The present disclosure generally relates to methods and user interfaces for displaying and managing user interfaces including information related to physiological measurements. In some embodiments, methods and user interfaces for displaying lab types based on whether a lab type had been previously designated are described. In some embodiments, methods and user interfaces for displaying a user interface that includes health topics, where information included in the user interface corresponds to a selected health topic, are described

The present disclosure generally relates to methods and user interfaces for displaying and managing user interfaces including information related to physiological measurements. In some embodiments, methods and user interfaces for displaying lab types based on whether a lab type had been previously designated are described. In some embodiments, methods and user interfaces for displaying a user interface that includes health topics, where information included in the user interface corresponds to a selected health topic, are described

A system and method for treating migraine and headache through a digital therapeutic. The systems and methods described herein allow a migraine patient to manage symptoms, triggers, and therapeutic lifestyle interventions through an interconnected system, facilitated by a care team, to treat the root causes of migraine, and improve patient quality of life. The method includes collecting datasets associated with migraine, headache, migraine-related comorbidities, and lifestyle behavior at the mobile device to analyze neurological trigger patterns. Using the digital therapeutic application allows a patient to monitor and track lifestyle habits, to receive real time interventions, otherwise missed in traditional care settings, helping the patient learn lifestyle interventions that may mitigate future attacks. Given the complex nature of treating migraine, therapeutic lifestyle interventions are tailored to a patient's Neuroindividuality and facilitated by a care team.

A system and method for treating migraine and headache through a digital therapeutic. The systems and methods described herein allow a migraine patient to manage symptoms, triggers, and therapeutic lifestyle interventions through an interconnected system, facilitated by a care team, to treat the root causes of migraine, and improve patient quality of life. The method includes collecting datasets associated with migraine, headache, migraine-related comorbidities, and lifestyle behavior at the mobile device to analyze neurological trigger patterns. Using the digital therapeutic application allows a patient to monitor and track lifestyle habits, to receive real time interventions, otherwise missed in traditional care settings, helping the patient learn lifestyle interventions that may mitigate future attacks. Given the complex nature of treating migraine, therapeutic lifestyle interventions are tailored to a patient's Neuroindividuality and facilitated by a care team.

A computer implemented method for prescribing optimized medical interventions includes retrieving a patient's updated electronic medical record (EMR) and mapping the diagnosis of the patient to a medical treatment database to select a plurality of likely medical intervention choices based on a score exceeding a defined threshold score. The method includes determining a rank order of the selected plurality of medical intervention choices by comparing simulation outcomes for each choice executed by the medical predictive algorithm, on respective choices among each of the selected likely medical interventions. The method also includes receiving by the patient's physician or patient's electronic medical record database, a rank order of recommended medical intervention choices including possible options and associated metrics based on an accepted level of simulated outcome.

In various implementations, computer-implemented method, such as one executed on a computer system or on instructions stored on computer-readable media may include: receiving from a user device associated with a user, a request to access one or more treatment plans for patient; identifying a treatment template for user, the treatment template representing treatment preferences of the user, the treatment template being expressed according to treatment domain-specific protocols; processing the treatment template with the treatment domain-specific protocols to convert one or more parts of the treatment template into one or more runtime elements that interactively display customized user interface elements related to the treatment plan, the customized user interface elements configured to provide one or more customized user interactions with the treatment plan in accordance with the treatment preferences of the user; and providing instructions to display the one or more runtime elements on the user device.

In various implementations, computer-implemented method, such as one executed on a computer system or on instructions stored on computer-readable media may include: receiving from a user device associated with a user, a request to access one or more treatment plans for patient; identifying a treatment template for user, the treatment template representing treatment preferences of the user, the treatment template being expressed according to treatment domain-specific protocols; processing the treatment template with the treatment domain-specific protocols to convert one or more parts of the treatment template into one or more runtime elements that interactively display customized user interface elements related to the treatment plan, the customized user interface elements configured to provide one or more customized user interactions with the treatment plan in accordance with the treatment preferences of the user; and providing instructions to display the one or more runtime elements on the user device.

A system and method that receive a distance matrix for multiple patients and a patient of interest, assign a radial distance value between the patient of interest and the other patients based on the distance matrix value for each of the multiple patients, generate an angular distance value between the multiple patients based at least in part on a measure of similarity between each patient, and minimize a cost function based at least in part on the angular distance value between each patient and each other patient. Minimizing the cost function may include calculating a patient contribution to the cost function for a plurality of angular distance values and selecting the angular distance value with the smallest patient contribution. The processor also may be configured to generate and display a radar plot based on the assigned radial distance value and generated angular distance value of each patient.

A system and method that receive a distance matrix for multiple patients and a patient of interest, assign a radial distance value between the patient of interest and the other patients based on the distance matrix value for each of the multiple patients, generate an angular distance value between the multiple patients based at least in part on a measure of similarity between each patient, and minimize a cost function based at least in part on the angular distance value between each patient and each other patient. Minimizing the cost function may include calculating a patient contribution to the cost function for a plurality of angular distance values and selecting the angular distance value with the smallest patient contribution. The processor also may be configured to generate and display a radar plot based on the assigned radial distance value and generated angular distance value of each patient.

A mechanism is provided in a data processing system to implement a personalized patient engagement engine. The personalized patient engagement engine develops a set of models for a plurality of behavioral phenotypes based on anonymized unstructured and structured patient-care management records for a plurality of patients over a period of time; matches a given patient to a behavioral phenotype; estimates a propensity of positive and/or negative behavioral responses of each of a plurality of targeted behaviors; dynamically updates personalized intervention effectiveness rankings in context for care manager and patient decision-making based on what has been shown to lead to positive responses for individuals with a similar behavioral profile; generates an intervention recommendation for the given patient based on the personalized intervention effectiveness rankings relative to the patient given an assigned goal and an individual intervention effect estimation; and provides the intervention recommendation to the care manager.