - ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring
G06F 17/18 - Complex mathematical operations for evaluating statistical data
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
G16H 20/10 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
79.
MACHINE LEARNING MODELS FOR AUTOMATED ENTITY FIELD CORRECTION
A computer system includes memory hardware configured to store a machine learning model, a record database, and historical feature vector inputs. Processor hardware is configured to execute instructions which include training the machine learning model to generate an entity field output, and for each of multiple database entities, scanning the database entity to generate a feature vector input, and processing the feature vector input to generate the entity field output. In response to determining that the entity field output includes at least one missing field value, the instructions include accessing the record database to identify a predicted value for the missing field value, analyzing the structured scan data or rescanning the database entity to determine whether the predicted value is present in the database entity, and assigning the database entity to the validated subset of the multiple database entities when the predicted value is present in the database entity.
G16H 20/10 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
A method for automated entity field correction includes scanning a database entity to generate structured scan data, generating a feature vector input according to the structured scan data, and processing, by a machine learning model, the feature vector input to generate an entity field output including multiple identified entity fields and values of the identified entity fields. In response to determining that the entity field output includes at least one missing field value, the method includes accessing a record database to identify a predicted value for the missing field value, comparing a predicted name string of the predicted value to a scanned name string of the structured scan data to determine at least one of a Levenshtein distance and a Jaro-Winkler distance, and transmitting the database entity to a prescription fill processing module for automated processing of a prescription fill specified by the database entity.
G16H 20/10 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
81.
Artificial intelligence system for modeling drug trends
A method for generating predictions for year-over-year change in drug spending and per member per month spending and for providing the predictions via a web portal includes receiving data collected from a health plan. The data includes per member per month costs of the health plan and demographic information of members of the health plan. The method includes selecting therapeutic classes based on the per member per month costs and demographic information, segmenting the data by the therapeutic classes, and detecting patterns by analyzing the segmented data. The method includes generating models for the therapeutic classes based on the patterns, and generating predictions for year-over-year change in drug spending and per member per month spending for the therapeutic classes by utilizing the models. The method includes providing the predictions via a web portal in at least one of a displayable graphical format and a downloadable data structure.
G16H 70/40 - ICT specially adapted for the handling or processing of medical references relating to drugs, e.g. their side effects or intended usage
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
82.
PHARMACEUTICAL CONTAINER PROCESSING SYSTEMS AND METHODS
A pharmaceutical container processor for a pharmaceutical container, components thereof, and associated methods. The pharmaceutical container includes a container body and a preexisting label on the container body. The preexisting label has opposite side edges defining a preexisting label gap therebetween. The pharmaceutical container processor includes a label holder, a label detector, and a container transporter. The label holder positions a patient label to be applied on the container body of the pharmaceutical container. The label detector detects the preexisting label on the container body. The container transporter orients the preexisting label on the container body of the pharmaceutical container relative to the label holder so that at least a portion of the preexisting label gap is uncovered by the patient label when the patient label is applied on the container body.
A pharmaceutical order processing system, components thereof, and associated methods for filling a prescription order. The pharmaceutical order processing system includes a lower insert placer, a syringe placer, a dosing cup placer, a pharmaceutical container placer, and/or an upper insert placer. The lower insert placer places a lower insert into a box. The syringe placer places a syringe into a syringe compartment of the lower insert. The dosing cup placer places a dosing cup into a dosing cup compartment of the lower insert. The pharmaceutical container placer places a pharmaceutical container into a pharmaceutical container compartment of the lower insert. The upper insert placer places an upper insert into the box after the box has received the lower insert and the lower insert has received the syringe, the dosing cup and the pharmaceutical container.
