A therapy platform can leverage mood tracking to personalize delivery of therapy. User input data is collected to generate one or more mood scores that change over time. Tracked mood scores can include an overall mood score (e.g., −100 to 100 where −100 represents a strongly negative or “bad” mood and 100 represents a strongly positive or “happy” mood) and/or enumerated mood scores (e.g., numerical scores tracking individual, enumerated moods, such as “anxious,” “sad,” “tired,” “happy,” and the like). In some cases, an overall mood score can be made up of enumerated mood scores. Tracked mood scores can be used to inform the selection of what therapy to provide. For example, a first therapy tool may be selected for delivery when the user evidences a first set of mood scores, whereas a second therapy tool may be selected when the user evidences a second set of mood scores.

A therapy platform can leverage mood tracking to personalize delivery of therapy. User input data is collected to generate one or more mood scores that change over time. Tracked mood scores can include an overall mood score (e.g., −100 to 100 where −100 represents a strongly negative or “bad” mood and 100 represents a strongly positive or “happy” mood) and/or enumerated mood scores (e.g., numerical scores tracking individual, enumerated moods, such as “anxious,” “sad,” “tired,” “happy,” and the like). In some cases, an overall mood score can be made up of enumerated mood scores. Tracked mood scores can be used to inform the selection of what therapy to provide. For example, a first therapy tool may be selected for delivery when the user evidences a first set of mood scores, whereas a second therapy tool may be selected when the user evidences a second set of mood scores.

Aspects of the invention include includes identifying a respective estimated clinical risk score for each of a first group of patients and a second group of patients. An alternative probability estimate is generated using a same set of inputs used to determine each respective estimated clinical risk score. An unreliability of a patient's clinical risk score is determined based at least in part on a feature of the patient and on a difference between the alternative probability estimate and the determined respective estimated clinical risk score.

Performing an operation comprising generating, by a computing system based on data received from a plurality of data sources, a data model describing a patient, wherein the data comprises medical history data of the patient and observation data received by the computing system during observation of at least one medical professional, generating, by the computing system and based on the model applied to the received data, a plurality of candidate diagnoses for the patient, executing, by the computing system, a plurality of simulations of a plurality of candidate treatments generated by the computing system based on the model, and identifying a first candidate treatment of the plurality of candidate treatments that reduces an uncertainty value of the data model below a threshold.

A plurality of events are extracted from a plurality of electronic health records associated with a first patient. The extracted plurality of events are analyzed to identify a plurality of stimulus events and a plurality of response events. An association between a first stimulus event and a first response event is determined. A stimulus-response (SR) variable is generated for the first patient based at least in part on the determined association, and the generated SR variable is integrated into one or more predictive cognitive models.

A device is configured to process medical-event related information, such as associated with a medical code event, such as by receiving medical-event related information, recording medical event information with timestamps, generating additional medical information, displaying medical events and additional medical information on media display, visual indicators, and user devices to provide real-time notifications of recorded and reminders for upcoming medical events, and sending medical events with timestamps and additional medical information to other devices for further processing. The device may be configured as a code clock which includes an analog clock.

A device is configured to process medical-event related information, such as associated with a medical code event, such as by receiving medical-event related information, recording medical event information with timestamps, generating additional medical information, displaying medical events and additional medical information on media display, visual indicators, and user devices to provide real-time notifications of recorded and reminders for upcoming medical events, and sending medical events with timestamps and additional medical information to other devices for further processing. The device may be configured as a code clock which includes an analog clock.

Apparatus and associated methods relate to presenting for selection services comprising at least one bundled set of healthcare services to be performed separately by respective providers, determining a bundle price for the at least one bundled set of healthcare services, and in response to receiving payment in an amount of the bundle price, generating a purchase data record selectively redeemable to receive each of the at least one bundled set of healthcare services, and transmitting a unique confirmation number generated for the purchase data record. One or more service of the bundled set may be a dental or veterinary service. The bundle price may be based on a location or time at which at least one service will be performed and may be determined using a user's remaining insurance deductible. Payment may be disbursed to multiple providers of the bundled set of healthcare services. A payment may be virtual funds.

A medical information navigation engine (“MINE”) is provided. In some embodiments, the system computes a current patient encounter vector for a current patient encounter, and then an optimal patient encounter vector is computed by assuming a best case patient encounter in accordance with the organizational objectives. The system is then able to compute the difference between the best case encounter and the current patient encounter. This difference is used to compute a corresponding payoff using an intelligent matrix.

A water prescribing system 1 is provided with a state storage unit 21 which stores a state variable relating to a physical constitution and health condition for each of a plurality of persons including a user, and a prescription unit 22 which creates a prescription of water suitable for the user based on the state variable.