Abstract: Techniques are disclosed for preparing data for use in artificial intelligence (AI)-based cardiac arrhythmia detection. In accordance with the techniques of this disclosure, a computing system may obtain a cardiac electrogram (EGM) strip that represents a waveform of a cardiac rhythm of a same patient. Additionally, the computing system may preprocess the cardiac EGM strip. The computing system may then apply a deep learning model to the preprocessed cardiac EGM strip to generate arrhythmia data indicating whether the cardiac EGM strip represents one or more occurrences of one or more cardiac arrhythmias.

Abstract: Methods, computer systems, and computer storage media are provided for sorting and presenting a patient's medical information by body system. A selection of a body system filter directed to a body system is received, and the patient's medical information is accessed. The selected body system filter is applied to the patient's medical information to generate a set of body-system specific patient information. The body-system specific patient information is presented on a body system view user interface.

Abstract: This description provides trigger identification notifications to patients suffering from respiratory diseases based on large amounts of patient data in order to help effect behavior changes in a patient to prevent inhaler rescue usage events from occurring. Rescue medication events, environmental conditions, and other contextually relevant patient information are detected by sensors associated with the patient's medicament devices and are collected from other sources, respectively to provide a basis to determine identify various triggers of rescue inhaler usage events for a patient. Each trigger is analyzed to determine the severity of the patient's reaction to the trigger and is used to send notifications accordingly.

Abstract: A method and system for detecting spinal stenosis is provided. The method may receive image data corresponding to a spine region of a patient. The method may also identify a spinal cord in the image data. The method may determine at least one compression of the spinal cord and may mark an anatomical element proximate to a location of the determined at least one compression to yield at least one marking. The method may generate a decompression plan based on the at least one marking.

Abstract: A process registers, at the user mobile computing device, one or more health-related documents for inclusion in a cloud-based digital health wallet. Furthermore, the process receives, at a user mobile computing device, a biometric identification input from the user for the registration of the one or more health-related documents. The process sends, from the user mobile computing device to a server computing device that stores the cloud-based digital health wallet, a first coded version of the biometric identification input for storage in a biometric validation data structure. Additionally, the process determines, at the user mobile computing device, a location of the user. Moreover, the process sends, from the user mobile computing device to the server computing device, a validation request at the location. The validation request includes a second coded version of a subsequently inputted biometric input from the user at the location.

Abstract: Healthcare is administered to members/enrollees of a healthcare plan according to objective quality standards. A patient population of eligible members/enrollees is identified and for each member/enrollee, medical information is aggregated via a web-based compilation of medical data from multiple sources that is continuously updated so as to provide an accurate, up-to-date and readily accessible compilation of a member/enrollee past diagnoses, healthcare history, medical procedures, medications and the like. Such member/enrollees are continuously tracked, on an individual basis, and monitored to ensure healthcare is delivered for a variety of specific medical conditions pursuant to objective health program quality criteria.

Abstract: One variation of a method for tracking and responding to mental health changes in a user, the method includes: rendering a graphical object within a graphical user interface; indexing an emotion value assigned to the graphical object through a spectrum of emotion values according to a direction of an input into the graphical user interface; within the graphical user interface, updating the graphical object to visually correspond to the emotion value assigned to the graphical object; recording submission of a final emotion value through the graphical user interface; and in response to the final emotion value equaling a trigger value, distributing a prompt to monitor the user to an external entity.

Abstract: A system for electronic patient care includes a gateway and a medical device. The gateway is configured to provide at least one of a routing functionality, a medical device software update, and a web service. The medical device is configured to operatively communicate with the gateway using the web service.

Abstract: Methods for associating medical images to a patient using a mobile image-capturing device and transmitting the medical images to a storage location are disclosed. One example method includes accessing by a user identifying information associated with a patient through an electronic health record (EHR) application installed in the mobile device, launching a second application on the mobile device from the EHR application, and upon the launching of the application from the EHR application, transmitting the patient identifying information accessed by the user from the EHR application to the second application. The second application may then retrieve one or more medical images stored in the mobile device, associate the one or more retrieved medical images with the patient using the identifying information, and transmit the one or more retrieved medical images with the associated patient identifying information from the mobile device to a storage location.

Abstract: A device may communicate with a first device to receive first data. The device may communicate with a second device to receive second data. The device may combine the first data and the second data into a user interface. The user interface may provide a single location for displaying communications with the set of entities and with a system associated with the set of entities. The user interface may include a first section that provides information that is persistently presented in the user interface. The user interface may include a second section that provides information that is selectively presented in the user interface. The device may provide the user interface for display.