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
G16H 20/10 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
A method includes generating an intervention model by determining principal components for features of a training set, associating each feature of the training set with a principal component, selecting features of the training set most highly correlated with principal components, training a machine learning model with at least some of the selected features, and saving the verified trained machine learning model as the intervention model. The method includes determining multiple channel-specific intervention expectations. Each channel-specific intervention expectation indicates a likelihood that the user will take action in response to an intervention being executed using the engagement channel corresponding to the channel-specific intervention expectation. The method includes selecting an intervention and scheduling the selected intervention for execution.
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
G06Q 50/00 - Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
G06Q 30/0201 - Market modelling; Market analysis; Collecting market data
G06Q 10/107 - Computer-aided management of electronic mailing [e-mailing]
G16H 20/10 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
G16H 80/00 - ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring
The shuttle system is configured to convey a container through a filling center. The shuttle system includes a shuttle and a base plate that is operably attached with the shuttle. A plurality of support members extend vertically upwardly from the base plate and surround a container receiving space. The support members are configured to directly contact side surfaces of the container and to support the container as the shuttle moves through the filling center without locking the container to the shuttle.
B65G 35/06 - Mechanical conveyors not otherwise provided for comprising a load-carrier moving along a path, e.g. a closed path, and adapted to be engaged by any one of a series of traction elements spaced along the path
B65G 47/94 - Devices for flexing or tilting travelling structures; Throw-off carriages
B65G 47/91 - Devices for picking-up and depositing articles or materials incorporating pneumatic, e.g. suction, grippers
A system and method for load balancing within a packing system may identify locations of carrier devices in the packing system based on optical communications between the carrier devices and route communication devices disposed at different locations along the routes of the packing system. The system and method can identify zones associated with different segments of the routes, determine whether a number and/or density of the carrier devices in a zone exceeds a threshold, and, responsive to the number and/or the density exceeding the threshold, (a) the carrier devices are directed to move to reduce the number and/or the density of the carrier devices and/or (b) the task performed by one or more of the task stations of the packing system is changed.
A packing system for packing products (e.g., medications) and other components into a container for shipping to customers is provided. The packing system includes a system controller that directs carrier devices along routes between task stations. The system controller can monitor the tasks performed by the task stations, the locations of the carrier devices, the tasks yet to be performed to complete packing of the containers at the task stations, and queues of other carrier devices at the stations. Based on this information, the system controller may direct the carrier devices to different stations and may change the task performed by or assigned to one or more of the stations.
Methods and systems for an accessibility system are provided. The methods and systems include operations comprising: receiving a request for a markup language document; obtaining the markup language document; processing a first portion of the markup language document with a machine learning technique to generate a first dictation corresponding to the first portion of the markup language document, the machine learning technique being trained to establish a relationship between a plurality of training markup language documents and training dictations corresponding to the training markup language documents; and replacing the first portion of the markup language document with the first dictation.
A computerized method includes receiving, from a predictive model, a personalization score representing a likelihood that a user is receptive to multiple communication protocols. The method includes selecting a set of communication protocols based on the personalization score. The method includes generating a compliance plan, for addressing a non-compliance failure, including a hierarchy of communication protocols and a set of rule-based conditions. The method includes automatically deploying the compliance plan by generating a first compliance message with a first communication protocol that corresponds to a first level of the hierarchy associated with the compliance plan. The method includes, in response to determining that the non-compliance failure persists for a threshold period of time, generating a second compliance message with a second communication protocol that corresponds to a second level of the hierarchy. The second level demands greater communication resources than the first level.
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
G16H 20/10 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
90.
MICROSERVICE ARCHITECTURE WITH AUTOMATED NON-INTRUSIVE EVENT TRACING
A computer system includes memory hardware configured to store structured microservice configuration data having multiple microservice entries each associated with one of multiple microservice applications of a request processing architecture. The system includes processor hardware configured to access structured microservice configuration data to identify the microservice applications of the request processing architecture, subscribing to messages transmitted by the identified microservice applications for event monitoring, and receiving multiple messages transmitted by the identified microservice applications. For each of the multiple received messages, the instructions include analyzing one or more fields of the received message to determine a correlation identifier associated with the received message, identifying one of the multiple request data structures, storing an event message entry in the identified request data structure, and transforming a user interface of a user device to display at least a portion of the multiple event message entries.
