Abstract: A computer system identifies supplemental materials most effective at increasing adherence for each of a plurality of different medications and provides the materials at an optimal point in time. An example method generates a first user interface for receiving an electronic prescription for a patient for a prescribed substance. Responsive to receiving the electronic prescription, the method includes obtaining adherence data for the patient, identifying supplemental programs associated with the prescribed substance from a database of supplemental programs, generating a second user interface that presents the supplemental programs for selection by the health care provider, and responsive to receiving selection of at least one of the supplemental programs in the second user interface, providing the supplemental programs to the patient. The supplemental programs identified from the database are associated with at least one rule relating to adherence data that is met by the adherence data for the patient.

Abstract: A method for generating DICOM images as part of a real-time virtual medical consultation includes receiving, by a handheld patient device associated with a patient, a DICOM image associated with the patient generated by a diagnostic device, encrypting, by the handheld patient device, the DICOM image and linking the encrypted DICOM image to a unique patient identifier associated with the patient, wherein the handheld patient device is one of a tablet computer and a smartphone, and transmitting, by the handheld patient device, the encrypted DICOM image to a server configured to provide a DICOM viewer option within a secure telemedicine platform accessible by a medical professional and executed by the server.

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: A user interface to a medical database stores context information from previous queries and uses the context information as part of information selection criteria for a current query, without requiring the users to fully specify the information selection criteria in each query. The context information is automatically stored as a profile for each user, for each group of users and, optionally, for each institution to which a user is affiliated. In response to a current user query, a combination of the information selection criterion currently entered by the user and one or more information selection criteria previously entered by the user, group and (optionally) institution is used to query the medical database. Optionally, a user's group membership may be automatically determined, based on current physical location of the user and potential groups, for example as estimated from a meeting calendar or signals received by a wireless access point.

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: Introduced here are health management platforms able to infer the health state of a subject based on behavioral changes reflected in the digital activities performed by a subject. A health management platform can initially acquire contextual data pertaining to digital activities performed by the subject. The health management platform can identify the target(s) of the digital activities by parsing the contextual data, and then compile the digital activities and corresponding activities into a personalized valence index. Thereafter, the health management platform can compare digital activities performed by the subject to the entries included in the personalized valence index. If a matching entry is not discovered, the health management platform can identify an instance of behavior change. These instances of behavior change may be indicative of changes in the subject's health state.

Abstract: Various systems and methods for collecting patient data are discussed herein. According to some systems and methods, a timer may be started, and a blood pressure data collection system is actuated to obtain a blood pressure measurement of a patient upon the expiration of the timer. The timer may be incorporated into a patient data collection system or method to ensure the patient is relaxed and calm prior to taking a blood pressure measurement. An event may be sensed by an environmental sensor system and the timer may be started in response to sensing the event. A clinician leaving a room where the patient is disposed is one example of an event. An interruption may be sensed by the environmental sensor system and the timer may be terminated in response to sensing the interruption. The clinician entering the room where the patient is disposed in one example of an interruption.

Abstract: A method for electronically determining patient medical treatment eligibility, coverage, copayment amount and insurer billing, by: (a) a patient requesting medical treatment at a retail clinic; (b) the patient presenting a health insurance card at the retail clinic; (c) the retail clinic transmitting patient health insurance card information to a centralized adjudication facility; (d) the retail clinic transmitting medical treatment information to the centralized adjudication facility; (e) the centralized adjudication facility determining patient medical treatment coverage, eligibility and copayment amount (f) transmitting the patient medical treatment coverage, eligibility and copayment amount from the centralized adjudication facility to the retail clinic; (g) the patient purchasing the medical treatment by paying the retail clinic the copayment amount, (h) transmitting a bill to the health care insurance provider; and (i) thereby informing the retail clinic clinician to sell the medical treatment to the pa

Abstract: A method, system and computer readable medium of: providing feature data of at least one organ at risk or target volume of said patient from a database of non-transitory data stored on a data storage device of prior patients data; generating, using a data processor, a distribution of dose points of the at least one organ at risk or target volume of said patient based on said feature data; calculating, using the data processor, at least one of (i) a probability of toxicity for the at least one organ at risk or (ii) a probability of treatment failure for the at least one target volume, based on said distribution of dose points; assessing, using the data processor, a dosimetric-outcome relationship based on the calculated probability; and automatically formulating, using the data processor, a treatment plan using the dosimetric-outcome relationship to minimize the at least one treatment-related risk.

