Abstract: A computer system includes a sorting device that receives a set of orders. The sorting device, for each fill of a first order of the set of orders, assigns the fill to one of a set of fulfillment devices. The computer system includes a sequence determination device configured to receive a first set of fills assigned to a first fulfillment device of the set of fulfillment devices. The sequence determination device adds the first set of fills to a first sequence corresponding to the first fulfillment device. The sequence determination device, for each fill of the first set of fills, determines a start time based on (i) a corresponding target date of the corresponding order and (ii) a priority of the corresponding order. The sequence determination device organizes the first sequence based on the start times. A forwarding device forwards the first sequence to the first fulfillment device.

Abstract: An event processing system is provided for providing resilient message processing using asynchronous communications. The event processing device includes a processor and a memory. The event processing device is in communication with a publisher microservice and subscriber microservices. The processor is configured to receive an event including a collection of data from the publisher microservice. The processor is also configured to process the event to identify a recipient microservice. The processor is configured to update a queue with a queue entry for each of the at least one recipient microservices for the event. Each queue entry is associated with a priority. The processor is also configured to attempt to transmit the event to each of the at least one recipient microservices until a transmission confirmation message is received. The processor is further configured to update the queue by removing the queue entry for which the transmission confirmation message is received.

Abstract: The imaging system includes a rotating element that is configured to rotate about a central axis. A plurality of scanners are fixedly attached with the rotating element. Each scanner has a lens that faces generally towards the central axis, and the scanners are spaced apart from one another around the central axis. The scanners are configured to identify an optically readable machine readable code contained on the medication container. An actuator is operably connected with the rotating element and is configured to rotate the rotating element and the scanners around the central axis from respective e first positions to respective second positions to allow the scanners to image different areas of the medication container in response to a failure of the scanners to identify the machine readable code when the scanners were in the respective first positions.

Abstract: Methods and systems for managing pricing guarantees for prescription drugs are described. In one embodiment, a target prescription drug discount guarantee associated with a pharmacy benefit manager client is accessed. A prescription drug discount associated with a plurality of prescription drug claims associated with the pharmacy benefit manager client is calculated to obtain a calculated prescription drug discount. A difference between the target prescription drug discount guarantee and the calculated prescription drug discount is determined. A prescription drug pricing schedule associated with the pharmacy benefit manager client is modified based on the difference between the target discount guarantee and the prescription drug discount to create a modified prescription drug pricing schedule. Other methods and systems are described.

Abstract: Method starts with processing, by a processor, audio signal to generate audio caller utterance and transcribed caller utterance. Processor generates identified tasks based on transcribed caller utterances. Processor obtains member context associated with member identification and obtains available tasks associated with member identification. Processor determines lengths of time associated with available tasks, respectively. Lengths of time associated with available tasks are lengths of time that the available tasks have been available. Processor determines messaging data associated with available tasks, respectively, that is based on dates of receipt of messages pertaining to available tasks. Processor, using a predictive analysis neural network, generates a predictive analysis result that is based on the available tasks, the lengths of time associated with the available tasks, or messaging data associated with the available tasks.

Abstract: A prescription handling system that takes filled prescription containers in an automated pharmacy and places them into a package for shipment is described. The handling system includes an inflow to feed containers to a turntable and a robot moves containers from the turntable to a container placement section, which places the containers in a pocket of a package for shipping. Each container for a prescription order is tracked to ensure that only associated containers are packaged together.

Abstract: Methods and systems for claim adjudication are described. In one embodiment, a status of a drug benefit plan associated with a member is determined. Claims data associated with the member is accessed. A current-filled prescription is identified based on the claims data. At least one adjudication operation for the current-filled prescription is performed prior to receiving a new request for the current-filled prescription. The new request is determined as fillable based on the performance of the at least one adjudication operation. A notification is generated to the member based on the determination. Additional methods and systems are disclosed.

Abstract: 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.

Abstract: A method includes defining model attributes of an organizational machine model that organizes feedback data from one or more sources of the feedback data into plural different topic groups based on similarities in concepts expressed in the feedback data. The model attributes represent criteria for establishment of the organizational machine model and include a topic model number that defines how many of the different topic groups are to be created by the organizational machine model and used to organize the feedback data into, a hyperparameter optimization alpha value that defines how likely a feedback datum in the feedback data is to be included in a single topic group of the different topic groupings or multiple topic groups of the different topic groupings, and a hyperparameter optimization beta value that defines how broadly each of the different topic groups are defined relative to the feedback data.