Methods and systems for selecting a machine learning algorithm are described. In one embodiment, one or more factors to be used by a plurality of machine learning algorithms in predicting a value of a required pharmacy element of a prescription are identified, each of the plurality of machine learning algorithms are trained to predict the value of the required pharmacy element using a first subset of previously received prescriptions, respective success rates for each of the plurality of machine learning algorithms at predicting respective known values of respective known required pharmacy elements for each of a second subset of the previously received prescriptions are determined, and a first of the plurality of machine learning algorithms having a highest success rate is selected to predict the value of the required pharmacy element of the prescription for a first predetermined period.
G16H 20/10 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
A system for generating dynamic user interfaces includes memory hardware storing instructions and processor hardware executing the instructions. The instructions include generating an interactive graphical user interface with fields corresponding to dates. The instructions include generating a selectable user interface element at a first field corresponding to a scheduled delivery date for a recipient. The instructions include, in response to a user dragging-and-dropping the selectable user interface element to a second field corresponding to an adjusted delivery date for the recipient, calculating a supply measure of a prior fill remaining with the recipient based on a stated duration of the prior fill and a date indicating receipt of the prior fill by the recipient. The instructions include, in response to the supply measure being greater than the threshold, moving the selectable user interface element to the second field and updating the scheduled delivery date to be the adjusted delivery date.
G16H 20/10 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
An AI record matching system may obtain patient records having different first names, compare demographic information in the records, determine whether the demographic information is linked with a common household, and identify nicknames by comparing the patient records using a first model. The first model may include mathematical relationships that represent different relationships among a first number of instances where the patient records have the first names that do not match, a second number of instances where the patient records having the first names that do not match but share a demographic marker, a threshold proportion of households for determining that the first names are the nicknames of each other, and a required volume of the households.
G16H 20/10 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G06F 16/215 - Improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors
94.
PACKAGING SYSTEM INCLUDING A SHRINK WRAP DEVICE FOR WRAPPING CONTAINERS THAT INCLUDE ENVIRONMENTALLY SENSITIVE PHARMACEUTICALS
A fulfillment system is provided and includes a perishable drug filling system and a non-perishable drug filling system. A shipping station is provided for delivering the coolers and the boxes to at least one delivery service. A conveyor is configured to move the boxes and the coolers from the drug filling systems to the shipping station. A decision station is located along the conveyor and is configured to determine if a container on the conveyor is a cooler or a box. The conveyor is configured to direct the coolers to a shrink wrap station and to direct the boxes to the shipping station while bypassing the shrink wrap station. The shrink wrap station is configured to apply a wrapper around the cooler and apply heat to the wrapper to shrink the wrapper around the cooler with the wrapper having a transparent section over a label on the cooler.
A method includes receiving a first set of identifiers selected based on commonality among descriptive data corresponding to the identifiers of the first set. Each identifier corresponds to a user who has been supplied a physical object. The method includes identifying event data for the first set within a specified epoch. The method includes training a machine learning model for the first set using the identified event data. The machine learning model is trained using parallel processing of records from a storage structure storing the event data. The parallel processing includes assigning analysis of the event data of each of a subset of the first set to respective processor threads for parallel execution on processing hardware. The trained machine learning model is configured to receive a selected identifier and generate an output representing an amount of resources expected to be used by the selected identifier for a subsequent epoch.
