Abstract: Methods for dynamic routing of queued network-based communications using real-time information and machine learning are performed by systems and devices. Requests associated with fulfillments are received over a network from requestor systems, and the requests are queued in a data structure of a queue. Information that includes geolocation information from a user device of a user that is associated with the fulfillment, temporal information from the user device, or related request information associated with another request is then received over the network, and a fulfiller and a fulfillment time for the fulfillment are determined from the information. The request is provided from the queue to the fulfiller at the fulfillment time over the network.

Abstract: Systems, methods, and devices are described for classifying and answering medical inquiries based on machine-generated data resources and machine learning models. A CCDA document including clinical information and observations of a patient are received from a requestor and utilized to generate a FHIR model instance specific to the CCDA document. Question text having medical inquires for the patient, and received with the CCDA document, is processed by a machine learning model to determine question categories for the medical inquiries which are utilized to map the inquires to objects of the model instance using another machine learning model. The model instance is queried based on the mapping to return values associated with the inquiries. The values are transmitted back to the requestor.

Abstract: Methods for dynamic routing of queued network-based communications using real-time information and machine learning are performed by systems and devices. Requests associated with fulfillments are received over a network from requestor systems, and the requests are queued in a data structure of a queue. Information that includes geolocation information from a user device of a user that is associated with the fulfillment, temporal information from the user device, or related request information associated with another request is then received over the network, and a fulfiller and a fulfillment time for the fulfillment are determined from the information. The request is provided from the queue to the fulfiller at the fulfillment time over the network.

Abstract: Systems and methods are provided for determining an intervention service to provide to a patient and communicating the determined intervention service opportunities to a healthcare provider as part of the processing of a healthcare transaction. A service provider computer may evaluate historical healthcare transaction data for a patient to determine if the patient should receive an intervention service and can store an indication to notify a healthcare provider about the intervention service. A healthcare transaction, such as a prescription billing transaction, may be received by the service provider computer from a healthcare provider computer. The service provider computer may determine if an intervention service has been identified for the patient. The service provider computer may generate a notification of the intervention service, append the notification to an adjudicated response to the healthcare transaction, and transmit the notification and adjudicated response to the healthcare provider computer.

Abstract: A method, apparatus, system and computer program product are provided for determining one or more current or future conditions regarding capacity and allocation of resources in an institution. The apparatus enables personnel to utilize predictive tools to identify in real-time or in the near future areas of capacity constraints within the institution. The apparatus includes a processor configured to analyze data which includes information associated with the institution. A portion of the data is generated in real-time during an actual time in which events occur. The processor is capable of using at least a portion of the data to identify current conditions or generate one or more predictions regarding conditions to occur in the future that are associated with resources and capacity of the institution. Also, the processor is capable of analyzing results of the predictions and allocating resources of the institution on the basis of the predicted results.

Abstract: Systems, methods, apparatus, and computer program products are provided for monitoring quality metrics for patients in health care facilities. For example, in one embodiment, a monitoring server can monitor a set of quality metrics associated with a patient in a health care facility. During the monitoring process, the monitoring server can determine whether activities associated with the respective quality metrics have been or need to be performed, providing medical providers information in time to correct care documentation. The monitoring server can also cause display of graphics that indicate the results of such determinations.

Abstract: A method for providing a patient quality monitor may include receiving an identification of quality metrics associated with each of a plurality of health care conditions in which the quality metrics correspond to external standards of care for the respective health care conditions, extracting clinical patient quality data regarding activities corresponding to the quality metrics identified from a database, sorting the clinical patient quality data according to health care condition, and presenting compliance data on a dashboard display indicative of compliance with the quality metrics of a selected one of the health care conditions based on the sorted clinical patient quality data. A corresponding computer program product and apparatus are also provided.

Abstract: A method, apparatus, system and computer program product are provided for determining one or more current or future conditions regarding capacity and allocation of resources in an institution. The apparatus enables personnel to utilize predictive tools to identify in real-time or in the near future areas of capacity constraints within the institution. The apparatus includes a processor configured to analyze data which includes information associated with the institution. A portion of the data is generated in real-time during an actual time in which events occur. The processor is capable of using at least a portion of the data to identify current conditions or generate one or more predictions regarding conditions to occur in the future that are associated with resources and capacity of the institution. Also, the processor is capable of analyzing results of the predictions and allocating resources of the institution on the basis of the predicted results.