Abstract: A method and system for assessing the risk of a cardiac event in a patient which utilizes real-time and historical data from Electronic Medical Record (EMR) systems is described. A risk of a cardiac event is estimated, in real-time or near-real-time, for a patient who is currently in a hospital emergency department. Batch data for one or more past patients is extracted from EMRs into a machine learning model. Using the machine learning model, a risk level for one or more past patients is calculated. A real-time database is constructed from streams of real-time Health Level 7 (HL7) clinical data, wherein at least one stream of real-time HL7 data is associated with the current patient, and a risk prediction is estimated by joining the calculated risk level for the patient in the machine learning model with the real-time HL7 clinical data from the patient.

Abstract: A client device presents a user interface including a macro entry field for defining a macro indicator from a plurality of macro indicators and transmits the macro indicator. A server stores a database of macro-based diagnoses, each macro-based diagnosis associated with one or more elements of an accession, and one or more specimens associated with the accession. The server also receives the macro indicator from the client device, retrieves an initial diagnosis from the database of macro-based diagnoses responsive to the macro indicator, and transmits the initial diagnosis. The client device, receives the initial diagnosis, pre-populates one or more text boxes on the user interface with information from the initial diagnosis, and enables the user to edit the pre-populated one or more text boxes.

Abstract: Determining cohesion of healthcare groups and clinics based on billed claims. A method includes determining a target office billing identifier associated with one or more of a healthcare group or a healthcare clinic and determining a practitioner billing a carrier claim comprising the target office billing identifier. The method includes identifying a plurality of carrier claims billed by the practitioner over a time period. The method includes calculating a proportion of the plurality of carrier claims that comprise the target office billing identifier.

Abstract: A diagnosis supporting system according to embodiments includes a memory that stores medical information including patient information relating to a condition of a patient, and intervention information relating to an intervention for the patient; and processing circuitry that extracts a change point in the medical information, that calculates a first change amount indicating a change in the patient information between before and after the change point, and a second change amount indicating a change in the intervention information between before and after the change point, and that performs display based on the first change amount and the second change amount in a display mode set according to at least one of the first change amount and the second change amount.

Abstract: Certain embodiments are directed to systems and methods for automatically providing data indicative of one or more characteristics of services that may be recommended to a particular patient, wherein the services are executable at least in part electronically based on data generated and provided by a system for facilitating access to the services. The generated data may be utilized for generating one or more user interfaces providing data regarding derived standard pricing data that is automatically assigned to the referred services and which may be attributable to a patient based at least in part on the patient's usage of the services.

Abstract: A computer implemented method for cross asset correlation includes receiving, by a processor, portfolio data for a plurality of portfolios, determining, by the processor, a single portfolio performance vector for each of the plurality of portfolios based on a portfolio specific model, determining, by the processor, a joint portfolio performance vector for the plurality of portfolios based on portfolio specific models, determining, by the processor, for each portfolio, a portfolio specific scalar based on the single portfolio performance vector and the joint portfolio performance vector; and modifying, by the processor, a portfolio risk based on the portfolio specific model and the portfolio specific scalar.

Abstract: Methods, apparatuses, and computer program products are disclosed for effectuating payment for consumable content. An example method includes receiving a request for payment associated with a content source device and identifying a first user device associated with a first user accessing consumable content of the content source device. The method further includes transmitting an actionable payment notification to the first user device. In an instance in which the computing device receives responsive authorization from the first user device, the method includes transmitting a first real-time payment to the content source device. In an instance in which the computing device fails to receive responsive authorization from the first user device, the method includes causing access of the consumable content to the first user device to halt.

Abstract: Embodiments of the present disclosure provide a cloud-based integrated charting system that utilizes a universal mapping service across services and clients to provide insights for the provider into customizations made by clients. Additionally, the system provides content building tools that enable clients to customize content to update models provided by the provider. A mapping service maps model codes corresponding to model concepts to a plurality of standard based concept codes corresponding to client domain specific customized concepts for an ontology of the one or more ontologies. A workflow recommendation is provided that enables a user to chart data and includes the model concepts comprising charting elements. Accordingly, the data is stored in a client database in accordance with the client domain specific customized concepts. Since the model concepts are mapped to the client domain specific customized concepts, the workflow recommendation can be prepopulated with data from the client database.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating a clinical recommendation for medical treatment of a patient.

Abstract: Computer program products, methods, systems, apparatus, and computing entities are described for identifying significant incidental findings from medical records. In one example embodiment, an example computing device receives a medical report and derives a textual component from the medical report. The computing device then identifies one or more medical findings from the textual component and determines a clinical context for each of the one or more medical findings. The computing device then identifies one or more clinical cues from the one or more medical findings and generates one or more condition signals from the one or more clinical cues. The computing device then generates a condition alert from the one or more condition signals. The condition alert is indicative of a significant incidental finding. Using various embodiments contemplated herein, significant incidental findings can be identified for follow-up by a user.

