Abstract: Data is combined from multiple independent data stores, and is then queried using a data correlation engine. Contemplated engines preferably keep track of previously run correlations, and then makes those correlations available to clinicians for their own use. For example, a preferred system might provide a listing of correlations run by other clinicians in a particular medical specialty, or a particular community, whether geographic or otherwise. In another example, a preferred system might provide a listing of correlations sorted by popularity, so that the most frequently accessed correlations appear near the top of the list. In any case a clinician could simply view the list, and check off which correlations he/she would like to have run for his/her practice, or practice community.

Abstract: A medical guideline integration engine is presented. The engine imports medical guideline information from disparate sources based on various guideline standards into a knowledge base. The knowledge base houses the information in a database. Upon request, the engine retrieves the information from the knowledge base and converts the information into a desired guideline format.

Abstract: A hub-spoke patient information service in which a patient's data can be obtained from a network of independent data sources through a centralized service. The hub of the service stores patient identification information and the spokes store the patient's clinical data. In a preferred embodiment, the spokes are independent sources (e.g. each spoke is generally unrelated to other spokes) and include hospitals, doctor offices, clinics, insurance companies, or other entities that store or track clinical data. Preferably, the data sources use a first authentication to properly identify or authentic the service. Once access is granted, the spoke sources are queried for the patient's data. In response, each data source provides the type of patient data available from the source. The user is shown the types of data available without generally showing the actual data. The user can then select the specific patient data to retrieve from the spoke sources.

Abstract: A medical guideline integration engine is presented. The engine imports medical guideline information from disparate sources based on various guideline standards into a knowledge base. The knowledge base houses the information in a database. Upon request, the engine retrieves the information from the knowledge base and converts the information into a desired guideline format.

Abstract: A hub-spoke patient information service in which a patient's data can be obtained from a network of independent data sources through a centralized service. The hub of the service stores patient identification information and the spokes store the patient's clinical data. In a preferred embodiment, the spokes are independent sources (e.g. each spoke is generally unrelated to other spokes) and include hospitals, doctor offices, clinics, insurance companies, or other entities that store or track clinical data. Preferably, the data sources use a first authentication to properly identify or authentic the service. Once access is granted, the spoke sources are queried for the patient's data. In response, each data source provides the type of patient data available from the source. The user is shown the types of data available without generally showing the actual data. The user can then select the specific patient data to retrieve from the spoke sources.

Abstract: A workflow management system is presented. The workflow management system can include a tasking module and rules engine. Users can interface with the tasking module to define tasks having rule-based task criteria. The rules engine monitors data associated with running a business, including data classified across business segments, to determine if an exception to the task criteria has occurred. If so, the tasking module can automatically generate an exception task to handle the exception and present exception tasks to one or more users.

Abstract: A medical guideline integration engine is presented. The engine imports medical guideline information from disparate sources based on various guideline standards into a knowledge base. The knowledge base houses the information in a database. Upon request, the engine retrieves the information from the knowledge base and converts the information into a desired guideline format.

Abstract: Data is combined from multiple independent data stores, and is then queried using a data correlation engine. Contemplated engines preferably keep track of previously run correlations, and then makes those correlations available to clinicians for their own use. For example, a preferred system might provide a listing of correlations run by other clinicians in a particular medical specialty, or a particular community, whether geographic or otherwise. In another example, a preferred system might provide a listing of correlations sorted by popularity, so that the most frequently accessed correlations appear near the top of the list. In any case a clinician could simply view the list, and check off which correlations he/she would like to have run for his/her practice, or practice community.

Abstract: A hub-spoke patient information service in which a patient's data can be obtained from a network of independent data sources through a centralized service. The hub of the service stores patient identification information and the spokes store the patient's clinical data. In a preferred embodiment, the spokes are independent sources (e.g. each spoke is generally unrelated to other spokes) and include hospitals, doctor offices, clinics, insurance companies, or other entities that store or track clinical data. Preferably, the data sources use a first authentication to properly identify or authentic the service. Once access is granted, the spoke sources are queried for the patient's data. In response, each data source provides the type of patient data available from the source. The user is shown the types of data available without generally showing the actual data. The user can then select the specific patient data to retrieve from the spoke sources.