G06F 9/451 - Execution arrangements for user interfaces
G16H 40/67 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for remote operation
G06F 17/11 - Complex mathematical operations for solving equations
G06Q 10/08 - Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
G16H 70/40 - ICT specially adapted for the handling or processing of medical references relating to drugs, e.g. their side effects or intended usage
A computerized method of capturing monitor device data in a blockchain includes receiving a product identifier and product registration information for a monitor device supplied by a vendor. The method includes generating a secret device key for the monitor device. The method includes configuring the monitor device with the secret device key. The method includes receiving a member identifier and member registration information for a member associated with the monitor device. The method includes generating, by a blockchain secret member key ledger, a secret member key. The method includes linking the secret member key with the monitor device. The method includes receiving, by a blockchain secret member-device association ledger, an associated pair of the secret device key with the secret member key to store the associated pair for further authentication and authorization by the blockchain secret member-device association ledger.
G16H 40/60 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
G16H 40/40 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management of medical equipment or devices, e.g. scheduling maintenance or upgrades
A pharmaceutical order filling system uses a physical parameter that occurs during attaching cap to a pharmaceutical container to determine if the cap is properly engaged. The physical parameter may be torque on the cap when placed on the container. An order processing device receives a pharmaceutical order and sends the order to a dispensing device that fills the container with a pharmaceutical in the pharmaceutical order. A cap device is configured to apply the cap the container containing the pharmaceutical from the dispensing device, wherein the cap device is configured to sense the physical parameter, e.g., torque, to the cap when applying the cap to the container.
B65B 7/28 - Closing semi-rigid or rigid containers or receptacles not deformed by, or not taking-up shape of, contents, e.g. boxes or cartons by applying separate preformed closures, e.g. lids, covers
B65B 57/00 - Automatic control, checking, warning or safety devices
B67B 3/20 - Closing bottles, jars, or similar containers by applying caps by applying and rotating preformed threaded caps
98.
COMPUTERIZED METHOD AND APPARATUS FOR AUTOMATED DISTRIBUTED INGEST AND PRESENTATION OF MULTI-DOMAIN METRICS
A computerized search method includes receiving first input designating a first location of a first analytic. The method includes, in response to a scheduling event, obtaining a first document from the first location, identifying a first predefined label within the first document, obtaining first and second data associated with the first predefined label, storing the first datum into a value index as a current value of the first analytic, and storing the second datum into a text index as a textual description of the first analytic. The method includes presenting a search interface and, in response to receiving a search query from a user: identifying a set of result analytics relevant to the search query based on the text index and presenting, for each of the result analytics, a textual description of the analytic from the text index and a most recent value of the analytic from the value index.
G06F 16/31 - Indexing; Data structures therefor; Storage structures
G16H 20/10 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
G06F 16/955 - Retrieval from the web using information identifiers, e.g. uniform resource locators [URL]
G06F 40/18 - Editing, e.g. inserting or deleting using ruled lines of spreadsheets
A wearable computing device for monitoring and facilitating prescription adherence by a patient is provided. The wearable computing device is in communication with an inventory management server. The wearable computing device includes a processor and a memory. The processor is configured to receive a set of prescription plan data including at least a prescription identifier and a prescription rate associated with the prescription identifier. The processor is further configured to determine an inventory level associated with the prescription identifier. The processor is also configured to determine, based at least on the prescription rate, a time value representing a period of time in which a patient is prescribed to take a pharmaceutical associated with the prescription identifier. The processor is additionally configured to present a prescription inventory indicator representing the inventory level. The processor is also configured to present a timer indicator representing the time value.
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
A61J 7/04 - Arrangements for time indication or reminder for taking medicine, e.g. programmed dispensers
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
100.
PHARMACY BENEFIT MANAGEMENT MACHINE LEARNING SYSTEMS AND METHODS
A machine learning process for use with a pharmacy benefits management system. The machine learning process identifies a first predicted set of drug benefit claims impacted by a pricing error, reprices a sample of the first predicted set of drug benefit claims to adjust for the error, and trains a predictive model as a function of the repriced sample. Based on the trained model, the machine learning process predicts a second predicted set of drug benefit claims impacted by the error and initiates automatic repricing.
G06K 9/62 - Methods or arrangements for recognition using electronic means
G16H 20/10 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
patents