Abstract: Methods and systems for predicting estimation of project factors in software development environment are described. In one embodiment, a project analyst device receives first input data including at least one type of first software development model and associated one or more first project development data from a user. A feedback device loaded in a project estimation device identifies one or more first software project risk factors based on the at least one type of the first software development model. The project estimation device processes the one or more first project development data using the identified one or more first software project risk factors to identify one or more first intermediate data required for project factors estimation, and predicts estimations of the project factors using the identified one or more first intermediate data. Additional methods and systems are disclosed.

Abstract: A mainframe deployment device for deploying code to a mainframe device in a stable, self-correcting manner is described. The mainframe deployment device is configured to receive a code section from the software management device, identify a set of valid sub-components from the code section using a dispatcher service associated with the dispatcher device, identify a set of elements in the code section identified for deployment, request the at least one testing service to perform at least one set of code diagnostics to determine whether the code section satisfies build requirements, attempt to create a deployment package from the code section, identify a production program running on the mainframe device, compare the production program to the deployment package to identify a set of synchronization errors, resolve the synchronization errors, and deploy the deployment package to the mainframe device upon resolving the set of synchronization errors.

Abstract: A web-based display system includes instructions for execution by a processor. The instructions include, in response to receiving a page load request from a user device associated with a user, obtaining a set of frames associated with the user and, for each of the first and second frames: (i) loading the frame and (ii) assigning a corresponding unique identifier to the frame. The instructions include accessing the plurality of authenticated identifiers and, for each of the first and second frames, in response to the assigned unique identifier of the frame matching an authenticated identifier of the plurality of authenticated identifiers, adding the frame to a set of authenticated frames. The instructions include generating a page including the set of authenticated frames and, in response to receiving a first message, selectively broadcasting a second message based on the first message to the set of authenticated frames.

Abstract: A machine learning system for training a data model to predict data states in medical orders is described. The machine learning system is configured to train a data model to predict whether a medical order requires prior authorization (“PA”) for medical orders within a medical order data set so that related systems may process incoming medical orders with PA determinations predicted by the data model. The machine learning system includes a first data warehouse system. The first prescription processing system generates a data model of historical orders and payer responses, apply a predictive machine learning model to the data model to generate a trained predictor of whether a medical order requires PA, associated with order data, apply the trained predictor to a plurality of production orders to determine PA for each of the plurality of production orders, and process the plurality of production orders with each associated PA determination.

Abstract: A computer-readable medium stores instructions including executing a first application. In response to a first configuration specification, the instructions configure a first choreographer, which requires at least one collector and at least one emitter and defines a sequence of processing stages. The first configuration specification specifies which available collectors, which available emitters will be used. The first configuration specification specifies, for each stage, which available processors will be invoked. The instructions include, in response to a reconfiguration request for the first application, pausing each of the at least one collector; subsequent to pausing the at least one collector, pausing each stage of the sequence of processing stages; subsequent to pausing the processors, pausing each of the at least one emitter; and subsequent to pausing the at least one emitter, configuring the first choreographer according to a second configuration specification.

Abstract: A method starts with processor retrieving member's initial context data. Processor receives a string that is a transcribed utterance or an electronic message from the communication session established between member client device and agent client device. Processor determines potential relationships between the member and a patient that is the subject of the string by processing the string using Long Short-Term Memory (LSTM) neural networks to generate a plurality of relationship values. Relationship values are associated with relationship types. Processor generates weight values based on member's initial context data for each of the plurality of relationship types, and generates probability values for the relationship types based on the relationship values and the weight values. Processor narrows the potential relationships, generates relationship data that includes the narrowed potential relationships, and causes the relationship data to be displayed by the agent client device.

Abstract: Method starts with processing, by a processor, audio signal to generate audio caller utterance and transcribed caller utterance. Processor generates identified task based on transcribed caller utterance. Processor samples audio caller utterance to generate samples of audio caller utterance. Processor generates loudness result based on loudness values of samples using loudness neural network associated with identified task. Processor generates pitch result based on pitch values of samples using pitch neural network associated with identified task. Processor generates tone result for each word in transcribed caller utterance using tone neural network associated with identified task. Using task completion probability neural network associated with identified task, processor generates task completion probability result that is based on at least one of: loudness result, pitch result, or tone result. Other embodiments are disclosed herein.