Abstract: A mechanism is provided in a data processing system comprising at least one processor and at least one memory, the at least one memory comprising instructions executed by the at least one processor to cause the at least one processor to implement a healthcare analytics management system. A healthcare analytics development sub-system of the healthcare analytics management system develops an analytics pipeline of a set of analytics assets for a selected healthcare based on a set of business needs for a healthcare analytics client and a healthcare analytics model based on the set of analytics assets and the set of business needs. The healthcare analytics model links to the analytics pipeline. A model deployment module of a healthcare analytics operation sub-system of the healthcare analytics management system deploys the healthcare analytics model on a set of computing devices of the selected healthcare consumer.

Abstract: A mechanism is provided in a data processing system comprising at least one processor and at least one memory, the at least one memory comprising instructions executed by the at least one processor to cause the at least one processor to implement a healthcare analytics management system. A healthcare analytics development sub-system of the healthcare analytics management system develops an analytics pipeline of a set of analytics assets for a selected healthcare based on a set of business needs for a healthcare analytics client and a healthcare analytics model based on the set of analytics assets and the set of business needs. The healthcare analytics model links to the analytics pipeline. A model deployment module of a healthcare analytics operation sub-system of the healthcare analytics management system deploys the healthcare analytics model on a set of computing devices of the selected healthcare consumer.

Abstract: A mechanism is provided to implement a healthcare analytics management system. A healthcare analytics development sub-system develops an analytics pipeline of a set of analytics assets for a selected healthcare based on a set of business needs for a healthcare analytics client and a healthcare analytics model based on the set of analytics assets and the set of business needs. A model deployment module of a healthcare analytics operation sub-system deploys the healthcare analytics model on a set of computing devices of the selected healthcare consumer. Responsive to detecting a performance deviation of the deployed healthcare analytics model from the set of business needs, a model feedback module determines improvement needs for the healthcare analytics model. The model feedback module feeds the improvement needs back to the healthcare analytics development sub-system. The healthcare analytics development sub-system customizes the healthcare analytics model based on the improvement needs.

Abstract: A mechanism is provided to implement a healthcare analytics management system. A healthcare analytics development sub-system develops an analytics pipeline of a set of analytics assets for a selected healthcare based on a set of business needs for a healthcare analytics client and a healthcare analytics model based on the set of analytics assets and the set of business needs. A model deployment module of a healthcare analytics operation sub-system deploys the healthcare analytics model on a set of computing devices of the selected healthcare consumer. Responsive to detecting a performance deviation of the deployed healthcare analytics model from the set of business needs, a model feedback module determines improvement needs for the healthcare analytics model. The model feedback module feeds the improvement needs back to the healthcare analytics development sub-system. The healthcare analytics development sub-system customizes the healthcare analytics model based on the improvement needs.

Abstract: A method, computing system and computer program product are provided. A first entity system that stores sensitive information associated with different entities applies a hash function a portion of the sensitive information to produce hash values. Transaction information pertaining to transactions performed on entity systems are stored within a blockchain database accessible to the entity systems. The transaction information includes hash values corresponding to associated entities from the entity systems. The hash values of the first entity system are compared to the hash values from others of the entity systems to determine entity systems containing information pertaining to same entities. The sensitive information for an entity of the first entity system is exchanged with the determined entity systems containing information for that entity.

Abstract: Patient assistant systems are provided. In various embodiments, health data of a user is read from one or more data source. A cohort of the user is determined based on a primary diagnosis of the user. The health data of the user includes the primary diagnosis. A co-morbidity of the primary diagnosis within the cohort is determined. One or more predictor of the co-morbidity within the cohort is determined. Assistance information is provided to the user based on the one or more predictor. The assistance information includes the predictor and one or more recommendation to mitigate the co-morbidity.

Abstract: A method, computing system and computer program product are provided. A first entity system that stores sensitive information associated with different entities applies a hash function a portion of the sensitive information to produce hash values. Transaction information pertaining to transactions performed on entity systems are stored within a blockchain database accessible to the entity systems. The transaction information includes hash values corresponding to associated entities from the entity systems. The hash values of the first entity system are compared to the hash values from others of the entity systems to determine entity systems containing information pertaining to same entities. The sensitive information for an entity of the first entity system is exchanged with the determined entity systems containing information for that entity.

Abstract: A mechanism is provided in a data processing system comprising at least one processor and at least one memory, the at least one memory comprising instructions executed by the at least one processor to cause the at least one processor to implement a healthcare analytics management system. A healthcare analytics development sub-system of the healthcare analytics management system develops an analytics pipeline of a set of analytics assets for a selected healthcare based on a set of business needs for a healthcare analytics client and a healthcare analytics model based on the set of analytics assets and the set of business needs. The healthcare analytics model links to the analytics pipeline. A model deployment module of a healthcare analytics operation sub-system of the healthcare analytics management system deploys the healthcare analytics model on a set of computing devices of the selected healthcare consumer.

Abstract: A mechanism is provided in a data processing system comprising at least one processor and at least one memory, the at least one memory comprising instructions executed by the at least one processor to cause the at least one processor to implement a healthcare analytics management system. A healthcare analytics development sub-system of the healthcare analytics management system develops an analytics pipeline of a set of analytics assets for a selected healthcare based on a set of business needs for a healthcare analytics client and a healthcare analytics model based on the set of analytics assets and the set of business needs. The healthcare analytics model links to the analytics pipeline. A model deployment module of a healthcare analytics operation sub-system of the healthcare analytics management system deploys the healthcare analytics model on a set of computing devices of the selected healthcare consumer.

