Centralized support user management in a distributed healthcare information management system. Support user management may include generation of permission data that may be distributed from a central server to one or more local systems. The local systems may execute a healthcare information management application such as, for example, a pharmacy workflow management application. In any regard, central support users at the central server may periodically require access to the local systems to perform, among other activities, technical support or troubleshooting in relation to the application executed at the local system. In turn, provision of permission data from the central server to the local system may allow support users to access the local system with specific permission identification's provided specific ones of the support users. In turn, specific user permissions may be established and support user tracking may be carried out at the local systems.

Centralized support user management in a distributed healthcare information management system. Support user management may include generation of permission data that may be distributed from a central server to one or more local systems. The local systems may execute a healthcare information management application such as, for example, a pharmacy workflow management application. In any regard, central support users at the central server may periodically require access to the local systems to perform, among other activities, technical support or troubleshooting in relation to the application executed at the local system. In turn, provision of permission data from the central server to the local system may allow support users to access the local system with specific permission identification's provided specific ones of the support users. In turn, specific user permissions may be established and support user tracking may be carried out at the local systems.

Systems and methods herein provide for a proxy infrastructure. In the proxy infrastructure, a network element (e.g., a supernode) is connected with a plurality of exit nodes. At one of a plurality of messenger units of the proxy infrastructure, a proxy protocol request is received directly from a client computing device. The proxy protocol request specifies a request and a target. In response the proxy protocol request, a selection is made between one between one of the plurality of exit nodes. A message with the request is sent from the messenger to the supernode connected with the selected exit node. Finally, the message is sent from the supernode to the selected exit node to forward the request to the target.

A server computer system, comprises a processor; a communications module coupled to the processor; and a memory coupled to the processor, the memory storing instructions that, when executed, configure the processor to receive, via the communications module and from a client device, a signal including a request to configure a transfer of data to a particular data record; determine that the particular data record is associated with a third party server; obtain a trust score associated with the particular data record; determine that the trust score satisfies trust criteria; and responsive to determining that the trust score satisfies trust criteria, enable one or more transfer features associated with a real-time transfer protocol.

Managing data to provide a cloud-based service for a plurality of work sessions, including: receiving a request to create a work session that is represented by a collection of tables; creating a work session table stored on a session server; receiving a request to add a user to the work session; storing user data related to the work session for the user in a record in the user table of the work session table; receiving a request to add an application to the work session; storing application data for the application related to the work session in a record in the application table of the work session table; and creating a session log which preserves information indicating an activity related to the work session including adding, accessing, changing, removing a file, person, application, or resource. Key words include work session and data access.

Managing data to provide a cloud-based service for a plurality of work sessions, including: receiving a request to create a work session that is represented by a collection of tables; creating a work session table stored on a session server; receiving a request to add a user to the work session; storing user data related to the work session for the user in a record in the user table of the work session table; receiving a request to add an application to the work session; storing application data for the application related to the work session in a record in the application table of the work session table; and creating a session log which preserves information indicating an activity related to the work session including adding, accessing, changing, removing a file, person, application, or resource. Key words include work session and data access.

Health care information for multiple patients is processed to classify patients into categories. Additional data fields related to a category in which a patient is classified are added to the patient record. These data fields are populated in part by automatically processing the existing patient data. Such automatic processing can result in a probability that the underlying data supports having a particular value stored in one of the added data fields, and this probability also can be stored. Over time, additional data can be obtained from patients, caregivers and other sources, for structured data fields based on data entry forms for patient reported outcomes, caregiver reported outcomes, events of interest, survival and resource utilization. A set of factor scores is computed for each patient, for each category in which the patient is classified. An outcome score is computed for each patient for each category in which the patient is classified, using an outcome function defined for that category, as a weighted function of one or more of the factor scores. The outcome function for a category is standardized across all patients classified in that category.

Health care information for multiple patients is processed to classify patients into categories. Additional data fields related to a category in which a patient is classified are added to the patient record. These data fields are populated in part by automatically processing the existing patient data. Such automatic processing can result in a probability that the underlying data supports having a particular value stored in one of the added data fields, and this probability also can be stored. Over time, additional data can be obtained from patients, caregivers and other sources, for structured data fields based on data entry forms for patient reported outcomes, caregiver reported outcomes, events of interest, survival and resource utilization. A set of factor scores is computed for each patient, for each category in which the patient is classified. An outcome score is computed for each patient for each category in which the patient is classified, using an outcome function defined for that category, as a weighted function of one or more of the factor scores. The outcome function for a category is standardized across all patients classified in that category.

Health care information for multiple patients is processed to classify patients into categories. Additional data fields related to a category in which a patient is classified are added to the patient record. These data fields are populated in part by automatically processing the existing patient data. Such automatic processing can result in a probability that the underlying data supports having a particular value stored in one of the added data fields, and this probability also can be stored. Over time, additional data can be obtained from patients, caregivers and other sources, for structured data fields based on data entry forms for patient reported outcomes, caregiver reported outcomes, events of interest, survival and resource utilization. A set of factor scores is computed for each patient, for each category in which the patient is classified. An outcome score is computed for each patient for each category in which the patient is classified, using an outcome function defined for that category, as a weighted function of one or more of the factor scores. The outcome function for a category is standardized across all patients classified in that category.

Health care information for multiple patients is processed to classify patients into categories. Additional data fields related to a category in which a patient is classified are added to the patient record. These data fields are populated in part by automatically processing the existing patient data. Such automatic processing can result in a probability that the underlying data supports having a particular value stored in one of the added data fields, and this probability also can be stored. Over time, additional data can be obtained from patients, caregivers and other sources, for structured data fields based on data entry forms for patient reported outcomes, caregiver reported outcomes, events of interest, survival and resource utilization. A set of factor scores is computed for each patient, for each category in which the patient is classified. An outcome score is computed for each patient for each category in which the patient is classified, using an outcome function defined for that category, as a weighted function of one or more of the factor scores. The outcome function for a category is standardized across all patients classified in that category.