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: The method of event-driven health and wellness decision support considers an individual's medical records and lifestyle; applies healthcare best practices; and recommends next steps. Medical and lifestyle records are input, converted to events and inserted in timestamp order in an event queue. Events are processed in queued order by handlers, and results recorded in a data structure called a “person state”. Some handlers create additional events and insert them in the event queue in timestamp order. Those events are in turn processed in timestamp order. Other handlers create no events, allowing processing of all queued events to eventually complete. After events representing actual occurrences are processed, events representing postulated activities are created, queued, and processed until a specific patient state representing a health and wellness goal obtains. This allows several activity paths to be compared to determine the best path to an optimal health goal. Next steps are recommended as output.

Abstract: An assist system that assists an operation of a medical institution, including a learning unit that performs machine learning using medical institution data including operation data relating to the operation of the medical institution and economic data relating to the economic efficiency, patient data relating to a patient in a region to which the medical institution belongs, and environment data relating to environment surrounding the medical institution; and a presentation unit that presents an operation policy for improving the economic efficiency of the medical institution based on a result of the machine learning.

Abstract: A system includes: a fluid delivery pump and a network of multiple record management processing nodes. The fluid delivery pump is in communication with one or more of the record management-processing nodes in the network. At least a first record management processing node receives input indicating a fluid delivery event. The fluid delivery event indicates fluid delivery from the fluid delivery pump to a recipient. The record management-processing node identifies code pertinent to the fluid delivery event; the code includes criteria in which to validate the fluid delivery event. In response to validation of the fluid delivery event as specified by the criteria in the code, a resource such as the record management-processing node triggers a transaction associated with the fluid delivery event.

Abstract: Concerted processing of a multiplicity of local apparatus status messages from dialysis apparatuses can be performed to enhance the quality of patient care delivered using the dialysis apparatuses. Typically, the dialysis apparatuses are operated in a group. A control agent, as described herein, performs a central calculation of prioritised warning messages for the group of dialysis apparatuses. The prioritisation is calculated in a concerted calculation according to a preconfigured system of rules.

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: The present disclosure is directed to a computerized method, system and software application for coordinating medical care through a Pathways Community Hub (HUB). A Pathways Community Hub is a network of care coordination agencies which focuses its mission towards reaching individuals within the community having the greatest risk-factors through the deployment of service providers such as community care coordinators. The Pathways Community Hub finds at-risk individuals in need of medical, health-related or social services, treats identified risk factors and measures a patient's risk status over time. The goal of the Pathways Community Hub is to achieve a reduction of risk among patients through open communication and collaboration among service providers including medical service providers and community-based organizations and to reduce the overall cost of medical, health-related and social services over time within a region.

Abstract: At least one aspect of this technical solution is directed to a system for generating a multi-factorial real-time predictive model for healthcare events, with a data processing system comprising memory and one or more processors to obtain a condition metric and a condition period associated with a participant object, generate, based on a model trained using historical condition-service data, a first participation metric for the participant object based on a participant service associated with the condition metric and the participant object, aggregate the first participation metric and the condition period into a first aggregated participation metric, receive, via a computing device associated with the participant object, a selection of an opportunity object associated with the condition metric, the opportunity object corresponding to an opportunity event provided via a third-party application that interfaces with the data processing system, generate, based on the model and the selection of the opportunity obj

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: The disclosed technology relates to a platform for providing improved compliance with a customized medical care plan. A customized medical care plan is generated based on a health condition of a user. A first measurement is solicited at a first predetermined time period. The first measurement is received from a measurement device within the first predetermined time period. A compliance score is generated based on receipt of the first measurement within the first predetermined time period. An intervention can be initiated based on the generated compliance score and the first measurement.

Abstract: Techniques are described for managing tasks of a dynamic system with limited resources using a machine-learning and combinatorial optimization framework. In one embodiment, a computer-implemented method is provided that comprises employing, by a system operatively coupled to a processor, one or more first machine learning models to determine a total demand for tasks of a dynamic system within a defined time frame based on state information regarding a current state of the dynamic system, wherein the state information comprises task information regarding currently pending tasks of the tasks. The method further comprises, employing, by the system, one or more second machine learning models to determine turnaround times for completing the tasks based on the state information, and determining, by the system, a prioritization order for performing the currently pending tasks based on the total demand and the turnaround times.