Abstract: Machine learning models can assess historical insurance claims data and prescription fulfillment records to reduce paybacks to prescription payers in the form of direct and indirect remuneration fees. A pharmacy computer receives prescription data and communicates at least a portion of the prescription data to a pharmacy benefit manager. The pharmacy computer receives a prescription benefit response back at the computerized application from the prescription payer software application. The pharmacy computer is configured to develop machine learning request data, selected from the prescription data and prescription benefit response data, and send the machine learning request data to machine learning software. The machine learning software calculates payback forecast data for the prescription data.

Abstract: A method includes identifying records in a database for labeling; presenting one of the records in the database to a first labeling entity; and receiving a first observation on an information source in the one of the records from the first labeling entity. The first observation has one of a plurality of observation types associated therewith. The plurality of observation types including a validation observation type in which the first observation comprises a confirmation of whether a second observation on the information source in the one of the records from another labeling entity is accurate and an edit for the second observation when the second observation is confirmed as inaccurate. The one of the records is updated in the database with the first observation on the information source in the one of the records from the first labeling entity.

Abstract: An apparatus, method and computer program product facilitate selective searching of at least a portion of a database. With respect to a method, a query is received that has a query context. In response to the query, the method reviews one or more data source tables including a first data source table that defines each of a plurality of data sources of data stored by the database. In reviewing the one or more data source tables, the method identifies one or more data sources that are accessible in response to the query. The method also searches the database for responsive data that: (i) was provided by the one or more data sources that were identified to be accessible in response to the query and (ii) is responsive to the query. Further, the method responds to the query with a representation of the responsive data.

Abstract: A method includes defining a plurality of data storage policies, each of the plurality of data storage policies providing rules for storing data among a plurality of data storage locations, each of the plurality of data storage locations having a data storage cost and a data retrieval cost associated therewith; determining a baseline policy distribution among the plurality of data storage policies for an entity; receiving new data items corresponding to the entity; storing the new data items in the plurality of data storage locations using the plurality of data storage policies based on the baseline policy distribution; and determining, using the artificial intelligence engine, a selected one of the plurality of data storage policies to use in storing the new data items corresponding to the entity based on the data storage cost for each of the plurality of data storage locations, and the data retrieval cost for each of the plurality of storage locations.

Abstract: In order to automate some aspects of software development, an application catalogue is provided. The application catalog is associated with an application (e.g., a medical device) and includes a plurality of parameters that each define a desired state of the software application when the software application is deployed). These parameters may include service parameters, application parameters, environmental parameters, feature parameters, API parameters, and infrastructure parameters. Before a software application is deployed to an environment, the states of the parameters with respect to the environment are determined and compared to the states of the parameters of the application catalog. The system then automatically takes the necessary steps to correct the states of any parameters of the environment to match those of application catalog.

Abstract: In order to improve the integrating of datasets, improved systems and methods for matching records from a first dataset and a second dataset are provided. Records from the first dataset and the second dataset that are associated with the same individuals are identified. The records are identified using a combination of Euclidean distance, Leviathan distance, and the application of one or more rules. Once the records that are associated with the same individuals are identified, the records can be combined in an integrated dataset.

Abstract: Embodiments are disclosed for automatically evaluating records. In the context of a method, an example embodiment includes receiving a set of text produced from a record, identifying, by block manipulation circuitry and from the set of text, one or more blocks of text that are related to a potential conclusion regarding the set of text, and extracting, by the block manipulation circuitry, the one or more blocks of text. The example method further includes concatenating, by the block manipulation circuitry, the extracted one or more blocks into a sequence of words, inputting the sequence of words into a machine learning model, and, in response to inputting the sequence of words into the machine learning model, producing, using the machine learning model, an indication of whether the potential conclusion regarding the record is supported by the sequence of words. Corresponding apparatuses and computer program products are also provided.

Abstract: A method includes receiving information associated with a stimulus, the information associated with the stimulus comprising first information associated with a medical claim for services provided to a patient and second information associated with a provider that provided the services to the patient; and predicting, using an artificial intelligence engine, when an event will occur in response to the stimulus.

Abstract: A method, apparatus and computer program product group records based upon a prediction of the content of the records. In the context of a method, data associated with respective subjects of the records is received and a threshold of a machine learning model is adjusted to satisfy an accuracy requirement for record categorization. In response to analyzing the data, but not the records, by the machine learning model, the method separates, using the machine learning model, the records into the first and second groups with the first group including records that the associated data indicates are more likely to support the addition of a code and the second group including records that the associated data indicates are less likely to support the addition of a code. The method also includes subsequently processing the records in different manners depending upon whether the records are included in the first or second group.

