Abstract: Physiological sensors may be utilized to obtain physiological data for a user. The sensor data may be utilized in predicting a user's outcome to a medical intervention using one or more models. The models may be automatically executed in response to receiving certain types and/or amount of data, such as data received from one or more physiological remote sensors, such as Internet of Things sensors. The sensors may include heart rate sensors, arterial pressure sensors, glucose sensors, temperature sensors, weight sensors, blood oxygen sensors, urine sensors, saliva sensors, skin conduction sensors, muscle sensors, brain signal sensors, and/or other sensors. A sensor may communicate over the 2360-2400 MHz and/or the 30-37.5 MHz radio frequency (RF) band. The data may be received from a networked data store. Execution of the models may identify health issues in substantially real time, and the operation of one or more medical devices may be modified and/or a communication may be generated.

Abstract: A data processing system is provided for determining clinical outcomes of medical data gathered by the system. The system can allow a person to define a medical study and can then administer the medical study and can collect and analyze data from potentially geographically diverse doctors, patients and other people associated with a study. Users enter sets of medical information. The system can analyze the medical data according to any number of clinical algorithms that may be custom defined and edited before and during the study. The system conditionally outputs the clinical outcome to the user. The clinical outcome can be used for treatment of patients participating in the study immediately after the data is input and analyzed. The medical outcomes can indicate such things as performance comparisons, composite outcomes, and risk stratification and assessments for such things as treatments, drugs, illnesses, doctors, patients and physician groups.

Abstract: A data processing system is provided for determining clinical outcomes of medical data gathered by the system. The system can allow a person (e.g. a doctor) to define a medical study and can then administer the medical study and can collect and analyze data in real-time from potentially geographically diverse doctors, patients and other people associated with a study. The system can analyze the medical data in real-time according to any number of clinical algorithms that may be custom defined and edited before and during the study. The clinical algorithms produce clinical outcome data that can be used for treatment of patients participating in the study immediately after the data is input and analyzed. The medical outcomes can indicate such things as performance comparisons, composite outcomes, and risk stratification and assessments for such things as treatments, drugs, illnesses, doctors, patients and physicians groups.

Abstract: A data processing system is provided for determining clinical outcomes of medical data gathered by the system. The system can allow a person to define a medical study and can then administer the medical study and can collect and analyze data from potentially geographically diverse doctors, patients and other people associated with a study. Users enter sets of medical information. The system can analyze the medical data according to any number of clinical algorithms that may be custom defined and edited before and during the study. The system conditionally outputs the clinical outcome to the user. The clinical outcome can be used for treatment of patients participating in the study immediately after the data is input and analyzed. The medical outcomes can indicate such things as performance comparisons, composite outcomes, and risk stratification and assessments for such things as treatments, drugs, illnesses, doctors, patients and physician groups.