Abstract: Provided are systems, methods, and devices for sleep intervention quality assessment. Methods include receiving measurement data from a plurality of data sources, the measurement data comprising a plurality of measurements of biological parameters of a user before and after a sleep intervention, and receiving treatment data comprising one or more treatment parameters associated with the sleep intervention. Methods further include generating, using one or more processors, a plurality of quality assessment metrics based on the received measurement data, the plurality of quality assessment metrics being generated based, at least in part, on a comparison of the plurality of measurements of biological parameters before and after the sleep intervention, and generating a report based, at least in part, on the plurality of quality assessment metrics.

Abstract: A system and method for obtaining prior authorization and fulfilling a prescription is described. The method includes receiving, by a computing device, prescription information for a patient from a prescriber; identifying, by the computing device, an electronic health record associated with the patient; collecting, by the computing device, medical information for the patient related to the prescription from the electronic health record; submitting, by the computing device, a claim for the prescription with a payor associated with the patient; and completing, by the computing device, a prior authorization request for the prescription.

Abstract: A clinical event outcome scoring system and method are used to determine a Severity of Illness Clinical Key (SICK) score, which is a probable degree of successful outcome for a patient about to undergo a specific clinical event, such as for example, coronary bypass surgery, hip replacement, bariatric surgery, discharge from a hospital for home recovery, a course of chemotherapy, radiation, or other treatment protocol. The system and method analyzes historical patient data to generate a statistical model for each specific clinical event of interest, which can then be used to determine a SICK score for a patient about to undergo the same clinical event. In some embodiments, the statistical model can be “fine-tuned” to render subcategories of statistical models tailored for certain patient populations about to undergo the same clinical event.

Abstract: A computer-implemented method includes selecting a group of sets. Each set has values for immutable attributes that match values for at least one mutable attribute in a prediction request. The method includes determining a conditional covariance matrix for the group of sets. The method includes generating a deviation model based on the conditional covariance matrix. The method includes sampling the deviation model to generate multiple sets of likely mutable attribute values. The method includes automatically selecting a neural network from a set of outcome models based on the likely mutable attribute values. Each neural network includes a set of layers. Each layer includes a set of nodes. A first layer receives inputs at the set of nodes of the input layer. Each layer other than the first layer receives outputs from a preceding layer and creates modified outputs. A last layer outputs the modified outputs from the neural network.

Abstract: Embodiments herein include a method for detecting a health condition of a subject. The method can include obtaining a biological sample from the subject and placing it into a container having a headspace surrounding the biological sample. The method can include contacting a gas from the headspace with a chemical sensor element, the chemical sensor element including one or more discrete graphene varactors. The method can include sensing and storing capacitance of the discrete graphene varactors to obtain a sample data set. Other embodiments are also included herein.

Abstract: An automatic patient recruitment system is operable generate abnormality data for medical scans by performing at least one inference function on image data of each medical scans by utilizing a computer vision model trained on a training set of medical scans. A subset of a plurality of patients is identified to be eligible for a pharmaceutical study by identifying medical scans having abnormality data that compares favorably to abnormality criteria of the pharmaceutical study. A size of the subset is compared to a minimum participant count requirement. A notification indicating the subset of the plurality of patients is transmitted based on the size of the subset comparing favorably to the minimum participant count requirement.

Abstract: A respiratory disease analytics system provides respiratory disease risk reports to a patient, provider, or third-party entity describing a patient's risk of experiencing a medication usage event given data in a geographic region. Regional data, including air pollutant conditions, weather conditions, demographic information, built environment factors, and regional health conditions for a geographic region are accessed from other sources and assigned based on event data recorded during a medicament usage event, as collected by sensors associated with the patient's medicament device/s. The regional data is assigned to medicament usage events occurring within a period of time. The assigned regional data is analyzed to determine an expected number of medication usage events for the geographic region occurring over the period of time.

Abstract: Systems and methods assist in gathering relevant data in a doctor-patient encounter for obtaining a properly specified diagnosis code. In one embodiment, selectable data items which are provided as part of a medical charting program may be correlated with one or more standardized diagnosis codes (e.g. ICD-10 codes). Upon selection of the appropriate data items when charting a patient encounter, one or more diagnosis codes which are correlated with the selected data items may be flagged and/or generated for later use, such as for filing a claim submission as part of a billing process or to further enhance the clinical workflow of patient encounter documentation.

Abstract: The present invention provides systems and methods for exchanging health data. A health data exchange platform includes health data from a plurality of data sources. The health data exchange platform preferably utilizes blockchain technology. The health data exchange platform includes both buyers of health data and suppliers of health data. The health data exchange platform includes a phenotype network system including at least one remote server, a user profile database, a report database, a permissions database, a geographic incident database, and a medical community database.

Abstract: A method and apparatus include receiving, by a device, medical information associated with a user. Inquiry information is determined based on the medical information associated with the user and a reinforcement learning model. The inquiry information is provided to permit response information to be received. The response information is received based on providing the inquiry information. Diagnosis information is determined based on the medical information and the response information using a machine learning model. The diagnosis information is provided to a set of devices via a network.