Abstract: In an embodiment, an electronic device includes a display screen, a memory circuit, and computing circuitry, which is coupled to the display screen and to the memory circuit, and which is configured to cause the display screen to display icons that are each related to respective data regarding a patient at a medical facility, to retrieve, from the memory, the respective data in response to a user of the electronic device selecting, via the display screen, a corresponding one of the displayed icons, and to cause the display screen to display the retrieved respective data.

Abstract: An alarm notification system can enable a clinician to respond to an alarm notification received via a computing device, which may have more advanced functionality than a pager. The clinician's device can include a notification client which can respond to alarm notifications. The notification client can also provide one or more user interfaces that enable the clinician to view information about an alarm, such as information about a patient's status, physiological parameter values, trend data, audio/video of the patient, combinations of the same, or the like. Further, the notification client can provide functionality for a clinician to respond to an alarm, annotate an alarm, and/or indicate that the clinician can or cannot respond to the alarm, among other features. In addition, the clinician device can also (or instead) include an admit module that provides for automatic association of a patient to a device or location.

Abstract: A system includes a processor and memory providing instructions for execution by the processor. The instructions include, responsive to a request from a user device indicating a group type and a time frame, selecting a set of users based on the group type. The instructions include retrieving the user data and historical data from a database and identifying a set of new users during the time frame. The instructions include adding the set of new users to the set of users and generating synthetic historical data for the set of users. The instructions include, based on the synthetic historical data for each user, computing a likelihood of discontinuation of a drugs and computing a likelihood of initiation of a drug. The instructions include estimating, for the group type, an aggregated output based on the likelihoods of initiation and discontinuation. The instructions include displaying the aggregated output on the user device.

Abstract: Provided herein is an engagement and care support platform (“ECSP”) computer system including at least one processor in communication with at least one memory device for facilitating senior user engagement. The processor is programmed to: (i) register a user through an application, (ii) register a caregiver associated with the user through the application, (iii) generate a senior profile based upon user personal and scheduling data, (iv) build a daily interactive user interface that reflects the senior profile, (v) display the daily interactive user interface at a first client device associated with the user, (vi) cause the first client device to initiate a daily interaction prompt to the user, (vii) determine whether any user interaction was received in response to the daily interaction prompt, and (viii) transmit a daily update message to a second client device associated with the caregiver, including an indication of whether any user interaction was received.

Abstract: A system and method for automatically calculating an accurate recommended dosage for hormone replacement therapy and automating the life cycle of a patient's treatment over time. The system and method can automatically acquire relevant patient parameters and apply a consistent formulaic approach to help reduce incorrect dosage determinations. A pellet insertion size may be determined and documented based on a calculated dosage, and an insertion side and lot numbers may be tracked and managed. In addition, corresponding revenues may be tracked and profitability may be reported for hormone replacement therapy practices.

Abstract: A method, apparatus and computer program product are provided for providing rebate claim validation. A drug manufacturer or associated computer may receive rebate claims from pharmacy benefit managers (PBMs). The manufacturer should not be obligated to pay the rebate if the associated prescription drug was initially sold by the manufacturer under a discount program such as 340B. However, manufacturers may not be able to discern which rebate claims are associated with a discount program. A service provider utilizes adjudicated prescription claims from a contract pharmacy, and encounter data from a covered entity to validate the rebate claims and indicate to the manufacturer whether a rebate claim is associated with a discount program such as 340B.

Abstract: Computer implemented methods are disclosed. The methods may include receiving historical data comprising at least one of provider data and patient data, and processing, using a processor, the historical data to identify one or more patterns. The method also may include generating one or more decision models from the historical data and the decision patterns, and providing one or more recommendations based on the one or more decision models.

Abstract: A system, method, and mobile device application are configured to capture, with a mobile device, a document such as a next generation sequencing (NGS) report that includes NGS medical information about a genetically sequenced patient. The method includes receiving, from a mobile device, an image of a medical document comprising NGS medical information of the patient, extracting a first region from the image, extracting NGS medical information of the patient from the first region into a structured dataset, the extracted NGS medical information including at least one RNA expression, correlating a portion of the extracted NGS medical information that includes the at least one RNA expression with summarized medical information from a cohort of patients similar to the patient, and generating, for display on the mobile device, a clinical decision support report comprising the summarized medical information.

Abstract: Predictions can be provided for admission, discharge, pathway, and units for a patient during a stay at a healthcare facility. In some aspects, a computing device receives initial data regarding the patient and generates an admission or discharge prediction indicating a probability that the patient will be admitted to or discharged from the healthcare facility. The computing device segments portions of the initial data into segmented data and stores the segmented data in one or more of a plurality of segmentation categories. The computing device compares the segmented data to one or more patterns of a predictive model and, based on the comparing, generates a total length-of-stay (LOS) prediction indicating a duration of time for which the patient will stay at the healthcare facility.

Abstract: A system and method of confirming administration of medication is provided. The method comprises the steps of receiving information identifying a particular medication prescription regimen, determining one or more procedures for administering such prescription regimen and identifying one or more activity sequences associated with such procedures. Activity sequences of actual administration of such prescription regimen are captured and then compared to the identified activity sequences to determine differences therebetween. A notice is provided if differences are determined.