Abstract: Methods are provided for validating theoretical improvements in the decision-support processes facilitating surveillance and monitoring of a patient's risk for developing a particular disease or condition and detecting the disease or condition. Patient information is received from a source and populated into an active risk assessment that monitors the patient's risk for developing Sepsis. At least a first and second set of actionable criteria for determining a patient's risk for developing sepsis are received. For each set of actionable criteria, it is determined that actionable criteria have been met. In some embodiments, software agents, operating in a multi-agent computing platform, perform each determination of whether actionable criteria are met.

Abstract: Data threat evaluation systems and methods are described. A data model structure includes a data subset from the plurality of data types that predate a known threat; this third data subset includes data types from both a first data subset and a second data subset. A model schema extracts, from the data subset, data types of the first subset that predicate and indicate the threat, the model schema to produce at least an individualized data threat regression model, a script originator regression model, and a script filler data threat regression model using the extracted data types. The system may use the models back on the data set to identify potential threats. The system can operate to integrate data to predict fraud, waste or abuse.

Abstract: Technologies for providing assistance to a surgeon during a surgical procedure are disclosed. An example method includes identifying a medical condition of a patient and recommending surgical procedures for treatment. An optimal surgical procedure is then determined based on correlations between the medical condition of the patient and outcomes of previous surgical procedures for other patients previously suffering from the medical condition. A 3D model of the patient may be created using current images of an affected area of the patient. Successively, a surgeon is trained using a Virtual Reality simulation. During the training, the surgeon may be allowed to provide annotations. Further, the recommended surgical procedures are based on medical data of the patient, including medical images. Surgical paths are retrieved for addressing the surgical need of the patient, and the surgical paths may be overlaid on image segments, for display for the surgeon.

Abstract: Disclosed herein are various embodiments of computer-implemented methods and systems for parsing information from messages containing a standardized electronic document format, such as a continuity of care document (“CCD”), and for generating referrals and other documents using data parsed from the messages and/or standardized electronic document format. In some embodiments, a message containing a CCD may be received, the CCD and the message may be parsed to extract information (e.g., patient information), the patient information may be mapped into a document template, and an electronic document containing mapped referral parameters may be generated.

Abstract: Techniques for identifying representative patients from a patient group are provided. Based on an outcome of interest, one or more patients can be grouped according to phenotyping features associated with the outcome of interest. Additionally, in response to grouping the one or more patients, a representative patient of the one or more patients can be determined based on values associated with the phenotyping features.

Abstract: A method, computer program product, and computing system for obtaining encounter information of a patient encounter, wherein the encounter information includes machine vision encounter information; and processing the encounter information to generate an encounter transcript.

Abstract: Computer program products are configured to perform methods for determining likely health conditions based on demographic information and/or determining appropriate wearable technology and services to monitor a patient's health. In one embodiment, a computer program product is configured to perform a method including receiving historical demographic data comprising a plurality of attributes; associating the historical demographic data with labels corresponding to known causes of particular health conditions; building a decision tree model using the historical demographic data and the associated label(s); generating a vector Yk using the model, Yk representing probable causes of a plurality of health conditions; and determining likely health conditions for a patient based on comparing the vector Yk to a second vector Zk, Zk representing probable causes of health conditions determined based on a health care record for the patient.

Abstract: Systems and methods for automated generation of medical device communication software, cloud-based storage of medical device data including an electronic medical device (EMD) application communication interface and a central communication interface, and user interface software to allow a user device to receive EMD data transmitted from a data storage medium (DSM) and transmit data to the DSM for transmission to the EMD, that meets one or more medical device standards set by government or industry regulatory bodies.

Abstract: Example embodiments are described that relate to the analysis of tissue damage in an injured patient. Example embodiments are methods and systems for collecting medical imaging data, identifying tissue damage in the medical imaging data, analyzing the tissue damage shown in the medical imaging data, and/or quantifying the tissue damage shown in the medical imaging data. The disclosed methods allow for determining a risk for multiple organ failure and systemic inflammation in a multiply injured patient.

Abstract: Methods and a system are provided for assessing postpartum hemorrhage risk and postpartum hemorrhage stages in a clinical setting. Generally, a clinician may indicate that the mass of several bloody items, indicated in type and quantity, is to be measured using a scale. The mass of bloody items is compared to the known unused dry mass of such items in order to accurately determine the quantitative blood loss (QBL) of a patient at the bedside. The cumulative QBL can be updated by weighing additional items. Based on the cumulative QBL, the patient's vital signs, and other factors, a corresponding hemorrhage stage is identified and communicated to the clinician. Recommendations specific to the hemorrhage stage are provided to a clinician. Some recommendations are selectable actions that trigger automatic placement of medical orders and notifications to relevant medical services, such as a blood bank or anesthesia.