Abstract: A method may include receiving, from one or more data systems, a message. A machine learning model may be applied to the message to determine whether the message is an actionable message or a non-actionable message. In response to the message being the actionable message, the machine learning model may be applied to extract, from the message, a clinically significant data. One or more tasks may be performed based on the clinically significant data. The one or more tasks may include performing, based on the clinically significant data, a resource allocation for a clinical workflow associated with the data systems. The one or more tasks may also include detecting systematic inefficiencies and bottlenecks associated with the clinical workflow. Related methods and articles of manufacture, including computer program products, are also disclosed.

Abstract: Systems for use with a medical device for reducing medical facility readmission risks are provided. In one aspect, a system includes a medical device that is configurable with operating limit parameters for providing testing or treatment to a patient, and a limiting system. The limiting system includes a memory that includes patient-specific information for the patient and a database that includes readmission risk information, and a processor. The processor is configured to compare readmission risk parameters with the patient-specific information, and provide a readmission risk score for integration with medical devices and processes corresponding to the patient. Methods and machine-readable media are also provided.

Abstract: Systems for use with a medical device for reducing medical facility readmission risks are provided. In one aspect, a system includes a medical device that is configurable with operating limit parameters for providing testing or treatment to a patient, and a limiting system. The limiting system includes a memory that includes patient-specific information for the patient and a database that includes readmission risk information, and a processor. The processor is configured to compare readmission risk parameters with the patient-specific information, and provide a readmission risk score for integration with medical devices and processes corresponding to the patient. Methods and machine-readable media are also provided.

Abstract: A method of obtaining and processing patient data and patient treatment data to provide a prognosis parameter related to a patient's disease state is provided. The method identifies and calculates coefficients related to appropriate predictor variables which are then used by the prediction model to calculate the prognosis parameter. The prediction model may be a logistic regression model. The method may also be used to assess the level of care being provided to patients, as well as providing a way of assessing the outcome of the patient's condition as a function of treatment. A method of calculating a harm index reflective of the risk of treatment is also provided.