Abstract: Healthcare object (HCO) discriminator systems and methods are presented. Systems can obtain a digital representation of a scene via a sensor interface. An HCO discriminator platform analyzes the digital representation to discriminate objects within the scene as being associated with a type of HCO or as being unrelated to a type of HCO. Once the HCO recognition platform determines that a type of HCO is relevant, it instantiates an actual HCO. The HCO can be routed to one or more destinations based on routing rules generated from a template or based on the manner in which the objects in the scene were discriminated.

Abstract: Embodiments of the present invention relate generally to non-invasive methods and tests that measure biomarkers (e.g., tumor antigens) and collect clinical parameters from patients, and computer-implemented machine learning methods, apparatuses, systems, and computer-readable media for assessing a likelihood that a patient has a disease, relative to a patient population or a cohort population. In one embodiment, a classifier is generated using a machine learning system based on training data from retrospective data and subset of inputs (e.g. at least two biomarkers and at least one clinical parameter), wherein each input has an associated weight and the classifier meets a predetermined Receiver Operator Characteristic (ROC) statistic, specifying a sensitivity and a specificity, for correct classification of patients.

Abstract: A system, method, and computer-readable media are provided for facilitating clinical decision making, and in particular, facilitating treatment of a person having congestive heart failure. The method includes the step of receiving patient information for a patient and using at least one solver to determine a patient condition or recommended treatment based on patient parameters or patient information.

Abstract: The disclosed systems and methods include displaying disease trigger icons within a disease trigger map in a GUI, where the disease trigger map corresponds to a particular disease symptom, and where the position and size of a particular trigger icon within the trigger map based one or more of (i) the degree or strength of a statistical association between the trigger icon's corresponding disease trigger and the disease symptom, and (ii) a cumulative frequency and/or amount of exposure to the trigger icon's corresponding disease trigger. Some embodiments also include displaying a patient population disease trigger map one or more relationships between (i) one or more disease triggers and (ii) one or more patients of the patient population. Some embodiments may further include facilitating communication and/or disease trigger information sharing among patients.

Abstract: Embodiments of the disclosure provide a method for aggregating and providing health data records to an electronic device. The method is performed by a server that includes a processor and a non-transitory computer readable medium with processor-executable instructions stored thereon. When the instructions are executed by the processor, the server performs the method including: (a) receiving collected data from one or more client devices, the collected data comprising health related data including at least one of step count data, heart rate data, sleep sensor data; (b) extracting metadata from the collected data; (c) pseudonymizing the collected data; (d) categorizing the collected data using the extracted metadata and enterprise ontology of the server; and (e) storing the collected data.

Abstract: A handheld personal communication apparatus for dialysis includes a reader to read a marking displayed on a dialysis fluid container to acquire data concerning at least one of a dialysis fluid type or a dialysis fluid volume from the marking; a processor using the at least one of the dialysis fluid type or the dialysis fluid volume to determine a dialysis dwell time for at least one cycle of a dialysis therapy, the dialysis dwell time being a time to achieve, over the at least one cycle, at least one of (a) a specified ultrafiltrate level, (b) a urea removal level, or (c) a creatinine removal level; and an output interface providing an indication to the patient of a completion of the dialysis dwell time.

Abstract: A decision support tool is provided for predicting a patient's length of stay within a healthcare unit, such as the emergency department. The predicted length of stay may be determined using patient information and facility information, which includes information about the department and the facility in which the department is located. The patient information and the facility information may be used to determine feature values input into a plurality of machine learning models. The models may be used sequentially such that initial models are used to predict variables relating to the patient's length of stay and output of such models is used with a length-of-stay model to determine the predicted length of stay. One or more response actions may be automatically initiated based on the predicted length of stay. Such response actions may include resource management actions to allocate resources within the healthcare unit.

Abstract: In one embodiment, a computer-implemented method that comprises receiving, a user request from a first system user of a plurality of system users for a communication of health data with a health information system. The health information system includes a data store that stores health data related to the plurality of system users.

Abstract: An information processing apparatus includes a first acquisition unit that acquires a user's instruction to change medical information to be displayed on a display unit, a second acquisition unit that acquires a plurality of pieces of medical information to be sequentially displayed on the display unit, a group generation unit that groups the acquired plurality of pieces of medical information based on the acquired user's instruction, a third acquisition unit configured to acquire representative information indicating the medical information contained in the group generated by the group generation unit, and an output unit configured to output the acquired representative information to the display unit.

Abstract: A method and system of audibly broadcasting responses to a user based on user queries about a specific patient molecular report, the method comprising receiving an audible query from the user to a microphone coupled to a collaboration device, identifying at least one intent associated with the audible query, identifying at least one data operation associated with the at least one intent, associating each of the at least one data operations with a first set of data presented on the molecular report, executing each of the at least one data operations on a second set of data to generate response data, generating an audible response file associated with the response data and providing the audible response file for broadcasting via a speaker coupled to the collaboration device.