Abstract: A computationally implemented system and method that is designed to, but is not limited to: electronically receiving user biological status information from electronically involved detection of one or more biological user conditions. In addition to the foregoing, other method aspects are described in the claims, drawings, and text forming a part of the present disclosure.

Abstract: Methods for classifying patients as responders or non-responders to treatment of a disease and predicting recurrence of disease in a patient using audio tunes are provided.

Abstract: A healthcare claims processing and decision support system and method are disclosed that allow for the pre-processing of the healthcare claims as well as a method to reduce much of this overhead and alerting the user to any errors that occur during the claims processing.

Abstract: Healthcare costs accumulated across a plurality of claims systems are managed using a centralized accumulator, which receives cost accumulator data for adjudicated claims from multiple sending claim systems. An accumulator record type is identified from the cost accumulator data and used to generate a cross-reference record. The record type includes an adjudicated claim. A routing message is generated for at least one receiving claim system according to the identified accumulator record type, the cost accumulator data received from the sending claim system, and an identity of the at least one receiving claim system. In response to sending the routing message to the receiving claim system, an acknowledgement is received, which is used to update the cross-reference record by the processor.

Abstract: A dynamic differential diagnosis training and evaluation system incorporates a beginner student learning mode, a beginner student test mode, an advanced student learning mode, and an advanced student test mode for training, nurturing, and evaluating dynamic differential diagnosis (dynamic DDx) reasoning skills for patient condition determination. In a preferred embodiment of the invention, the dynamic differential diagnosis training and evaluation system incorporates one or more computerized user interfaces for displaying, choosing, and interacting with a simulated virtual patient, hypotheses selections for the patient condition determination, simulated physical exam selections, simulated medical test selections, simulated medical test results, a computerized expert's feedback and answers, and an iterative differential diagnosis (DDx) list modification and refinement process that simulates real-life dynamic differential diagnosis (dynamic DDx).

Abstract: A value icon for a web-based health or health support program packages access information for a website in a value icon physically embodying the abstract benefits of the welfare program in order to encourage initial access of the health support website. The value icon may be a compact container holding a three-dimensional article having a health support-related utility, at least one printed coupon representing a healthcare program credit and may provide the address to a health support website which offers additional programs based on information from an individual in a questionnaire on the health support website.

Abstract: Systems and methods are described relating to detecting an indication of at least one attribute of an individual; accepting sensor data about the individual; and presenting a set of health care options at least partially based on the detecting an indication of at least one attribute of the individual and the accepting sensor data about the individual.

Abstract: Systems and methods are described relating to accepting an indication of at least one attribute of an individual; accepting sensor data about the individual; presenting a set of health care options at least partially based on the accepting sensor data about the individual; and providing a matching system for procurement of at least one selected health service option.

Abstract: Systems and methods are described relating to accepting an indication of at least one attribute of an individual; activating at least one sensor at least partially based on the accepting an indication of at least one attribute of the individual; accepting sensor data from the at least one sensor; and presenting a set of health care options at least partially based on the accepting sensor data from the at least one sensor.

Abstract: The invention is directed to a method of identifying a patient undergoing periodic hemodialysis treatments at increased risk for death that includes determining at least one of the patient's clinical or biochemical parameters, including systolic blood pressure, serum albumin concentration level, body weight, body temperature, serum bicarbonate concentration level, serum potassium concentration level, serum calcium concentration level, hemoglobin concentration level, serum phosphorus concentration level, neutrophil to lymphocyte ratio, equilibrated normalized protein catabolic rate (enPCR), equilibrated fractional clearance of total body water by dialysis and residual kidney function (eKdrt/V), EPO resistance index, transferrin saturation index, serum ferritin concentration level, serum creatinine concentration level, platelet count, Aspartat-Aminotransferase level, and Alanin-Aminotransferase level at periodic hemodialysis treatments, and identifying a patient as having an increased risk for death if the pati

Abstract: Systems and methods are described relating to accepting an indication of at least one attribute of an individual; accepting sensor data about the individual; and presenting a set of health care options at least partially based on the accepting an indication of at least one attribute of the individual and the accepting sensor data about the individual.

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: Secure associate ordering and transaction methods and systems. An order for an alternative device different from a baseline device is received at an order processing platform. The alternative device is available for purchase by the associate at a cost differential between the alternative and baseline devices. The cost differential is based on a predetermined enterprise discount. A message including a secure link associated with the order is sent to the associate. Payment information associated with the cost differential is received by a secure payment (SP) platform from the associate via a secure website using the secure link. The payment information is submitted to a payment institution. The order processing platform receives a transaction confirmation from the SP platform when the payment information is accepted and adds at least features of the alternative device associated with the baseline device to a service account of the enterprise customer for the service provider.

Abstract: A patient monitoring system (8) monitors physiological functions of a plurality of patients (12). Each clinician (10) and each patient (12) has an associated identification device (20, 22), which each includes an identification code corresponding to respective clinician and patient. Each identification device (20, 22) includes a respective body-coupled communication device (24, 26) for communicating the identification code to a medical device (14). The clinician (10) activates the medical device (14) which includes a body-coupled communication device (40) including an ID reader (42). The ID reader (42) scans the area to detect whether the clinician identification is present. After the clinician's identification code is read, the medical device (14) is ready to take measurements. The clinician (10) takes the medical device (14) to the patient (12). The ID reader (42) scans the area to detect the patient identification code.