Abstract: Mechanisms are provided to implement secure distributed patient consent and patient information management that addresses the competing needs for efficient access to electronic medical records by authorized parties while maintaining protection of privacy of patient health related information and complying with governing regulations. The mechanisms of the illustrative embodiments implement a tamper-proof and immutable ledger storage system to manage patient consent information and distribution of patient information based on the patient consent information. The ledger storage system operates in conjunction with a master patient record index (MPRI) component to enable the exchange of patient information among health providers once consent has been granted by the patient.

Abstract: Mechanisms are provided for executing patient information transactions. The mechanism store, in a ledger storage system, for each patient, a history of patient consents associated with patient transactions in a healthcare network, comprising patient consent data structures associated with the patient information transferred between participants as part of the transaction. The mechanisms store a master patient record index (MPRI) for each of the patients. The MPRI stores record locators identifying locations of portions of patient information for the patient on different computing devices associated with different health providers. The mechanisms execute, by a transaction manager, a transaction to grant access to a portion of a patient's information based on consent information stored in the ledger storage system and record locators in the MPRI. The mechanisms update, by a ledger storage engine of the data processing system, the history of transactions based on the execution of the transaction.

Abstract: An application as a service provided in a secure environment. A sandbox in a user's computing environment may be created. An application may be downloaded to the user's computing environment to run within the sandbox. Data sources associated with the user's computing environment may be searched and connectivity established with data registry of the data sources based on data description received with the application. The application may be run within the sandbox using the established connectivity. Metering may be performed to monitor usage of the application at the user's computing environment.

Abstract: An application as a service provided in a secure environment. A sandbox in a user's computing environment may be created. An application may be downloaded to the user's computing environment to run within the sandbox. Data sources associated with the user's computing environment may be searched and connectivity established with data registry of the data sources based on data description received with the application. The application may be run within the sandbox using the established connectivity. Metering may be performed to monitor usage of the application at the user's computing environment.

Abstract: An application as a service provided in a secure environment. A sandbox in a user's computing environment may be created. An application may be downloaded to the user's computing environment to run within the sandbox. Data sources associated with the user's computing environment may be searched and connectivity established with data registry of the data sources based on data description received with the application. The application may be run within the sandbox using the established connectivity. Metering may be performed to monitor usage of the application at the user's computing environment.

Abstract: An application as a service provided in a secure environment. A sandbox in a user's computing environment may be created. An application may be downloaded to the user's computing environment to run within the sandbox. Data sources associated with the user's computing environment may be searched and connectivity established with data registry of the data sources based on data description received with the application. The application may be run within the sandbox using the established connectivity. Metering may be performed to monitor usage of the application at the user's computing environment.

Abstract: Techniques are disclosed for capturing and visualizing data lineage in content management systems. For example, a method comprises the following steps. A plurality of data sets is received. Each of the data sets is associated with a party and comprises a plurality of information. A set of lineage data about one or more of the data sets is received. The lineage data comprises information about the history of a particular data set. A user interface is presented that conveys a representation of one or more of the plurality of received data sets and at least a portion of the lineage data about the history of one or more of the data sets. A command is received at the user interface to merge or unmerge two data sets in the plurality of data sets. Two or more data sets in the plurality of data sets are merged or unmerged based on the received command.

Abstract: Techniques are disclosed for capturing, storing, querying and analyzing provenance data for automatic discovery of enterprise process information. For example, a computer-implemented method for managing a process associated with an enterprise comprises the following steps. Data associated with an actual end-to-end execution of an enterprise process is collected. Provenance data is generated based on at least a portion of the collected data, wherein the provenance data is indicative of a lineage of one or more data items. A provenance graph that provides a visual representation of the generated provenance data is generated, wherein nodes of the graph represent records associated with the collected data and edges of the graph represent relations between the records. The generated provenance graph is stored in a repository for use in analyzing the enterprise process.

Abstract: Receiving from each of a plurality of low level monitor models an outbound event comprising information associated with a respective data source. The information received in each of the outbound events can be collected to a global monitoring context in which the information is automatically aggregated. Via a global cube associated with the global monitoring context, the information can be presented in a report. At least one new outbound event can be received. The new outbound event can include updated information associated with at least one of the data sources. Responsive to receiving the new outbound event, the information presented the report can be updated in real time to reflect the updated information.

Abstract: A method, system and computer program product for determining health of a case. The method includes the steps of: obtaining at least one correlated trace from (i) task descriptions or (ii) data related to the task descriptions or a process instance; calculating at least one current metric using (i) the task descriptions, (ii) the data, (iii) the correlated trace or (iv) a first model; calculating at least one prognostic metric using a second model; and creating at least one combination metric from the current metric and the prognostic metric; where at least one of the steps is carried out using a computer device.

Abstract: Receiving from each of a plurality of low level monitor models an outbound event comprising information associated with a respective data source. The information received in each of the outbound events can be collected to a global monitoring context in which the information is automatically aggregated. Via a global cube associated with the global monitoring context, the information can be presented in a report. At least one new outbound event can be received. The new outbound event can include updated information associated with at least one of the data sources. Responsive to receiving the new outbound event, the information presented the report can be updated in real time to reflect the updated information.