Abstract: A wearable audio device includes a speaker, a wireless communications interface, an audio sensor configured to capture ambient noise in an environment occupied by a user wearing the wearable audio device, and memory having instructions stored thereon that, when executed by one or more processors, cause the one or more processors to perform operations including receiving, via the wireless communications interface, a first user input identifying a frequency range to be attenuated, generating an audio signal from the captured ambient noise, attenuating the audio signal to reduce an amplitude of one or more frequency components based on the frequency range, and causing the speaker to produce sound based on the attenuated audio signal.

Abstract: Disclosed and described herein are systems and methods of performing computer-aided analysis of health claims to determine if a current claim is consistent with past claims for a member. Consistent claims are directed to a healthcare payor while non-consistent claims are returned for review and/or revision.

Abstract: A method, apparatus and computer program product refine an automated coding model, such as for a medical chart. For each respective candidate code from a set of candidate codes, the method predicts a probability of the respective code being contained in a medical chart. The method also selects one of the candidate codes as being contained in the medical chart based upon the probability and removes the selected candidate code from the set of candidate codes. The method then repeatedly predicts the probability of a respective code being contained in the medical chart, selects one of the candidate codes based upon the predicted probability and removes the selected candidate code from the set of candidate codes. The method further determines a categorical crossentropy loss as to permit adjustment of one or more parameters of the automated coding model.

Abstract: A method, apparatus and computer program product are provided for implementing an actor-critic model for processing a large document. The document is processed in smaller portions, and the information is accumulated or aggregated in a vector representation of the document. The vector representation may be reconfigured with each time step so that the vector representation includes an estimate of the most relevant information from the document processed thus far. The vector representation may be used to classify the document, such as by determining a primary and/or secondary diagnosis in a medical record. Feedback from the critic is provided in the form of a reward signal to the actor, which fine tunes its parameters and processes the different portions of the document. The actor-critic model may be trained with training data including documents and their known associated classifications.

Abstract: A method, apparatus and computer program product are provided for generating a predefined sized vector representative of a healthcare claim including a variable number of service lines. A neural network is trained to identify hierarchical relationships between claim lines and services lines and to represent the relationships in the predefined sized vector. The predefined sized vector may be used to make predictions regarding adjudication, such as probability of denial (claim-level or service-level), days to pay, probability of being paid as a diagnosis related group (DRG), allowed amount, and/or denial reason. Predictions may also be made from the predefined sized vector relating to the likelihood and/or identification of missing procedure codes.

Abstract: Disclosed and described herein are systems, methods and computer program products providing elastic data privacy-compliant healthcare analytics that enables privacy certification on a case-by-case basis.

Abstract: An augmented reality pharmacy system and method for assisting pharmacy personnel with health care-related tasks is presented. The augmented reality pharmacy system can reduce or eliminate common pharmacy fulfillment errors attributable to human error. The present disclosure improves pharmacy fulfilment error rates by providing image processing systems adapted to characterize prescription and drug related information to verify prescription fulfillment; incorporates augmented reality systems with pharmacy systems to provide enhanced fulfillment systems where real-world objects can be over-laid with virtual reality elements to provide additional pharmaceutical information to a user; and shortens the time spent by a user looking for a specific drug bottle in a maze of similar-looking drug bottles by incorporating wayfinding technology coupled with location based components.

Abstract: A healthcare information system, method and computer program product are provided to receive, process and output healthcare data in compliance with data use restrictions associated with the healthcare data, even in instances in which data projections are assembled from the data elements. In regards to a healthcare information system, processing circuitry is configured to assemble the data projection from a plurality of data elements. At least some data elements have different data use restrictions associated therewith. The processing circuitry is also configured to determine a combined data use restriction for the data projection based upon the data use restrictions of the data elements from which the data projection is assembled. The processing circuitry is further configured to associate metadata with the data projection including the combined data use restriction. Further, the processing circuitry is configured to control access to the data projection in accordance with the combined data use restriction.

Abstract: A method, apparatus, and computer program product are provided herein to facilitate clinical diagram generation and interaction. Methods may include: providing for display of a clinical diagram, where the clinical diagram includes a depiction of the vascular system, where vessels of the vascular system include a plurality of vessel segments, where each segment is formed from a pair of cardinal splines and end lines between adjacent ends of the cardinal splines; providing for generation of a clinical report associated with the clinical diagram; and populating the clinical report in response to user input received in the clinical diagram, where the user input is indicative of at least one clinical finding and a location corresponding to the user input based on a segment selected by the user input.

Abstract: A system and method for providing secure cryptoassets in a blockchain platform.

Abstract: A method, computing device and computer program product are provided to obtain information from a plurality of dissimilar records by estimating the most accurate value for each field of the plurality of records. A computing device may include processing circuitry configured to: receive a first record including two or more elements, where a first element of the first record has a first value; receive a second record comprising two or more elements, where a first element of the second record has a second value; receive a third record having two or more elements, where a first element of the third record has a third value; and determine a resultant value for the first element, where the resultant value for the first element is determined based on a frequency of occurrence of a value for the first element among the first value, the second value, and the third value.